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Representation sequencing in computer-based engineering education

Published: 01 March 2014 Publication History

Abstract

Multimedia engineering instruction typically includes verbal descriptions and diagrams, which can be presented in a contextualized format, using descriptions and illustrations of real-life elements (e.g., light bulb and battery), or in an abstract format, using conventional electrical engineering symbols. How the sequencing of these representation formats influences learning of conceptual knowledge has been examined in prior research. The present study examines how the representation sequencing impacts procedural learning of engineering problem solving. The study compared four sequences of representation (abstract abstract, contextualized contextualized, contextualized abstract, or abstract contextualized) during computer-based learning to determine which of the four sequences best promotes student learning. Learning outcomes were measured with a problem-solving posttest and learner perceptions were assessed using a learner questionnaire. The study results indicated that the abstract contextualized condition resulted in significantly higher near- and far-transfer posttest scores than the contextualized contextualized condition and in significantly higher near-transfer posttest scores than the contextualized abstract condition. Computer-based instruction in engineering problem solving for novice learners should initially employ abstract representations that convey the conceptually-relevant solution procedures shared across similar problems. Providing a variety of problem contexts in later stages of learning can assist learners in transfer of key procedural problem solving principles to novel problem settings with different superficial features. An experiment investigated different sequences of representation formats.Abstract to contextualized format promoted near- and far-transfer problem solving.Early abstract representations focus attention on the underlying problem structures.Later contextualized representations assist transfer to novel problems.Problem solving instruction should employ abstract to contextualized sequences.

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  • (2015)Transitional feedback schedules during computer-based problem-solving practiceComputers & Education10.1016/j.compedu.2014.10.02081:C(270-280)Online publication date: 1-Feb-2015

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cover image Computers & Education
Computers & Education  Volume 72, Issue C
March 2014
386 pages

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Elsevier Science Ltd.

United Kingdom

Publication History

Published: 01 March 2014

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  1. Abstract representation
  2. Contextualized representation
  3. Instructional sequences
  4. Problem solving
  5. Representation type

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  • (2015)Color Coding of Circuit Quantities in Introductory Circuit Analysis InstructionIEEE Transactions on Education10.1109/TE.2014.231267458:1(7-14)Online publication date: 1-Feb-2015
  • (2015)Transitional feedback schedules during computer-based problem-solving practiceComputers & Education10.1016/j.compedu.2014.10.02081:C(270-280)Online publication date: 1-Feb-2015

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