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http://delivery.acm.org/10.1145/1830000/1822126/p123-perkovic.pdf?ip=173.244.4.179&id=1822126&acc=ACTIVE%20SERVICE&key=7777116298C9657D%2EE233A4FEE91C1906%2E4D4702B0C3E38B35%2E4D4702B0C3E38B35&CFID=810525398&CFTOKEN=82074520&__acm__=1467859962_dea9f3dce7af720181da8a7215d94c5d

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http://stemforall2016.videohall.com/presentations/777

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Learning Computational Thinking Through Creative Movement

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We present VENVI (Virtual ENVironment Interactions), a curriculum and platform that teaches computational thinking through an embodied pedagogical approach. Aimed at middle school children, VENVI t...

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http://dl.acm.org/citation.cfm?id=1822126

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A framework for computational thinking across the curriculum

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COMPUTATIONAL
THINKING
A PROBLEM-SOLVING TOOL
FOR EVERY CLASSROOM

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COMPUTATIONAL
THINKING
A PROBLEM-SOLVING TOOL
FOR EVERY CLASSROOM

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http://digitalis.nwp.org/sites/default/files/files/81/Computational%20Thinking%20for%20Every%20Classroom_1.pdf

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https://www.cs.cmu.edu/~CompThink/resources/education.html

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Scratch has an amazing online community where kids post their programs and learn from each others' efforts. Scratch encourages tinkering which is really important in developing computational concepts and skills.

Lightbot is a pictorial programming activity that introduces basic computational concepts like recursion.

Kids Ruby provides kid-friendly lessons in the Ruby language.

K-12
The Google Exploring Computational Thinking website
Computer Science Education Act ( H.R.5929), proposed by PA Senator Casey and CO Representative Polis.

Computational Fairy Tales by Jeremy Kubica

" Computer Science Teachers Association. CSTA's website is rich with computer science materials for K-12 teachers. It also links to national reports that advocate the importance of computer science education in K-12, e.g., "Running on Empty" and the New Educational Imperative"

International Society for Technology in Education (ISTE) produced this video to explain the importance of computational thinking for all.

The " Exploring Computer Science" course was tested in the UCLA unified school district and is now being tested in Chicago. It is a fully developed course with teaching materials and lesson plans for an entire 1-year course in computing for junior high or early high school students.

Curiosity Cycle: Preparing Your Child for the Ongoing Technological Explosion, by Jonathan Mugan. A book about how parents can help their child think like a computer scientist.
AP® Computer Science: Principles
High School

University of Colorado/Boulder:
Ioannidou, A., Bennett, V., Repenning, A., Koh, K., Basawapatna, A., Computational Thinking Patterns. Paper presented at the 2011 Annual Meeting of the American Educational Research Association (AERA) in the symposium "Merging Human Creativity and the Power of Technology: Computational Thinking in the K-12 Classroom", New Orleans, April 8-12, 2011. teacher training: http://www.9news.com/news/local/article/202987/222/Teachers-play-video-games-for-science-
International CSUnplugged British Royal Society Education Projects

Brown University: Computational thinking for humanities and literature students

Carnegie Mellon University: 15-110 Principles of Computing Course ( Fall 2010, Fall 2011)

Carnegie Mellon University: 15-112 Course

The College Board: CS Principles, A New First Course in Computing

Harvard University: Computer Science 1. Great Ideas in Computer Science
Catalog Number: 6903
Henry H. Leitner
Half course (spring term). Tu., Th., 10-11:30. EXAM GROUP: 12, 13
An introduction to the most important discoveries and intellectual paradigms in computer science, designed for students with little or no previous background. Explores problem-solving using high and low-level programming languages; presents an integrated view of computer systems, from switching circuits up through compilers and GUI design. Examines theoretical and practical limitations related to unsolvable and intractable computational problems, and the social and ethical dilemmas presented by such issues as software unreliability and invasions of privacy. Note: May not be taken for credit after completing Computer Science 50. This course, when taken for a letter grade, meets the General Education requirement for Empirical and Mathematical Reasoning or the Core area requirement for Quantitative Reasoning.
er completing Computer Science 50. This course, when taken for a letter grade, meets the General Education requirement for Empirical and Mathematical Reasoning or the Core area requirement for Quantitative Reasoning.

Harvey Mudd College: CS 5. Introduction to Computer Science
Requirements: Computer Science core course required for all HMC students.
Credit Hours: 3.0
Offered: Fall semester.
Introduction to elements of computer science. Students learn general computational problem-solving techniques and gain experience with the design, implementation, testing and documentation of programs in a high-level language. In addition, students learn to design digital devices, understand how computers work, and learn to program a computer in its own machine language. Finally, students are exposed to ideas in computability theory. The course includes discussions of societal and ethical issues related to computer science.

MIT: Introduction to Computer Science and Programming

Princeton University: Computer Science 116. The Computational Universe

An incomplete list of schools that have similar courses: Brown, Bryn Mawr, Colorado State University, Columbia, Eastern Michigan University, Georgetown, Georgia Tech, Harvard, Harvey Mudd, Haverford, Kent State, MIT, New York City College of Technology, Northwestern, Princeton, Rochester Institute of Technology, St Joseph's U, U of Alabama-Birmingham, U of Florida, UNC-Charlotte, U of Puerto Rico, UTexas-Arlington, U of Wisconsin-La Crosse, Vanderbilt, Villanova, William & Mary
University of Waterloo International
National University of Ireland Maynooth: Computational Thinking at NUI Maynooth

The University of Hong Kong: Everyday Computing and the Internet

Computational Thinking in Egypt

Software Carpentry, Greg Wilson, including a chapter on Principles of Computational Thinking

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New First Course in Computing Harvard University

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Computer Science and Programming Princeton University

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St Joseph 's U , U of Alabama-Birmingham

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Principles High School University of Colorado/Boulder

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International CSUnplugged British Royal Society Education Projects Brown University

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William & Mary University of Waterloo International National University of Ireland Maynooth

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International Society for Technology in Education

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Center for Computational Thinking, Carnegie Mellon

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Scratch has an amazing online community where kids post their programs and learn from each others' efforts. Scratch encourages tinkering which is really important in developing computational concepts and skills. Lightbot is a pictorial programming activity that introduces basic computational concepts like recursion. Kids Ruby provides kid-friendly lessons in the Ruby language.

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http://www.teachprimarycomputing.org.uk/planning/writing-lesson-plans-that-focus-on-computational-thinking/

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CAS QuickStart Computing Interactive Progression Pathways

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Writing lesson plans that focus on computational thinking

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Computational thinking is an activity that occurs in all aspects of the computing curriculum and so should be considered whenever computing lessons are planned. A four step cycle to lesson planning is used to show the process and highlight how the integration can take place.

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SUNDAY, APRIL 6, 2014Lesson Plans for Teaching Computational Thinking

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SUNDAY, APRIL 6, 2014Lesson Plans for Teaching Computational Thinking

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http://www.freetech4teachers.com/2014/04/lesson-plans-for-teaching-computational.html#.V32-y-srLcs

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Google offers dozens of lessons for exploring computational thinking through the use of Python programming. Now if you're wondering, "what the heck does that mean?" don't worry, I wondered the same. Exploring computational thinking through Python is a series of lessons in which middle school and high school students use the Python programming language to try to put mathematics and science concepts to use.

Applications for Education
Exploring Computational Thinking is a series of lessons for designed to help middle school and high school students explore mathematics and science concepts. Google developed these lessons to use Python. As Google states in their Teacher's Guide Introduction to Python, the reason for using Python is, "A computer program gives students the opportunity to directly apply the algorithms they learn in class and provides them with a tangible reason for using variables rather than specific numbers in math."

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Free Technology for Teachers: Lesson Plans for Teaching Computational Thinking

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Google offers dozens of lessons for exploring computational thinking through the use of Python programming. Now if you're wondering, "what the heck does that mean?" don't worry, I wondered the same. Exploring computational thinking through Python is a series of lessons in which middle school and high school students use the Python programming language to try to put mathematics and science concepts to use.

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https://csta.acm.org/Curriculum/sub/CurrFiles/472.11CTTeacherResources_2ed-SP-vF.pdf

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https://www.google.com/edu/resources/programs/exploring-computational-thinking/

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Google for Education: Computational Thinking

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Computational thinking (CT) involves a set of problem-solving skills and techniques that software engineers use to write programs that underlie the computer applications you use such as search, email, and maps

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Computational thinking, 10 years laterMarch 24, 2016 by Jeannette M. Wing

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Computational thinking, 10 years laterMarch 24, 2016 by Jeannette M. Wing

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http://phys.org/news/2016-03-years.html

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"Not in my lifetime." That's what I said when I was asked whether we would ever see computer science taught in K-12. It was 2009, and I was addressing a gathering of attendees to a workshop on computational thinking convened by the National Academies.

I'm happy to say that I was wrong.

It's been 10 years since I published my three-page " Computational Thinking" viewpoint in the March 2006 issue of the Communications of the ACM. To celebrate its anniversary, let's consider how far we've come.

Think back to 2005. Since the dot-com bust, there had been a steep and steady decline in undergraduate enrollments in computer science, with no end in sight. The computer science community was wringing its hands, worried about the survival of their departments on campuses. Unlike many of my colleagues, I saw a different, much rosier future for computer science. I saw that computing was going to be everywhere.

I argued that the use of computational concepts, methods and tools would transform the very conduct of every discipline, profession and sector. Someone with the ability to use computation effectively would have an edge over someone without. So, I saw a great opportunity for the computer science community to teach future generations how computer scientists think. Hence "computational thinking."

I must admit, I am surprised and gratified by how much progress we have made in achieving this vision: Computational thinking will be a fundamental skill used by everyone in the world by the middle of the 21st century. By fundamental, I mean as fundamental as reading, writing and arithmetic.
The third pillar of the scientific method
I knew that in the science and engineering disciplines, computation would be the third pillar of the scientific method, along with theory and experimentation. After all, computers were already used for simulation of large, complex physical and natural systems. Sooner or later, scientists and engineers of all kinds would come to recognize the power of computational abstractions, such as algorithms, data types and state machines.

And today, with the advent of massive amounts of data, researchers in all disciplines-including the arts, humanities and social sciences-are discovering new knowledge using computational methods and tools.

In the past 10 years, I visited nearly 100 colleges and universities worldwide and witnessed a transformation at the undergraduate level. Computer science courses are now offered to students who are not majoring in computer science. These courses are not computer programming courses, but rather focus on core concepts in computer science. At Harvard, this course (CS50) is one of the most popular courses not just on its campus but also at rival Yale's campus. And what about computer science enrollments? They are skyrocketing!

Perhaps the most surprising and gratifying result is to see what is happening at the K-12 level. First, the United Kingdom's grassroots effort Computing At School led the Department of Education to require computing in K-12 schools in England starting September 2014. The statutory guidance for the national curriculum says, "A high-quality computing education equips pupils to use computational thinking and creativity to understand and change the world."

In addition, the BBC, in partnership with Microsoft and other companies, funded the design and distribution of the BBC micro:bit. One million of these small programmable devices will be distributed free this month: One for every 11-12 year-old (Year 7) student in the UK, along with their teachers. Microsoft Research contributed to the design and testing of the device; and the MSR Labs Touch Develop team provided a programming language and platform for the BBC micro:bit, as well as teaching materials.

Second, code.org is a nonprofit organization, started in 2013, dedicated to the mission of providing access to computer science education to all. Microsoft, along with hundreds of other corporate and organizational partners, helps sponsor the activities of code.org.

Third, internationally there is a groundswell interest in teaching computer science at the K-12 level. I know of efforts in Australia, Israel, Singapore and South Korea. China is likely to make a push soon, too.
Computer science for all
Most gratifying to me is President Barack Obama's pledge to provide $4 billion in funding for computer science education in U.S. schools as part of the Computer Science for All Initiative he announced on January 30. That initiative includes $120 million from the National Science Foundation, which will be used to train as many as 9,000 more high school teachers to teach computer science and integrate computational thinking into their curriculum.This push for all students to learn computer science comes partly from market demand for workers skilled in computing-from all sectors, not just information technology. We see this at Microsoft too; our enterprise customers in all sectors, such as automotive, manufacturing and pharmaceutical, are coming to Microsoft because they need more computing expertise.

Still, practical challenges and research opportunities remain. The main practical challenge is that we do not have enough K-12 teachers trained to teach computer science to K-12 students. I am optimistic that, over time, we will solve this problem.

There also are interesting research questions that I would encourage computer scientists to pursue, working with the cognitive and learning sciences communities. First, what computer science concepts should be taught when, and how?

Consider an analogy to mathematics. We teach numbers to 5-year-olds, algebra to 12-year-olds and calculus to 18-year-olds. We have somehow figured out the progression of concepts to teach in mathematics, where learning one new concept builds on understanding the previous concept, and where the progression reflects the progression of mathematical sophistication of a child as he or she matures.

What is that progression in computer science? For example, when is it best to teach recursion? Children learn to solve the Towers of Hanoi puzzle (for small n) and in history class we teach "divide and conquer" as a strategy for winning battles. But is the general concept better taught in high school? We teach long division to 9-year-olds in 4th grade, but we never utter the word "algorithm." And yet the way it is taught, long division is just an algorithm. Is teaching the general concept of an algorithm too soon for a 4th grader? More deeply, are there concepts in computing that are innate and do not need to be formally learned?

Second, we need to understand how best to use computing technology in the classroom. Throwing computers in the classroom is not the most effective way to teach computer science concepts. How can we use technology to enhance the learning and reinforce the understanding of computer science concepts? How can we use technology to measure progress, learning outcomes and retention over time? How can we use technology to personalize the learning for individual learners, as each of us learn at a different pace and have different cognitive abilities?

We have made tremendous progress in injecting computational thinking into research and education of all fields in the last ten years. We still have a ways to go, but fortunately, academia, industry and government forces are aligned toward realizing the vision of making computational thinking commonplace.

Provided by: Microsoft

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"Not in my lifetime." That's what I said when I was asked whether we would ever see computer science taught in K-12. It was 2009, and I was addressing a gathering of attendees to a workshop on computational thinking convened by the National Academies. I'm happy to say that I was wrong.

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http://www.open.edu/openlearn/science-maths-technology/computing-and-ict/introduction-computational-thinking/content-section-3.1

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PS | 650 |  | Computational Thinking in Our World
This course will discuss why computers and computation are ubiquitous in our world and the implications of that ubiquity, including security, gaming, military, GPS, social-networks, stock-trading, voting, and beyond. Students will learn how these systems work at an appropriate level of detail. To give a deeper understanding of these topics a significant component of the course will be student programming labs to explore simple versions of these systems. No previous programming experience will be required.
UL
Lect: 3 hrs./Lab: 1 hr.

GPA Weight: 1.00
Billing Units: 1

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 CPS650 - Computational Thinking in Our World - Winter 2016

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 CPS650 - Computational Thinking in Our World - Winter 2016

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http://cps650.sarg.ryerson.ca/Resources/

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International Journal of Computers for Mathematical Learning Technology

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DePaul University Computational Thinking in Archiving

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CPS650 - Computational Thinking in Our World - Winter 2016

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By it's nature this page is always a work in progress... It will continue to grow as we learn. You can follow the blog for the course here.

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Integrating Creative Writing and Computational Thinking to Develop Interdisciplinary Connections,   2016 ASEE Annual Conference & Exposition

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Integrating Creative Writing and Computational Thinking to Develop Interdisciplinary Connections,   2016 ASEE Annual Conference & Exposition

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http://www.asee.org/public/conferences/64/papers/15382/view

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A typical college curriculum does not make it easy for students to establish connections between required general education courses and courses in their majors. Intentional linking of courses from different disciplines using interdisciplinary pedagogical strategies allows students to make those connections while developing the interdisciplinary skills which will benefit their college and post-college careers.

In addition to communication, critical thinking and reasoning, and collaborative skills, it has been recently argued that computational thinking (i.e., the application of computing concepts and methods to solve problems) should also be a part of a twenty-first century liberal education for a broad range of college students, including those not majoring in computing. Computational thinking concepts and skills can help students frame problems in a variety of fields and disciplines (not just STEM disciplines) using novel strategies, and, in so doing, to become better problem solvers in their professions.

At our institution, many students not majoring in computing (or a STEM discipline) take a first-year problem-solving with computer programming course (PS), which is designed for Computer Science majors, to satisfy the computer literacy/fluency requirement in their degree or to learn computational thinking concepts and skills. However, since PS is a gateway course for Computer Science majors, it is even more challenging for non-majors, resulting in high non-passing and withdrawal rates. To integrate computational thinking in required liberal arts courses, we created a general education interdisciplinary course, Programming Narratives: Computer Animated Storytelling, aimed at non-computer majors, which emphasizes creative writing and computational thinking. In this interdisciplinary course, students learn the structure of narrative, concepts of problem solving, and the logic of computer programming languages as they develop a narrative-driven video game prototype. This process helps students achieve the college-wide learning goal of making meaningful and multiple connections among the liberal arts majors, as well as between the liberal arts and the areas of study leading to a major or profession.

Our findings suggest that the learning objectives and the pedagogical approaches used in the course are adequate for a broad range of non-computer majors. Performance on writing and computing assessments as well as final grades (75% of students obtained a grade of C or better) indicated that a vast majority of students successfully achieved the learning objectives. These results were consistent with student perceptions as reflected in an end-of-course survey. There is also evidence that students satisfactorily integrated creative writing and computer programming to develop their video game prototypes, making in-depth interdisciplinary connections along the way. We believe that this intentional emphasis on connections between disciplines develops the interdisciplinary skills and perspectives which are important for graduation, and it lays the groundwork for interdisciplinary thinking in the workplace.

The full paper will be available to logged in and registered conference attendees once the conference starts on June 26, 2016, and to all visitors after the conference ends on July 29, 2016

Are you a researcher? Would you like to cite this paper? Visit the ASEE document repository at peer.asee.org for more tools and easy citations.

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Integrating Creative Writing and Computational Thinking to Develop Interdisciplinary Connections: American Society for Engineering Education

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A typical college curriculum does not make it easy for students to establish connections between required general education courses and courses in their majors. Intentional linking of courses from different disciplines using interdisciplinary pedagogical strategies allows students to make those connections while developing the interdisciplinary skills which will benefit their college and post-college careers.

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Steve Jobs: ‘Computer Science Is A Liberal Art’ : NPROctober 7, 2011 at 3:29 am

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Steve Jobs: ‘Computer Science Is A Liberal Art’ : NPROctober 7, 2011 at 3:29 am

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https://computinged.wordpress.com/2011/10/07/steve-jobs-computer-science-is-a-liberal-art-npr/

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Steve Jobs: 'Computer Science Is A Liberal Art' : NPR

How very cool!

On computer science as a liberal art
"In my perspective ... science and computer science is a liberal art, it's something everyone should know how to use, at least, and harness in their life. It's not something that should be relegated to 5 percent of the population over in the corner. It's something that everybody should be exposed to and everyone should have mastery of to some extent, and that's how we viewed computation and these computation devices."

via Steve Jobs: 'Computer Science Is A Liberal Art' : NPR.

Entry filed under: Uncategorized. Tags: computing education, computing for everyone.

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Steve Jobs: 'Computer Science Is A Liberal Art' : NPR

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How very cool! On computer science as a liberal art "In my perspective ... science and computer science is a liberal art, it's something everyone should know how to use, at least, and harness in their life. It's not something that should be relegated to 5 percent of the population over in the corner.

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Computational Thinking for The Rest of US

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Computational Thinking for The Rest of US

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https://www.learntechlib.org/p/130715

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Society for Information Technology & Teacher Education International Conference, in Jacksonville, Florida, United States ISBN 978-1-939797-07-0 Publisher: Association for the Advancement of Computing in Education (AACE), Chesapeake, VA

Abstract

Recruiting talented college students remain a significant problem because of difficulties relating and connecting their knowledge with wider audiences. We implemented over the past two years Google Computer Science for High School (CS4HS) workshops with computer science students, faculty, and middle and high school teachers. Computer science students developed hands-on programming lessons using Scratch Programming and App Inventor, presented these lessons during most of the sessions, and participated in a panel discussion about computer science at the middle and high school levels. We evaluated the effectiveness of our workshops through teacher and student surveys. In the short term, students highly valued the opportunity to enrich their education and found our efforts to be socially meaningful. In the long term, our goal is to create a feedback loop where students train teachers in computational thinking, thereby helping them in turn mentor future computer science students.

Citation

Cho, S., Pauca, P., Johnson, D. & James, Y. (2014). Computational Thinking for the Rest of Us: A Liberal Arts Approach to Engaging Middle and High School Teachers with Computer Science Students. In M. Searson & M. Ochoa (Eds.), Proceedings of Society for Information Technology & Teacher Education International Conference 2014 (pp. 79-86). Chesapeake, VA: Association for the Advancement of Computing in Education (AACE).

Keywords

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Society for Information Technology & Teacher Education International Conference

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Proceedings of Society for Information Technology & Teacher Education International Conference

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Liberal Arts Approach to Engaging Middle

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Computational Thinking for the Rest of Us: A Liberal Arts Approach to Engaging Middle and High School Teachers with Computer Science Students

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Recruiting talented college students remain a significant problem because of difficulties relating and connecting their knowledge with wider audiences. We implemented over the past two years Google Computer Science for High School (CS4HS) workshops with computer science students, faculty, and middle and high school teachers.

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Computer Science for the Rest of Us, New York Times, March 31, 2012

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Computer Science for the Rest of Us, New York Times, March 31, 2012

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http://www.nytimes.com/2012/04/01/business/computer-science-for-non-majors-takes-many-forms.html?_r=0

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READING, writing and - refactoring code?

Many professors of computer science say college graduates in every major should understand software fundamentals. They don't argue that everyone needs to be a skilled programmer. Rather, they seek to teach "computational thinking" - the general concepts programming languages employ.

In 2006, Jeannette M. Wing, head of the computer science department at Carnegie Mellon University, wrote a manifesto arguing that basic literacy should be redefined to include understanding of computer processes. "Computational thinking is a fundamental skill for everyone, not just for computer scientists," she wrote. "To reading, writing and arithmetic, we should add computational thinking to every child's analytical ability."

There is little agreement within the field, however, about what exactly are the core elements of computational thinking. Nor is there agreement about how much programming students must do, if any, in order to understand it.

Most important, the need for teaching computational thinking to all students remains vague.

At the college level, computer science courses intended for non-majors run a gamut. In some classes, students start coding right away with a mainstream language. Others exclude programming and examine social and ethical issues related to computer use.

At Carnegie Mellon, students who are not computer science majors are invited to try "Principles of Computation." It starts with a history of computation, but in Week 2, students start learning the programming language Ruby. Then the course covers iteration, recursion, random number generators and other topics.

Tom Cortina, who teaches the course, says that some students perceive the programming as challenging, especially those who aren't majoring in a field of science, technology, engineering or mathematics and are not accustomed to "the preciseness required."

At Wheaton College in Norton, Mass., Mark D. LeBlanc, a professor of computer science, teaches "Computing for Poets." The only prerequisite, according to the course syllabus, is "a love of the written (and digital) word."

Professor LeBlanc has his students learn the basics of Python, another modern language used in the software industry. But this course is tied to two courses offered by the English department on J.R.R. Tolkien and Anglo-Saxon literature. Students in the computing course put concepts to immediate use by analyzing large bodies of text. The syllabus is more like what one would find for a humanities course.

"In the class, we take on big problems," Professor LeBlanc says. "The majority of the students are overwhelmed - 'Where do we start?' " This provides opportunities to illustrate the concept of decomposition, which he describes as "breaking a large problem into small manageable problems."

Professor LeBlanc estimates that just 5 percent of students who enroll each semester find it "worse than a foreign language" and drop the course. He believes that most graduates of Wheaton, a liberal arts college, will work in fields where they must learn how to program. The liberal arts college offers "a safe place to be a novice," he says.

