Algorithm Teaching Assistant

Teaching Role #

Teaching Assistant for Algorithm course under Professors Dr. Hossein Falsafain and Dr. Zeinab Maleki at Isfahan University of Technology.

Primary Responsibilities #

• Debugging Assistance: Helped students identify and resolve issues in algorithm implementations
• Homework Support: Provided guidance on complex algorithm homework assignments
• Code Review: Analyzed student code for efficiency and correctness improvements
• Concept Clarification: Explained algorithmic concepts and problem-solving strategies

Algorithm Topics Covered #

• Sorting and Searching: Various sorting algorithms and search techniques
• Graph Algorithms: BFS, DFS, shortest path, and minimum spanning tree algorithms
• Dynamic Programming: Optimization problems and memoization techniques
• Greedy Algorithms: Local optimization strategies and proof techniques
• Divide and Conquer: Recursive problem-solving approaches
• Complexity Analysis: Big O notation and algorithm efficiency evaluation

Student Support Activities #

• One-on-One Debugging: Individual sessions to help students debug complex algorithm implementations
• Group Problem Solving: Collaborative sessions to work through challenging algorithmic problems
• Code Optimization: Taught students to improve algorithm efficiency and reduce time complexity
• Testing Strategies: Guided students in developing comprehensive test cases for their algorithms

Educational Impact #

• Problem-Solving Skills: Enhanced students' analytical and algorithmic thinking abilities
• Debugging Proficiency: Improved students' ability to identify and fix programming errors
• Code Quality: Helped students write cleaner, more efficient algorithmic solutions
• Competitive Programming: Prepared students for programming contests and technical interviews

Teaching Methods #

• Interactive Debugging: Step-by-step code analysis and problem identification
• Visual Algorithm Explanation: Used diagrams and examples to illustrate algorithm execution
• Practical Examples: Connected theoretical algorithms with real-world applications
• Progressive Learning: Gradually increased complexity of problems and solutions

Student Development Outcomes #

• Improved algorithmic problem-solving capabilities
• Enhanced debugging and code analysis skills
• Better understanding of algorithm complexity and optimization
• Increased confidence in tackling complex programming challenges