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💡 CT Solution:

Decomposition: Break down the challenge by identifying different learning needs - students who need more support, students who need enrichment, visual/auditory/kinesthetic learners.

Pattern Recognition:  Observe when and where students struggle or excel - do certain students need more help with reading, while others grasp math concepts quickly? Are there common challenges across the class?

Abstraction: Focus on the key differences in learning styles and understanding levels rather than trying to individualize every lesson completely.

Algorithmic Thinking: Develop a structured plan for differentiation, such as tiered activities, flexible grouping, and multimodal instruction - hands on activities, visuals, verbal explanations.

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CT Solution:

Decomposition: Break down the problem by determining which assignments take the longest to evaluate and how long it takes to grade each student.

Pattern Recognition: Identify trends, if grading open-ended assignments takes much longer than multiple-choice ones, delays are common during peak assessment periods, and teachers in similar grade levels report the same problem.

Abstraction: Focus on the essentials; students gain the most from fast and relevant feedback and not every assignment requires thorough written comments.

Algorithmic Thinking: Create a step-by-step method, organize assignments by kind and grading time necessary, and determine which ones may be auto-graded or peer-reviewed. Wherever possible, incorporate technology to speed up grading.

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🛠 Challenge: Students frequently turn in late assignments or procrastinate on work.

💡 CT Solution:

Decomposition: Identify if it is all assignments (is it only classroom work, tests/quizzes, homework etc)

Pattern Recognition: Track how long each assignment actually takes (not how long it should take)

Abstraction: Focus on the assignments that are taking the longest and are causing the most distractions.

Algorithmic Thinking: Create a step-by-step plan on how to cut down on procrastination.

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Apply computational thinking strategies to solve this challenge.

🛠 Challenge: Teachers spend too much time grading, delaying feedback for students.

💡 CT Solution:

Decomposition:

break down into key aspects (how many graded assignments is the teacher giving, how much time does the teacher have to grade things, what other things does the teacher spend their time on, what assignments take the most time to grade)

Pattern Recognition: teacher would find out what assignments take longer to grade, and other reoccurring reasons for the grades to be late.

Abstraction:

teachers will focus on the key aspects of getting grades in on time (when to start grading assignments, what assignments should be graded first, how to grade more efficiently)

Algorithmic Thinking:

teachers will set a grading schedule where an appropriate ammount of time is dedicated to grading each assignment depending on how demanding the feedback required is.

Where do we see algorithmic thinking in everyday classroom activities?

the class schedule for each day and the lesson plan.

How computational thinking helped you break down the problem?

the problem was originally very broad but it was able to be broken down into manageable parts that had solutions. It is a great way to solve complex problems that require complex solutions.

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CT Solutions:

1. Decomposition: Talk to student alone about what the bigger issue may be. For example he could be struggling in other classes or home life etc.

2. Pattern Recognition: Observe and talk to find out if the student may be struggling in other categories or if theres a trend matching up to the work turned it late. There should be a bigger picture!

3. Abstraction: It's most important to get to the root of the problem because there is a reason or more then just one for work being turned in late or just not getting done. Once that is figured out the correction can be made. If you notice the child is struggling that cannot be ignored!

4. Algorithmic Thinking: After everything is talked about I will come up with a strategy based off of the students needs to better help them complete school work on time. We will work together so the student knows I care and want them to succeed!

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🛠 Challenge: Transitions between lessons or activities take too long, wasting instructional time.

💡 CT Solution:

Decomposition: Identify the components of the transition process (e.g., preparing materials, getting students' attention, organizing physical space, moving between tasks).

Pattern Recognition: Look for any recurring behaviors or timing issues that might be causing the slowdowns (e.g., students needing additional instructions, classroom setup taking too long).

Abstraction: Focus on the most important steps needed for an efficient transition (e.g., clear signals for when transitions start and end, clear instructions on what students need to do).

