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Check out https://community.alteryx.com/t5/Data-Science/Kids-Explain-Data-Science-Episode-1-Clustering-the-Laundry/ba-p/559212 for the grown-up explanation!

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Florence the Data Scientist and Her Magical Bookmobile

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Florence the Data Scientist and Her Magical Bookmobile

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Follow along as Beatrice documents and analyzes data from a bookmobile that comes to her neighborhood! Digital E-book is free with email signup, and a hard copy book is available on amazon

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About Domino and the Author

What Do I Tell My Daughter on Career Day?

Hi there! My name is Ryan Kelly and I'm a marketing leader at Domino Data Lab.

I dreamed up this idea of writing the world's first-ever children's book about data science at something we call a "hack-a-thon" here at Domino, a week-long event where employees break up into dynamic, nimble teams to dream up big ideas and solve tough problems.

But, to tell you the truth, I didn't write this children's book to just encourage the next generation to get passionate about future careers in data science. I wrote it to inspire a passion for problem solving. Because, well, our world is full of problems and our future relies on the passion and willingness of future generations to solve them. I was also tired of trying to describe to my daughter what I did at work...

About Domino Data Lab: Domino is the enterprise MLOps platform trusted by 20% of the Fortune 100. Our platform accelerates research, speeds model deployment, and increases collaboration for code-first data science teams at scale. Unleash data science with Domino: learn more about our products here or watch a demo here.

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Florence the Data Scientist and Her Magical Bookmobile: The First-Ever Children's Book on Data Science | Domino Data Lab

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About Domino and the Author Hi there! My name is Ryan Kelly and I'm a marketing leader at Domino Data Lab.

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Write a short description and link to the website.

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For ages 6 - 19+

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Details

In this Activity Kit, you will help students train simple machine-learning models and use them to play games and complete interactive projects. This Activity Kit introduces students to the principles and implications of machine learning and artificial intelligence. In this activity, you and your students will input data and the machine creates links that help it answer questions that are not in the data. You can pick from over two dozen activities to fit your time and audience age requirements.

This activity kit will require the following resources:

An IBM Cloud account for the instructor

Experience with the programming language Scratch is helpful but not required

Students must have computers with internet access - sharing one computer between 2-3 students works well

Instructions

1. Learn more about machine learning and artificial intelligence on DeveloperWorks.

2. Become familiar with the Machine Learning for Kids site and available activities.

3. Learn more about IBM Cloud.

1. Ensure the school or group you are teaching will have computers with internet access; sharing one computer between 2-3 students works well.

2. Register for an IBM Cloud account if you do not have one already.

3. Select the Machine Learning Project(s) that you want to use for your event from the "Worksheet" page on the Machine Learning for Kids site. Ensure you choose Projects that are relevant to the age group you are teaching and for the appropriate amount of time. The screenshot below shows an example Scratch, a simplified programming language, that uses building blocks to teach kids about programming.

Example of one of the Scratch activities in the Machine Learning for Kids Activity Kit.

4. Download the Project Instructions sheets for Teachers and for Students for the Project you select. These instruction pages will provide helpful information about what exactly the students need to do to complete the Project. You may also want to print copies of the Student instructions for the Project(s) you have selected to hand out to the class.

5. Once you have decided on the Project on the Worksheet page, you will need to create an account. Click the link below and click "Get Started." On the following page, click "Sign Up" and then click "I am a teacher or leader of coding club" and follow the instructions for an "Unmanaged Class Account." This Class Account will be the account your students use to log in to participate in the Project and requires an IBM Cloud account. After confirming your email, you can log back into the Machine Learning for Kids site and use your Class Account for your activity. The Machine Learning for Kids website provides access to Watson Assistant running in the IBM Cloud. As the teacher, you will need to access the IBM Cloud and create API keys. These keys give the instructor access to Watson Assistant, IBM's Machine Learning system. As a teacher, the anonymous user ID and password you create will be distributed to your class who will then be able to access IBM's Watson Assistant. Information about how to do this and a step-by-step guide can be found here (note: you will need to be logged into the Machine Learning for Kids site).

6. Review this help guide for any questions that arise during your rehearsal or set up here:

1. Allow approximately 1 hour to walk through the Projects you have selected, review both the Teacher instructions and Student instructions and to create your IBM Cloud Account and your Class Account

2. Review this help guide for any questions that arise during your rehearsal or set up.

1. Give a brief overview of machine learning and the Project(s) the students will be doing.

2. Instruct students to log onto Machine Learning for Kids using your Class Account credentials:

3. Instruct students to download and follow the instructions for the Machine Learning Project you have selected, or hand out the printed copies.

4. Have fun!

IBM Cloud Account Information for Volunteers

IBM employees are encouraged to use their internal IBM Cloud accounts, which include all Lite services at no charge. IBM volunteers can also register for a Lite account following the link below. Questions can also be posted on the IBM Volunteers Slack channel.

