Article ID Journal Published Year Pages File Type
350820 Computers in Human Behavior 2013 9 Pages PDF
Abstract

•Examined impact of representation type and guidance on integrating representations.•Learning module presented abstract or contextualized representations of electric circuits.•Verbal guidance denoted correspondences among representations.•Without guidance, abstract representations led to better learning outcomes.•Contextualized representations were more effective when guidance was provided.

An experiment examined the effects of providing explicit verbal guidance to learners in integrating information with abstract or contextualized representations during computer-based learning of engineering. Verbal guidance supported learners in identifying correspondences and making mental connections among multiple textual and diagrammatic representations. Results from a 2 (abstract (A) or contextualized (C) representation) × 2 (no guidance or guidance) design showed that without guidance, abstract representations led to better transfer than contextualized representations. Moreover, learners in the contextualized representation group benefitted from the guidance, while the abstract representation group did not benefit from guidance. These findings suggest that abstract representations promote the development of deep, transferrable knowledge and that verbal guidance denoting correspondences among representations can facilitate learning when less effective representational formats are utilized.

Related Topics
Physical Sciences and Engineering Computer Science Computer Science Applications
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