Impact of different temporal lenghts on collaboration quality prediction

Python
Investigated impact of different temporal lengths on the performance of collaboration prediction model

GitHub DOI

Project overview

This project aimed at identifying optimal temporal window size to aggregate multimodal data into features that can improve generalizability of collaboration prediction models. The project analyzed audio and logs data collected from groups working to solve a given problem in collaboration.

Research Paper

The findings of this project were published in the Learning Analytics & Knowledge conference organized in Arizona, USA in 2023. You can access the paper here

🎖️ Honorable Mention:

This paper received an Honorable Mention award (top 5% of submissions) at the prestigious Learning Analytics and Knowledge (LAK’23) conference.

⚡ Key Contributions
  • Processed audio and logs data using different temporal window sizes
  • Developed machine learning models for predicting collaboration using processed data
  • Evaluated models at different levels of generalizability

Skills Applied

Python Programming, Web Development, DevOps, Bayesian Modeling

Libraries Used

pgmpy,pandas,matplotlib,numpy,dash

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