📅 2024-09-12 — Session: Matrix Algebra Exam Preparation and Code Implementation
🕒 17:25–18:50
🏷️ Labels: Linear Algebra, Python, Education, Github, Matrix Operations
📂 Project: Teaching
⭐ Priority: MEDIUM
Session Goal
The session aimed to prepare exam exercises and implement code solutions for teaching linear algebra concepts, including matrix inversion, Gaussian elimination, and base change in vector spaces.
Key Activities
- Exam Exercise Proposal: Designed exercises to evaluate students on matrix inversion, base change, and solving systems of linear equations.
- Code Implementation: Developed Python functions for matrix operations such as row echelon transformation, matrix inversion using back substitution, and Gaussian elimination.
- Numerical Precision Review: Addressed numerical precision issues in matrix inversion calculations, suggesting improvements using
np.allclose. - GitHub Setup: Organized student submissions via Git, including repository setup and instructions for exam submissions.
- Algorithm Correction: Corrected the Gaussian elimination algorithm to ensure proper storage of reduction factors in matrix L.
Achievements
- Created a comprehensive set of linear algebra exercises for educational purposes.
- Enhanced Python scripts for matrix operations, improving both functionality and accuracy.
- Established a GitHub-based workflow for managing student submissions effectively.
Pending Tasks
- Further review of numerical precision adjustments in matrix calculations.
- Continuous monitoring and feedback on student submissions through GitHub.