Scaffolding Self-Explanation to Improve Learning in Exploratory Learning Environments

Successful learning though exploration in open learning environments has been shown to depend on whether students possess the necessary meta-cognitive skills, including systematic exploration, hypothesis generation and hypothesis testing. We argue that an additional meta-cognitive skill crucial for effective learning through exploration is self-explanation: spontaneously explaining to oneself available instructional material in terms of the underlying domain knowledge. In this paper, we describe how we have expanded the student model of ACE, an open learning environment for mathematical functions, to track a learner’s self-explanation behaviour and how we use this model to improve the effectiveness of a student’s exploration.