At many other campuses, computer science departments introduce computational thinking by sparing students from learning an industrial-strength programming language in order to try applying the general concepts. Instead, students learn visual scripting languages that produce interactive animation. Scratch, which was developed for elementary and middle-school students, is one such language.

Marie desJardins, a computer science professor at the University of Maryland, Baltimore County, says her department uses Scratch in its "Introduction to Computers and Programming" course, in which students can try a few basic concepts. About 25 percent of the semester is spent on programming.

Explaining why Scratch is used at the college level, she says that all students arrive on campus having taken high school classes in English, math, biology and so on, but that many have not taken a computer science class.

Michael Littman, who leads the computer science department at Rutgers University, agrees. "Computational thinking should have been covered in middle school, and it isn't," he says. "So we in the C.S. department must offer the equivalent of a remedial course."

At Grinnell College in Iowa, students can take "The Digital Age," which covers the "great ideas in the field of computer science, focusing on underlying algorithmic principles and social implications." But it does not entail learning a programming language.

" 'Literacy' implies reading and writing, so 'computer literacy' suggests that writing programs is a required skill for activity under this name," says Henry M. Walker, a computer science professor at Grinnell. "However, general citizens may or may not have to write programs to function effectively in this technological age." He prefers to promote "computer fluency," attainable without assignments in programming.

Someday, the understanding of computational processes may be indispensable for people in all occupations. But it's not yet clear when we'll cross that bridge from nice-to-know to must-know.

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Computer Science for Non-Majors Takes Many Forms

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READING, writing and - refactoring code? Many professors of computer science say college graduates in every major should understand software fundamentals. They don't argue that everyone needs to be a skilled programmer. Rather, they seek to teach "computational thinking" - the general concepts programming languages employ. In 2006, Jeannette M.

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Should liberal arts students learn computational thinking -- BU News May 24, 2012

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Should liberal arts students learn computational thinking -- BU News May 24, 2012

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http://www.bu.edu/hic/2012/05/24/computational-thinking/

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Your brain in bytes: should the basic concepts behind computer science and language be required learning for everyone?

Should the three Rs be four Rs, as in reading, 'riting, 'rithmetic, and 'rogramming? That's the argument made by Carnegie Mellon computer scientist Jeannette Wing and increasingly by academics from a broad spectrum of disciplines. They insist American education is shorting students, even those who'll be poets and philosophers, by failing to equip them with the basics of "computational thinking," the general ideas undergirding computing.

Andrea Berlin, a College of Arts & Sciences professor of archaeology, who specializes in Middle Eastern pottery made during the period from five centuries before Christ to 640 C.E., is one of them. Berlin says archaeological digs and other historical research have uncovered such a mountain of data that "most archaeologists cannot wrap their arms around it." She's hoping to develop a website and app that would allow scholars who aren't computer scientists to gather, mix, and match that information-by time period, region, and other traits. Then a political scientist, for instance, could "compare the patterns, intensity, and direction of trade under earlier political regimes as revealed by archaeological evidence, and gain hard data and real insight into the relationship between economies and various imperial systems," she says. Currently, no one can do that, because "there's no venue by which somebody could access the data."

Computers and computational thinking have revolutionized the way she regards information and its uses. "I used to think of archaeological data as a great mass comprised of many separate items-whole things," she says. But like an atom, each individual datum can be split into different attributes, and "different users might want to deploy selections of those attributes for different and various questions," like that hypothetical political scientist mapping ancient trade routes.

She's seeking a grant for her project from the Rafik B. Hariri Institute for Computing and Computational Science & Engineering. The vision of BU trustee Bahaa Hariri (Questrom'90) in launching the institute with a $15 million gift was exactly what Berlin wants: the marriage of computational techniques and all fields of knowledge. The Hariri institute's founding director, Azer Bestavros, says computational thinking encourages scholars to ask questions they wouldn't ask without it. All academicians, he says, will ask more and better questions if they know those questions can be answered.

Bestavros, a CAS professor of computer science, argues for mandatory instruction in computational thinking in high schools and colleges, insisting that there are ways to teach it without plunging nonscientists into a flummoxed coma. "Computational thinking is not programming," he says.

Leonid Reyzin, a CAS associate professor of computer science, seconds that. "Computation simply means working with information. And because we are in the information age, you can't fully participate in society without such understanding." For example, says Reyzin, understanding the current debate over congressional legislation to combat online copyright infringement overseas requires rudimentary knowledge of how people get information today, and how the legislation would change that.

A College Board commission currently devising a new high school Advanced Placement course in computer science has flagged general practices defining computational thinking. They include "analyzing the effects of computation," "creating computational artifacts" (apps), using abstractions and models, and working effectively in teams.

Some universities already include programming in their computational-thinking-for-dummies courses. Carnegie Mellon, admittedly a techie school, teaches the programming language Ruby, Wheaton College offers Computing for Poets, which requires learning the programming language Python, and the University of Maryland uses Scratch, a visual animation language developed for children.

At BU, CAS requires all students to do course work in mathematics/computer science, not computational thinking per se. For a humanities major seeking an introduction, Dean of Arts & Sciences Virginia Sapiro suggests MA/CS 109, The Art and Science of Quantitative Reasoning, taught jointly by the math and computer science departments. The course description reads: "Buying music online, making phone calls, predicting the weather, or controlling disease outbreaks would be impossible without mathematics, statistics, and computer science. Focuses on methods of reasoning common to these disciplines, and how they enable the modern world."

Bestavros assures students that there isn't a minute of programming instruction in the course-just as "you don't have to use a telescope to appreciate" astronomy, he says.

"We thought that there were more important topics given our limited time," says Reyzin, who codeveloped and teaches the class. Given his druthers, though, he'd teach programming, because "it is learning by doing." In Bestavros' ideal university curriculum, MA/CS 109 would be part of a menu of approaches, with students electing whether to learn programming as part of computational thinking.

There are skeptics of the importance of teaching computational thinking, and some of them are computer scientists. The Yale Daily News reports hostility from the school's computer science department, whose professors frown on such instruction as "trade school."

Bestavros thinks they're wrong about that. "Computational thinking is a big idea," he says, "and 20, 30 years from now, there may be a standard way of teaching it. We are nowhere close to that. But I think society is going through this transformation, and if you want to be competitive 20 years from now, in whatever profession, you really have to get on that bandwagon."

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Rafik B. Hariri Institute for Computing and Computational Science & Engineering

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Should Liberal Arts Students Learn "Computational Thinking"?

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Your brain in bytes: should the basic concepts behind computer science and language be required learning for everyone? Should the three Rs be four Rs, as in reading, 'riting, 'rithmetic, and 'rogramming? That's the argument made by Carnegie Mellon computer scientist Jeannette Wing and increasingly by academics from a broad spectrum of disciplines.

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Computational Thinking and the Liberal Arts

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Computational Thinking and the Liberal Arts

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http://www.eschoolnews.com/2016/06/24/5-ways-to-engage-students-in-real-coding-this-summer-hint-its-not-by-playing-minecraft/?ps=vickyricci%40hotmail.com-0013000000j0oW6-0033000000qhuON

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A coding expert shares how to get students truly invested in computer science that goes beyond drag and drop

Teaching students how to code software is one of the most valuable skills you can give them, and will virtually guarantee them employment once they're in the workforce. According to the US Department of Labor, the median pay for a software developer in 2015 was $100,690, and the growth in available positions is expected to be 17 percent during the period 2014-2024 (more than twice the average growth rate across all occupations).

Many schools are offering coding courses over the summer. I've spent the last two years building a platform that makes learning to code software as easy as playing a game so I've learned a thing or two about how to engage students in coding. Here's some advice for choosing the right learning platform for your community:

Make sure it's age-appropriate and will engage children and teens.

Many of these courses were designed for adults, and even if a child is off-the-charts intelligent, he/she might be bored if the course is all coding and no fun. Courses for kids should incorporate some element of gamification to keep them engaged. Look for courses that were designed specifically for children and teens.

Students should be writing actual code, not just dragging and dropping.

Programs like Scratch are a good method for very young children (K-2), but within a few hours becomes boring for older children, who won't learn very much. To keep kids engaged, they need to start writing real code very quickly.

Get them started on a 'beginner' programming language.

Javascript and Python are two great beginner languages. Java and Swift are much more complex and may intimidate a beginner, ruining the experience for them.

Don't get stuck in the Minecraft trap.

Many people think playing Minecraft helps children learn to code. It doesn't. It's engaging, and it teaches children binary logic, but they aren't learning to code. Don't get tricked into letting children or teens play Minecraft all day and think they are learning programming.

Make sure there is some collaboration involved.

Single-player is fun for a child for a while, but they quickly want to show off what they've done, and that's easier with multi-player coding - especially when the course involves gamification.

There are also some good options for children who may not be ready for a course yet, but who want to do some light learning as a first step. Check out board games such as Robot Turtles, and programmable robot building kits (such as Dash & Dot or a Sphero), which are great activities to work into a summer camp program. But teachers shouldn't just hand their students a game and step back - these activities are more valuable when teachers and students do them together.

This advice and these tools can easily be carried back into the classroom in September. Happy summer, and happy coding!

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5 ways to engage students in real coding this summer (hint: it's not by playing Minecraft)

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Teaching students how to code software is one of the most valuable skills you can give them, and will virtually guarantee them employment once they're in the workforce. According to the US Department of Labor, the median pay for a software developer in 2015 was $100,690, and the growth in available positions is expected to be 17 percent during the period 2014-2024 (more than twice the average growth rate across all occupations).

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 Great article   regarding learning to learn Post June 24 16

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 Great article   regarding learning to learn Post June 24 16

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http://www.eschoolnews.com/2016/06/13/the-7-questions-every-new-teacher-should-be-able-to-answer/

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The 7 questions every new teacher should be able to answer

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Technology News & Innovation in K-12 Education

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In this project we focus on using liberal studies courses – part of the education of the vast majority of undergraduates – as a vehicle for the teaching of computational thinking.

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In this project we focus on using liberal studies courses – part of the education of the vast majority of undergraduates – as a vehicle for the teaching of computational thinking.

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College of Computingand Digital Media

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Computational Thinking Across the Curriculum

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Computational Thinking Across the Curriculum

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http://compthink.cs.depaul.edu/

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http://www.eschoolnews.com/files/2015/09/Critical-Thinkers.pdf?ast=25&astc=11469

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Great article explaining the four C's. The focus is for K-12 but great info

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Great article explaining the four C's. The focus is for K-12 but great info

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http://www.nea.org/assets/docs/A-Guide-to-Four-Cs.pdf

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Being a 21st-century educator is a tall order. In my 15 years in the classroom, my most important "helpers" are technology, movement, and networking. Here's why.

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A Computational Thinking Web Quest for Teachers

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A Computational Thinking Web Quest for Teachers

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http://www.edci.purdue.edu/lehman/ct/teacher.html

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The purpose of this WebQuest is to introduce prospective teachers to the concept of computational thinking, provide opportunities for them to do computational thinking, and encourage them to apply computational thinking in their own discipline and instructional practice.

Learners and Content

This WebQuest is designed for students in EDCI 27000, Introduction to Educational Technology and Computing, at Purdue University, but it is applicable to prospective and practicing teachers in any discipline. The WebQuest addresses computational thinking, which may be conceptualized as a thinking skill or an approach to problem-solving that draws on concepts from computer science but is applicable to a wide variety of problems and disciplines. Teachers can encourage students to develop computational thinking skills through the integration of computational thinking activities into elementary and secondary education.

Learning Environment

As designed, the individual study components of this WebQuest can be completed by students who have access to a computer with Internet connectivity. Activities could be done in a laboratory setting or completed at home. For the group component of the WebQuest, students need access to an online discussion board, such as a forum in Blackboard or other course management system. The course textbook referenced in this WebQuest is:

Newby, T. J., Stepich, D. A., Lehman, J. D., Russell, J. D., and Ottenbreit-Leftwich, A. (2011). Educational technology for teaching and learning, 4th ed. Boston, MA: Allyn & Bacon/Pearson Education, Inc.

Standards

The WebQuest addresses the following ISTE/NETS Educational Technology Standards for teachers

Facilitate and Inspire Student Learning and Creativity

Design and Develop Digital-Age Learning Experiences and Assessments

Model Digital-Age Work and Learning

Introduction

The computer has had a profound impact on many aspects of society, education, and our daily lives. For examples, refer to the discussion of the educational computing in Chapter 1 of your textbook. One way that the computer has impacted us is in the realm of thinking and problem-solving skills. Computational thinking is relatively new conception of certain thinking and problem-solving skills. What is computational thinking? That is what you will have the opportunity to learn in this WebQuest!

What is a WebQuest? A WebQuest is an inquiry-oriented activity in which some or all of the information used in the activity is drawn from the Web. It is a popular way to integrate Internet resources into education, and you will learn more about WebQuests later in this course. For more information, refer to pp. 194-196 of your textbook. By experiencing this WebQuest, you will learn more about WebQuests while also learning about computational thinking.

The purpose of this WebQuest is to give you the opportunity to:

create your own definition and understanding of computational thinking,

design an activity for incorporating computational thinking in the teaching of your discipline, and

explore and refine your ideas with classmates via an online discussion.

Task

Imagine that you have just been hired for your first teaching position. The principal of your school asks for your help in addressing a new state standard on computational thinking. The principal explains, "There is a new academic standard which states that students should have an understanding of computational thinking and its application in design and problem solving in real-world contexts. As I understand it, computational thinking is something that can be addressed no matter which subject is being taught. The expectation is that students will be able to see that computational thinking is everywhere in daily life and can be applied to a wide variety of problems and content." The principal continues, "I know you had course work in educational technology at Purdue, so I think you can set an example for the rest of the faculty by developing an activity for your classroom to introduce your students to computational thinking."

So, your task is to design a class activity to introduce your students to some aspect of computational thinking and/or its application.

Process

To complete the WebQuest, go through the steps outlined below in the order they are presented. The first part of the WebQuest will be completed individually, and then you will participate in an online discussion to share ideas with classmates.

What do you know already?

You should have received an e-mail with a link to a short survey designed to assess your current understanding of computational thinking concepts. Before getting started, be sure to complete that short survey.

What is computational thinking?

To begin, read this short article by Wing (2006), a computer scientist and educator, who popularized the term "computational thinking."
http://www.cs.cmu.edu/afs/cs/usr/wing/www/publications/Wing06.pdf

More information about computational thinking is provided on the cs4fn website. Follow the links on the site to learn more about aspects of computational thinking such as logical thinking, algorthmic thinking, efficient solutions, scientific thinking, and innovative thinking.
http://www.cs4fn.org/computationalthinking/

Experiencing computational thinking

To get a better understanding of computational thinking, in this case the idea of algorthms, do the following activity at the cs4fn website: http://www.cs4fn.org/algorithms/swappuzzle/.

Try another activity, in this case one that helps you to understand how computers can represent images: http://sucs.org/~tobeon/project/image.html.

Integrating computational thinking in the classroom

Explore the following websites to get ideas for how you might integrate a computational thinking activity for students in your own classroom.

Design a computational thinking activity

Based on your major and teaching interest, develop a preliminary design for your own classroom activity on computational thinking. Your design should identify a specific skill, technique, concept, or aspect of computational thinking that your activity will address and a brief (less than 150 words) description for how you will teach it. Draw on what you've learned about planning learning experiences (see chapters 4 - 8 of your textbook). You may also find it helpful to visit the Wiki repository to find a lesson plan that you are interested in and then try to integrate a computational thinking activity in it.

Share ideas with classmates via online discussion

Post your computational thinking preliminary design in the Computational Thinking WebQuest online discussion forum in the EDCI 27000 Blackboard site no later than Thursday of the assigned week.

Review the examples of computational thinking activities posted by your classmates. Post responses to at least two of your classmates. As you frame your response, consider the following questions.

What makes a good classroom learning activity?

Which of the preliminary design examples that have been presented do you think will make for a good computational thinking activity? Why?

How has using this WebQuest helped you to develop your own understanding of computational thinking?

Complete your responses no later than the end of the discussion period for this online discussion. See the Evaluation section for the scoring rubric.

What have you learned?

At the end of the online discussion, you will receive an e-mail with a link to another short survey about computational thinking concepts. Please complete the short survey.

As a final step, review the Conclusion page of the WebQuest.

Evaluation

Name:______________________________________ Points:_______________

Online discussion response grading rubric

Conclusion

At the conclusion of this WebQuest, you will have a better understanding of the concept of computational thinking, and you will have had an opportunity to design an activity for introducing computational thinking with your own students in the classroom.

How do you think computational thinking skills can be of benefit to your students? In what ways can you help your students to develop computational thinking skills? Which examples of computational thinking activities from the class did you find particularly interesting or appealing?

If you find this kind of thing interesting, you might consider preparing to become a teacher of computer science. Purdue now offers a computer science teaching endorsement program that leads to a supplemental teaching license in computer education. This program is open to all secondary teaching majors and may be of particular interest to students majoring in math, science, or technology.

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Inspire Student Learning and Creativity Design

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The purpose of this WebQuest is to introduce prospective teachers to the concept of computational thinking, provide opportunities for them to do computational thinking, and encourage them to apply computational thinking in their own discipline and instructional practice.

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The push to learn code in early childhood

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The push to learn code in early childhood

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https://www.eimacs.com/blog/2012/04/computational-thinking-for-kids/T

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Unless you've been hiding under a rock for the past year, you'll have noticed that the campaign to teach kids (and adults) how to code is everywhere you turn. As parents, politicians, and educators debate how to produce more graduates in technology fields, the push to introduce computing at an earlier age gets stronger. For example, MIT's Lifelong Kindergarten group is collaborating on programming software aimed at kids in preschool to second grade. There are even board books for babies on HTML and CSS! We suspect that such novelties are more for tech parents' enjoyment.

IMACS believes these efforts are well-intentioned and some, when implemented, will be well-designed. But before you click over to Amazon to buy your little drool monster a book on Web design, IMACS can offer you a few examples of how to introduce computational thinking to children through easy activities that are familiar to you, even if you think you're computationally challenged.
Computational Thinking vs. Coding
This short and informative paper by Jeannette Wing, head of the Computer Science Department at Carnegie Mellon University, explains clearly what computational thinking is and is not. The following excerpted quote is a good summary of the focus of this blog post:

"Thinking like a computer scientist means more than being able to program a computer. It requires thinking at multiple levels of abstraction."

Learning to think abstractly is an essential skill if you want to succeed in computer science. It makes solving problems easier, which in turn makes working on those problems more fun. Notably, students can learn to think like a computer scientist without entering a single line of code into a computer. In fact, our experience in teaching CS is that writing computer programs is trivial for students who first develop computational thinking skills. Let's see where in our daily lives we can show kids relatable examples to help them make the transition to abstract thinking.
Stacks and Queues
In computing, a stack is an object in which data expressions are stored and retrieved in such a way that the first data expression to be stored is always the last data expression to be retrieved. It is an example of a so-called Last-In-First-Out (LIFO) object. The same idea applies to various real-life constructs that young kids encounter, even babies who love board books.

Obviously, you can't explain LIFO with words to a baby and expect the baby to understand, but you can certainly demonstrate the concept with your actions. Take the classic Fisher-Price Rock-a-Stack, for example. Start with the rings off the cone and then load them on in the intended manner with the blue ring going on first. Try to get just the blue ring off. Can you do it while the other rings are still on the cone? No, you have to take the rings off one by one with the blue ring coming off last.

Older kids can appreciate the same concept with examples they come across in their lives: unloading plates from the dishwasher into the cupboard, setting the table with said plates the next day, selecting a product such as cosmetics from a store shelf, putting said product back if you decide not to buy it. You get the picture.

A queue is similar to a stack in that it is an object used to store data expressions. In the case of a queue, however, the first data expression to be stored is always the first to be retrieved. Queues are examples of First-In-First-Out (FIFO) objects. Kids encounter them every time they go through a checkout line or a drive-thru. Switch that Rock-a-Stack cone for an empty paper towel roll, and you've got yourself a baby-friendly queue.
Sorting Algorithms
Sorting is one of the oldest problems in computer science. Although the end goal (an ordered list) is conceptually easy to understand, getting there can be complex. Add to that the need for sorting algorithms to be computationally efficient and you've got yourself an interesting abstract puzzle.

If your kids are old enough to know or learn how to put words in alphabetical order, then make a project out of sorting the books on their bookshelf. Decide on a sorting key such as title or author's name. For this example, we'll use title. For the first shelf, ask your child to try a simple bubble sort. Traverse the shelf from left to right, compare the titles of two books, and swap them if they are in the wrong order. Repeat this process until all books on this shelf are in the correct order.

For the next shelf, you can use a simple insertion sort. Take all the books off that shelf and put them in order one by one in a pile on the floor. Each time that you add a book to the ordered pile, be sure to put it in the right place relative to the books that were previously added.

Now that you have two properly sorted sets of books, you and your child can work together to sort all books. Sounds like a good time to use a merge sort. Move the sorted books off the first shelf into another pile on the floor while keeping them properly ordered and separate from the pile of books from the second shelf. Reshelve the books as follows: repeatedly compare the titles of the two books that are atop the two piles, selecting the one that goes first, and continuing until both piles are exhausted.
Object Oriented Programming
An "object" in computer programming is a complex structure containing data fields and instructions. These objects interact with each other to create even more complex computer programs. The beauty of object oriented programming is that you can reuse objects to do common computing tasks without having to reinvent them each time. Over time, programmers can build up a "library" of useful objects.

The following analogy certainly isn't perfect, but it will help get the point across about these seemingly mysterious objects. If you're planning an outing with kids, you'll need a few things to help keep your sanity: nourishment, entertainment, and possibly a change of clothes. So grab three bags and make some objects! In the nourishment object, you'll probably need fruits, carb snacks, a protein, and beverages. For the entertainment object, how about art supplies, books, sporting equipment, and portable gaming device? Kids are made to get dirty, and the weather may change, so pack a top, bottom, and outerwear in the clothing object. Throw those "objects" in your huge tote "library" and you're ready to go!
Think Like a Computer Scientist
Planting the seeds of computational thinking, especially the ability to think abstractly, is really a matter of recognizing the examples in your life that can be used to foster discussion with your children. Like any new endeavor, remembering to look at events in a computational light takes practice. You might just find yourself thinking like a computer scientist when it comes to solving the data problems in your own adult life.

Enhance your computational thinking skills with online computer science courses from IMACS! Register for our free aptitude test. Solve weekly IMACS logic puzzles on Facebook.

# data[].attributes.attachment_link.description
Unless you've been hiding under a rock for the past year, you'll have noticed that the campaign to teach kids (and adults) how to code is everywhere you turn. As parents, politicians, and educators debate how to produce more graduates in technology fields, the push to introduce computing at an earlier age gets stronger.

# data[].attributes.attachment_link.readable_text
Unless you've been hiding under a rock for the past year, you'll have noticed that the campaign to teach kids (and adults) how to code is everywhere you turn. As parents, politicians, and educators debate how to produce more graduates in technology fields, the push to introduce computing at an earlier age gets stronger. For example, MIT's Lifelong Kindergarten group is collaborating on programming software aimed at kids in preschool to second grade. There are even board books for babies on HTML and CSS! We suspect that such novelties are more for tech parents' enjoyment.

IMACS believes these efforts are well-intentioned and some, when implemented, will be well-designed. But before you click over to Amazon to buy your little drool monster a book on Web design, IMACS can offer you a few examples of how to introduce computational thinking to children through easy activities that are familiar to you, even if you think you're computationally challenged.
Computational Thinking vs. Coding
This short and informative paper by Jeannette Wing, head of the Computer Science Department at Carnegie Mellon University, explains clearly what computational thinking is and is not. The following excerpted quote is a good summary of the focus of this blog post:

"Thinking like a computer scientist means more than being able to program a computer. It requires thinking at multiple levels of abstraction."

