Developed student report generation pipeline

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Developed student report generation pipeline

  • Day: 2025-06-26
  • Time: 03:05 to 04:25
  • Project: Teaching
  • Workspace: WP 2: Operational
  • Status: In Progress
  • Priority: MEDIUM
  • Assignee: Matías Nehuen Iglesias
  • Tags: Student Reports, Data Processing, Python, Education, Report Generation

Description

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.

Evidence

  • source_file=2025-06-26.sessions.jsonl, line_number=3, event_count=0, session_id=9c1d1396cea213430227d818ecc246633c2f8b5089cd1befc50e0620cd99e241
  • event_ids: []

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