📅 2025-06-26 — Session: Developed student report generation pipeline
🕒 03:05–04:25
🏷️ Labels: Student Reports, Data Processing, Python, Education, Report Generation
📂 Project: Teaching
⭐ Priority: MEDIUM
Session Goal
The session aimed to develop a robust pipeline for generating individualized student reports from Google Sheets data, focusing on transparency, personalization, and pedagogical value.
Key Activities
- Reflected on emotional communication and self-voice in personal relationships.
- Outlined a strategy for generating student reports, emphasizing transparency and personalization.
- Detailed a structured approach for creating reports using Python libraries like Pandas, Jinja2, and WeasyPrint.
- Provided step-by-step instructions for loading Google Sheets data into Pandas DataFrames using gspread.
- Executed data preprocessing steps for normalization and score parsing.
- Discussed core design goals and created a blueprint for student report sheets.
- Implemented a data cleaning model for student data, focusing on metadata and score separation.
Achievements
- Established a comprehensive plan and methodology for student report generation.
- Developed a workflow for loading and preprocessing Google Sheets data.
- Created a design blueprint that includes pedagogical goals and data visualization elements.
Pending Tasks
- Implement the report generation code using the outlined methodologies.
- Test the pipeline with real student data to ensure accuracy and efficiency.