Learning to think abstractly is an essential skill if you want to succeed in computer science. It makes solving problems easier, which in turn makes working on those problems more fun. Notably, students can learn to think like a computer scientist without entering a single line of code into a computer. In fact, our experience in teaching CS is that writing computer programs is trivial for students who first develop computational thinking skills. Let's see where in our daily lives we can show kids relatable examples to help them make the transition to abstract thinking.
Stacks and Queues
In computing, a stack is an object in which data expressions are stored and retrieved in such a way that the first data expression to be stored is always the last data expression to be retrieved. It is an example of a so-called Last-In-First-Out (LIFO) object. The same idea applies to various real-life constructs that young kids encounter, even babies who love board books.

Obviously, you can't explain LIFO with words to a baby and expect the baby to understand, but you can certainly demonstrate the concept with your actions. Take the classic Fisher-Price Rock-a-Stack, for example. Start with the rings off the cone and then load them on in the intended manner with the blue ring going on first. Try to get just the blue ring off. Can you do it while the other rings are still on the cone? No, you have to take the rings off one by one with the blue ring coming off last.

Older kids can appreciate the same concept with examples they come across in their lives: unloading plates from the dishwasher into the cupboard, setting the table with said plates the next day, selecting a product such as cosmetics from a store shelf, putting said product back if you decide not to buy it. You get the picture.

A queue is similar to a stack in that it is an object used to store data expressions. In the case of a queue, however, the first data expression to be stored is always the first to be retrieved. Queues are examples of First-In-First-Out (FIFO) objects. Kids encounter them every time they go through a checkout line or a drive-thru. Switch that Rock-a-Stack cone for an empty paper towel roll, and you've got yourself a baby-friendly queue.
Sorting Algorithms
Sorting is one of the oldest problems in computer science. Although the end goal (an ordered list) is conceptually easy to understand, getting there can be complex. Add to that the need for sorting algorithms to be computationally efficient and you've got yourself an interesting abstract puzzle.

If your kids are old enough to know or learn how to put words in alphabetical order, then make a project out of sorting the books on their bookshelf. Decide on a sorting key such as title or author's name. For this example, we'll use title. For the first shelf, ask your child to try a simple bubble sort. Traverse the shelf from left to right, compare the titles of two books, and swap them if they are in the wrong order. Repeat this process until all books on this shelf are in the correct order.

For the next shelf, you can use a simple insertion sort. Take all the books off that shelf and put them in order one by one in a pile on the floor. Each time that you add a book to the ordered pile, be sure to put it in the right place relative to the books that were previously added.

Now that you have two properly sorted sets of books, you and your child can work together to sort all books. Sounds like a good time to use a merge sort. Move the sorted books off the first shelf into another pile on the floor while keeping them properly ordered and separate from the pile of books from the second shelf. Reshelve the books as follows: repeatedly compare the titles of the two books that are atop the two piles, selecting the one that goes first, and continuing until both piles are exhausted.
Object Oriented Programming
An "object" in computer programming is a complex structure containing data fields and instructions. These objects interact with each other to create even more complex computer programs. The beauty of object oriented programming is that you can reuse objects to do common computing tasks without having to reinvent them each time. Over time, programmers can build up a "library" of useful objects.

The following analogy certainly isn't perfect, but it will help get the point across about these seemingly mysterious objects. If you're planning an outing with kids, you'll need a few things to help keep your sanity: nourishment, entertainment, and possibly a change of clothes. So grab three bags and make some objects! In the nourishment object, you'll probably need fruits, carb snacks, a protein, and beverages. For the entertainment object, how about art supplies, books, sporting equipment, and portable gaming device? Kids are made to get dirty, and the weather may change, so pack a top, bottom, and outerwear in the clothing object. Throw those "objects" in your huge tote "library" and you're ready to go!
Think Like a Computer Scientist
Planting the seeds of computational thinking, especially the ability to think abstractly, is really a matter of recognizing the examples in your life that can be used to foster discussion with your children. Like any new endeavor, remembering to look at events in a computational light takes practice. You might just find yourself thinking like a computer scientist when it comes to solving the data problems in your own adult life.

Enhance your computational thinking skills with online computer science courses from IMACS! Register for our free aptitude test. Solve weekly IMACS logic puzzles on Facebook.

# data[].attributes.attachment_link.description
Unless you've been hiding under a rock for the past year, you'll have noticed that the campaign to teach kids (and adults) how to code is everywhere you turn. As parents, politicians, and educators debate how to produce more graduates in technology fields, the push to introduce computing at an earlier age gets stronger.

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Good article with some relevant links to other information

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Good article with some relevant links to other information

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https://www.linkedin.com/pulse/20140616144007-94166942-computational-thinking

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There is more to computer science than programming The new Computing At Schools (CAS) curriculum puts 'Computational Thinking' as a main feature of the program of study. At first, I didn't pay special attention to the term; I thought as long as it's something related to programmers and computer scie

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Provides some good examples of computational thinking in various disciplines

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Provides some good examples of computational thinking in various disciplines

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https://www.cs.cmu.edu/afs/cs/usr/wing/www/talks/ct-and-tc-long.pdf

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Link to various articles from E-School News regarding critical thinking

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Link to various articles from E-School News regarding critical thinking

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http://www.eschoolnews.com/2015/09/04/critical-thinking-and-technology/

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http://marciaconner.com/blog/ten-skills/

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Sense-making, social intelligence, novel & adaptive thinking, cross-cultural competency, computational thinking, new-media literacy, transdisciplarity, design mindset, cognitive load management, virtual collaboration.

These are the 10 skills needed for the future workforce. For a full report, see the work done by the Institute for the Future with Apollo Group looking at the Skills Needed by 2020 ( also available on the IFTF website). A summary map is also available.

The related, Shape of Jobs to Come: Possible New Careers Emerging from Advances in Science and Technology (2010 - 2030) full study from FastFuture is also very insightful ( summary of study). I wonder, though, how long it will be until we no longer see the first new shape, "Body Parts Maker," as a bit funny and out of this world.

Note: last time I checked, the FastFuture website had exceeded its bandwidth limit. I was able to find the Shape of Jobs to Come research on another site.
Thanks to Josep Comas for pointing me to these resources.
[Last updated November 6, 2013.]

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Sense-making, social intelligence, novel & adaptive thinking, cross-cultural competency, computational thinking, new-media literacy, transdisciplarity, design mindset, cognitive load management, virtual collaboration. These are the 10 skills needed for the future workforce. For a full report, see the work done by the Institute for the Future with Apollo Group looking at the Skills Needed by 2020 ( also available on the IFTF website).

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Four Skills You’ll Need to Succeed in the Future WorkplacePosted on March 24, 2014 by The Groves Center

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Four Skills You’ll Need to Succeed in the Future WorkplacePosted on March 24, 2014 by The Groves Center

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http://www.kvccgrovescenter.com/skills/4-skills-to-succeed/

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It's no secret that the state of the workplace landscape is transforming at a historically unprecedented speed. Smart machines, social media, increasing lifespans and global connectedness are all factors creating daily efficiencies as well as frustrations.

How the workplace operates is something we like to keep track of here at The Groves Center, since we are here to build the skills and competencies that employers need to grow and compete in the marketplace. We strive to forecast to employers the outlook of the workplace and workforce, by listening to employers and customizing classes and seminars based on workplace trends and what employers are telling us.

When it comes to designing classes, we take multiple factors into consideration to make sure we prepare employees and employers for success in today's work environment and beyond.

In recognition of the changing work landscape, below are four skills the Groves Center suggests that employees will need to acquire and employers be prepared to support, as the future becomes the present.

Novel and Adaptive Thinking: With the automation of routine work, job opportunities are centralizing around high-skill, high-wage professional, technical, and management positions; and low-skill, low-wage positions like food service and personal care.

Both these categories require a sense of adaptive thinking, meaning the need to respond to occurrences on the fly. The ability to think and come up with solutions to unexpected circumstances will be at a premium in the evolving workplace landscape.

Computational Thinking: Computational thinking skills are a hot commodity as the amount of data at our disposal increases exponentially. Familiarity with the Microsoft Suite won't be adequate, as applicants will need statistical analysis and quantitative reasoning skills.

Computers can do a lot for us, but the human element is crucial to how companies leverage the technology. The ability to understand the feeding of the data, along with understanding its limitations, and the ability to act in the absence of data are traits employees will be expected to possess.

New Media Literacy: Audiences today are demanding more sophisticated information presentation techniques. Content creation skills in tools beyond the traditional slide deck of a PowerPoint presentation are required to engage and persuade learners. Workers will need to be fluent in multiple forms of content creation including the likes of videos, blogs, podcasts and more.

With the abundance of user-friendly editing programs and tools, video language concepts like frame, depth of field, etc. will become common vernacular. Workers will need the skills to be comfortable to both create and present their own visual information.

Transdisciplinarity: This day and age, we face multifaceted problems which require transdiciplinarity solutions. This means the ability to understand concepts across multiple disciplines. Ideal workers will bring a deep understanding of at least one field, but showcase ability to converse in a broader range of disciplines. A worker who shows curiosity and willingness to learn will thrive.

The shift has major implications for the skillset that knowledge workers will need to bring to organizations. The Groves Center works closely with employers to identify the multiple disciplines that are required for employees to be successful on the job. Visit our Training Catalog to see an overview of the disciplines and training programs we offer.

Success in the modern business world means adaptation. Take a look at the courses we are currently offering and be sure to check back often as it is a constantly changing list based on demands customized to meet workplace trends. If you don't see what you need, give us a call at 269.353.1253. We will be happy to discuss your training needs.

To see additional workplace factor and workforce skill forecasts, review the University of Phoenix Research Institute's Future Work Skills 2020 white paper in its entirety.

Trish Schroeder
Director of Corporate Training - The Groves Center
Kalamazoo Valley Community College
email: pschroeder@kvcc.edu

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Four Skills You'll Need to Succeed in the Future Workplace

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It's no secret that the state of the workplace landscape is transforming at a historically unprecedented speed. Smart machines, social media, increasing lifespans and global connectedness are all factors creating daily efficiencies as well as frustrations.

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Introducing Teachers to Computational Thinking

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Introducing Teachers to Computational Thinking

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http://www.educationbusinessuk.net/index.php/features/5-/4766-introducing-teachers-to-computational-thinking

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http://www.edci.purdue.edu/lehman/ct/teacher.html

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The purpose of this WebQuest is to introduce prospective teachers to the concept of computational thinking, provide opportunities for them to do computational thinking, and encourage them to apply computational thinking in their own discipline and instructional practice.

Learners and Content

This WebQuest is designed for students in EDCI 27000, Introduction to Educational Technology and Computing, at Purdue University, but it is applicable to prospective and practicing teachers in any discipline. The WebQuest addresses computational thinking, which may be conceptualized as a thinking skill or an approach to problem-solving that draws on concepts from computer science but is applicable to a wide variety of problems and disciplines. Teachers can encourage students to develop computational thinking skills through the integration of computational thinking activities into elementary and secondary education.

Learning Environment

As designed, the individual study components of this WebQuest can be completed by students who have access to a computer with Internet connectivity. Activities could be done in a laboratory setting or completed at home. For the group component of the WebQuest, students need access to an online discussion board, such as a forum in Blackboard or other course management system. The course textbook referenced in this WebQuest is:

Newby, T. J., Stepich, D. A., Lehman, J. D., Russell, J. D., and Ottenbreit-Leftwich, A. (2011). Educational technology for teaching and learning, 4th ed. Boston, MA: Allyn & Bacon/Pearson Education, Inc.

Standards

The WebQuest addresses the following ISTE/NETS Educational Technology Standards for teachers

Facilitate and Inspire Student Learning and Creativity

Design and Develop Digital-Age Learning Experiences and Assessments

Model Digital-Age Work and Learning

Introduction

The computer has had a profound impact on many aspects of society, education, and our daily lives. For examples, refer to the discussion of the educational computing in Chapter 1 of your textbook. One way that the computer has impacted us is in the realm of thinking and problem-solving skills. Computational thinking is relatively new conception of certain thinking and problem-solving skills. What is computational thinking? That is what you will have the opportunity to learn in this WebQuest!

What is a WebQuest? A WebQuest is an inquiry-oriented activity in which some or all of the information used in the activity is drawn from the Web. It is a popular way to integrate Internet resources into education, and you will learn more about WebQuests later in this course. For more information, refer to pp. 194-196 of your textbook. By experiencing this WebQuest, you will learn more about WebQuests while also learning about computational thinking.

The purpose of this WebQuest is to give you the opportunity to:

create your own definition and understanding of computational thinking,

design an activity for incorporating computational thinking in the teaching of your discipline, and

explore and refine your ideas with classmates via an online discussion.

Task

Imagine that you have just been hired for your first teaching position. The principal of your school asks for your help in addressing a new state standard on computational thinking. The principal explains, "There is a new academic standard which states that students should have an understanding of computational thinking and its application in design and problem solving in real-world contexts. As I understand it, computational thinking is something that can be addressed no matter which subject is being taught. The expectation is that students will be able to see that computational thinking is everywhere in daily life and can be applied to a wide variety of problems and content." The principal continues, "I know you had course work in educational technology at Purdue, so I think you can set an example for the rest of the faculty by developing an activity for your classroom to introduce your students to computational thinking."

So, your task is to design a class activity to introduce your students to some aspect of computational thinking and/or its application.

Process

To complete the WebQuest, go through the steps outlined below in the order they are presented. The first part of the WebQuest will be completed individually, and then you will participate in an online discussion to share ideas with classmates.

What do you know already?

You should have received an e-mail with a link to a short survey designed to assess your current understanding of computational thinking concepts. Before getting started, be sure to complete that short survey.

What is computational thinking?

To begin, read this short article by Wing (2006), a computer scientist and educator, who popularized the term "computational thinking."
http://www.cs.cmu.edu/afs/cs/usr/wing/www/publications/Wing06.pdf

More information about computational thinking is provided on the cs4fn website. Follow the links on the site to learn more about aspects of computational thinking such as logical thinking, algorthmic thinking, efficient solutions, scientific thinking, and innovative thinking.
http://www.cs4fn.org/computationalthinking/

Experiencing computational thinking

To get a better understanding of computational thinking, in this case the idea of algorthms, do the following activity at the cs4fn website: http://www.cs4fn.org/algorithms/swappuzzle/.

Try another activity, in this case one that helps you to understand how computers can represent images: http://sucs.org/~tobeon/project/image.html.

Integrating computational thinking in the classroom

Explore the following websites to get ideas for how you might integrate a computational thinking activity for students in your own classroom.

Design a computational thinking activity

Based on your major and teaching interest, develop a preliminary design for your own classroom activity on computational thinking. Your design should identify a specific skill, technique, concept, or aspect of computational thinking that your activity will address and a brief (less than 150 words) description for how you will teach it. Draw on what you've learned about planning learning experiences (see chapters 4 - 8 of your textbook). You may also find it helpful to visit the Wiki repository to find a lesson plan that you are interested in and then try to integrate a computational thinking activity in it.

Share ideas with classmates via online discussion

Post your computational thinking preliminary design in the Computational Thinking WebQuest online discussion forum in the EDCI 27000 Blackboard site no later than Thursday of the assigned week.

Review the examples of computational thinking activities posted by your classmates. Post responses to at least two of your classmates. As you frame your response, consider the following questions.

What makes a good classroom learning activity?

Which of the preliminary design examples that have been presented do you think will make for a good computational thinking activity? Why?

How has using this WebQuest helped you to develop your own understanding of computational thinking?

Complete your responses no later than the end of the discussion period for this online discussion. See the Evaluation section for the scoring rubric.

What have you learned?

At the end of the online discussion, you will receive an e-mail with a link to another short survey about computational thinking concepts. Please complete the short survey.

As a final step, review the Conclusion page of the WebQuest.

Evaluation

Name:______________________________________ Points:_______________

Online discussion response grading rubric

Conclusion

At the conclusion of this WebQuest, you will have a better understanding of the concept of computational thinking, and you will have had an opportunity to design an activity for introducing computational thinking with your own students in the classroom.

How do you think computational thinking skills can be of benefit to your students? In what ways can you help your students to develop computational thinking skills? Which examples of computational thinking activities from the class did you find particularly interesting or appealing?

If you find this kind of thing interesting, you might consider preparing to become a teacher of computer science. Purdue now offers a computer science teaching endorsement program that leads to a supplemental teaching license in computer education. This program is open to all secondary teaching majors and may be of particular interest to students majoring in math, science, or technology.

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Inspire Student Learning and Creativity Design

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The purpose of this WebQuest is to introduce prospective teachers to the concept of computational thinking, provide opportunities for them to do computational thinking, and encourage them to apply computational thinking in their own discipline and instructional practice.

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https://www.staffs.ac.uk/assets/Access%20to%20SQL.pdf

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Center for Computational Thinking at Carnegie Melllon

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Center for Computational Thinking at Carnegie Melllon

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http://www.cs.cmu.edu/~CompThink/

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What is computational thinking?
"Computational Thinking is the thought processes involved in formulating problems and their solutions so that the solutions are represented in a form that can be effectively carried out by an information-processing agent." Cuny, Snyder, Wing
Computational thinking is a way of solving problems, designing systems, and understanding human behavior that draws on concepts fundamental to computer science. To flourish in today's world, computational thinking has to be a fundamental part of the way people think and understand the world.

Computational thinking means creating and making use of different levels of abstraction, to understand and solve problems more effectively.

Computational thinking means thinking algorithmically and with the ability to apply mathematical concepts such as induction to develop more efficient, fair, and secure solutions.

Computational thinking means understanding the consequences of scale, not only for reasons of efficiency but also for economic and social reasons.

Computational thinking is a Carnegie Mellon thing

Computational thinking makes it possible for transplant surgeons to realize that more lives can be saved by optimizing the exchange of organs among pools of donors and recipients. It enables new drug designs to be analyzed so that they are less likely to create drug-resistant strains of diseases. Artists, when given the tools to think and express themselves computationally, can create totally new modes of human experience. Users of the Internet, when empowered with computational thinking, can demystify privacy technologies and surf the web safely.

These and several other possibilities are being realized in the Center for Computational Thinking at Carnegie Mellon University through a collection of PROBlem-oriented Explorations. Working closely with Microsoft Research, PROBEs explore specific opportunities to demonstrate the power and value of computational thinking in a wide range of domains. Our vision is that computational thinking is for everyone, not just computer scientists. To see more, visit our PROBEs page .

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Center for Computational Thinking, Carnegie Mellon

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What is computational thinking? "Computational Thinking is the thought processes involved in formulating problems and their solutions so that the solutions are represented in a form that can be effectively carried out by an information-processing agent." Cuny, Snyder, Wing Computational thinking is a way of solving problems, designing systems, and understanding human behavior that draws on concepts fundamental to computer science.

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Innovative Use of What if Analysis for
Visualization   International Journal of Soft Computing and Engineering (IJSCE)
ISSN: 2231-2307, Volume-2, Issue-6, January 2013

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Innovative Use of What if Analysis for
Visualization   International Journal of Soft Computing and Engineering (IJSCE)
ISSN: 2231-2307, Volume-2, Issue-6, January 2013

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http://www.ijsce.org/attachments/File/v2i6/F1169112612.pdfInternational Journal of Soft Computing and Engineering (IJSCE) ISSN: 2231-2307, Volume-2, Issue-6, January 2013

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The essence of computational thinking is thinking about data and ideas, and using
and combining these resources to solve problems. Teachers can encourage students
to “think computationally” by moving technology projects beyond “using” tools and
information toward “creating” tools and information.

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The essence of computational thinking is thinking about data and ideas, and using
and combining these resources to solve problems. Teachers can encourage students
to “think computationally” by moving technology projects beyond “using” tools and
information toward “creating” tools and information.

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http://www.csta.acm.org/Resources/sub/ResourceFiles/CompThinking.pdf

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Advancing Computational Thinking via Scenario-Based Learning. This is a course

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Advancing Computational Thinking via Scenario-Based Learning. This is a course

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http://webs.purduecal.edu/sunrise/professional-development-opportunities/summer-institute-i/advancing-computational-thinking-via-scenario-based-learning/

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Computational Thinking
Jeannette M. Wing 

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Computational Thinking
Jeannette M. Wing 

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http://research.microsoft.com/en-us/um/redmond/events/asiafacsum2012/day1/Jeannette_Wing.pdf

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A Close-up on CSE 3: Fluency with Informational Technology 

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A Close-up on CSE 3: Fluency with Informational Technology 

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http://acsweb.ucsd.edu/~vkle/CSE3/Lab9/PowerPoint.pdf

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http://www.ictineducation.org/home-page/2013/11/4/computational-thinking-and-spreadsheets.html

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One way you can "get into" computational thinking is through spreadsheets. Taking a practical view of what "computational thinking" means (see What is Computational Thinking?), I'd say that spreadsheets definitely fit the bill. In order to try to solve a problem using a spreadsheet, which is a tool for modelling or simulation, you have to do the following things:

Work out what it is you are trying to find out

Frame the problem in terms a computer (spreadsheet) will understand

Work out what the influential changeable elements are (ie the variables)

Decide what operation/s is/are required, ie what algorithm is/are needed

Design the spreadsheet

Construct it, automating as much of it as possible, especially the error-checking

Test it

Decide on the best (eg most efficient) solution

As a bonus, if you use Excel then you will automatically have the built-in programming language, Visual Basic for Applications (VBA). In a forthcoming post I will relate what the benefits of VBA are. In another post or two I will give examples of spreadsheets I've created that exemplify computational thinking.

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One way you can "get into" computational thinking is through spreadsheets. Taking a practical view of what "computational thinking" means (see What is Computational Thinking?), I'd say that spreadsheets definitely fit the bill.

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https://www.computer.org/csdl/proceedings/fie/2011/468/00/06142980.pdf

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COMPUTATIONAL THINKING ACROSS THE CURRICULUM

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COMPUTATIONAL THINKING ACROSS THE CURRICULUM

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http://www.csta.acm.org/Curriculum/sub/CurrFiles/CTExamplesTable.pdf

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COMPUTATIONAL THINKING ACROSS THE CURRICULUM

# data[].attributes.subject
COMPUTATIONAL THINKING ACROSS THE CURRICULUM

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http://www.csta.acm.org/Curriculum/sub/CurrFiles/CTExamplesTable.pdf

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Computational Thinking with Spreadsheet:
Convolution, High-Precision Computing and Filtering
of Signals and Images International Journal of Computer Applications (0975 - 8887)
Volume 60 - No. 19, December 2012
 

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Computational Thinking with Spreadsheet:
Convolution, High-Precision Computing and Filtering
of Signals and Images International Journal of Computer Applications (0975 - 8887)
Volume 60 - No. 19, December 2012
 

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http://research.ijcaonline.org/volume60/number19/pxc3884405.pdf

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Teaching Computational Thinking to Non computing Majors Using Spreadsheet Functions

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Teaching Computational Thinking to Non computing Majors Using Spreadsheet Functions

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http://www.researchgate.net/publication/251422111_Teaching_Computational_Thinking_to_Non_computing_Majors_Using_Spreadsheet_Functions

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Teaching Computational Thinking to Non computing Majors Using Spreadsheet Functions

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Recently, higher education has seen an increasing emphasis on the prominent role of computational thinking in all disciplines. Computational thinking is advocated as not only a fundamental skill...

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Reigniting the economy with computational thinking

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Reigniting the economy with computational thinking

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http://robotenomics.com/2014/05/01/reigniting-the-economy-with-computational-thinking/

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I first saw psychologist Daniel Kahneman in 2001, the year before he won the Nobel Prize for Economics. Dan has since become known as the grandfather of Behavioral Economics and a big influence on computer programmers and researchers developing Artificial Intelligence, smartphones and cognitive computing.

In nine words Dan changed how I think. Those 9 words are:

"We think much less than we think we think."

Dan's most important achievements are in his research into human decision making under uncertainty, showing how human decision making behaviors deviate systematically from standard predicted results following economic theories. How we use biases and heuristics - the mental shortcuts we take to make decisions and form opinions.

