π 2025-03-11 β Session: Development of Exercise Enrichment Framework
π 03:30β05:00
π·οΈ Labels: Exercise Enrichment, AI, Data Science, Education, Metadata Extraction
π Project: Teaching
β Priority: MEDIUM
Session Goal
The session aimed to develop a comprehensive framework and processes for enriching educational exercises, leveraging AI and data science methodologies to enhance learning outcomes.
Key Activities
- Analysis of Exercise Enrichment: Proposed structured approaches to enrich exercises in educational settings using AI for better evaluation and learning pattern detection.
- Loading Data from Google Sheets: Implemented data loading techniques using Python libraries such as gspread and pandas.
- Installation of gspread Library: Set up necessary Python libraries to facilitate data handling from Google Sheets.
- Framework for Analyzing Exercises: Developed a reflective framework to analyze exercises, focusing on insights and actionable outcomes.
- AI-Driven Enrichment Models: Designed models combining human analysis and AI automation for exercise enrichment.
- Optimization in Data Science: Proposed workflows to optimize data science processes, focusing on maximizing insights and reducing redundancies.
- Exercise Enrichment Schema: Created schemas for programming exercises to integrate scientific and pedagogical insights.
- Asynchronous Metadata Extraction: Developed Python functions for extracting structured metadata using OpenAIβs API.
- Exercise Dataset Processing Pipeline: Outlined a pipeline for AI-based metadata extraction and dataset enrichment.
- Evaluation of AI Metadata Extraction: Assessed AIβs performance in metadata extraction, identifying strengths and areas for improvement.
Achievements
- Developed comprehensive frameworks and models for exercise enrichment.
- Implemented data handling and metadata extraction techniques using Python.
- Evaluated AIβs performance in metadata extraction, providing insights for further optimization.
Pending Tasks
- Further optimization of AI models for improved metadata extraction.
- Scaling the developed frameworks and models for broader application.