Both IBM volunteers and non-IBM volunteers who require Cloud access beyond a Lite account are encouraged to request access to the IBM Citizenship Cloud by sending an email to citizenshipcloud@ibm.com with the following subject line "Citizenship Cloud Access." In the body of the email, please outline what cloud resources you need and which Activity Kit will be used. Students will get appropriate access directly from their teachers. Volunteers who only require a Lite account do not need to ask for access to the IBM Citizenship Cloud.

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Details In this Activity Kit, you will help students train simple machine-learning models and use them to play games and complete interactive projects. This Activity Kit introduces students to the principles and implications of machine learning and artificial intelligence.

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Berkeley's reimplementation of Scratch: https://snap.berkeley.edu/

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Bernat Romagosa, Michael Ball, Jens Mönig, Brian Harvey, Jadge Hügle

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The Snap! Community. Snap! is a blocks-based programming language built by UC Berkeley and used by hundreds of thousands of programmers around the world.

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Illustration by Rhiannon Newman for the Urban Institute

When the COVID-19 pandemic first shut down in-person learning, we knew education wouldn't be the same. How could kids - especially younger kids in elementary schools - learn and socialize if they weren't in a real classroom? In late 2021, we worked with a team of people from various groups - including the Concord Consortium, Esri, Found Spatial, the American Statistical Association, the Launch Years initiative at the University of Texas at Austin, and faculty members at the University of Memphis and the University of Tennessee - to provide an open repository of data-related educational material for educators, which resulted in our Data4Kids project.

The question of how to teach kids about data in a virtual environment inspired us to host a four-day special in March 2020 as part of the Data@Urban Digital Discussion series, a daily video conversation with leaders in the data science field. The special series for children focused on how to create data visualizations, write code with Scratch, design map projections, and collect and analyze data. More than 200 children from around the world attended these one-hour live sessions. As kids enthusiastically engaged with us, we saw their hunger for more information, resources, and education.

With support from the South Big Data Hub (via the National Science Foundation), the Urban Institute and our partners created a set of tools and resources to help teach kids in primary and secondary school about data, data science, and data visualization in a virtual environment. We balanced our expertise in data science and data visualization with our partners' expertise in conducting in-person and online instruction to children across the country.
Preparing the project
Although we are not professional educators, we believe analyzing and communicating data skills will be the currency of the next generation. As such, learning data science concepts is crucial. And as education at all levels increasingly turns to virtual teaching and virtual resources, we wanted to offer parents, educators, and students resources to help them along the way.

To conduct this work, we reached out to STEM educators across the country. We didn't know exactly what form the final product would be, but we knew it would live on a webpage, be open source and free, and be a living, growing, and evolving project.

With help from our Urban colleagues, we identified 10 people and organizations to participate in the project and invited them to join one of two five-hour virtual meetings in mid-September 2021.
Collaborating across education fields to brainstorm
In our first meeting, we brainstormed what the final project might look like. We discussed how we might engage Urban researchers in the project, make the existing Education Data Portal more kid friendly, and create some kind of "data.gov"-type resource for teachers.

As we brainstormed, we acknowledged some of these ideas were too large to tackle within our time and budget. We also wanted to provide educators tools or resources they could easily use today - but not an information dump. Instead, our tool or resource needed to guide instructors through the concepts, data, and visualizations. Finally, our tool or resource had to engage kids at various ages - what are they learning, how do they learn, and how can educators most effectively teach these concepts?

We landed on "data stories," or a series of educational resources around different topic areas. Each story would provide a starter kit for educators at different levels - grades 3-5, grades 6-8, and grades 9-12 - and include four primary components:

· data in Microsoft Excel, comma separated value, and Google Sheet formats

· a data dictionary in Microsoft Word and Google Doc formats

· teaching slides in Microsoft PowerPoint and Google Slides formats

· instructor guides that provide additional teaching resources and notes for each story in Microsoft Word and Google Docs formats

Despite already deciding on a path for our project in the first brainstorming meeting, we still needed collaborators' help in the second brainstorming meeting to define the pieces of the stories and to help us set specific learning goals and an overall organizing principal.

Our second brainstorming session showed us yet another reason why our collaborators are essential - we needed educators to help us shape the content. As one of our participants mentioned, "Teachers need to know what a lesson is designed to teach. It doesn't constrain them - it frees them to play with the lesson and decide how to best achieve that goal with their students."

With the data story concept in hand, our second meeting focused on what content would appear in each story and how to structure the instructor guides. In this one meeting, we refined the guide to five main sections:

1. data question

2. data collection

3. data analysis

4. data visualization

5. data equity, ethics, and privacy

As a group, we felt these five areas defined the core tasks in a data analysis workflow. Each section includes a learning goal with sample questions and answers for each aggregate grade level. We also created separate data files for each grade band and a secondary dataset with errors that would prime students to inspect, analyze, and understand the data.
Prototyping the data stories
Guided by our concept, we created the first data story prototype about state-level food insecurity and related measures. Our story contained the four primary components for each grade band and sections. The teaching slides (figure 1) indicate which slides are for each grade band. We then repeat this information with additional notes in the instructor guide (figure 2).