Kahneman has frequently confirmed the influence of Herbert Simon, a famous American computer scientist and psychologist, and one of the 'founders' of Artificial Intelligence and cognitive science, who won the Turing award in 1975 and the Nobel Prize in Economics in 1973. Like Kahneman, Herb Simon's Nobel Prize in economics resulted for his work in decision-making.

Both Kahneman and Simon taught us how easy it is to make mistakes and fool ourselves through the way we think - or rather don't think.
So how do we change this and change our way of thinking to get better results?
To thrive in this new world of human and machine collaboration and get the best out of the advances in technology requires a new way of thinking. Jeanette Wing, a Carnegie Mellon University professor, research analyst at Microsoft and currently assistant director of the US National Science Foundation's computer programs calls this 'computational thinking.'

Professor Wing has a vision of computational thinking becoming a fundamental skill, ranking alongside reading, writing and arithmetic. The Singapore Government say: "computational thinking should be taught to all Singaporeans and made a national capability."

Businesses such as Boeing, Google (who are committed to expose everyone to this key 21 st century skill), Microsoft and many others are adopting computational thinking to improve their decision-making. According to Jeanette Wing:

Computational thinking can be understood as a fundamental analytical skill that everyone can use to solve problems, design systems, and understand human behavior.

Earlier this week Chris Giles, the Economics Editor of the Financial Times, tweeted a chart showing the growth of demand in the job markets for people with computational thinking skills and the decline of jobs in financial services based on data from the Office of National Statistics:

But as Jeanette Wing states Computational Thinking should be a process everyone learns, not just those involved in computer sciences. As computation and information technology becomes more prevalent, individuals competent in computational thinking are better able to understand the ways which technology can improve the choices and decisions we make.

Computational Thinking is not programming, nor is it about more computer power. You can't just throw more petaflops at a problem and expect it to be solved. Likewise, you can't expect machine learning by itself to learn deeply if it isn't coupled to human debate, reasoning and knowledge.

According to Google specific Computational Thinking techniques include:

Problem decomposition - The ability to break down a task into minute details so that we can clearly explain a process to another person or to a computer, or even to just write notes for ourselves.

Pattern recognition - The ability to notice similarities or common differences that will help us make predictions or lead us to shortcuts. Pattern recognition is frequently the basis for solving problems and designing algorithms. According to some researchers: the secret of the human brain is pattern recognition.

Pattern generalization to define abstractions or models - The ability to filter out information that is not necessary to solve a certain type of problem and generalize the information that is necessary.

Algorithm design - The ability to develop a step-by-step strategy for solving a problem. An algorithm is a series of step-by-step instructions, designed to complete a certain task in a finite amount of time.
Data analysis and visualization
Dan Kahneman's work is particularly relevant to Computational Thinking as we deal with more and more data and more computing power. He teaches that we see patterns in random data; that we are even more prone to see patterns in random data when in possession of a theory predicting such patterns; that we overweight outcomes we can imagine easily; that even though we prefer more information to less we are hopeless at processing it; that we are hopeless at gauging correlations until they are very obvious.

Economists such as Ricardo Hausmann, a Professor of Economics at Harvard University says:

One idea about which economists agree almost unanimously is that, beyond mineral wealth, the bulk of the huge income difference between rich and poor countries is attributable to neither capital nor education, but rather to 'technology.'

But what is often missing from this discussion is a key component of technology - knowhow.

Computational Thinking puts that knowhow into the hands of those that choose to learn this important process. Knowhow is an ability to recognize patterns and respond with effective actions.

For those that want to improve their ability to understand and respond to the changing nature of technology, Computational Thinking can be a powerful way to bridge the gap between the problems of big data, robotics, artificial intelligence and cognitive assistants and improve practical decision making.

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Reigniting the economy with computational thinking

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I first saw psychologist Daniel Kahneman in 2001, the year before he won the Nobel Prize for Economics. Dan has since become known as the grandfather of Behavioral Economics and a big influence on computer programmers and researchers developing Artificial Intelligence, smartphones and cognitive computing. In nine words Dan changed how I think.

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Integrating Computational Thinking into a General
Education Course 

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Integrating Computational Thinking into a General
Education Course 

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http://digitalcommons.georgiasouthern.edu/cgi/viewcontent.cgi?article=2024&context=sotlcommons

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Developing Computational Thinking Skills across the Undergraduate Curriculum

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Developing Computational Thinking Skills across the Undergraduate Curriculum

# data[].attributes.body
https://www.academia.edu/1014702/Developing_Computational_Thinking_Skills_across_the_Undergraduate_Curriculum

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Developing Computational Thinking Skills across the Undergraduate Curriculum

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Academia.edu is a platform for academics to share research papers.

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A Multi-tiered Mentoring Model (M3) for Increasing Minority and Women Participation in Computing

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A Multi-tiered Mentoring Model (M3) for Increasing Minority and Women Participation in Computing

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http://www.uab.edu/ramsaycompthinking/component/content/article?id=33:about-the-m3-project

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Multi-tiered Mentoring Model (M3) tests a new model for sustainable computer science education for a large urban school system's students, who are predominantly minority (98% African American) and underserved (about 30% below the national poverty line). The project targets four different age groups to provide high-level instruction in computational thinking. M3 engages minority students in a culture of computing that includes them in the pipeline to computational-intense careers, which are critical to the economic progress of the US.
M3 has six specific aims:

Recruit a cadre of minority and women middle and high school students into the computing pipeline by presenting engaging technology experiences with mentors;

Expose pre-service secondary education students to pedagogical and technical aspects of computing education, through interdisciplinary peer mentorship;

Extend the coverage of computational thinking among high school teachers in predominantly minority schools with opportunities to both learn and teach computer science topics;

Support undergraduate computer science minority student retention by providing contextualized and meaningful opportunities to create tools for computing education under faculty mentorship;

Engage K-12 administrators and family members of participants through information awareness sessions that highlight the benefits of careers in computing; and

Evaluate the effects of M3 on student self-efficacy, teacher and student aptitude and interest, and historical tracking of career choices among participants.

Tier 1 includes undergraduate computer science and secondary education students from one of the most diverse university campuses in the US. These students learn the basics of computer science and technology education in two fall courses, Introduction to Computing through Alice and Computer Science Education Delivery. In these courses, the Education and CS students work collaboratively to understand the best methods for delivering computer science education in middle and high schools. Student participants design inquiry-based experiences that will form the core lesson plan for the high school course that they will mentor in the spring. Further, the secondary school teachers and PIs participate as active facilitators in the methods course to guide the UAB students toward developing effective teaching tools and curricula for the spring course.

In Tier 2, the Tier 1 UAB students go out to area high schools in the spring and teach what they learned in the fall. The educational opportunity is part of the regular curriculum of the high school and is an alternative to the standard required course that focuses on computer applications (e.g., Microsoft Office). The high school students become adept at computational thinking via lesson plans using topics from CS Unplugged, Scratch and Alice. This becomes an entrée to summer camps in Java and Robotics that are offered in collaboration with UAB. The students also gain pedagogical tools for Tier 3.

In Tier 3, the Tier 2 high school students (aided by their UAB mentors) teach Alice camps (30 hours) to middle school students during the summer at UAB. This provides an early engagement into computational thinking for the middle school students.

This demonstration project has potential for local impact by serving 180 high school students, 60 middle school students, 18 university students, and 12 high school teachers. Its broader impact is to demonstrate that mentoring models like M3 can provide sustainable education opportunities for underserved schools and increase the pipeline to CS-related careers, including those in CS education.

Principal investigators:
J. Michael Wyss, University of Alabama at Birmingham, Jeff Gray, University of Alabama
Julian Daily, Shaundra Daily, g8four
Gypsy Abbott, Alan Shih, Scott Snyder, University of Alabama at Birmingham
Karzetta Bester and Joanne Stevens, Birmingham City Schools

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Alice and Computer Science Education Delivery

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UAB - M3 Computational Thinking - M3 Computational Thinking

# data[].attributes.attachment_link.description
Multi-tiered Mentoring Model (M3) tests a new model for sustainable computer science education for a large urban school system's students, who are predominantly minority (98% African American) and underserved (about 30% below the national poverty line). The project targets four different age groups to provide high-level instruction in computational thinking.

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Microsoft, Carnegie Mellon Establish Center for Computational Thinking

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Microsoft, Carnegie Mellon Establish Center for Computational Thinking

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https://news.microsoft.com/2007/03/26/microsoft-carnegie-mellon-establish-center-for-computational-thinking/

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PITTSBURGH - March 26, 2007 - Microsoft Corp. and Carnegie Mellon University today announced the creation of the Microsoft Carnegie Mellon Center for Computational Thinking. The center was made possible through a three-year, $1.5 million grant from Microsoft.

The center represents a long-term collaboration between Microsoft Research and Carnegie Mellon's Computer Science Department and will support research in emerging areas of computer science, particularly those that can influence the thinking of other disciplines.

"Increasingly, scientists and researchers rely on computer science to enable them to sift through massive amounts of data and find breakthroughs that could provide new insights into the human body, the earth we live on and even the universe," said Rick Rashid, senior vice president of Microsoft Research. "We are eager to explore this exciting new area of research with Carnegie Mellon."

Rashid spoke at the Carnegie Mellon Symposium for Computational Thinking. Computational thinking, as developed by Jeannette M. Wing, head of Carnegie Mellon's Computer Science Department, involves solving problems, designing systems and understanding human behavior by drawing on the concepts fundamental to computer science.

"Carnegie Mellon itself is an example of how the power of computational thinking can energize disciplines across the campus," said University President Jared L. Cohon. "Our psychologists use machine learning techniques to decipher brain scans. Our biologists build computer models of cells to find causes of cancer. And business professors harness artificial intelligence to better understand markets. We are delighted that Microsoft is joining us in furthering this concept."

The Microsoft Carnegie Mellon Center for Computational Thinking will support research in core computer science areas using an approach called problem-oriented explorations, pioneered by Carnegie Mellon's ALADDIN Center. Researchers from a variety of fields will address specific, real-world problems; initial topics include privacy, e-commerce, multicore computing and embedded medical devices. In addition, the center will develop and disseminate courses and curricula suitable for graduate and undergraduate students, as well as K-12 classes.

"Computer technology has rapidly transformed education, commerce and entertainment, but - more profoundly - computational thinking is transforming how new science is discovered in fields as varied as biology, astronomy, statistics and economics," said Wing.

As part of the ongoing relationship with Microsoft, the center will host a series of "mindswaps" organized as annual meetings between Microsoft and Carnegie Mellon researchers for the purpose of data sharing, problem solving, resource sharing and collaborating on bigger computer challenges. Mindswaps will ultimately lead to problem-oriented explorations as part of the work of the center.

Microsoft is deeply committed to education at all levels and has a long history of collaboration throughout academia. This institute is the result of work by the External Research & Programs Group and becomes the eighth such center Microsoft Research has formed worldwide to pursue particular areas of research.

About Carnegie Mellon University's Computer Science Department

The Computer Science Department is the largest of six academic units within Carnegie Mellon's School of Computer Science. Consistently ranked among the world's premier institutions for computer science research and education, the school also includes leading programs in robotics, human-computer interaction, software research, language technologies and machine learning.

About Microsoft Research

Founded in 1991, Microsoft Research is dedicated to conducting both basic and applied research in computer science and software engineering. Its goals are to enhance the user experience on computing devices, reduce the cost of writing and maintaining software, and invent novel computing technologies. Researchers focus on more than 55 areas of computing and collaborate with leading academic, government and industry researchers to advance the state of the art in such areas as graphics, speech recognition, user-interface research, natural language processing, programming tools and methodologies, operating systems and networking, and the mathematical sciences. Microsoft Research employs more than 700 people in five labs located in Redmond, Wash.; Silicon Valley, Calif.; Cambridge, England; Beijing, China; and Bangalore, India. Microsoft Research collaborates openly with colleges and universities worldwide to enhance the teaching and learning experience, inspire technological innovation, and broadly advance the field of computer science. More information can be found at http://www.research.microsoft.com.

About Microsoft

Founded in 1975, Microsoft (Nasdaq "MSFT") is the worldwide leader in software, services and solutions that help people and businesses realize their full potential.

Note to editors: If you are interested in viewing additional information on Microsoft, please visit the Microsoft® Web page at http://www.microsoft.com/presspass on Microsoft's corporate information pages. Web links, telephone numbers and titles were correct at time of publication, but may since have changed. For additional assistance, journalists and analysts may contact Microsoft's Rapid Response Team or other appropriate contacts listed at http://www.microsoft.com/presspass/contactpr.mspx.

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Carnegie Mellon 's Computer Science Department

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Microsoft Carnegie Mellon Center for Computational Thinking

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Computer Science Department The Computer Science Department

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Carnegie Mellon Symposium for Computational Thinking

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Carnegie Mellon 's School of Computer Science

# data[].attributes.attachment_link.title
Microsoft, Carnegie Mellon Establish Center for Computational Thinking

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PITTSBURGH - March 26, 2007 - Microsoft Corp. and Carnegie Mellon University today announced the creation of the Microsoft Carnegie Mellon Center for Computational Thinking. The center was made possible through a three-year, $1.5 million grant from Microsoft.

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Computational thinking as an essential skillset for our next-generation innovators

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Computational thinking as an essential skillset for our next-generation innovators

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https://news.microsoft.com/en-sg/2015/04/15/computational-thinking-as-an-essential-skillset-for-our-next-generation-innovators/

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Over the past few decades, technology has radically transformed how we work and play. Automation has changed entire industries, and the Internet has revolutionised how we access information and make decisions.

The imminent reality is that our world will only come to depend more and more on technology, and jobs will become increasingly skills-biased. The workforce of tomorrow has to not only work productively to "consume" technology, but also understand how technology works.

This is especially true for Singapore - where we have a vision to become the first Smart Nation in the world. More so than other nations, we have an urgent and critical need to develop computational thinking as a national capability to lay the foundational building blocks that will realise this vision. After all, a large part of being a Smart Nation is tapping new technologies to problem-solve.

Computational thinking, often defined as a thought process that allows one to break down problems and formulate solutions systematically - much like how computers "think", has come into focus as a fundamental skill for the next-generation workforce. The ability to problem-solve by applying logic and creative thinking are skills that employers in every sector will seek, not just in technology.

To reading, writing and arithmetic, we need to add computational thinking to every child's analytical ability. While often imparted through coding, computational thinking is embraced not only for computer science applications, but also for its wide applicability to solve everyday problems.

An example is how two young medical students who envisioned the use of technology to help people live and stay healthy applied computational thinking and coding to develop an application called Eyenaemia. Eyenaemia is a non-invasive and easily-accessible screening tool for anaemia made for use by anyone. With this application, screening is now as simple as taking a selfie with a smart phone - after which the application analyses the conjunctiva and calculates the risk of anaemia, putting years of medical training into the hands of untrained users.

Stories like these inspired Microsoft to speak to 1,850 students under 24 years old in eight countries across Asia Pacific about their interest in coding. They told us that they recognise the value of coding in their education and the opportunities it creates for their future careers.

In Singapore, 76 percent of the 250 students we spoke to indicated that they want to know more about coding, and 72 percent said that coding is important to their future careers. 59 percent of these students agreed that coding will be relevant to all careers in the future, regardless of areas of specialisation.

This revealed a broad understanding amongst students of the impact of technology considering they represented a variety of specialisation including arts and humanities, STEM (Science, Technology, Engineering, and Mathematics) and business. What is especially interesting is that 78 percent of students who specialise in the arts and humanities want to learn more about coding. This strong positivity towards coding was also shared equally by male (79 percent) and female (74 percent) students, although coding has been a field dominated by males.

While the battle may be half-fought with keen interest from the students, there is still much to be done to accelerate the development of computational thinking among our youths.

The study revealed that students in Singapore feel relatively unsupported in their interest for coding. Even though 66 percent of the students we spoke to wish coding is offered as a core subject in their schools, only 45 percent said they had the opportunity to learn coding in school either as a core subject or an extracurricular activity. This is one of the lowest figures among the Asia Pacific countries surveyed. Furthermore, only 49 percent of students said their parents think coding is important to their future.

The evident disconnect between students' interests and the support they are receiving from schools and at home indicate a pressing need for educators and parents in Singapore to better support our youths to understand computational thinking. The majority of students (54 percent) said they would be willing to take up coding classes outside of regular school hours. Currently, 44 percent of the students have already looked beyond the classroom and picked up coding on their own through online tutorials.

Today, programmes such as Code@SG by the Infocomm Development Authority (IDA) acknowledges the importance of computational thinking as an essential skill that will future-proof our youths. Through Code@SG, IDA works closely with stakeholders to introduce coding to more students in schools in a fun and easy-to-learn manner.

However, the drive towards computational thinking as a national capability is not the sole responsibility of government agencies. Private organisations and communities can contribute actively too. Microsoft's YouthSpark #WeSpeakCode campaign has the mission to inspire youths in Singapore and around the region to start coding. By connecting student coders of all skill levels with the tools, resources, and experiences they need to turn their innovative ideas into reality regardless of the amount of time they can invest, we hope to equip youths with computational thinking skills and eventually nurture a generation of future innovators into savvy leaders and citizens that can make a real impact for a better Singapore.

While that is our long-term goal, what is more important now is to get everyone started on their coding journey, be it in big or small ways, in order for youths to have the right skillsets to unlock the opportunities in our future.

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Computational thinking as an essential skillset for our next-generation innovators

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Over the past few decades, technology has radically transformed how we work and play. Automation has changed entire industries, and the Internet has revolutionised how we access information and make decisions. The imminent reality is that our world will only come to depend more and more on technology, and jobs will become increasingly skills-biased.

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Computational Thinking free course missed it check back later

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Computational Thinking free course missed it check back later

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https://computationalthinkingcourse.withgoogle.com/course?use_last_location=true

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Computational Thinking (CT) is a problem solving process that includes a number of characteristics and dispositions. CT is essential to the development of computer applications, but it can also be used to support problem solving across all disciplines, including math, science, and the humanities. Students who learn CT across the curriculum can begin to see a relationship between subjects as well as between school and life outside of the classroom.

CT involves a number of skills, including:

Formulating problems in a way that enables us to use a computer and other tools to help solve them

Logically organizing and analyzing data

Representing data through abstractions such as models and simulations

Automating solutions through algorithmic thinking (a series of ordered steps)

Identifying, analyzing, and implementing possible solutions with the goal of achieving the most efficient and effective combination of steps and resources

Generalizing and transferring this problem solving process to a wide variety of problems

These skills are supported and enhanced by a number of dispositions or attitudes that include:

Confidence in dealing with complexity

Persistence in working with difficult problems

Tolerance for ambiguity

The ability to deal with open ended problems

The ability to communicate and work with others to achieve a common goal or solution

CT concepts are the mental processes (e.g. abstraction, algorithm design, decomposition, pattern recognition, etc) and tangible outcomes (e.g. automation, data representation, pattern generalization, etc) associated with solving problems in computing. These include and are defined as follows:

Abstraction: Identifying and extracting relevant information to define main idea(s)

Algorithm Design: Creating an ordered series of instructions for solving similar problems or for doing a task

Automation: Having computers or machines do repetitive tasks

Data Analysis: Making sense of data by finding patterns or developing insights

Data Collection: Gathering information

Data Representation: Depicting and organizing data in appropriate graphs, charts, words, or images

Decomposition: Breaking down data, processes, or problems into smaller, manageable parts

Parallelization: Simultaneous processing of smaller tasks from a larger task to more efficiently reach a common goal

Pattern Generalization: Creating models, rules, principles, or theories of observed patterns to test predicted outcomes

Pattern Recognition: Observing patterns, trends, and regularities in data

Simulation: Developing a model to imitate real-world processes

See our Computational Thinking Concepts Guide for a printable version of this list, along with teaching tips for each concept.

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Google for Education: Computational Thinking

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Computational Thinking (CT) is a problem solving process that includes a number of characteristics and dispositions. CT is essential to the development of computer applications, but it can also be used to support problem solving across all disciplines, including math, science, and the humanities.

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http://www.csta.acm.org/Curriculum/sub/CurrFiles/472.11CTTeacherResources_2ed-SP-vF.pdf

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http://www.cs.cmu.edu/link/research-notebook-how-design-practices-affect-results

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By Steven P. Dow

In their 2001 book Art & Fear: Observations On the Perils (and Rewards) of Artmaking, David Bayles and Ted Orland share a story about a ceramics teacher who divided his class into two groups. He told one half they would be graded on quantity, so they should "produce as many ceramics you can in one quarter, that will be your grade," while he told the other half they would be graded based on one good ceramic.

Balyes and Orland found that "while the quantity group was busily churning out piles of work--and learning from their mistakes--the quality group had sat theorizing about perfection, and in the end had little more to show for their efforts than grandiose theories and a pile of dead clay." Iterative deliberate practice led to better results.

Iteration, or, in simpler terms, repetition, is a basic tenet of design practice. (In mathematics and computer science, iteration describes the act of solving a problem by computing a series of approximations, each building on the previous one, to achieve an accurate result.)

While the story about the ceramics class resonates with some people, others might say, "This isn't how it works in industry where we have real time constraints. Yes, it would be wonderful to try lots of alternatives, but we simply don't have time." This raises a question about how design practices affect results--under time constraints, should people iterate or should they focus on refinement?

My research centers on questions about creativity and collaboration. I seek to uncover the cognitive and social factors that affect the often-messy process of design and scientific inquiry, and to investigate these issues within the modern landscape of social media, online gaming and crowdsourcing. Ultimately, I'm interested in understanding and improving how people can design better products, services and systems.

I developed these interests as a post-doc at Stanford University. Stanford has a school of design known as the "dSchool." About five years ago, they began to teach a problem-solving process known as "design thinking." Design thinking is an interdisciplinary method of problem solving which puts a premium on prototyping and developing empathy for the target users.

These days, when you step into the dSchool, you'll find posters urging students to defer judgment, go for quantity, encourage "wild" ideas, build on the ideas of others, have one conversation at a time, stay focused on their topic, and think "visually." Rolling whiteboards, adjustable furniture and ongoing student projects are on display, encouraging collaboration and a free exchange of ideas. These are also signs of commitment to design thinking that say, "Believe in Process." Often the commitment to particular problem solving strategies rests largely on faith, not on concrete, empirical evidence.

That's where my research comes in. My colleagues and I have run a series of experiments that examine how prototyping practices affect design results.

But how can we measure creative thinking skills? Scientists have long been interested in creativity. One classic insight experiment is the nine-dot problem, invented by American psychologist Norman Maier in 1930. (Figure 1) Participants must connect nine dots with four straight lines without ever lifting the pen. The insight that participants often miss is that the lines must extend "outside the box." (Yes, that's where the phrase "outside-the-box thinking" originated.) The length of time it takes people to solve the problem provides a dependent measure. (Figure 2)

When we thought about how design and engineering unfold in real practice, we realized we needed a better Petri dish. Unlike the nine-dot problem, we wanted participants to demonstrate creativity. Real-world design problems have many possible solutions and many different paths to success. We also wanted to have objective and subjective criteria--we needed a good way to contrast solutions people come up with.

Our insight here was to leverage the "egg drop design" task where participants design a vessel (like the one in Figure 3) to protect a raw egg from a fall. Our dependent variable: how high can you drop the egg without the egg breaking?

In one experiment, in the spirit of the ceramics story, we explicitly examined iteration. Half of our participants were encouraged to rapidly generate new ideas for egg-drop containers; the other half focused on perfecting one design. Everyone came up with very different ideas, with varying degrees of success. (Figure 4)

The results showed quantitatively that, even under tight time constraints, people who were forced to rapidly iterate outperformed those who didn't.