Algorithmic Thinking: Implement time limits or checkpoints to ensure that transitions stay on schedule. A routine process for transitioning that students can follow (e.g., “Step 1: Finish current task. Step 2: Put materials away. Step 3: Take out materials for the next activity. Step 4: Wait for the transition signal”)

Reflect:

How computational thinking helped you break down the problem?

Computational thinking helped break down the transition process by breaking it into smaller components, such as preparing materials and getting students’ attention. This approach made it easier to identify specific issues and focus on improving key areas instead of addressing the entire process at once.

Why is pattern recognition important in problem-solving?

Pattern recognition was important because it helped identify recurring issues, like students needing extra instructions or classroom setup delays. By recognizing these patterns, we could focus on the root causes of slow transitions and find targeted solutions to improve efficiency.

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CT Solution:

Decomposition:

Break down the grading process, we can identify inefficiencies and find solutions for each part. Like what tasks take up the most time, what tools are being used to grade, and what types of assignments require the most feedback.

Pattern Recognition:

Recognizing patterns in grading can highlight common challenges like repetitive feedback and certain assignments take longer to grade. Understanding patterns helps predict grading bottlenecks and find solutions.

Abstraction:

This will help us focus on essential elements and critical grading components, we can design rubrics, self-assessments, and AI-powered feedback tools.

Algorithmic Thinking:

Teachers can have a structured grading workflow, where auto-grading for multiple choice questions, pre-made comment banks for writing feedback, and peer reviews for first drafts before teacher feedback can be used.

Overall, the CT solution has faster grading through automation and structured workflows. Timely feedback for students, improving learning outcomes. Reduced teacher workload with teach-assisted strategies. Lastly, More meaningful feedback by prioritizing high-impact grading. By intergrating CT, we optimize grading workflows and ensure better learning experiences for students.

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Challenge: Transitions between lessons or activities take too long, wasting instructional time.

Decomposition: Break the problem down. Are transitions slow because kids don't know what to do? Are materials disorganized? Are directions unclear?

Pattern Recognition: Try and identify when it happens the most. Does it happen after recess? Before lunch? Is it the same students who are struggling each time?

Abstraction: Focus on the most common issue (ex: students not knowing where to go next/ what to do) instead of trying to fix every small delay.

Algorithmic Thinking: Create a routine with clear steps

1. Timer is somewhere all students can see

2. Music cue for clean-up

3. Use a picture chart that shows next steps

4. Practice the new routine until it become automatic

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🛠 Challenge: Students have varying levels of understanding and learning styles.

💡 CT Solution:

Decomposition: Make sure all information is broken down into smaller steps and similar levels of thinking. Instead of doing a huge lesson all at once it can be separated into different categories or at a different pace.

Pattern Recognition: Allow students to complete assignments in ways they have been successful before instead of trying to force new material in a way they have never seen before.

Abstraction: Maybe take small assignments out of lessons that will confuse students and allow them to focus on the important material and necessary assignments.

Algorithmic Thinking: Create different versions of assignments for students with different learning styles or needs and allow them to follow one of the paths based on their strengths.

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Computational thinking helped me break down this issue to look at both sides. By using the four strategies, I had two main areas of concern in this challenge. The teacher's efficiency and the relevancy of the parents' questions. Pattern recognition helped me because it gave me space to reflect on the challenge as a whole, asking if this is a pattern the teacher has had in previous school years or if its something occurring in the whole grade, which then brings my attention to the parents. I think that algorithmic thinking happens in everyday life, as it is one of the most common and effective forms of problem solving. This is certainly a method that we can teach students when needing to problem solve by practicing the breakdown of challenges and attempting to solve in different ways.

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🛠 Challenge: Teachers spend too much time grading, delaying feedback for students.

💡 CT Solution:

Decomposition: Break it down into categories based on how long it will take to grade. Short assignments include in-class worksheets and homework assignments. Longer assignments would be projects, tests, and essays.