Figure 1. Screenshot of "Data Question" slide for grade band I from the Food Insecurity Data Story.

Figure 2. Screenshot of the instructor guide that outlines the "Data Question" for grade band I from the Food Insecurity Data Story.

With our prototype as an example, our collaborators formed teams and developed data stories, such as who visits national parks, where the highest eviction rates are, and more. We hope parents and educators will use these stories to teach kids about data science.
-Claire Bowen Want to learn more? Sign up for the Data@Urban newsletter.
But we're not done yet! We've included an open form for possible future collaborators to contribute and pitch their ideas for more data stories. We have created templates in all the above toolkits so anyone can assemble a dataset, formulate questions and answers, and develop data visualizations to help educators around the world. We hope you will consider collaborating with us to provide more data stories and data science resources.

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How Data4Kids Helps Students Log on to Learn

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When the COVID-19 pandemic first shut down in-person learning, we knew education wouldn't be the same. How could kids - especially younger kids in elementary schools - learn and socialize if they weren't in a real classroom?

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This is more of an introduction to coding in general, but it exposes kids to the logic of how computers read and interpret commands and information.

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With ScratchJr, young children (ages 5-7) can program their own interactive stories and games.

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SOAR (STEAM, Outreach, Achievement Recreation) is an organization at UNC that works to serve Latine students at McDougle Middle School. They are looking to recruit dedicated volunteers to serve as mentors for the 6th, 7th, and 8th grade kids in their program.

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Are you interested in the STEAM (Science Technology Engineering Art and Math) Fields? Are you looking for a reliable community service opportunity where you can really make a difference? SOAR (STEAM, Outreach, Achievement Recreation) is an organization at UNC that works to serve Latine students at McDougle Middle School. We are looking to recruit dedicated volunteers to serve as mentors for the 6th, 7th, and 8th grade kids in our program. You do NOT have to identify as Latine, and must only be committed to working hard to make a difference in our students lives!

As a member of SOAR you will help plan and teach STEM related experiments, lead activities that implement art, design, and reflection, and serve as positive role model for our students. You will be given the opportunity to mentor, serve and be a positive influence through our weekly sessions with our students. Most importantly, as a member of SOAR, you will be able to help our students SOAR and become confident that they can accomplish their dreams!

SOAR meets once a week. Volunteering this semester is currently on Thursday from 3:15 - 5:00 pm

Based on your application, we will conduct individual interviews if chosen.

If you have any questions please contact us at: uncsoar@gmail.com

Thank you!

DISCLAIMER: Meetings for SOAR this Spring may be held virtually due to the pandemic.

Please fill out the information below.

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Are you interested in the STEAM (Science Technology Engineering Art and Math) Fields? Are you looking for a reliable community service opportunity where you can really make a difference? SOAR (STEAM, Outreach, Achievement Recreation) is an organization at UNC that works to serve Latine students at McDougle Middle School.

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Data Science Lessons from youcubed & Stanford Graduate School of Education

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Data Science Lessons from youcubed & Stanford Graduate School of Education

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This page shares five units of youcubed lessons that introduce students (and teachers) to data science. The units start with an introduction to the concept of data and move to lessons that invite students to explore their own data sets.

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This page shares five units of youcubed lessons that introduce students (and teachers) to data science. The units start with an introduction to the concept of data and move to lessons that invite students to explore their own data sets. These lessons teach important content through a pattern-seeking, exploratory approach, and are designed to engage students actively. The culminating unit is a citizen science project that gives students an opportunity to conduct a data inquiry. The lessons accompany a new online course for teachers, where some of the lessons are featured, along with other lesson ideas. These lessons are offered with ideas for in-person or online teaching, and can be taught at any time of year.

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This page shares five units of youcubed lessons that introduce students (and teachers) to data science. The units start with an introduction to the concept of data and move to lessons that invite students to explore their own data sets. These lessons teach important content through a pattern-seeking, exploratory approach, and are designed to engage students actively.

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Data Nuggets are free classroom activities, co-designed by scientists and teachers. When using Data Nuggets students are provided with the details of authentic science research projects, and then get to work through an activity that gives them practice looking for patterns and developing explanations about natural phenomena using the scientific data from the study.

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Data Nuggets are free classroom activities, co-designed by scientists and teachers. When using Data Nuggets students are provided with the details of authentic science research projects...

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Data Clubs | Three Youth-oriented Modules

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Data Clubs | Three Youth-oriented Modules

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Data Clubs modules are designed to reflect the interests of middle school learners but are also appropriate for older youth.

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Data Clubs modules are designed to reflect the interests of middle school learners but are also appropriate for older youth. We have three modules in development: