Learning Recursion Through the Use of a Mental Model-Based Programming Environment

The mental model-based learning environment, PETAL, externalizes mental models for generating recursive programs into Programming Environment Tools (PETs). Such externalization supports cognitive and meta-cognitive problem-solving activity. PETs seem to help students internalize concepts, organize relevant knowledge, and lead to improved learning. The paper describes an empirical study to evaluate PETAL. Excerpts from protocols are discussed to show the evolution of one student's knowledge about recursion and recursive programming, the change from novice level to expert level induced by the PETs. Finally, the paper makes suggestions for incorporating cognitive support through user interfaces into Intelligent Tutoring Systems (ITSs).