Bayesian modeling of students’ mathematics skills

Python
Web
Bayesian Inference
Processed and analyzed students’ interaction data from a learning platform to model their mathematics skill mastery levels for 9th standard Algebra curriculam

GitHub Doc

Project overview

This Django project analyzes students’ interaction data stored in xAPI statements from the Vara learning platform. The dataset captures various key learning features including:

Number of attempts per activity
Hint usage patterns
Score achievement
Time spent on activities

The system also incorporates a mapping of each learning activity to specific mathematics skills aligned with a 9th Standard Algebra curriculum.

Technical Implementation

The solution combines a processing pipeline and dashboards for teachers and students.

Research Paper (Poster)

Some parts of this project’s results are presented in a Poster paper at the presitigious conference of Learning Analytics & Knowledge organized in Dublin, Ireland in 2025. You can access the paper here

⚡ Key Contributions
  • Preprocessed interaton data for student modeling
  • Developed open learner models for students using Bayesian Inference
  • Built dashboards to visualize learner model at individual and class levels

Skills Applied

Python Programming, Web Development, DevOps, Bayesian Modeling

Libraries Used

pgmpy,pandas,matplotlib,numpy,dash

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