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Analyzing and Optimizing Abstract Data Types with AI Support
Example developed based on CLOs from: CS 261 – Introduction to Data Structures.
Purpose
This assignment helps students analyze and optimize abstract data types by using AI tools to evaluate and refine their solutions. It emphasizes critical thinking and problem-solving in the context of real-world computational challenges.
Learning Outcomes
- Analyze the properties and behaviors of abstract data types for specific problem scenarios.
- Use AI tools to identify potential optimizations in data structure implementations.
- Reflect on the process of improving abstract data type performance and usability.
Instructions
Format (Final Deliverable)
- Abstract Data Type Analysis
- Review the properties and behaviors of a provided abstract data type (e.g., a stack, queue, or sorted collection).
- Use Microsoft Copilot to suggest potential optimizations for improving its performance in given scenarios.
- Evaluate the AI-generated suggestions and implement one optimization.
- Implementation
- Modify the provided implementation of the abstract data type to include your selected optimization.
- Document your changes with detailed comments explaining the rationale behind the optimization.
- Reflection
- Write a 300-word reflection addressing:
- How AI tools supported your analysis and optimization process.
- Challenges faced and insights gained during implementation.
- The impact of the optimization on data type performance and usability.
- Write a 300-word reflection addressing:
Grading Criteria
- Depth and accuracy of the analysis (40%)
- Quality and correctness of the optimized implementation (30%)
- Effective use of AI tools with proper documentation (20%)
- Insightfulness of reflection (10%)
Resources
- Writing Center consultations for organizing and refining reflections.
- Microsoft Copilot for generating optimization suggestions.
- Python resources, such as GeeksforGeeks Abstract Data Types Guide, for reference.