The experimental results were not particularly surprising, and confirmed the intuitions of the ceramics teacher. Most of us would expect that rapid iteration would yield benefits. But, what was really interesting is what we saw qualitatively in the participant interviews: Independent of study condition, participants tended to pick one idea and stick with it. Participants said things such as, "For some reason, (this design) seems to be the only (way). There needs to be a platform and then as good of a cushion as possible. I don't see any other way." Or, "I kind of just had one idea and I was going to try to make it work." Or, "I went with the whole parachute idea - I had from the beginning."

Time constraints certainly contributed to participants' limited exploration, but more interestingly, people felt they had fully explored the concepts, and they could not see any other alternatives for the materials.

In design, people often fixate on one solution without considering others. Participants in our egg-drop experiments exhibited a psychological effect known as functional fixation, first studied by German-American psychologist Karl Duncker back in the 1930s. He did a series of experiments that have come to be known as the "Candle Problem." Duncker presented his participants with a table pushed up against a wall. The table held a candle, a box of thumbtacks and a pack of matches. Duncker then asked his participants to affix the candle to the wall so that the wax does not drip on the table. This is a challenging puzzle for most people.

The hidden insight is that the box of tacks--once emptied--can be tacked to the wall and used to hold the candle and catch the dripping wax. Participants in Duncker's experiments often exhibited functional fixation; they viewed the box's only function as a container for tacks. As in our egg drop experiment, once the participants developed an initial idea, they became fixated on making that idea work, instead of exploring different ideas.

Subsequent tests of Duncker's candle problem have showed that if the exact same materials are provided, but the tacks are left outside the box, loose on the table, people are much more likely to solve the puzzle.

Following our egg-drop experiment, we wondered, instead of just iterating solutions to a problem and soliciting feedback on each iteration, what if people created and tried different designs in parallel? (Figure 5)

To answer this empirical question, we gave participants a design task where the solutions were both creatively diverse and objectively measurable. This time, instead of egg-drop vessels, we had participants design Web advertisements for Stanford's Ambidextrous magazine, a student-run journal of design and engineering. We were then able to place the ads online and collect objective outcome metrics--how many clicks an ad receives, compared to how many times it's shown.

In the study, each participant created five prototypes and a final design within the same overall time period. In the Serial condition, participants received critiques on one prototype at a time. Participants in the Parallel condition created three prototypes, received critiques on all three, then made two more prototypes, and received critiques again. The critique statements were technical in nature, intended to provide high-level direction, without using explicitly positive or negative language. Importantly, the only difference between conditions was the timing of the critique.

In the end, we got lots of ads. (Figure 6) We took all 33 final participant ads and launched a 15-day ad campaign online. In total, we generated about 1 million ad appearances.

What were the results of this experiment? According to the ad campaign data, Web users clicked more Parallel ads per appearance than Serial ads. Not only did Parallel ads generate more visitors to the Ambidextrous website, those visitors spent more time on the client site, so the Parallel ads did better at reaching the target audience.

Moreover, independent expert raters--both ad professionals and the magazine editors-- judged the Parallel ads to be better than Serial ads. By all measures, the "Parallel" process outperformed the serial process.

Why did we see this difference? Why does a parallel approach lead to better results?

One reason has to do with our basic human ability to draw contrasts. In a 2003 study, Dedre Gentner, Jeffrey Loewenstein and Leigh Thompson compared a traditional case-based learning approach--where participants independently read and described separate case studies--to a more comparative approach. In the comparative approach, participants were explicitly prompted to describe the parallels of both solutions. They found that when prompted to explicitly draw a comparison, participants were nearly three times more likely to understand the principle behind the cases and to transfer what they learned. People do a better job of capturing the underlying structure when they compare.

Going back to our ad study, then, we can surmise that comparing critique statements on two ads side-by-side helped participants extract important graphic design principles.

The interviews provided additional context. In design, feedback is often a double-edged sword: it helps people learn, but it can also damage the ego because people tend to invest emotionally in the things they produce. Eight out of 17 participants in the Serial group reacted negatively, calling the feedback "negative." One participant told us, "There was a short period (after each critique) where the emotional response overwhelmed any positive logical impact."

None of the Parallel participants described the critiques as negative. Although the language in the Serial critiques was not any more negative than the Parallel critiques, it was just perceived that way. The groups who worked on ads using the Parallel approach did not emotionally invest in individual solutions; instead, they were open to multiple possible outcomes.

We then asked ourselves, "If people react this way to critiques from a random expert, how would this play out in small groups? In groups, would creating and sharing multiple designs improve the outcome, over just bringing one design?"

Turing Award winner Fred Brooks once said, "Prototypes can be more articulate than people." Prototypes help ground communication and embody the entailments of design concepts. However, the presence of a concrete prototype may--for better or worse--focus a discussion on refining that idea, rather than thinking more broadly. Moreover, people tend to polish prototypes to look good in front of their colleagues.

Alternatively, designers may choose to share multiple prototypes at group meetings. In theory, this should help reduce fixation and give group members license to be more candid and critical of their own and other's ideas. But generating multiple alternatives can also have adverse effects. It leaves less time to polish each idea, and increasing the number of options on the table--and the number of implications that arise from these alternatives--may complicate the decision process and jeopardize a group's ability to achieve consensus.

We hypothesized that sharing multiple prototypes would lead to better results because people would explore more concepts and be more open to adopting and merging new ideas. Again, we had participants design Web advertisements, this time for FaceAIDS.org, a non-profit organization dedicated to fighting AIDS in Africa. Again, we could launch the ads online through Google's ad networks and collect relative performance metrics.

We recruited 84 participants, balanced for prior experience and gender, and placed them into one of three conditions. In the "share multiple" condition, participants created three ad designs and shared all three in a group meeting with their partner, where they critiqued each other's ideas. In the "share best" condition, participants created three ads, but then chose only one to share with their partner. In the "share one" condition, participants spent an equivalent amount of time on just one ad, and then shared that with their partner. We chose these three conditions to separate the effects of producing multiple designs from sharing multiple designs.

In all conditions, after the group meeting, each of our 84 participants went back and individually created a final ad. Some were great, some were cliché, and some were very clever. These final ads were launched simultaneously in a 12-day ad campaign through Google AdWords. In total, we generated 474,539 impressions. We also had a range of experts--including the FaceAIDS clients-- rate the ads on their effectiveness.

The results showed that Web users clicked more ads per appearance created by the "Share Multiple" conditions than either of the other conditions. (Figure 7) Moreover, ad experts and the clients all rated Share Multiple ads higher than the other conditions.

Again we must ask, "Why does creating and sharing multiple designs lead to better results?" Our analysis examined the literature on examples, design exploration, conceptual blending and group rapport.

For one thing, it helps to have more ideas on the table. In a 2010 study, Brian Lee, Scott Klemmer and colleagues of Stanford University's HCI Group found that people produce better Web designs when given a gallery of examples. Examples expose people to more design features and diverse perspectives.

Were there differences in how participants in each condition explored concepts? How much did that group meeting affect the final designs? Interviews revealed that participants in the Share Best and Share One conditions tended to stick with what they had. The Share Multiple groups took the best of multiple concepts and blended their ideas.

We quantified this notion of blending concepts by counting features that migrated from one participant's early designs into their partner's final design--similar kinds of images, shared phrasing, and a reddish background color. It turns out that participants in the Share Multiple conditions borrowed far more features than pairs in the other conditions. (Figure 8)

One reason for this was the visibility of work. Much like a design studio, people learn by simply being able to see their peers' ideas. It exposes people to the space of possibilities. Further, during "crits," Share Multiple participants were less invested in a single outcome, so they did a great job of exchanging ideas, while Share One and Share Best participants tended to bottle up and sit there in silence for fear of offending their partner.

Our studies revealed a number of quantitative differences of sharing multiple designs. We concluded that better design was a function of better comparison, more individual exploration, more feature-sharing, increased in-group rapport, and more conversational turns. A simple change in the process not only produced better designs, it led to more idea sharing and better overall collaboration.

This research on creative process directly informs my future projects. I'm interested in how these phenomena play out in new contexts, particularly with online crowds. I have two new projects, supported by grants from the National Science Foundation, which will examine the intersection of design and crowdsourcing. The first is a collaborative effort with Bjoern Hartmann of the University of California at Berkeley that explores how group dynamics affect creative work done by online crowds. The second is a collaborative effort with Liz Gerber of Northwestern University that examines at how we can bring crowdsourcing resources--such as social media, Amazon Mechanical Turk, and crowd-funding--into the classroom to help inform student innovations.

Crowdsourcing techniques and web analytics provide an opportunity to do experimental research on creativity with objective outcomes. We have been able to get leverage by giving participants tasks--like Web banner ad design--where the solutions are both creatively different and objectively measurable. Our work shows that design thinking methods have measurable value in the online world, and that simple process changes can lead to better solutions.

-- Steven Dow is an assistant professor of human-computer interaction at Carnegie Mellon University, where he researches human-computer interaction, creative problem solving, prototyping practices and crowdsourcing. He is a recipient of Stanford University's Postdoctoral Research Award and co-recipient of a Hasso Plattner Design Thinking Research Grant. Dow earned both his M.S. and Ph.D. in human-centered computing at the Georgia Institute of Technology, and a B.S. in industrial engineering at the University of Iowa.

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Hasso Plattner Design Thinking Research Grant

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Research notebook: How design practices affect results

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By Steven P. Dow In their 2001 book Art & Fear: Observations On the Perils (and Rewards) of Artmaking, David Bayles and Ted Orland share a story about a ceramics teacher who divided his class into two groups.

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Modeling is an essential skill of the experienced communication designer. From the design of relatively simple two-fold brochures, to complex websites, and to services, the designersÛª work involves understanding the projectÛªs information and the context in a structured fashion. 

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Modeling is an essential skill of the experienced communication designer. From the design of relatively simple two-fold brochures, to complex websites, and to services, the designersÛª work involves understanding the projectÛªs information and the context in a structured fashion. 

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http://www.cs.cmu.edu/calendar/computational-thinking-seminar-6

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Modeling is an essential skill of the experienced communication designer. From the design of relatively simple two-fold brochures, to complex websites, and to services, the designers‰Ûª work involves understanding the project‰Ûªs information and the context in a structured fashion. Designers also use common models to critique and revise their solutions. I will illustrate how computational thinking is already part of communication design activities. I will then present early experiments using computing in visual design from the Visible Language Workshop at MIT. These examples will be followed by my own work on dynamic information design, where I attempted to use the multiagent model for representing information design. Based on this overview, I will speculate that the notion of computational intuition may be a valuable asset for communication designers.

Suguru Ishizaki uniquely combines scholarly and practical qualifications with 18 years of experience in interaction design, visual design and basic research on visual and verbal communication. His current research focuses on visual communication pedagogy‰ÛÓincluding intelligent critiquing systems, assessment methods, visual communication literacy, and online self-learning environments for non-designers. In his collaboration with David Kaufer in the past 10 years on text analysis, he has designed and implemented a suite of computational tools for the analysis and interactive visualization of rhetorical strategies.

Suguru is currently an Associate Professor of Rhetoric and Communication Design in the Department of English at Carnegie Mellon. Before this appointment, he worked at QUALCOMM on the research and development of mobile user interfaces. Prior to that, he was on the faculty of the School of Design at Carnegie Mellon. He earned his Ph.D. and M.S. at MIT‰Ûªs Media Laboratory where he studied under Muriel Cooper and William Mitchell, after receiving his Bachelor Art & Design from Tsukuba University, Japan. He is the author of Improvisational Design: Continuous Responsive Digital Communication (MIT Press, 2003), and a co-author of The Power of words: Unveiling the Speaker and Writer‰Ûªs Hidden Craft (Erlbaum 2004).

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Modeling is an essential skill of the experienced communication designer. From the design of relatively simple two-fold brochures, to complex websites, and to services, the designers‰Ûª work involves understanding the project‰Ûªs information and the context in a structured fashion. Designers also use common models to critique and revise their solutions.

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The quilt displays a multicolored "word cloud" of the 1000 most common passwords in the social gaming website

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The quilt displays a multicolored "word cloud" of the 1000 most common passwords in the social gaming website

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http://www.cs.cmu.edu/news/cranor%E2%80%99s-%E2%80%9Csecurity-blanket%E2%80%9D-wins-recognition-visualization-contest

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International Science & Engineering Visualization Challenge

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CyLab Usable Privacy and Security Laboratory

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Language Technologies Institute Special Talk Carnegie Mellon School of Computer Science 5000 Forbes Avenue Pittsburgh

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Allen Newell Award for Research Excellence Mark Stehlik SCS

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Cranor's "Security Blanket" Wins Recognition in Visualization Contest | Carnegie Mellon School of Computer Science

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Lorrie Cranor, an associate professor of computer science and engineering and public policy, and director of the CyLab Usable Privacy and Security Laboratory, was recently recognized as one of 18 winners, honorable mentions and people's choice awardees from the International Science & Engineering Visualization Challenge.

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communication design Computtional thinking and 

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communication design Computtional thinking and 

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http://www.cs.cmu.edu/calendar/computational-thinking-seminar-6

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Modeling is an essential skill of the experienced communication designer. From the design of relatively simple two-fold brochures, to complex websites, and to services, the designers‰Ûª work involves understanding the project‰Ûªs information and the context in a structured fashion. Designers also use common models to critique and revise their solutions. I will illustrate how computational thinking is already part of communication design activities. I will then present early experiments using computing in visual design from the Visible Language Workshop at MIT. These examples will be followed by my own work on dynamic information design, where I attempted to use the multiagent model for representing information design. Based on this overview, I will speculate that the notion of computational intuition may be a valuable asset for communication designers.

Suguru Ishizaki uniquely combines scholarly and practical qualifications with 18 years of experience in interaction design, visual design and basic research on visual and verbal communication. His current research focuses on visual communication pedagogy‰ÛÓincluding intelligent critiquing systems, assessment methods, visual communication literacy, and online self-learning environments for non-designers. In his collaboration with David Kaufer in the past 10 years on text analysis, he has designed and implemented a suite of computational tools for the analysis and interactive visualization of rhetorical strategies.

Suguru is currently an Associate Professor of Rhetoric and Communication Design in the Department of English at Carnegie Mellon. Before this appointment, he worked at QUALCOMM on the research and development of mobile user interfaces. Prior to that, he was on the faculty of the School of Design at Carnegie Mellon. He earned his Ph.D. and M.S. at MIT‰Ûªs Media Laboratory where he studied under Muriel Cooper and William Mitchell, after receiving his Bachelor Art & Design from Tsukuba University, Japan. He is the author of Improvisational Design: Continuous Responsive Digital Communication (MIT Press, 2003), and a co-author of The Power of words: Unveiling the Speaker and Writer‰Ûªs Hidden Craft (Erlbaum 2004).

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Modeling is an essential skill of the experienced communication designer. From the design of relatively simple two-fold brochures, to complex websites, and to services, the designers‰Ûª work involves understanding the project‰Ûªs information and the context in a structured fashion. Designers also use common models to critique and revise their solutions.

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ART&&Code: DIY 3D Sensing and Visualization

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ART&&Code: DIY 3D Sensing and Visualization

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Electronic Art Language Technologies Institute Special Talk Carnegie Mellon School of Computer Science 5000 Forbes Avenue Pittsburgh

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Allen Newell Award for Research Excellence Mark Stehlik SCS

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ART&&Code: DIY 3D Sensing and Visualization | Carnegie Mellon School of Computer Science

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Hands-on workshops (not included in the General Registration fee; generally $80 for each 2-hour session) include arts-engineering classes in a variety of popular programming toolkits, including Processing, OpenFrameworks, Max/MSP, PureData, Arduino, C++, C#, and Scratch.

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Computational Thinking: Celebrating Six Years of MSR-CMU Collaboration

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Computational Thinking: Celebrating Six Years of MSR-CMU Collaboration

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http://www.cs.cmu.edu/calendar/computational-thinking-celebrating-six-years-msr-cmu-collaboration

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Allen Newell Award for Research Excellence Mark Stehlik

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Specification and Verification in Introductory Computer Science

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Computer Science Department Language Technologies Institute Special Talk Carnegie Mellon School of Computer Science 5000 Forbes Avenue Pittsburgh

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Computational Thinking: Celebrating Six Years of MSR-CMU Collaboration | Carnegie Mellon School of Computer Science

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9:10 am - The Importance of the Center for Computational Thinking - Randy Bryant Dean and University Professor, School of Computer Science

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Article from the Link - magazine of Carnigie Mellon University

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Article from the Link - magazine of Carnigie Mellon University

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http://www.cs.cmu.edu/link/research-notebook-computational-thinking-what-and-why

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By Jeannette M. Wing

In a March 2006 article for the Communications of the ACM, I used the term "computational thinking" to articulate a vision that everyone, not just those who major in computer science, can benefit from thinking like a computer scientist [Wing06]. So, what is computational thinking? Here's a definition that Jan Cuny of the National Science Foundation, Larry Snyder of the University of Washington, and I use; it was inspired by an email exchange I had with Al Aho of Columbia University:

Computational thinking is the thought processes involved in formulating problems and their solutions so that the solutions are represented in a form that can be effectively carried out by an information-processing agent. [CunySnyderWing10]

Informally, computational thinking describes the mental activity in formulating a problem to admit a computational solution. The solution can be carried out by a human or machine, or more generally, by combinations of humans and machines.

My interpretation of the words "problem" and "solution" is broad. I mean not just mathematically well-defined problems whose solutions are completely analyzable, e.g., a proof, an algorithm, or a program, but also real-world problems whose solutions might be in the form of large, complex software systems. Thus, computational thinking overlaps with logical thinking and systems thinking. It includes algorithmic thinking and parallel thinking, which in turn engage other kinds of thought processes, such as compositional reasoning, pattern matching, procedural thinking, and recursive thinking. Computational thinking is used in the design and analysis of problems and their solutions, broadly interpreted.
The Value of Abstraction
The most important and high-level thought process in computational thinking is the abstraction process. Abstraction is used in defining patterns, generalizing from specific instances, and parameterization. It is used to let one object stand for many. It is used to capture essential properties common to a set of objects while hiding irrelevant distinctions among them. For example, an algorithm is an abstraction of a process that takes inputs, executes a sequence of steps, and produces outputs to satisfy a desired goal. An abstract data type defines an abstract set of values and operations for manipulating those values, hiding the actual representation of the values from the user of the abstract data type. Designing efficient algorithms inherently involves designing abstract data types.

Abstraction gives us the power to scale and deal with complexity. Applying abstraction recursively allows us to build larger and larger systems, with the base case (at least for computer science) being bits (0's and 1's). In computing, we routinely build systems in terms of layers of abstraction, allowing us to focus on one layer at a time and on the formal relations (e.g., "uses," "refines" or "implements," "simulates") between adjacent layers. When we write a program in a high-level language, we're building on lower layers of abstractions. We don't worry about the details of the underlying hardware, the operating system, the file system, or the network; furthermore, we rely on the compiler to correctly implement the semantics of the language. The narrow-waist architecture of the Internet demonstrates the effectiveness and robustness of appropriately designed abstractions: the simple TCP/IP layer at the middle has enabled a multitude of unforeseen applications to proliferate at layers above, and a multitude of unforeseen platforms, communications media, and devices to proliferate at layers below.

Computational thinking draws on both mathematical thinking and engineering thinking. Unlike mathematics, however, our computing systems are constrained by the physics of the underlying information-processing agent and its operating environment. And so, we must worry about boundary conditions, failures, malicious agents, and the unpredictability of the real world. And unlike other engineering disciplines, in computing --thanks to software, our unique "secret weapon"--we can build virtual worlds that are unconstrained by physical realities. And so, in cyberspace our creativity is limited only by our imagination.
Computational Thinking and Other Disciplines
Computational thinking has already influenced the research agenda of all science and engineering disciplines. Starting decades ago with the use of computational modeling and simulation, through today's use of data mining and machine learning to analyze massive amounts of data, computation is recognized as the third pillar of science, along with theory and experimentation [PITAC 2005].

The expedited sequencing of the human genome through the "shotgun algorithm" awakened the interest of the biology community in computational methods, not just computational artifacts (such as computers and networks). The volume and rate at which scientists and engineers are now collecting and producing data--through instruments, experiments and simulations--are demanding advances in data analytics, data storage and retrieval, as well as data visualization. The complexity of the multi-dimensional systems that scientists and engineers want to model and analyze requires new computational abstractions.

These are just two reasons that every scientific directorate and office at the National Science Foundation participates in the Cyber-enabled Discovery and Innovation, or CDI, program, an initiative started four years ago with a fiscal year 2011 budget request of $100 million. CDI is in a nutshell "computational thinking for science and engineering."

Computational thinking has also begun to influence disciplines and professions beyond science and engineering. For example, areas of active study include algorithmic medicine, computational archaeology, computational economics, computational finance, computation and journalism, computational law, computational social science, and digital humanities. Data analytics is used in training Army recruits, detecting email spam and credit card fraud, recommending and ranking the quality of services, and even personalizing coupons at supermarket checkouts.

At Carnegie Mellon, computational thinking is everywhere. We have degree programs, minors, or tracks in "computational X" where X is applied mathematics, biology, chemistry, design, economics, finance, linguistics, mechanics, neuroscience, physics and statistical learning. We even have a course in computational photography. We have programs in computer music, and in computation, organizations and society. The structure of our School of Computer Science hints at some of the ways that computational thinking can be brought to bear on other disciplines. The Robotics Institute brings together computer science, electrical engineering, and mechanical engineering; the Language Technologies Institute, computer science and linguistics; the Human-Computer Interaction Institute, computer science, design, and psychology; the Machine Learning Department, computer science and statistics; the Institute for Software Research, computer science, public policy, and social science. The newest kid on the block, the Lane Center for Computational Biology, brings together computer science and biology. The Entertainment Technology Center is a joint effort of SCS and the School of Drama. SCS additionally offers joint programs in algorithms, combinatorics and optimization (computer science, mathematics, and business); computer science and fine arts; logic and computation (computer science and philosophy); and pure and applied logic (computer science, mathematics, and philosophy).
Computational Thinking in Daily Life
Can we apply computational thinking in daily life? Yes! These stories helpfully provided by Computer Science Department faculty demonstrate a few ways:

Pipelining: SCS Dean Randy Bryant was pondering how to make the diploma ceremony at commencement go faster. By careful placement of where individuals stood, he designed an efficient pipeline so that upon the reading of each graduate's name and honors by Assistant Dean Mark Stehlik, each person could receive his or her diploma, then get a handshake or hug from Mark, and then get his or her picture taken. This pipeline allowed a steady stream of students to march across the stage (though a pipeline stall occurred whenever the graduate's cap would topple while getting hug from Mark).

Seth Goldstein, associate professor of computer science, once remarked to me that most buffet lines could benefit from computational thinking: "Why do they always put the dressing before the salad? The sauce before the main dish? The silverware at the start? They need some pipeline theory."

Hashing: After giving a talk at a department meeting about computational thinking, Professor Danny Sleator told me about a hashing function his children use to store away Lego blocks at home. According to Danny, they hash on several different categories: rectangular thick blocks, other thick (non-rectangular) blocks, thins (of any shape), wedgies, axles, rivets and spacers, "fits on axle," ball and socket and "miscellaneous." They even have rules to classify pieces that could fit into more than one category. "Even though this is pretty crude, it saves about a factor of 10 when looking for a piece," Danny says. Professor Avrim Blum overheard my conversation with Danny and chimed in "At our home, we use a different hash function."

Sorting: The following story is taken verbatim from an email sent by Roger Dannenberg, associate research professor of computer science and professional trumpeter. "I showed up to a big band gig, and the band leader passed out books with maybe 200 unordered charts and a set list with about 40 titles we were supposed to get out and place in order, ready to play. Everyone else started searching through the stack, pulling out charts one-at-a-time. I decided to sort the 200 charts alphabetically O(N log(N)) and then pull the charts O(M log(N)). I was still sorting when other band members were halfway through their charts, and I started to get some funny looks, but in the end, I finished first. That's computational thinking."
Benefits of Computational Thinking
Computational thinking enables you to bend computation to your needs. It is becoming the new literacy of the 21st century. Why should everyone learn a little computational thinking? Cuny, Snyder and I advocate these benefits [CunySnyderWing10]:

Computational thinking for everyone means being able to:

Understand which aspects of a problem are amenable to computation,

Evaluate the match between computational tools and techniques and a problem,

Understand the limitations and power of computational tools and techniques,

Apply or adapt a computational tool or technique to a new use,

Recognize an opportunity to use computation in a new way, and

Apply computational strategies such divide and conquer in any domain.

