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Evaluation of Mental Models: Using Highly Interactive Model-Based Assessment Tools and Technologies (Himatt) in Mathematics Domain
Aytac Gogus

This study used HIMATT (Highly Interactive Model-based Assessment Tools and Technologies) to evaluate the cognitive models of individuals who are solving complex mathematical problems. The goal was to determine the ability of HIMATT to assess learning in mathematics. Research on cognitive and mental models proposes that internal conceptual systems are not easily observable; therefore, researchers can only learn about internal conceptual systems by interpreting individuals’ communications and representations of their own knowledge. This study used HIMATT to compare the mental models of university students and their instructors and observe their transition from novice to expert. Subjects in this study used two tools in HIMATT: DEEP (Dynamic Evaluation of Enhanced Problem Solving) and T-MITOCAR (Text-Model Inspection Trace of Concepts and Relations). According to this study’s findings, by using a reference model to compare with individual students’ conceptualizations, HIMATT can be used successfully to assess the learning in a complex mathematical domain.

Keywords: Mental models, assessment of learning in complex domains, model based assessment, HIMATT, DEEP, T-MITOCAR, expertise.

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