PSO-based Fuzzy Markup Language for Student Learning Performance Evaluation and Educational Application

24 Feb 2018Chang-Shing LeeMei-Hui WangChi-Shiang WangOlivier TeytaudJialin LiuSu-Wei LinPi-Hsia Hung

This paper proposes an agent with particle swarm optimization (PSO) based on a Fuzzy Markup Language (FML) for students learning performance evaluation and educational applications, and the proposed agent is according to the response data from a conventional test and an item response theory. First, we apply a GS-based parameter estimation mechanism to estimate the items parameters according to the response data, and then to compare its results with those of an IRT-based Bayesian parameter estimation mechanism... (read more)

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