Computational thinking for scientists, engineers, and other professionals further means being able to:

Apply new computational methods to their problems,

Reformulate problems to be amenable to computational strategies,

Discover new science through analysis of large data,

Ask new questions that were not thought of or dared to ask because of scale, but which are easily addressed computationally, and

Explain problems and solutions in computational terms.

Computational Thinking in Education
Campuses throughout the United States and abroad are revisiting their undergraduate curriculum in computer science. Many are changing their first course in computer science to cover fundamental principles and concepts, not just programming. For example, at Carnegie Mellon we recently revised our undergraduate first-year courses to promote computational thinking for non-majors [Link10].

Moreover, the interest and excitement surrounding computational thinking has grown beyond undergraduate education to additional recent projects, many focused on incorporating computational thinking into kindergarten through 12th grade education. Sponsors include professional organizations, government, academia and industry.

The College Board, with support from NSF, is designing a new Advanced Placement (AP) course that covers the fundamental concepts of computing and computational thinking (see the website at www.csprinciples.org). Five universities are piloting versions of this course this year: University of North Carolina at Charlotte, University of California at Berkeley, Metropolitan State College of Denver, University of California at San Diego and University of Washington. The plan is for more schools--high schools, community colleges and universities--to participate next year.

Computer science is also getting attention from elected officials. In May 2009, computer science thought leaders held an event on Capitol Hill to call on policymakers to put the "C" in STEM, that is, to make sure that computer science is included in all federally-funded educational programs that focus on science, technology, engineering and mathematics (STEM) fields. The event was sponsored by ACM, CRA, CSTA, IEEE, Microsoft, NCWIT, NSF, and SWE .

The U.S. House of Representatives has now designated the first week of December as Computer Science Education Week (www.csedweek.org); the event is sponsored by ABI, ACM, BHEF, CRA, CSTA, Dot Diva, Google, Globaloria, Intel, Microsoft, NCWIT, NSF, SAS, and Upsilon Pi Epsilon. In July 2010, U.S. Rep. Jared Polis (D-CO) introduced the Computer Science Education Act (H.R. 5929) in an attempt to boost K-12 computer science education efforts.

Another boost is expected to come from the NSF's Computing Education for the 21st Century (CE21) program, started in September 2010 and designed to help K-12 students, as well as first- and second-year college students, and their teachers develop computational thinking competencies. CE21 builds on the successes of the two NSF programs, CISE Pathways to Revitalized Undergraduate Computing Education (CPATH) and Broadening Participating in Computing (BPC). CE21 has a special emphasis on activities that support the CS 10K Project, an initiative launched by NSF through BPC. CS 10K aims to catalyze a revision of high school curriculum, with the proposed new AP course as a centerpiece, and to prepare 10,000 teachers to teach the new courses in 10,000 high schools by 2015.

Industry has also helped promote the vision of computing for all. Since 2006, with help from Google and later Microsoft, Carnegie Mellon has held summer workshops for high school teachers called "CS4HS." Those workshops are designed to deliver the message that there is more to computer science than computer programming. CS4HS spread in 2007 to UCLA and the University of Washington. By 2010, under the auspices of Google, CS4HS had spread to 20 schools in the United States and 14 in Europe, the Middle East and Africa. Also at Carnegie Mellon, Microsoft Research funds the Center for Computational Thinking (www.cs.cmu.edu/~CompThink/), which supports both research and educational outreach projects.

Computational thinking has also spread internationally. In August 2010, the Royal Society--the U.K.'s equivalent of the U.S.'s National Academy of Sciences--announced that it is leading an 18-month project to look "at the way that computing is taught in schools, with support from 24 organizations from across the computing community including learned societies, professional bodies, universities and industry." (See www.royalsociety.org/education-policy/projects/.) One organization that has already taken up the challenge in the U.K. is called Computing At School, a coalition run by the British Computing Society and supported by Microsoft Research and other industry partners.
Resources Abound
The growing worldwide focus on computational thinking means that resources are becoming available for educators, parents, students and everyone else interested in the topic.

In October 2010, Google launched the Exploring Computational Thinking website (www.google.com/edu/computational-thinking), which has a wealth of links to further web resources, including lesson plans for K-12 teachers in science and mathematics.

Computer Science Unplugged (www.csunplugged.org), created by Tim Bell, Mike Fellows and Ian Witten, teaches computer science without the use of a computer. It is especially appropriate for elementary and middle school children. Several dozen people working in many countries, including New Zealand, Sweden, Australia, China, Korea, Taiwan and Canada, as well as in the United States, contribute to this extremely popular website.

The National Academies' Computer Science and Telecommunications Board held a series of workshops on "Computational Thinking for Everyone" with a focus on identifying the fundamental concepts of computer science that can be taught to K-12 students. The first workshop report [NRC10] provides multiple perspectives on computational thinking.

Additionally, panels and discussions on computational thinking have been plentiful at venues such as the annual ACM Special Interest Group on Computer Science Education (SIGCSE) symposium and the ACM Educational Council. The education committee of the CRA presented a white paper [CRA-E10] at the July 2010 CRA Snowbird conference, which includes recommendations for computational thinking courses for non-majors. CSTA produced and distributes "Computational Thinking Resource Set: A Problem-Solving Tool for Every Classroom." It's available for download at the CSTA's website (www.csta.acm.org).
Final Remarks--and a Challenge
Computational thinking is not just or all about computer science. The educational benefits of being able to think computationally--starting with the use of abstractions--enhance and reinforce intellectual skills, and thus can be transferred to any domain.

Computer scientists already know the value of thinking abstractly, thinking at multiple levels of abstraction, abstracting to manage complexity, abstracting to scale up, etc. Our immediate task ahead is to better explain to non-computer scientists what we mean by computational thinking and the benefits of being able to think computationally. Please join me in helping to spread the word!
Jeannette Wing is head of the Computer Science Department at Carnegie Mellon University and the President's Professor of Computer Science. She earned her bachelor's, master's and doctoral degrees at the Massachusetts Institute of Technology and has been a member of the Carnegie Mellon faculty since 1985. Bibliography and Further Reading
From 2007 to 2010, Wing served as assistant director for the Computer and Information Science and Engineering Directorate of the National Science Foundation. She is a fellow of the American Academy of Arts and Sciences, the American Association for the Advancement of Science, the Association for Computing Machinery and the Institute of Electrical and Electronic Engineers.
[CRA-E10] Computer Research Association, "Creating Environments for Computational Researcher Education," August 9, 2010. http://www.cra.org/uploads/documents/resources/rissues/CRA-E-Researcher-Education.pdf

[CunySnyderWing10] Jan Cuny, Larry Snyder and Jeannette M. Wing, "Demystifying Computational Thinking for Non-Computer Scientists," work in progress, 2010

[NRC10] "Report of a Workshop on the Scope and Nature of Computational Thinking," National Research Council, 2010 (www8.nationalacademies.org/cp/projectview.aspx?key=48969)

[Link10] Randal E. Bryant, Klaus Sutner and Mark Stehlik, "Introductory Computer Science Education: A Deans' Perspective," The Link, Fall 2010
Acronyms of Organizations:
[PITAC05] President's Information Technology Advisory Council, "Computational Science: Ensuring America's Competitiveness," Report to the President, June 2005
Acronyms of NSF Programs:
[Wing06] Jeannette M. Wing, "Computational Thinking," Communications of the ACM, Vol. 49, No. 3, March 2006, pp. 33-35

ABI: Anita Borg Institute for Women and Technology
ACM: Association for Computing Machinery
BHEF: Business-Higher Education Forum
CISE: Computer and Information Science and Engineering
CRA: Computing Research Association
CRA-E: Computing Research Association-Education
CSTA: Computer Science Teachers Association
CSTB: Computer Science and Telecommunications Board
IEEE: Institute for Electrical and Electronic Engineers
NCWIT: National Center for Women and Information Technology
NSF: National Science Foundation
SIGCSE: ACM Special Interest Group on Computer Science Education
SWE: Society for Women Engineers

BPC: Broadening Participating in Computing
CDI: Cyber-enabled Discovery and Innovation
CE21: Computing Education for the 21st Century
CPATH: CISE Pathways to Revitalized Undergraduate Computing Education

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ACM Special Interest Group on Computer Science Education

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National Center for Women and Information Technology NSF

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Institute of Electrical and Electronic Engineers

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Computer and Information Science and Engineering Directorate of the National Science Foundation

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Anita Borg Institute for Women and Technology ACM : Association for Computing Machinery

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Computer Science and Telecommunications Board

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National Academies ' Computer Science and Telecommunications Board

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Research Notebook: Computational Thinking--What and Why?

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By Jeannette M. Wing In a March 2006 article for the Communications of the ACM, I used the term "computational thinking" to articulate a vision that everyone, not just those who major in computer science, can benefit from thinking like a computer scientist [Wing06]. So, what is computational thinking?

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http://www.cs.cmu.edu/news/microsoft-carnegie-mellon-establish-center-computational-thinkinginitiative-seeks-understand

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BY Byron Spice -

Microsoft and Carnegie Mellon University today announced the creation of the Microsoft Carnegie Mellon Center for Computational Thinking. The center was made possible through a three-year, $1.5 million grant from Microsoft.

The center represents a long-term collaboration between Microsoft Research and Carnegie Mellon's Computer Science Department and will support research in emerging areas of computer science, particularly those that can influence the thinking of other disciplines.

"Increasingly, scientists and researchers rely on computer science to enable them to sift through massive amounts of data and find breakthroughs that could provide new insights into the human body, the earth we live on and even the universe," said Rick Rashid, Microsoft Research senior vice president. "We are eager to explore this exciting new area of research with Carnegie Mellon."

Rashid made the announcement at the Carnegie Mellon Symposium for Computational Thinking. Computational thinking, as conceived by Jeannette M. Wing, head of Carnegie Mellon's Computer Science Department, involves solving problems, designing systems and understanding human behavior by drawing on the concepts fundamental to computer science.

"Carnegie Mellon itself is an example of how the power of computational thinking can energize disciplines across the campus," said Carnegie Mellon President Jared L. Cohon. "Our psychologists use machine learning techniques to decipher brain scans. Our biologists build computer models of cells to find causes of cancer. And business professors harness artificial intelligence to better understand markets. We are delighted that Microsoft is joining us in furthering this concept."

The Microsoft Carnegie Mellon Center for Computational Thinking will support research in core computer science areas using an approach called problem-oriented explorations, pioneered by Carnegie Mellon's ALADDIN Center. Researchers from a variety of fields will address specific, real-world problems. Initial topics include privacy, e-commerce, multicore computing and embedded medical devices. Additionally, the center will develop and disseminate courses and curricula suitable for graduate and undergraduate students, as well as K-12 classes.

"Computer technology has rapidly transformed education, commerce and entertainment. But, more profoundly, computational thinking is transforming how new science is discovered in fields as varied as biology, astronomy, statistics and economics," said Wing.

As part of the ongoing relationship with Microsoft, the center will host a series of Mindswaps, organized as annual meetings between Microsoft and Carnegie Mellon researchers for the purpose of sharing data, solving problems, sharing resources and collaborating on bigger computer challenges. Mindswaps will ultimately lead to problem-oriented explorations as part of the center's work.

Microsoft is deeply committed to education at all levels and has a long history of partnerships throughout academia. This institute is the result of work by its External Research & Programs group and becomes the eighth center Microsoft Research has formed to pursue particular areas of research.

About Carnegie Mellon's Computer Science Department: The Computer Science Department is the largest of six academic units within Carnegie Mellon's School of Computer Science. Consistently ranked among the world's premier institutions for computer science research and education, the school also includes leading programs in robotics, human-computer interaction, software research, language technologies and machine learning.

About Microsoft Research: Founded in 1991, Microsoft Research is dedicated to conducting both basic and applied research in computer science and software engineering. Its goals are to enhance the user experience on computing devices, reduce the cost of writing and maintaining software, and invent novel computing technologies. Researchers focus on more than 55 areas of computing and collaborate with leading academic, government and industry researchers to advance the state of the art in such areas as graphics, speech recognition, user-interface research, natural language processing, programming tools and methodologies, operating systems and networking, and the mathematical sciences. Microsoft Research employs more than 700 people in five labs located in Redmond, Wash.; Silicon Valley, Calif.; Cambridge, England; Beijing, China; and Bangalore, India. Microsoft Research collaborates openly with colleges and universities worldwide to enhance the teaching and learning experience, inspire technological innovation, and broadly advance the field of computer science. More information can be found at www.research.microsoft.com

About Microsoft: Founded in 1975, Microsoft (Nasdaq:MSFT) is the worldwide leader in software, services and solutions that help people and businesses realize their full potential.
Microsoft, Xbox, MSN and Virtual Earth are either registered trademarks or trademarks of Microsoft Corp. in the United States and/or other countries. The names of actual companies and products mentioned herein may be the trademarks of their respective owners.

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Microsoft Carnegie Mellon Center for Computational Thinking

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Carnegie Mellon Symposium for Computational Thinking

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Carnegie Mellon 's School of Computer Science

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Microsoft, Carnegie Mellon Establish Center for Computational Thinking Initiative Seeks To Understand New ApproachesTo Problem-Solving With Computing at Its Core

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BY Byron Spice - Microsoft and Carnegie Mellon University today announced the creation of the Microsoft Carnegie Mellon Center for Computational Thinking. The center was made possible through a three-year, $1.5 million grant from Microsoft.

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"Computational Thinking" should be honed as a fundamental skill in educational programs, says expert at CMU

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"Computational Thinking" should be honed as a fundamental skill in educational programs, says expert at CMU

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http://www.cs.cmu.edu/news/computational-thinking-should-be-honed-fundamental-skill-educational-programs-says-expert-cmu

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BY Byron Spice -

DOHA, QATAR- "Thinking like a computer scientist means more than being able to program a computer," said Jeannette M. Wing, Ph.D., the President's Professor of Computer Science and Head of the Computer Science Department at Carnegie Mellon University. Carnegie Mellon Qatar invited Wing to speak as part of its Computer Science Distinguished Lecture Series.

"Computational thinking is a fundamental skill used by everyone in the world, and should be incorporated into educational programs along with reading, writing and arithmetic to grow every child's analytical ability."

Wing, an internationally recognized leader and expert in computer science, was discussing her global vision and what she sees as important in the 21st century in front of a crowded audience of students, academics, alumni and other VIP guests on Tuesday at Carnegie Mellon University in Qatar. In her lecture titled "Computational Thinking", she emphasized the importance of computational thinking and its positive impact on future generations.

Computational thinking draws on the fundamental concepts of computer science such as abstraction, problem solving, designing systems and understanding human behavior. Mathematics and engineering principles are fundamentals in computational thinking- logic, efficiency, correctness, interaction. Computational thinking helps us figure out how to solve problems through reduction, embedding, transformation, decomposition or simulation. Skills that are used every day- such as planning, learning, scheduling, searching, making trade-offs - all come into play with computational thinking. There are many examples of the influence computational thinking has had on other disciplines. From deciding which line to stand in at the supermarket to sequencing the human genome, from air traffic control to the discovery and development of anti-inflammatory drugs- computational thinking comes in to play.

"Teaching computational thinking can not only inspire future generations to enter the field of computer science because of its intellectual adventure, but will benefit people in all fields," added Wing.

"Everyone is able to learn concepts of computational thinking and we should be taking advantage of the tech-savvy generation in order to teach more about computer science. We should try to teach the younger generation the reasons behind new technology," commented Wing.

Wing has received numerous awards and recognition for her work with respect to computational thinking and education. She was assistant director of the National Science Foundation's Computer and Information Science and Engineering directorate (NSF), and was recently elected as a member of the Computer Research Association's (CRA) board of directors.

Wing's involvement in major NSF programs including those focused on discovery and innovation, trustworthy computing and data-intensive computing, has helped push the boundaries of research in computing science, and has been cited as a critical dimension of America's innovation economy.

"Jeannette's 2006 viewpoint paper in the Communications of the Association for Computing Machinery, titled "Computational Thinking" started a discussion on how computer science needed to be viewed. She convincingly argued that the broad skills of computer scientists represent a universally applicable attitude and skill set everyone, including students and scientists from almost every other discipline, should have" said Kemal Oflazer, Ph.D., professor of computer science at Carnegie Mellon University in Qatar. "This is now being embraced by undergraduate curricula not just at CMU but at many other higher education institutions and also by secondary schools."

Carnegie Mellon Qatar's Computer Science Department has been very active since the introduction of the program in 2004, helping to spread technology awareness and knowledge in the Qatar community through its high school outreach programs as well as its academic courses. "At Carnegie Mellon, we teach students who are studying computer science to be innovative in their problem solving, to create new ways of doing something that has never been done before. They are able to do this through computational thinking- understanding the thought process behind layers of abstraction and mapping the process. Our graduates have been hired by organizations in energy, finance, real estate, media as well as technology because their thinking and approach to solving problems easily adapt to many disciplines," Oflazer added.

Carnegie Mellon's School of Computer Science is a premier institution for computer science research and education. Its Ph.D. program is currently ranked number one by US News and World Report. The faculty is made up of renowned researchers and academics, developing new methods and technologies, which have a significant impact across a wide variety of fields.

Jeannette M. Wing is an alumna of the Massachusetts Institute of Technology, where she earned bachelor's and master's degrees in electrical engineering and computer science, and a doctorate in computer science. She began her career as an assistant professor at the University of Southern California, and joined the Carnegie Mellon faculty in 1985. She has worked or consulted for AT&T Bell Laboratories, Xerox Palo Alto Research Laboratories, Digital Equipment Corp., USC/Information Sciences Institute, the Jet Propulsion Laboratory and Microsoft Corp.

Carnegie Mellon University in Qatar hosts a number of distinguished lectures that aim to bring leaders from around the world to the Doha campus to share their experience and discuss their area of expertise with university students and the community.

# data[].attributes.attachment_link.entities[].name
Carnegie Mellon Qatar 's Computer Science Department

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National Science Foundation 's Computer and Information Science

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Jet Propulsion Laboratory and Microsoft Corp.

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Communications of the Association for Computing Machinery

# data[].attributes.attachment_link.entities[].name
Carnegie Mellon 's School of Computer Science

# data[].attributes.attachment_link.title
"Computational Thinking" should be honed as a fundamental skill in educational programs, says expert at CMU

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BY Byron Spice - DOHA, QATAR- "Thinking like a computer scientist means more than being able to program a computer," said Jeannette M. Wing, Ph.D., the President's Professor of Computer Science and Head of the Computer Science Department at Carnegie Mellon University. Carnegie Mellon Qatar invited Wing to speak as part of its Computer Science Distinguished Lecture Series.

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https://cs4hs.cs.washington.edu/content/Resources/SessionMaterials/bin-o-slides/Jeannette_Wing_CT.pdf

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Scientific Thinking and computational thinking

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Scientific Thinking and computational thinking

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http://www.cs4fn.org/computationalthinking/scientificthinking.php

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Computer Science for Fun - cs4fn: What is Computational Thinking? Scientific Thinking

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Computer Science is of course in part a science. Not suprising given the name! Though actually it isn't purely a science, as it draws on other things like engineering too. It's not suprising that scientific thinking is a part of the Computational Thinking Skill set though.

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A couple of interesting articles related to computational thinking  -- computing education blog

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A couple of interesting articles related to computational thinking  -- computing education blog

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https://computinged.wordpress.com/2010/08/12/go-to-the-data-two-stories-of-really-computational-thinking/

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Go to the Data: Two stories of (really) Computational Thinking

Barb is on a panel on Computational Thinking at the Scratch Conference this afternoon. We're as confused as anyone else what "Computational Thinking" means, but I've had a couple of recent experiences that have highlighted for me one aspect of computational thinking, something which I feel is really computational thinking - not computer science, not algorithmic thinking, not mathematical thinking.

Story 1: It's in my foot and my iPod. I like to run. Running doesn't always like me. I had knee surgery for a torn meniscus three years ago. The last two Peachtree 10K runs, I've been registered, but have torn a muscle (calf one year, hamstring the next) within weeks of the race and missed it, forced to take 6-8 weeks off. I have now been running since January without injury.

So I was really bummed when I went out to run a five mile a couple weeks, and after two miles, I had the all-too-familiar feeling of my hamstring straining. It didn't pull or tear, but I turned around, and ended up walking more than a mile of the two miles back. I took a couple days off, ran short runs and worked out on the elliptical, and within a week, was running 3 miles again without pain. What happened? And how could I avoid it in the future?

I have been running with Nike+ iPod since Christmas. A fob goes on my iPod, and a sensor goes in my shoe. When I next synched my iPod to the Nike+ website, I decided to look at my last few weeks worth of runs. Here's what I saw, with my scribbled red arrow on the run where I was hurting:

When I look at this graph, I see lots of runs averaging around 3 miles (particularly when I was traveling alot), then one run above 4 miles, then a handful of shorter runs, then within two days, my two longest runs of the summer (4.71 and 4.75 miles). Two days later (with elliptical and weight work in between - no rest days), I tried to go even further at five miles. Well, duh! I think I pushed myself too quickly. It's one thing to increase my distance. It's another to do it day-after-day, without shorter runs or rests. I have to ramp up slowly, not increase my longest distance every day. That helps to explain my Peachtree training injuries too, as I tried too quickly to ramp up to 10K mile runs.

I showed this graph to Barb and told her my reasoning. She said, "That's computational thinking!" I think she's right.

Story 2: It's not blowing in the wind. Atlanta, like most of the country, has been wicked hot this summer. The newspapers are using phrases like, "Hottest summer in 30 years!" Is it really? I was wondering, and I was wondering how I could find out.

I went to WolframAlpha and typed in "temp in Atlanta." From the "History" pull-down menu, I selected "Last 5 years" and saw this graph.

I find this graph unconvincing that this is the hottest summer in even the last five years. This looks like pretty much the exact same curve and the exact same maximums across the five years. Then I clicked the "More" link, and got these graphs:

The humidity is high, but it looks higher back in 2007. But look at that last one, the wind speed. To my novice eye, that looks like the lowest wind speeds in the last five years. Maybe that's why it feels so hot? It's not the temperature, it's the lack of wind? And maybe that is related to the high humidity?

Computational Thinking includes Going to the Data. The common theme in both of these stories is "Go to the data." In both cases, I realized that data had been collected that could help me to answer my question. This is computational thinking. In our modern world, there are lots of data being collected (or can easily be collected), stored in the cloud, and available for processing. Dealing with these data is different than mathematical thinking (though the interpretation of the visualizations is clearly mathematics), algorithmic thinking, and notably for me, computer science. None of the above looks like computer science to me. However, it feels like it's important for 21st Century citizens to be able to do this kind of reasoning.

Some of the questions that I had to answer for myself here, and that we'd want students to be able to answer for themselves, include:

Are the data already collected that help me to answer my question? Or can I easily collect the data? WolframAlpha has an amazing collection of data already available to crunch. My run data comes for free after I put the sensor in the shoe, and run with my iPod - which I like to do anyway. (FYI, my current top running accompaniment are tunes by John Prine, Pink, Coldplay, and the soundtrack to "Mama Mia!")

Is the data what I want? Do I trust the data?

What can I access in the data?

How can I query and visualize the data?

Of course, next comes the interpretation of the data, the inference and development of hypotheses. I'm not saying that that's computational thinking. Understanding a model requires knowledge of science and mathematics. But it really is uniquely computational thinking to find (or create) these collections of data and use them to create the visualizations that allow us to apply our knowledge of science and mathematics to answer our questions.

