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CSP Python — Unit 6 Assessment Lists & Data Collections (Quizzes + Mini Project)
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Description

Assess student understanding of Python lists and data collections with this complete Computer Science Principles (CSP) Unit 6 Assessment Bundle.

This bundle includes two quizzes and one mini project, providing a balanced mix of concept checks, tracing, reasoning, and real-world data application. Students demonstrate mastery of list fundamentals, looping through lists, and interpreting lists as simple datasets.

All assessments follow the Mr. H Codes assessment style — clear, structured, student-friendly, and sub-ready, with full answer keys and a grading rubric included.

📚 What’s Included in This Assessment Bundle

Quiz A — Lessons 6.1–6.3 (Lists Fundamentals)

  • What lists are and why they’re used
  • Creating lists with brackets [ ]
  • Zero-based indexing
  • Accessing list values
  • Modifying lists with append() and remove()
  • Tracing list changes and debugging errors

📄 12-question quiz with multiple-choice, short answer, tracing, and reasoning questions

Quiz B — Lessons 6.4–6.5 (Lists + Data Thinking)

  • Looping through lists with for loops
  • Loop–list tracing and output prediction
  • Debugging list-loop logic
  • Lists as simple datasets
  • Data interpretation and reasoning

📄 12-question quiz with tracing tables, output prediction, and written reasoning

Unit 6 Mini Project — List Data Analyzer

  • Students create a list representing real-world data
  • Use loops to process the data
  • Analyze highest/lowest values and patterns
  • Interpret and explain what the data shows

📄 Includes:

  • Step-by-step project instructions
  • JDoodle setup guidance
  • Submission checklist
  • 20-point grading rubric

🧠 Skills Assessed

  • Data abstraction using lists
  • Indexing and modifying collections
  • Loop execution and tracing
  • Debugging list-based code
  • Data interpretation and reasoning
  • Computational thinking

🧑‍🏫 Best For

  • Computer Science Principles (CSP)
  • Python-based CS courses
  • Grades 9–12
  • End-of-unit assessments
  • In-class testing, sub plans, or project-based learning

⏱️ Time Required

  • Quizzes: 20–30 minutes each
  • Mini Project: 1–2 class periods

🖥️ Programming Language

Python

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Reported resources will be reviewed by our team. Report this resource to let us know if this resource violates TPT's content guidelines.

CSP Python — Unit 6 Assessment Lists & Data Collections (Quizzes + Mini Project)

Mr. H Codes
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Highlights

Digital downloads
Grades icon
Grades
9th - 12th, Adult Education, Higher Education
Standards icon
Standards
Pages
12
Answer Key
Included
Teaching Duration
3 days

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Description

Assess student understanding of Python lists and data collections with this complete Computer Science Principles (CSP) Unit 6 Assessment Bundle.

This bundle includes two quizzes and one mini project, providing a balanced mix of concept checks, tracing, reasoning, and real-world data application. Students demonstrate mastery of list fundamentals, looping through lists, and interpreting lists as simple datasets.

All assessments follow the Mr. H Codes assessment style — clear, structured, student-friendly, and sub-ready, with full answer keys and a grading rubric included.

📚 What’s Included in This Assessment Bundle

Quiz A — Lessons 6.1–6.3 (Lists Fundamentals)

  • What lists are and why they’re used
  • Creating lists with brackets [ ]
  • Zero-based indexing
  • Accessing list values
  • Modifying lists with append() and remove()
  • Tracing list changes and debugging errors

📄 12-question quiz with multiple-choice, short answer, tracing, and reasoning questions

Quiz B — Lessons 6.4–6.5 (Lists + Data Thinking)

  • Looping through lists with for loops
  • Loop–list tracing and output prediction
  • Debugging list-loop logic
  • Lists as simple datasets
  • Data interpretation and reasoning

📄 12-question quiz with tracing tables, output prediction, and written reasoning

Unit 6 Mini Project — List Data Analyzer

  • Students create a list representing real-world data
  • Use loops to process the data
  • Analyze highest/lowest values and patterns
  • Interpret and explain what the data shows

📄 Includes:

  • Step-by-step project instructions
  • JDoodle setup guidance
  • Submission checklist
  • 20-point grading rubric

🧠 Skills Assessed

  • Data abstraction using lists
  • Indexing and modifying collections
  • Loop execution and tracing
  • Debugging list-based code
  • Data interpretation and reasoning
  • Computational thinking

🧑‍🏫 Best For

  • Computer Science Principles (CSP)
  • Python-based CS courses
  • Grades 9–12
  • End-of-unit assessments
  • In-class testing, sub plans, or project-based learning

⏱️ Time Required

  • Quizzes: 20–30 minutes each
  • Mini Project: 1–2 class periods

🖥️ Programming Language

Python

Report this resource to TPT
Reported resources will be reviewed by our team. Report this resource to let us know if this resource violates TPT's content guidelines.

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Standards

to see state-specific standards (only available in the US).
Follow precisely a complex multistep procedure when carrying out experiments, taking measurements, or performing technical tasks, attending to special cases or exceptions defined in the text.
Follow precisely a complex multistep procedure when carrying out experiments, taking measurements, or performing technical tasks; analyze the specific results based on explanations in the text.
Make sense of problems and persevere in solving them. Mathematically proficient students start by explaining to themselves the meaning of a problem and looking for entry points to its solution. They analyze givens, constraints, relationships, and goals. They make conjectures about the form and meaning of the solution and plan a solution pathway rather than simply jumping into a solution attempt. They consider analogous problems, and try special cases and simpler forms of the original problem in order to gain insight into its solution. They monitor and evaluate their progress and change course if necessary. Older students might, depending on the context of the problem, transform algebraic expressions or change the viewing window on their graphing calculator to get the information they need. Mathematically proficient students can explain correspondences between equations, verbal descriptions, tables, and graphs or draw diagrams of important features and relationships, graph data, and search for regularity or trends. Younger students might rely on using concrete objects or pictures to help conceptualize and solve a problem. Mathematically proficient students check their answers to problems using a different method, and they continually ask themselves, "Does this make sense?" They can understand the approaches of others to solving complex problems and identify correspondences between different approaches.
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