Recommending Data Structures for Use Cases with AI Support

Purpose

This assignment helps students apply their knowledge of linear data structures by using AI tools to recommend suitable implementations for specific problem scenarios. It emphasizes critical thinking and evaluation in selecting appropriate solutions.

Learning Outcomes

• Identify suitable linear data structures for various problem scenarios.
• Use AI tools to generate and refine recommendations for data structure implementations.
• Reflect on the decision-making process and evaluate the effectiveness of AI-generated solutions.

Instructions

Format (Final Deliverable)

1. Scenario-Based Recommendations
   • Review three problem scenarios provided by the instructor. Each scenario will include specific constraints (e.g., efficiency, memory usage, ease of implementation).
   • Use Microsoft Copilot to recommend appropriate linear data structures for each scenario.
     • Example prompt: “What is the best data structure to implement a queue with high throughput for insertion and deletion operations?”
     • Evaluate the AI-generated suggestions, considering their feasibility and alignment with scenario constraints.
     • Write a short justification for your chosen data structure based on your evaluation.
2. Implementation
   • Implement the recommended data structure in Python for one of the scenarios.
   • Document your code with comments explaining your design choices and the rationale for your implementation.
3. Reflection
   • Write a 300-word reflection addressing:
     • How AI tools supported your decision-making process.
     • Insights gained from the implementation.
     • Challenges faced and strategies for improving future work.

Grading Criteria

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

Resources

• Writing Center consultations for organizing and refining written justifications and reflections.
• Microsoft Copilot for generating recommendations and improving code.
• Python documentation and resources, such as W3Schools Python Tutorial.