Analyzed and Optimized Academic Course Structures

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Analyzed and Optimized Academic Course Structures

  • Day: 2023-11-16
  • Time: 20:30 to 23:50
  • Project: Teaching
  • Workspace: WP 2: Operational
  • Status: Completed
  • Priority: MEDIUM
  • Assignee: Matías Nehuen Iglesias
  • Tags: Python, Data Manipulation, Optimization, Education, Curriculum

Description

Session Goal:

The session aimed to analyze and optimize the structure of academic courses using data manipulation and optimization techniques in Python.

Key Activities:

  • Data Filtering: Implemented a Python script to filter unrelated course pairs in the lower triangle of a DataFrame, enhancing data clarity.
  • Optimization: Utilized cvxpy to solve a quadratic optimization problem, assigning course levels based on a matrix of correlativities.
  • Data Replacement: Replaced values in a DataFrame that exceeded absolute 100 with NaN using Pandas’ applymap for better data handling.
  • Difference Calculation: Developed a method using Pandas and NumPy to calculate semester differences between courses, facilitating data interpretation.
  • Lower Triangle Calculation: Computed the lower triangle of differences between DataFrames and replaced zeros with NaN for improved visualization.
  • Timeline Reconstruction: Reflected on a payment request event timeline to understand key actions and communications.
  • Email Template Creation: Created a structured email template to communicate curriculum correlativity analysis findings.
  • Academic Flexibility Analysis: Reflected on the flexibility of mathematics course sequences, proposing adjustments to course prerequisites.

Achievements:

  • Successfully filtered and optimized course data, providing clear insights into academic course structures.
  • Developed tools and templates to enhance communication and analysis of curriculum structures.

Pending Tasks:

  • Further analysis of curriculum flexibility and potential adjustments to enhance academic offerings.

Evidence

  • source_file=2023-11-16.sessions.jsonl, line_number=1, event_count=0, session_id=0a11c332aed099c913e64ee2c0a51b3fefeb42ee837dcf93d8351fac2711441b
  • event_ids: []

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