Entry filed under: Uncategorized. Tags: computational thinking.

# data[].attributes.attachment_link.title
Go to the Data: Two stories of (really) Computational Thinking

# data[].attributes.attachment_link.description
Barb is on a panel on Computational Thinking at the Scratch Conference this afternoon. We're as confused as anyone else what "Computational Thinking" means, but I've had a couple of recent experiences that have highlighted for me one aspect of computational thinking, something which I feel is really computational thinking -- not computer science, not algorithmic...

# data[].attributes.attachment_link.embed_code
Barb is on a panel on Computational Thinking at the Scratch Conference this afternoon.  We’re as confused as anyone else what “Computational Thinking” means, but I’ve had a couple of recent experiences that have highlighted for me one aspect of computational thinking, something which I feel is really computational thinking — not computer science, not algorithmic thinking, not mathematical thinking.

Story 1: It’s in my foot and my iPod. I like to run.  Running doesn’t always like me.  I had knee surgery for a torn meniscus three years ago.  The last two Peachtree 10K runs, I’ve been registered, but have torn a muscle (calf one year, hamstring the next) within weeks of the race and missed it, forced to take 6-8 weeks off.  I have now been running since January without injury.

So I was really bummed when I went out to run a five mile a couple weeks, and after two miles, I had the all-too-familiar feeling of my hamstring straining.  It didn’t pull or tear, but I turned around, and ended up walking more than a mile of the two miles back.  I took a couple days off, ran short runs and worked out on the elliptical, and within a week, was running 3 miles again without pain.  What happened? And how could I avoid it in the future?

I have been running with Nike+ iPod since Christmas. A fob goes on my iPod, and a sensor goes in my shoe.  When I next synched my iPod to the Nike+ website, I decided to look at my last few weeks worth of runs.  Here’s what I saw, with my scribbled red arrow on the run where I was hurting:

When I look at this graph, I see lots of runs averaging around 3 miles (particularly when I was traveling alot), then one run above 4 miles, then a handful of shorter runs, then within two days, my two longest runs of the summer (4.71 and 4.75 miles). Two days later (with elliptical and weight work in between — no rest days), I tried to go even further at five miles.  Well, duh!  I think I pushed myself too quickly.  It’s one thing to increase my distance.  It’s another to do it day-after-day, without shorter runs or rests. I have to ramp up slowly, not increase my longest distance every day.  That helps to explain my Peachtree training injuries too, as I tried too quickly to ramp up to 10K mile runs.

I showed this graph to Barb and told her my reasoning.  She said, “That’s computational thinking!” I think she’s right.

Story 2: It’s not blowing in the wind. Atlanta, like most of the country, has been wicked hot this summer.  The newspapers are using phrases like, “Hottest summer in 30 years!”  Is it really?  I was wondering, and I was wondering how I could find out.

I went to WolframAlpha and typed in “temp in Atlanta.” From the “History” pull-down menu, I selected “Last 5 years” and saw this graph.

I find this graph unconvincing that this is the hottest summer in even the last five years.  This looks like pretty much the exact same curve and the exact same maximums across the five years.  Then I clicked the “More” link, and got these graphs:

The humidity is high, but it looks higher back in 2007. But look at that last one, the wind speed.  To my novice eye, that looks like the lowest wind speeds in the last five years.  Maybe that’s why it feels so hot?  It’s not the temperature, it’s the lack of wind?  And maybe that is related to the high humidity?

Computational Thinking includes Going to the Data.  The common theme in both of these stories is “Go to the data.”  In both cases, I realized that data had been collected that could help me to answer my question.  This is computational thinking.  In our modern world, there are lots of data being collected (or can easily be collected), stored in the cloud, and available for processing.  Dealing with these data is different than mathematical thinking (though the interpretation of the visualizations is clearly mathematics), algorithmic thinking, and notably for me, computer science.  None of the above looks like computer science to me.  However, it feels like it’s important for 21st Century citizens to be able to do this kind of reasoning.

Some of the questions that I had to answer for myself here, and that we’d want students to be able to answer for themselves, include:

Are the data already collected that help me to answer my question? Or can I easily collect the data?  WolframAlpha has an amazing collection of data already available to crunch.  My run data comes for free after I put the sensor in the shoe, and run with my iPod — which I like to do anyway.  (FYI, my current top running accompaniment are tunes by John Prine, Pink, Coldplay, and the soundtrack to “Mama Mia!”)

Is the data what I want? Do I trust the data?

What can I access in the data?

How can I query and visualize the data?

Of course, next comes the interpretation of the data, the inference and development of hypotheses.  I’m not saying that that’s computational thinking.  Understanding a model requires knowledge of science and mathematics.  But it really is uniquely computational thinking to find (or create) these collections of data and use them to create the visualizations that allow us to apply our knowledge of science and mathematics to answer our questions.

# data[].attributes.body
http://www.cs.toronto.edu/~sme/papers/2014/Easterbrook-ICT4S-2014.pdf

# data[].attributes.body
http://download.springer.com/static/pdf/230/art%253A10.1007%252Fs11423-006-8806-y.pdf?originUrl=http%3A%2F%2Flink.springer.com%2Farticle%2F10.1007%2Fs11423-006-8806-y&token2=exp=1443849718~acl=%2Fstatic%2Fpdf%2F230%2Fart%25253A10.1007%25252Fs11423-006-8806-y.pdf%3ForiginUrl%3Dhttp%253A%252F%252Flink.springer.com%252Farticle%252F10.1007%252Fs11423-006-8806-y*~hmac=6ab635b1e7ca156bea8cacd2967b59b329ba013bd1ce95573097bc0ccfe29131

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Educational Technology Research & Development

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Journal of Interactive Media in Education

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Handbook of research for educational communications

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International Journal of Intelligent Simulations

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Educational Technology Research and Development Dickey

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5th International Digital Arts and Culture Conference

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CrossRefGoogle Scholar © Association for Educational Communications

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Game Design Narrative for Learning: Appropriating Adventure Game Design Narrative Devices and Techniques for the Design of Interactive Learning Environments

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The purpose of this conceptual analysis is to investigate how contemporary video and computer games might inform instructional design by looking at how narrative devices and techniques support problem

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https://thejournal.com/articles/2015/09/15/5-fundamental-apps-for-steam-classrooms.aspx

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Mobile Computing

5 Fundamental Apps for STEAM Classrooms

By

Common Sense Media's service Graphite, which offers independent ratings and reviews of learning apps and websites, has compiled this list of apps that every STEAM classroom must have. For complete reviews, and for each app's "Learning Rating," visit the Graphite website.

The Robot Factory
Grades: K-8
Price: $3.99
Concepts: Design thinking, engineering, physics, applying information, making new creations
With the Robot Factory app, students can design robots and test them through physics-driven trial and error. Using hundreds of mechanical parts, kids can choose the torso, head, arms, legs, hands, facial features and color scheme of their creations. From there, students can save their robots to their collections and test them in the "real world," where they navigate over and around obstacles. Their experiments, and the ability to continually edit their designs, will help them think like scientists and learn which robot parts work best on which kinds of terrain. The Robot Factory's dazzling graphics and open-ended play make the app a great introduction to design thinking, iteration, and other STEAM concepts and skills. Read the full Graphite review.

DIY App - Creative Community for Kids
Grades: 2-5
Price: Free
Concepts: Innovation, asking questions, making new creations, giving and receiving feedback, social media
DIY App - Creative Community for Kids is the companion to the crafty, creative how-to website DIY.org. Both the app and website allow kids to post their DIY projects, get feedback from other users and participate in a community of young makers. This highly engaging app helps kids learn by following directions, asking questions, presenting their work, communicating their feedback and earning badges as they complete projects. The app version makes it easy for kids to take images and post them on the site, a key part of participating in the DIY community. Whether used for simple browsing or for getting involved in the greater DIY/maker movement, the app is a virtual treasure trove of creative activities and crafty, skill-building ideas. Read the full Graphite review.

Pixel Press Floors
Grades: 3-8
Price: Free
Concepts: Imagination, digital creation, defining problems, problem-solving
Pixel Press Floors gives students the tools to create and customize their own video games, bringing their ideas to life and allowing them to share their creations with a global community. Using the app's "glyph" notation, students can draw their ideas for a game, take a photo and upload it to their levels. The emphasis on iteration and access to solid creation tools makes learning basic design and engineering skills fun. Kids will learn a lot by creating their own problems to solve and seeing their drawings become real-life video games. For those students who are always eager to play games in class, this is a great resource to get them thinking about the work that goes into making those games. Read the full Graphite review.

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5 Fundamental Apps for STEAM Classrooms -- THE Journal

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Mobile Computing By Common Sense Media's service Graphite, which offers independent ratings and reviews of learning apps and websites, has compiled this list of apps that every STEAM classroom must have. For complete reviews, and for each app's "Learning Rating," visit the Graphite website.

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LittleBits opens up access tokits in educational settings

https://thejournal.com/Articles/2015/09/24/LittleBits-Opens-Up-Access-to-Kits-in-Educational-Settings.aspx

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STEM

LittleBits Opens Up Access to Kits in Educational Settings

LittleBits, the four-year-old maker of kits that allow children and adults to create inventions with a platform of electronic building blocks, is launching LittleBits Education to enhance the use of its products for schools and libraries.

Since 2011, the company has been making and distributing pre-made kits that can help children make gadgets like musical instruments and robotic cars.

A Base Kit, which retails online for $99, is designed to help students learn the basics of electronics and the principals of science, technology, engineering, art and math (STEAM). The kit comes with 10 modules like a DC motor, buzzer, dimmer and light sensor (and more can be ordered); an instruction book with eight projects and access to more online; and 150,000 possible circuit combinations.

In order to make LittleBits kits more accessible in the classroom, the company has released four new products:

LittleBits STEAM PD, a stand-alone professional development program designed to help teachers integrate STEAM instruction into the classroom;

LittleBits Invention Lab, a bundle of products to be used in libraries and other environments that will allow access to up to 72 students at one time;

LittleBits Classroom Integration, for schools that want to integrate LittleBits and a STEAM curriculum into multiple classrooms at once; and

LittleBits 1:1, a collection of products that will provide every student with his or her own mobile makerspace.

"We launched LittleBits Education because we wanted to make it easy for educational institutions everywhere to find a way to bring more 21 st-century learning to their students," said LittleBits Founder and CEO Ayah Bdeir.

Marymount School of New York, a private girls school in New York City, is the first institution to take advantage of the 1:1 portable invention kits.

"Giving every girl her own mobile makerspace of LittleBits offers them opportunities for rapid prototyping their innovations and inventions," said Marymount Headmistress Concepcion Alvar.

About the Author

Michael Hart is a Los Angeles-based freelance writer and the former executive editor of THE Journal.

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LittleBits Opens Up Access to Kits in Educational Settings -- THE Journal

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STEM LittleBits, the four-year-old maker of kits that allow children and adults to create inventions with a platform of electronic building blocks, is launching LittleBits Education to enhance the use of its products for schools and libraries. Since 2011, the company has been making and distributing pre-made kits that can help children make gadgets like musical instruments and robotic cars.

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Practical employment of new media often ignores their rich contexts, which contain examples of the distinct logics and different affordances of those media, wasting the very characteristics that make them most effective and potentially revolutionary for pedagogy. On Multimodality: New Media in Composition Studies urges composition scholars and teachers to become aware of the rich histories and rhetorical capabilities of new media so that students’ work with those media is enlivened and made substantive.

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Practical employment of new media often ignores their rich contexts, which contain examples of the distinct logics and different affordances of those media, wasting the very characteristics that make them most effective and potentially revolutionary for pedagogy. On Multimodality: New Media in Composition Studies urges composition scholars and teachers to become aware of the rich histories and rhetorical capabilities of new media so that students’ work with those media is enlivened and made substantive.

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Non-Member Price: $36.00

NCTE Member Price: $34.00

Author(s): Jonathan Alexander, Jacqueline Rhodes

This is a print version of the book. A PDF ebook version is also available.

Jonathan Alexander and Jacqueline Rhodes argue that composition's embrace of new media and multimedia often makes those media serve the rhetorical ends of writing and composition, as opposed to exploring the rhetorical capabilities of those media. CCCC/NCTE Studies in Writing & Rhetoric (SWR) series

Winner of the 2015 CCCC Outstanding Book Award

Level(s): College

ISBN/ISSN: 9780814134122

Stock No.: 34122

Description

Winner of the 2015 CCCC Outstanding Book Award

As our field of composition studies invites students to compose with new media and multimedia, we need to ask about other possibilities for communication, representation, and making
knowledge-including possibilities that may exceed those of the letter, the text based, the composed.

In this provocative look at how composition incorporates new forms of media into actual classrooms, Jonathan Alexander and Jacqueline Rhodes argue persuasively that composition's embrace of new media and multimedia often makes those media serve the rhetorical ends of writing and composition, as opposed to exploring the rhetorical capabilities of those media. Practical employment of new media often ignores their rich contexts, which contain examples of the distinct logics and different affordances of those media, wasting the very characteristics that make them most effective and potentially revolutionary for pedagogy. On Multimodality: New Media in Composition Studies urges composition scholars and teachers to become aware of the rich histories and rhetorical capabilities of new media so that students' work with those media is enlivened and made substantive.

CCCC/NCTE Studies in Writing & Rhetoric Series. 232 pp. 2014. College.
No. 34122

# data[].attributes.attachment_link.title
On Multimodality: New Media in Composition Studies

# data[].attributes.attachment_link.description
Non-Member Price: $36.00 NCTE Member Price: $34.00 Author(s): Jonathan Alexander, Jacqueline Rhodes This is a print version of the book. A PDF ebook version is also available. Jonathan Alexander and Jacqueline Rhodes argue that composition's embrace of new media and multimedia often makes those media serve the rhetorical ends of writing and composition, as opposed to exploring the rhetorical capabilities of those media.

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Century Education -LRB- Pedagogy & Digital Innovation

# data[].attributes.attachment_link.entities[].name
Virtual Realities in Higher Education How

# data[].attributes.attachment_link.entities[].name
Teachers See Interdisciplinary Opportunities Education Week News

# data[].attributes.attachment_link.description
Educators help students recognize and understand the nuances of a discipline by using strategies that "make their thinking visible." They promote classroom reading, writing, listening, speaking and critical thinking using authentic materials that support the development of content-specific knowledge and that transfer to real world situations.They guide students through these complex texts by using strategies that develop conceptual understanding of language and set expectations for relevant application of skills.

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http://idc-cema.com/eng/about-idc/company-overview

# data[].attributes.attachment_link.entities[].name
Company Overview International Data Corporation

# data[].attributes.attachment_link.description
With a coordinated network of regional centers and local offices in 21 countries in Central and Eastern Europe, the Middle East, and Africa, IDC delivers practical advice and insight based on first-hand knowledge of emerging markets and local expertise in a unique combination with regional context and global technology background.

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Computational Thinking a Digital Age Skill for Everyone

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Computational Thinking a Digital Age Skill for Everyone

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VR Article

# data[].attributes.attachment_link.title
Computational Thinking a Digital Age Skill for Everyone

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https://scratch.mit.edu/help/faq/

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General Questions

What is Scratch, and what can I do with it?

Scratch is a programming language and online community where you can create your own interactive stories, games, and animations -- and share your creations with others around the world. In the process of designing and programming Scratch projects, young people learn to think creatively, reason systematically, and work collaboratively.To learn more about Scratch, check out the About Scratch page.

How do I make a game or animation with Scratch?

Check out the help page to see lots of ways to get started with Scratch. Or just dive in to the project editor.

What are the system requirements for Scratch?

To run Scratch 2, you need a relatively recent web browser ( Chrome 35 or later, Firefox 31 or later, or Internet Explorer 9 or later) with Adobe Flash Player version 10.2 or later installed. Scratch 2 is designed to support screen sizes 1024 x 768 or larger. If your computer doesn't meet these requirements, you can try downloading and installing Scratch 1.4, which you can still use to share projects to the Scratch 2 website.

Do you have a downloadable version so I can create and view projects offline?

The Scratch 2 offline editor (beta version) is now available. You can also still use Scratch 1.4. Note: You can have both Scratch 1.4 and 2 on your computer.

Can I still upload projects created with older versions of Scratch to the website?

Yes - you can share or upload projects made with earlier versions of Scratch, and they will be visible and playable. (However, you can't download projects made with or edited in later versions of Scratch and open them in earlier versions. For example, you can't open a Scratch 2 project in Scratch 1.4, because Scratch 1.4 doesn't know how to read the .sb2 project file format.)

Can I record a video of my Scratch project?

Yes, you can record a video of your Scratch project up to 60 seconds. In the Scratch editor, from the File menu, select "Record Project Video." (You need to be signed in to see this option.) You can choose additional recording options (such as recording sound and mouse clicks) through the "More Options" menu. Then, run your project however you'd like. Once the recording is done, follow the instructions to download the file to your computer. Depending on what kind of computer you have, you may need to download another program like the VLC Media Player to play the file. This file will run on YouTube, Vimeo, and Facebook, but may need to be converted for other websites like Twitter or Tumblr.

How much does Scratch cost? Do I need a license?

Scratch is and always will be free. You don't need a license to use Scratch in your school, home, or anywhere else. The development and maintenance of Scratch is paid for by grants and donations. If you'd like to contribute to Scratch, check out our Donate page.

Who created Scratch?

Scratch is developed and maintained by the Scratch Team at the Lifelong Kindergarten group at MIT Media Lab.

Privacy Policy

What information do you ask for during account registration?

To protect the privacy of our community members, we limit what we collect and what we publish on the website. During the registration process, we ask for the following information:

username - We ask that users avoid using their real names or other identifying information.

country

birth month and year - We use this to confirm ownership of the account if the owner loses the password and email or asks to close an account.

gender

contact email address - If the account holder is younger than 13, we ask for the email address of their parent or guardian. We do not send email to this address except when someone requests to have the account password reset.

The username and country of the account holder are displayed publicly on their profile page. The birth month / year, email address, and gender associated with the account are not displayed publicly. We collect this info so we can know the age and gender of our users in aggregate, and for research purposes. We do not sell or rent information about our users to anyone.

What data is collected from people while they use the website?

When a user logs in, the Scratch website asks their browser to put an http cookie on their computer in order to remember that they are logged in while they browse different pages. We collect some data on where users click and which parts of the site they visit using Google Analytics. This "click data" helps us figure out ways to improve the website.

Some of the information and data collected on the Scratch website are used in research studies intended to improve our understanding of how people learn with Scratch. The results of this research are shared with educators and researchers through conferences, journals, and other publications. You can find out more on our Research page.

Does the Scratch Team sell or rent information about users of Scratch to anyone?

No.

Can the Scratch Team view unshared projects on my 'My Stuff' page?

Since the Scratch Team is responsible for moderation, we have access to all content stored on the Scratch website - including unshared projects. If you prefer to work on projects in complete privacy, you can use either the Scratch 2 offline editor or Scratch 1.4.

Remixing and Copying

What is a remix?

When a Scratcher makes a copy of someone else's project and modifies it to add their own ideas (for example, by changing scripts or costumes), the resulting project is called a "remix." Every project shared to the Scratch website can be remixed. We consider even a minor change to be a valid remix, as long as credit is given to the original project creator and others who made significant contributions to the remix.

Why does the Scratch Team require that all projects be "remixable"?

We believe that viewing and remixing interesting projects is a great way to learn to program, and leads to cool new ideas. That's why the source code is visible for every project shared to the Scratch website.

What if I don't want others to remix my projects?

By publishing your project on the Scratch website, you agree to license it under a Creative Commons Share Alike license. If you don't want others to view and remix your creations, don't share them on the Scratch website.

Can I use images / sounds / media from the internet in my projects?

It's important to respect the original creator's wishes regarding remixing. If you choose to integrate someone else's work into your own, be sure to give them credit on the project "credits" section, and include a link back to the original. To find art / sounds that are already licensed for remixing, check out the Creative Commons search page.

Accounts

What is a "confirmed" Scratch account?

A confirmed account on Scratch lets you share projects, write comments, and create studios. Confirming your account also lets you receive email updates from the Scratch Team.

How can I check whether my account has been confirmed?

To check whether your account is confirmed, you must first log into your Scratch account in the top right of the screen. Once logged in, click on your username in the top right and select "Account Settings", then "Email Settings" on the left hand side. Confirmed email addresses will show a small green checkmark. Otherwise, you will see the text "Your email address is unconfirmed" in orange.

How do I confirm my account?

After registering for Scratch, you will receive an email with a link to confirm your account. If you cannot find the email, check your Spam folder. To resend the email, go to your Account Settings, click the Email tab, and follow the instructions there. Please note that it may take up to an hour for the email to arrive. If you still don't see the email after an hour, let us know.

Do I have to confirm my account?

You can still use many aspects of Scratch without confirming your account, including creating and saving projects (without sharing them). Note: If you created an account before February 11, 2015, then you can still use social features on Scratch without confirming your account.

I forgot my password, how can I reset it?

Enter your account name on the password reset page. The website will send an email to the address associated with the account containing a link you can use to reset your password.

How do I change my password?

Go to the Scratch website, login, and then click your username in the upper right corner of the window. Choose "account settings", and click the link to change your password.

How do I change my email address?

Go to the Scratch website, login, and then click your username in the upper right corner of the window. Choose "account settings", and click the link to change your email.

How do I transition from 'New Scratcher' to 'Scratcher'?

Make and share projects, comment helpfully on other Scratcher's projects, and be patient! After a few weeks of being active, a link will appear on your profile page inviting you to become a Scratcher. (Note that we don't promote New Scratchers to Scratcher on request - even when bribed with fancy chocolates.)

Can I have more than one account?

It's fine to have a few accounts on the Scratch website, as long as none of them are used to break the Community Guidelines. In that case, all related accounts may be blocked or deleted.

Is it OK to have more than one person logged into an account?

This is discouraged, because the website and project editor can easily get confused when more than one person is logged into the same account.

Can I change my username?

The structure of the Scratch website depends on having a consistent account name, so it's not possible to change your username. If you really need to, you can make a new account - but you'll have to copy your projects over on your own.

What information can I share on / with my account?

Please don't share personal contact information, such as your physical address, email, phone number, or anything else that can be used to make contact outside of the Scratch website. Please report projects, comments, or forum posts that contain this kind of information so the Scratch team can remove it, and remind the author of our policy.

How do I delete my account?

Log in to Scratch, and then click your username in the top right-hand corner. Select "Account Settings," then click the "I want to delete my account" link at the bottom of the page.

Licensing and Permissions

Is Scratch free?

Yes! Scratch is available free of charge. You can use it in your school, and you can teach a course about it (even a course that costs money). You don't need to buy a license - it's free.

Can I use Scratch and / or screenshots of Scratch in a textbook or a CD?

Yes, you can even write a book or chapter about Scratch. You may also use the Scratch logo when referring to Scratch. You may create screenshots / images of the Scratch application and website, and consider them to be licensed under the Creative Commons Attribution-ShareAlike license. We ask that you include a note on your textbook / CD / what have you that says "Scratch is developed by the Lifelong Kindergarten Group at the MIT Media Lab. See http://scratch.mit.edu".

Can I include a description of Scratch and the Scratch logo in brochures or other materials?

Sure! We recommend the following description: "Scratch is a programming language and online community where you can create your own interactive stories, games, and animations -- and share your creations with others around the world. In the process of designing and programming Scratch projects, young people learn to think creatively, reason systematically, and work collaboratively. Scratch is a project of the Lifelong Kindergarten group at the MIT Media Lab. It is available for free at http://scratch.mit.edu"

Can I present Scratch at a conference?

Please feel free to make presentations about Scratch to educators or other groups. We grant our permission to make presentations.

May I use / remix Scratch support materials, sprites, images, sounds or sample projects I've found on the website?

