Probabilistic Models for Computerized Adaptive Testing: Experiments

2016/01/28 by Martin Plajner, Plajner, Martin, Jiří Vomlel +1
Computer Science · #AI-based Problem Solving and Planning #Artificial Intelligence (cs.AI) #Bayesian Modeling and Causal Inference #FOS: Computer and information sciences #Intelligent Tutoring Systems and Adaptive Learning

paper · pdf · doi:10.48550/arxiv.1601.07929

openalex publication_date 2016/01/28 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28

Abstract

This paper follows previous research we have already performed in the area of Bayesian networks models for CAT. We present models using Item Response Theory (IRT - standard CAT method), Bayesian networks, and neural networks. We conducted simulated CAT tests on empirical data. Results of these tests are presented for each model separately and compared.

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