Published July 18, 2022
| Version v1
Conference paper
Open
Online Item Response Theory (OIRT) - Tracking Student Abilities in Online Learning System
Creators
Contributors
Editors:
- 1. University of Canterbury, NZ
- 2. University of Illinois Urbana–Champaign, US
Description
In this study, we proposed an Online Item Response Theory Model (OIRT) by combining the Item Response Theory and Performance Factor Analysis (PFA) models. We fitted the proposed model with modified Variational Inference (VI) to perform real-time student
and item parameter estimation using both simulated data and real time series data collected from an online adaptive learning environment. Results showed that modified VI parameter estimation method outperformed other Bayesian parameter estimation methods in efficiency and accuracy. We also demonstrated that OIRT tracked students' ability growth
dynamically and efficiently, it also predicted students' future performance with reasonable AUC given limited input features.
Files
2022.EDM-posters.89.pdf
Files
(582.6 kB)
Name | Size | Download all |
---|---|---|
md5:f66a65b05a3ee1cafd834a51f8e32979
|
582.6 kB | Preview Download |