Pattern Recognition: Seeing that some assignments take longer to evaluate than others (for example: an essay being graded vs a worksheet)

Abstraction: Focus on providing feedback where students would benefit most from. Adding notes to a study guide is important so students can study the correct material. Adding feedback to an in-class worksheet would not be a priority.

Algorithmic Thinking: Making a schedule to ensure that grades are completed on time. Setting aside time each day to grade some of the assignments at a time. (example: grading five essays a day on Monday-Thursday so students can receive their grade on Friday)

How did decomposition help you understand the problem? Decomposition helped me to understand the problem since it made me see what would potentially cause delays in grading. Breaking it down into steps makes it more manageable and allows you to focus on one thing at a time.

How can we use abstraction to make student learning more efficient? We can use abstraction to make student learning more efficient by only providing feedback where it would benefit students most. We can also do this by assigning work that will positively impact students learning the most. For example, one longer assignment including all the key information rather than “busy work.”

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Challenge 4_ Reducing Student Procrastination and Missing Assignments - Maddie Liebert

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Decomposition: Break down the transition process into smaller steps to identify where delays occur. For example: Ending the previous activity, Giving instructions for the next activity, Students moving from one place to another, Managing materials and supplies and Settling into the new activity.

Pattern Recognition: Identify common issues that slow down transitions like, students not listening to instructions, unclear expectations and off-task behavior

Abstraction: Focus on the important aspects of a smooth transition while ignoring unnecessary details. For example:

Define a consistent routine that applies to all transitions.

Use visual/auditory cues instead of lengthy explanations.

Minimize steps needed to switch tasks.

Algorithmic Thinking: Create a step-by-step process to ease transitions like a cue to the transition (e.g., play a short sound, display a timer, use a verbal cue).

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Apply computational thinking strategies to solve this challenge.

🛠 Challenge: Students have varying levels of understanding and learning styles.

💡 CT Solution:

Decomposition: Identify the needs of each individual student. See which students need additional support.

Pattern Recognition: Analyze students partaking in activities. See where students need the most guidance and make adjustments accordingly, so every student learns efficiently.

Abstraction: Group students based on their levels of learning and which students need the most help or guidance in class. This will give every student ample amount of time to learn in class.

Algorithmic Thinking: Create an algorithm to group and teach students effectively. Come up with activities and assignments that enhance their learning.

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🛠 Challenge: Students have varying levels of understanding and learning styles.

💡 CT Solution:

Decomposition: Break down the problem into smaller, more manageable parts. Instead of tackling the entire issue at once, focus on Identifying individual learning styles, recognizing different levels of understanding, and addressing specific areas of difficulty or misunderstanding for students.

Pattern Recognition: Look for patterns in how students learn, engage, and progress such as Identifying which teaching methods work best for each learning style, spotting common areas where students tend to struggle and recognizing trends in performance or behavior related to different teaching strategies.

Abstraction: Remove unnecessary details and focus on the core problem: helping students learn effectively despite their varying levels and styles. Designing a flexible system that adapts to each student's needs and simplifying the solution to avoid overcomplication while ensuring all essential needs are met.

Algorithmic Thinking: Create a step-by-step process for addressing the challenge. This could be: assessing each student’s learning style and understanding level, tailoring the teaching method to fit the student’s needs and adjusting the approach based on feedback and performance data.

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🛠 Challenge: Teachers spend too much time grading, delaying feedback for students.

💡 CT Solution:

Decomposition: Break down grading into smaller tasks like grading multiple choice, essays, and providing feedback, then focus on automating or streamlining the most time consuming parts.

Pattern Recognition: Identify patterns in common assignments that can be automatically graded such as multiple choice and recurring feedback themes for students to speed up the process.

Abstraction: Simplify grading by using standardized rubrics, automated grading systems for objective questions, and templated feedback to minimize complexity and speed up feedback delivery.