Yes - Scratch support materials made available on the Scratch website by the Scratch Team are available under the Creative Commons Attribution-ShareAlike license, with the exception of the Scratch Logo, Scratch Cat, and Gobo (Scratch trademarks).

Can I sell my Scratch projects?

Certainly - your project is your creation. Keep in mind that once you share your project on Scratch, everyone is free to download, remix, and reuse it as per the terms of the CC-BY-SA 2.0 license. So if you intend to sell your project, you may want to un-share it from Scratch.

Where can I find the source code for Scratch?

The source code for Scratch 2 (website and editor) is not yet available. The source code for Scratch 1.4, written in Squeak, is available on github. The source code for the first version of the Scratch website - ScratchR - is available on Assembla.

Inappropriate Content

How do I know what is or isn't okay to share on the Scratch website?

Check out the Scratch community guidelines - they're brief and don't include a lot of legal stuff. There's a link at the bottom of every page on Scratch.

What do I do if I see something that's inappropriate?

You can click the link that says "report" on any project, comment, discussion post, or user page where you think something isn't ok for Scratch. If the situation is complicated, you can use the Contact Us link to explain. Be sure to include as much detail as you can, with links to relevant pages.

What do I do if I see someone being mean or disrespectful?

Don't add to the flames! Responding to mean comments with more mean comments just makes things worse, and could result in your account being blocked. Instead, simply report anything that is disrespectful or unconstructive, and we'll follow up with the author. We check reports every day, multiple times per day - so rest assured, we'll sort things out.

What does the Scratch team do when something is reported or flagged?

The Scratch Team reviews reported comments and projects every day. If something breaks the Scratch community guidelines, we may remove it and send a warning to the account. Depending on how bad it is (or if we've already warned the account), we may also block the accounts or networks that were used to share it.

What happens when an account is blocked?

When an account is blocked, the owner can no longer access it, or use it to create projects or comments. When they login, they see a page that explains why the account was blocked with a web form they can use to request to be unblocked. If the owner can show that they understand why their account was blocked, and promises to follow the community guidelines in the future, the Scratch Team will review their case. Accounts will only be unblocked in cases where the account owner's word can be trusted. Otherwise, the account (and most likely other accounts owned or created by that person) may be blocked permanently.

My mean brother / Kaj / some other bad guy stole my account and got it banned, what do I do?

You are responsible for keeping your password secure. If someone in real life takes control of your account and does bad stuff, tell the adults in charge of the computers. If you think someone you don't know got access to your account, change the password and / or use the contact us link to explain the situation. If you got blocked for doing something that broke the community guidelines, don't just say you got hacked. If we can't trust you, we won't unblock you.

Cloud Data

What is cloud data?

Cloud data is a feature in Scratch 2 that allows for data from a project to be saved and shared online. You can use cloud data to make surveys and other projects that store numbers over time.

Who can see the data stored in cloud data?

When you interact with a project using cloud data blocks, your information can be stored along with your username, and others can view it. Each project keeps a log of who interacted with it and any data they shared.

Why is cloud data currently limited to only numbers -- with no strings or lists?

The current site is limited to numbers in variables as an initial step to work out any issues with their use on the site. We plan to roll out cloud data features incrementally. If the infrastructure is working well, we plan to add other features (cloud lists, support for strings, etc.).

If I see someone post inappropriate content using cloud data, how do I report it?

Click the "Report this" button (under on the project player) to report inappropriate content in cloud data. The report form includes a link to a log of all cloud data in that project and who left it - you may want to take look at it before sending your report. Make sure that you mention "cloud data" when you type your reason in the report.

Can I make chat rooms with cloud data?

While it is technically possible to create chat rooms with cloud data, they are not currently allowed. We will reconsider this policy once we have a better sense of our capability for moderating and managing reports on cloud data.

How do I add a cloud variable when I'm making a project?

When you make a variable, you can check the box that says "Cloud variable." Any data you store will be saved on the server and visible to others.

Who can change the information in a cloud variable?

Only your project can store data in its cloud variable. If people change or remix your code, it creates a different variable in their project with the same name.

I am logged in, but I still cannot use projects with cloud data. What is going on?

You need to have become a "Scratcher" on the website to have access to cloud data. You can become a Scratcher through actively participating on the website.

Is it possible to make multiplayer games with cloud data?

Multiplayer games may be difficult to create, due to network speed and synchronization issues. However, some Scratchers are coming up with creative ways to use the cloud data for turn-by-turn and other games.

How long does it take for cloud data to reach another Scratcher?

It depends. If both Scratchers have a reasonably fast Internet connection (DSL/Cable), and there are no restrictive firewalls on the computers/network, updates should be transmitted in milliseconds. However, a lot of computers have firewall software running in them, and if the firewall software blocks outgoing connections to TCP port 531 and TCP port 843, the time-lag becomes one-second. We are currently trying to figure out ways in which we can work around this limitation.

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What is Scratch, and what can I do with it? Scratch is a programming language and online community where you can create your own interactive stories, games, and animations -- and share your creations with others around the world.

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http://scratched.gse.harvard.edu/ct/

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Computational thinking has received considerable attention over the past several years, but there are many perspectives on what computational thinking entails. We are interested in the ways that design-based learning activities - in particular, programming interactive media - support the development of computational thinking in young people.

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http://research.microsoft.com/apps/video/default.aspx?id=179285&r=1

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Computational thinking will be a fundamental skill used by everyone in the world. To reading, writing, and arithmetic, we should add computational thinking to every child's analytical ability. Computational thinking involves solving problems, designing systems, and understanding human behavior by drawing on the concepts that are fundamental to computer science. Thinking like a computer scientist means more than being able to program a computer. It requires the ability to abstract and thus to think at multiple levels of abstraction.

In this keynote address from Asia Faculty Summit 2012, Jeannette Wing, head of the Computer Science Department at Carnegie Mellon University, provides examples of computational thinking, argues that it has already influenced other disciplines, and promotes the idea that teaching computational thinking can not only inspire future generations to enter the field of computer science but benefit people in all fields.

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Computational Thinking - Microsoft Research

# data[].attributes.attachment_link.description
Computational thinking will be a fundamental skill used by everyone in the world. To reading, writing, and arithmetic, we should add computational thinking to every child's analytical ability. Computational thinking involves solving problems, designing systems, and understanding human behavior by drawing on the concepts that are fundamental to computer science.

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http://ct-stem.northwestern.edu/

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Teach with confidence

Our tried and tested lesson plan are NGSS-aligned, browser-friendly and free.

Designed to integrate with conventional curricula, CT-STEM lesson plans can be implemented on their own, or used to supplement lessons that you already feel comfortable teaching. Either way, your students will explore authentic computational practices that enrich convententional subject matter learning and nurture computational literacy.

Our content is co-designed with teachers, classroom tested, and backed by years of research at Northwestern University.

In addition, we offer discipline-specific coaching to all computing abilities. Our CT-STEM consultations and workshops have helped teachers confidently address the Next Generation Science Standards and equip their students for the future.

# data[].attributes.attachment_link.description
Our tried and tested lesson plan are NGSS-aligned, browser-friendly and free. Designed to integrate with conventional curricula, CT-STEM lesson plans can be implemented on their own, or used to supplement lessons that you already feel comfortable teaching. Either way, your students will explore authentic computational practices that enrich convententional subject matter learning and nurture computational literacy.

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https://studio.code.org/unplugged/unplug2.pdf

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http://download-star.com/8860478/ddl/103787/jRItzAxDhIzZDOWEzUAvzcpEAuzoixLcUQBLZtBbHGrbNkotrJ?b_adgroupid=3219657260&b_adid=8368571368&b_bidmatchtype=bb&b_campaignid=191060058&b_device=c&b_match=b&b_orderitemid=40775151513&b_query=scratch+2.0

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Scratch is one of the most popular programms at the moment, download it for free here. The free version has many new features. Speed of the whole programm was increased, some errors had been fixed, new functions had been added. Scratch will help you to get the best out of your computer - download now the free version for free.

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Computational Thinking - a 4 step approach and a new pedagogy ---A 4 step approach to solving real problems with Computational Thinking. A method and approach for use in the secondary school enviornment.

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Computational Thinking - a 4 step approach and a new pedagogy ---A 4 step approach to solving real problems with Computational Thinking. A method and approach for use in the secondary school enviornment.

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http://www.slideshare.net/StrategicITbyPFH/computational-thing-a-4-step-process

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Step Process Paul Herring St Peters Lutheran College Brisbane

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• Biology • Chemistry • Physics • Astronomy • Neurological Science

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School Wireless Coverage Practical Examples

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Computational Biology • Cryptography & Encryption

# data[].attributes.attachment_link.title
Computational Thinking - a 4 step approach and a new pedagogy

# data[].attributes.attachment_link.description
A 4 step approach to solving real problems with Computational Thinking. A method and approach for use in the secondary school enviornment.

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AP Computer Science Principles draws arts students into computational thinking in Alabama printed

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AP Computer Science Principles draws arts students into computational thinking in Alabama printed

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http://www.nsf.gov/discoveries/disc_summ.jsp?cntn_id=134321

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Discovery
Artful coders

Last December, the College Board launched a new Advanced Placement (AP) course designed to teach Computer Science Principles (CSP). The course, developed with support from the National Science Foundation (NSF), intends to make computer science accessible to all students and to increase participation by females, underrepresented minorities and students with disabilities.
March 6, 2015
For courses like this to be offered across the country, schools need instructors who are able to teach computer science. The CS10K initiative, led in part by NSF, aims to increase the number of computer science teachers to 10,000, and teacher professional development is critical to accomplishing this goal.

Carol Yarbrough, a computer science teacher at the Alabama School of Fine Arts, attended professional development training for CSP in 2013 and has taught the course at her school ever since.

In the past, her computer science courses were filled with students from the math and science track. However, in 2013, Alabama began to allow CSP and AP Computer Science to count as a math credit for students' graduation requirements. Previously, computer science had been treated as an elective that did not contribute to graduation requirements, which is the case in roughly half of the United States.

Two years after attending the training, Yarbrough's computer science classes are now filled with arts students, who focus on creative writing, dance, music, theater and visual arts.

"The old, mathematically-based, computing problems are not very exciting to students who use a smart phone and the Internet every day," she explained.

Instead, students taking CSP learn computing in a context that is exciting to them and allows them to see "how learning computing is relevant to their lives," Yarbrough said.

Her arts students have embraced the CSP course, she believes, because they are able to use mathematics and computer programs to express their creativity. In the class, students create designs that are aesthetically pleasing, write programs to play beautiful music and create interesting shapes using 3-D printers. Along the way, they learn mathematics, programming and computational thinking--a way of solving problems that draws on concepts fundamental to computer science.

CSP is opening up new worlds for these students by merging art with computing.

"The approach that the CS Principles course takes--teaching kids that computing is part of everything, rather than teaching it as a subject in isolation--is vital for these students," she said. "Once they have taken the CS Principles course and know more about computing, then they are interested in taking other computing courses because they now see the relevance it has to their lives."

Teaching students with different interests has also helped Yarbrough refresh her teaching and incorporate new strategies.

Yarbrough found that her arts students embrace open-ended creative projects that could be frustrating to her math and science students. They are enthusiastic about creating products that reflect their vision. These students need more mathematics instruction, but they easily pick up on design and aesthetic concepts.

Yarbrough has also seen reverse benefits for the math and science focused students.

"With the implementation of the Computer Science Principles course, I have seen my Math/Science students become more creative and grow tremendously by hanging on to do some things that are a little out of their comfort zone," Yarbrough said. "They used to tell me, 'I'm not creative, I'm Math and Science.' I don't hear that so much anymore because this class has helped them discover their creative side."

Jeff Gray has been piloting a college-level version of the CSP course at the University of Alabama since 2011 and has helped in facilitating a unique form of CSP professional development. Working with his co-principle investigators, Mary Boehm and Carol Crawford of A+ College Ready, on an NSF grant, their design of the CS4Alabama professional development adopts a teacher leader model, where a cohort of lead teachers mentor new teachers. In CS4Alabama, the majority of the teaching resources are developed and shared by the teachers themselves.

"This method respects the experiences of the teachers in their own classrooms and recognizes the special insights that they may bring to the course, which I may not know about," Gray said.

The professional development follows a blended format, with face-to-face meetings and online interactions. Teachers enroll in a massive open online course (MOOC) during the summer and join an online community, in addition to participating in three face-to-face meetings a year.

Bi-weekly online hangouts are facilitated by teacher leaders, and Google supported an extension to the MOOC that allowed over 1,100 other teachers across the United States to receive part of the online training.

In the first two years of offering the CSP course, Gray has seen significant demographic changes in the students who take Computer Science across Alabama. The CS4Alabama project, which is being evaluated by Haynie Research and Evaluation, is seeing a much broader interest in computing in Alabama classrooms. Currently, the enrollment is 47 percent young women or underrepresented minorities--as opposed to the 19 percent female and 12 percent underrepresented minorities, who took last year's AP Computer Science exam.

Gray believes this is because "CS Principles is not just about programming, but many other things related to computing that show the creative and impactful nature."

Gray will be reaching more teachers in the upcoming year. The third cohort of the CSP professional development just added 22 additional teachers who will begin their training this spring. Since 2011, Gray has taught the CSP course to over 30 pre-service mathematics teachers at the University of Alabama, which now allows the course to fulfill the programming requirement.

"CS Principles was intentionally designed to be relevant and engaging across a wide range of students," said Jan Cuny, program director for computing education at NSF. "Teachers are empowered to make many decisions--choosing the programming languages, applications and innovations that are to be taught--in order appeal to the interests and concerns of their specific students. One size doesn't fit all and Carol Yarbrough's experience shows the power of this approach."

Investigators
Jeffrey Gray
Mary Boehm

Related Institutions/Organizations
University of Alabama Tuscaloosa

Locations
Tuscaloosa , Alabama

Related Programs
STEM-C Partnerships: Computing Education for the 21st Century

Related Awards
#1240944 CS 10K: A Model for Statewide Deployment of CS Principles Courses
#1441045 Collaborative Research: CS10K: Infusing Cooperative Learning into Computer Science Principles Courses to Promote Engagement and Diversity

Years Research Conducted
2013 - 2015

Total Grants
$1,663,184

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Investigators Jeffrey Gray Mary Boehm Related Institutions/Organizations University of Alabama Tuscaloosa Locations Tuscaloosa

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Artful coders | NSF - National Science Foundation

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Discovery Artful coders Last December, the College Board launched a new Advanced Placement (AP) course designed to teach Computer Science Principles (CSP). The course, developed with support from the National Science Foundation (NSF), intends to make computer science accessible to all students and to increase participation by females, underrepresented minorities and students with disabilities.

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Developing computational thinking skills in an undergraduate curricululm

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Developing computational thinking skills in an undergraduate curricululm

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http://www.nsf.gov/awardsearch/showAward?AWD_ID=0939032

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CPATH-1: Developing Computational Thinking Skills Across the Undergraduate Curriculum
Award Abstract #0939032

NSF Org:
CNS
Division of Computer and Network Systems

Program Manager:
Harriet G. Taylor
CNS Division of Computer and Network Systems
CSE Directorate for Computer & Information Science & Engineering

Investigator(s):
Christopher Kuster ckuster@carrollu.edu (Principal Investigator)
Chenglie Hu (Co-Principal Investigator)

Sponsor:
Carroll University
100 North East Avenue
Waukesha, WI 53186-3103 (262)524-7654

NSF Program(s):
INFORMATION TECHNOLOGY RESEARC,
CPATH

ABSTRACT

This Carroll College CPATH Planning Grant is focused on increasing the number of students developing Computational Thinking (CT) competencies by infusing CT experiences into the undergraduate general education curriculum. The project team is: 1) reviewing and revising the BS degree requirements, and replacing the current math and computer science requirements with two new CT courses, 2) developing an interdisciplinary undergraduate minor in computational science, 3) developing an interdisciplinary undergraduate major in computational science, and finally 4) training faculty to teach new BS courses and help them integrate CT throughout individual curricula.

Intellectual Merit: These educators believe, based on the computing education literature that they have reviewed, that it is essential to begin building CT skills early in the undergraduate education for all students. Reaching students early in their undergraduate career ensures that students are prepared with the CT skills that they need to pursue graduate studies and that are highly desirable for future employment. Because CT skills will be so integral to the 21st century workplace, this project begins by developing two lower-level CT courses to be integrated into the general education curriculum for all BS degree students ? approximately 80% of the Carroll College student body.

To round out the college?s computational offerings, they are developing undergraduate minor and major programs in computational science. The computational courses developed through the proposed minor program will serve as a common area for collaboration among faculty from different fields. The major and minor programs will also allow students who have an interest in computational science to explore a variety of applications while learning the theory behind the techniques. Finally, the project team is integrating computational techniques into the student learning experience as a whole. They are working with faculty to keep the introductory-level courses relevant to current research and thus are ensuring that the knowledge that students gain early in their time at Carroll will be used throughout their undergraduate education.

Broader Impact

This NSF CISE CPATH planning grant is enabling Carroll College, a predominately undergraduate institution, to make a first critical step towards invigorating and strengthening offerings in the computational sciences. With this project, Carroll College will be able to significantly improve the computational thinking skills of their undergraduate student population. Additionally, this NSF CISE CPATH grant is enabling the College to develop faculty expertise in computational science program development that will result in opportunities for students to acquire computational thinking competency within multidisciplinary majors. It is expected that this curricular program will serve as a national model and will demonstrate how to develop computational thinking competency within a general education curriculum. It is expected that this program will work to attract more women and underrepresented minority students into the computational science field while providing the enhanced curriculum needed to ensure that students succeed in completing major and minor programs in computational science.

BOOKS/ONE TIME PROCEEDING

Christopher Kuster, John Symms,
Christopher May, Chenglie Hu. "Developing Computational Thinking Skills
across the Undergraduate Curriculum",&nbsp10/01/2010-09/30/2011,&nbsp" Proceedings of the 2011 Midwest
Instruction and Computing Symposium",&nbsp&nbsp2011,&nbsp"http://www2.css.edu/mics/proceedings.
html".

Please report errors in award information by writing to: awardsearch@nsf.gov.

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CNS Division of Computer and Network Systems Program

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Harriet G. Taylor CNS Division of Computer and Network Systems CSE Directorate for Computer & Information Science & Engineering Investigator

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NSF Award Search: Award#0939032 - CPATH-1: Developing Computational Thinking Skills Across the Undergraduate Curriculum

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CPATH-1: Developing Computational Thinking Skills Across the Undergraduate Curriculum Award Abstract #0939032 NSF Org: CNS Division of Computer and Network Systems Program Manager: Harriet G.

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http://www.nsf.gov/attachments/108852/public/wing_cacm.pdf

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National Science Foundation and the Museum of Science

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National Science Foundation and the Museum of Science

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http://www.nsf.gov/news/news_summ.jsp?cntn_id=135497

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Press Release 15-073
World premiere of 'The Science Behind Pixar' illustrates power of computational thinking

NSF-supported exhibition offers a unique look into the Pixar process July 7, 2015

This summer, visitors to the Museum of Science, Boston will be inspired by the science and technology behind some of the most beloved animated films and their characters, with the world premiere of The Science Behind Pixar.

This interactive 10,000-square-foot exhibition showcases the science, technology, engineering, and math (STEM) concepts used by the artists and computer scientists who help bring Pixar's award-winning films to the big screen.

The Science Behind Pixar was developed by the Museum of Science and Pixar Animation Studios with support from the National Science Foundation (NSF). The exhibition features more than 40 interactive exhibit elements and offers a variety of hands-on activities that empower visitors to imagine the STEM concepts behind Pixar's films.

" The Science Behind Pixar is a behind-the-scenes look at how our movies are made," said Ed Catmull, president of Pixar and Disney Animation Studios. "The interactive exhibition gives people the opportunity to learn about the jobs our filmmakers do every day and tackle similar problems. It's a great demonstration of how much creativity and imagination is involved in the science, technology, engineering, art and math thinking essential to our filmmaking process."

An NSF award to Clara Cahill of the Museum of Science in 2013 is helping to ensure that the design strategies for select exhibits in The Science Behind Pixar build computational thinking skills, especially for diverse middle and high school learners.

"Computational thinking" is the term used to describe a set of problem-solving skills in which a problem is broken down into variables and all possible solutions are considered--much like a computer would do--to help to ensure the correct decision is made.

"Increasingly, computational thinking is valued across a wide range of disciplines and efforts to cultivate computational thinking are critical," said Jim Kurose head of Computer and Information Science and Engineering at NSF. " The Science Behind Pixar provides an engaging, research-based means to do so across a range of learners."

Cahill and her team aimed to identify how museum exhibitions can help novice learners make sense of and interact with computational thinking tools, problem solving strategies, and technical solutions. The six components of the exhibition designed by Cahill's team teach visitors to break complex problems into smaller elements that are easier to understand. This process, known as decomposition, is a critical part of computational problem-solving.

The research study was prefaced with rigorous, iterative prototyping and formative evaluation with museum audiences, including diverse learners from grades 6-12. The testing focused on improving learning outcomes, engagement, usability, and accessibility. After each round of prototyping and formative evaluation with museum audiences, iterative changes were made to the software, graphics, physical design, labels, and/or the user experience design to improve the visitor experience.

Overall, nearly 500 visitors participated in the evaluation efforts for these select exhibits, which ensured the exhibits in the show met their intended educational goals.

"Preliminary findings from the first phase of our research were used to inform the design of learning supports to help students engage in the kinds of sophisticated thinking and learning strategies used by more experienced computer programmers," said Cahill. "Preliminary findings from the second phase of the research suggest that the exhibition has the potential not only to stimulate awareness and practice of computational thinking skills, but also to increase self-efficacy and interest for computing and computing careers among diverse learners who may not otherwise have exposure to computational thinking."

The exhibition will be on view at the Museum of Science, Boston until December 2015, and will then travel to venues throughout the U.S. over the following five years. Over its lifespan, the team expects the exhibition to be viewed by at least 1 million visitors.

-NSF-

Media Contacts
Aaron Dubrow, NSF, 703-292-4489, adubrow@nsf.gov
Erin Shannon, Museum of Science, (617) 589-0250, eshannon@mos.org

Principal Investigators
Clara Cahill, Museum of Science, 617-723-2500, ccahill@mos.org

Related Websites
The Science Behind Pixar: http://www.mos.org/exhibits/the-science-behind-pixar
Research on Learning in Formal and Informal Settings at NSF: https://www.nsf.gov/div/index.jsp?org=DRL

The National Science Foundation (NSF) is an independent federal agency that supports fundamental research and education across all fields of science and engineering. In fiscal year (FY) 2016, its budget is $7.5 billion. NSF funds reach all 50 states through grants to nearly 2,000 colleges, universities and other institutions. Each year, NSF receives more than 48,000 competitive proposals for funding and makes about 12,000 new funding awards. NSF also awards about $626 million in professional and service contracts yearly.

Get News Updates by Email

Useful NSF Web Sites:
NSF Home Page: http://www.nsf.gov
NSF News: http://www.nsf.gov/news/
For the News Media: http://www.nsf.gov/news/newsroom.jsp
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Computer and Information Science and Engineering

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World premiere of 'The Science Behind Pixar' illustrates power of computational thinking | NSF - National Science Foundation

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Press Release 15-073 World premiere of 'The Science Behind Pixar' illustrates power of computational thinking NSF-supported exhibition offers a unique look into the Pixar process July 7, 2015 This summer, visitors to the Museum of Science, Boston will be inspired by the science and technology behind some of the most beloved animated films and their characters, with the world premiere of The Science Behind Pixar.

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http://www.p21.org/our-work/p21-framework

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https://live360events.com/Events/Orlando-2015/Sessions/Thursday/SQH15-Eye-Vegetables-and-Eye-Candy-How-to-Visualize-Your-Data.aspx

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http://www8.cs.umu.se/education/examina/Rapporter/LinneaWarmedal.pdf

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