Mining Key Formative Assessment Rules based on Learner Profiles for Web-based Learning Systems

Abstract

Currently, online learning is becoming more and more important, but there is still lack of an effective learning performance assessment mechanism on it. Traditional summative evaluation only considers final learning outcomes. However, the use of learning portfolios in a web-based learning environment can be beneficially applied to record the procedure of the learning, evaluate the learning performance of learners, and feed information back to learners in ways that enable the learner to learn better. Accordingly, this study proposes a formative assessment approach using data mining techniques to identify the key formative assessment rules based on the web-based learning portfolios of an individual learner. Moreover, the factor analysis provides benefit in terms of obtaining simple and clear learning assessment rules.