Algorithmic Thinking: Create an algorithm that automates grading for objective questions, flags subjective ones for review, and uses templates for faster personalized feedback.

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🛠 Challenge: Transitions between lessons or activities take too long, wasting instructional time.

💡 CT Solution:

Decomposition: Break down the transition process into smaller steps, such as gathering materials, transitioning between spaces, and refocusing attention.

Pattern Recognition: Identify common delays or bottlenecks in transitions, like disorganization or unclear instructions.

Abstraction: Focus on the core elements that need to be streamlined, such as a clear routine or visual cues for students.

Algorithmic Thinking: Create a set of clear, repeatable steps for transitioning, such as a 3-minute timer or a specific sequence of actions to follow.

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🛠 Challenge: Students frequently turn in late assignments or procrastinate on work.

💡 CT Solution:

Decomposition: Break down the assignment process into smaller tasks, like setting deadlines, tracking progress, and reviewing work.

Pattern Recognition: Identify common reasons for procrastination, such as unclear deadlines or overwhelming tasks.

Abstraction: Focus on key factors that can encourage timely submissions, like setting clear expectations and reminders.

Algorithmic Thinking: Create a step by step plan for students to follow, such as breaking assignments into smaller chunks with more mini deadlines and regular check-ins.

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🛠 Challenge: Teachers struggle to keep up with parent communication and respond to emails/messages efficiently.
💡 CT Solution:

Decomposition: Break down the communication tasks into smaller parts, such as categorizing messages urgent, non urgent, feedback, inquiries and assigning time blocks for responses.

Pattern Recognition: Identify common questions or concerns that parents frequently raise and create response templates or automated replies to address those.

Abstraction: Focus on the core communication needs (acknowledging receipt of emails, answering common questions) while simplifying less relevant details to save time

Algorithmic Thinking: Develop a set of steps or guidelines for handling incoming messages based on urgency and type, like triaging urgent concerns first and automating routine responses.

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🛠 Challenge: Transitions between lessons or activities take too long, wasting instructional time.

💡 CT Solution:

Decomposition: Break the transition up into pieces with clean up and/or set up for the next activities.

Pattern Recognition: Address the recurring issues. Identify what is taking too long and discuss how you can make a solution.

Abstraction: Establish consistency. Create a routine that eliminates the waste of instructional time.

Algorithmic Thinking: Make a step-by-step routine or checklist of how to transition between activities

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Apply computational thinking strategies to solve this challenge.

🛠 Challenge: Transitions between lessons or activities take too long, wasting instructional time.

💡 CT Solution:

Decomposition: Breaking the issue into these smaller parts allows for targeted solutions to streamline the process. Transitions take too long due to factors like unclear instructions, slow material handling, and student distractions.

Pattern Recognition: Observe inefficiencies that occur in lab setups, group work, and digital task-switching, where structured routines improve efficiency(collecting material/cleanup). By analyzing these patterns, we can apply strategies such as automation, clear instructions, and role assignments.

Abstraction: Focus on the key issue being minimizing lost instructional time, so identify reducing unnecessary steps and distractions. Individual student behaviors may vary, but establishing a universal routine and expectations ensures consistency overall.

Algorithmic Thinking: Structured transition plans including countdown timers, assigned roles for material distribution, and preloaded digital tools. Reinforcing these steps through practice and incentives ensures smoother and faster transitions.

Reflect:

How computational thinking help you break down the problem?: Computational thinking allowed me to recognize a structured way to analyze the inefficiencies in transitions by breaking the issue into smaller, manageable parts. Being able to analyze delays for targeted solutions such as streamlining instructions, assigning roles, and using timers.

Why is pattern recognition important in problem-solving?: Pattern recognition helps identify similarities between this problem and other situations where efficiency is key, such as lab setups or daily activities like transitioning between warmups and note taking or daily assignments. Recognizing these patterns allows for the implementation of strategies to improve transitions effectively and make the most of the available class time.