Build strong problem-solving habits with this complete Unit 2 Computational Thinking bundle for Intro to Computer Science.

In this unit, students learn how computer scientists approach complex problems using four core strategies:
Decomposition, Pattern Recognition, Abstraction, and Algorithms. Through real-world examples, guided reasoning, and hands-on practice, students see how these strategies work together to create clear, efficient solutions.

This unit is designed to follow Unit 1 and prepares students for future algorithm design and coding.

📦 What’s Included in Unit 2

🧩 Lessons

✔ Lesson 2.1 — Decomposition
✔ Lesson 2.2 — Pattern Recognition
✔ Lesson 2.3 — Abstraction
✔ Lesson 2.4 — Computational Thinking in Action

Each lesson includes:

• Student worksheet with mini lesson and examples
  
• Vocabulary with student-friendly definitions
  
• Guided practice with numbered examples
  
• Online coding practice (Python-Lite via JDoodle)
  
• Independent practice, critical thinking, and reflection
  
• Teacher guide with pacing, misconceptions, and discussion prompts
  
• Complete answer key
  

📝 Assessment & Project

✔ Unit 2 Quiz — Computational Thinking
✔ Unit 2 Mini Project — Computational Thinking Challenge

The mini project serves as a capstone application, requiring students to apply all four strategies to a real-world problem and explain their reasoning.

🧠 Skills & Concepts Covered

• Breaking complex problems into manageable parts
  
• Identifying patterns and repetition
  
• Focusing on essential details through abstraction
  
• Writing step-by-step algorithms
  
• Applying multiple strategies together
  
• Explaining problem-solving reasoning clearly
  

👩‍🏫 Classroom Use

• Intro to Computer Science
  
• Computational Thinking units
  
• Python-Lite courses
  
• Career & Technical Education (CTE)
  
• Grades 7–10
  
• Designed for 1–1.5 weeks of instruction
  

All materials follow Mr. H Codes formatting, are print-friendly, and classroom-ready with no prep required.