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Recommending Data Structures with AI Support

Example developed based on CLOs from: CS 162 – Introduction to Computer Science II.

Purpose

This assignment helps students apply their knowledge of data structures to real-world problem scenarios.

Learning Outcomes

  • Identify and evaluate suitable data structures for specific problem scenarios.
  • Implement data structures in Python programs and analyze their performance.
  • Reflect on the decision-making process and evaluate the effectiveness of selected solutions.

Instructions

Format (Final Deliverable)

  1. Problem Scenarios and Data Structure Selection
    • Review three problem scenarios provided by the instructor, each with specific constraints (e.g., efficiency, memory usage, ease of implementation).
    • Use Microsoft Copilot to generate recommendations for data structures to address each scenario.
      • Example prompt: “What is the most efficient data structure to handle a queue with high insertion and deletion rates?”
      • Evaluate the AI-generated recommendations and select the most suitable data structure for each scenario, justifying your choice.
  2. Implementation
    • Implement your selected data structures in Python for one of the scenarios.
    • Include comments in your code explaining the rationale for your implementation choices.
  3. Reflection
    • Write a 300-word reflection addressing:
      • The role of AI tools in supporting your decision-making process.
      • Challenges and insights gained during the implementation.
      • The importance of understanding data structure properties in real-world applications.

Grading Criteria

  • Appropriateness of data structure selection and justification (40%)
  • Quality and correctness of the Python implementation (30%)
  • Effective use of AI tools with proper documentation (20%)
  • Depth of reflection on decision-making and implementation process (10%)

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