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Supporting students’ self-regulated learning with an open learner model in a linear equation tutor. (English)
Lane, H. Chad (ed.) et al., Artificial intelligence in education. 16th international conference, AIED 2013, Memphis, TN, USA, July 9‒13, 2013. Proceedings. Berlin: Springer (ISBN 978-3-642-39111-8/pbk). Lecture Notes in Computer Science 7926, 219-228 (2013).
Summary: Self-assessment and study choice are two important metacognitive processes involved in self-regulated learning. Yet not much empirical work has been conducted in ITSs to investigate how we can best support these two processes and improve students’ learning outcomes. The present work redesigned an open learner model (OLM) with three features aimed at supporting self-assessment (self-assessment prompts, delaying the update of the skill bars and progress information on the problem type level). We also added a problem selection feature. A $2\times 2$ experiment with 62 7th graders using variations of an ITS for linear equation solving found that students who had access to the OLM performed significantly better on the post-test. To the best of our knowledge, the study is the first experimental study that shows an OLM enhances students’ learning outcomes with an ITS. It also helps establish that self-assessment has key influence on student learning of problem solving tasks.
Classification: C30 R40 U50 H30 R20