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Representation Guidance with Abstract and Contextualized Representation: Effects on Engineering Learning Performance in Technological Literacy Education

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Conference

2012 ASEE Annual Conference & Exposition

Location

San Antonio, Texas

Publication Date

June 10, 2012

Start Date

June 10, 2012

End Date

June 13, 2012

ISSN

2153-5965

Conference Session

NSF Grantees' Poster Session

Tagged Topic

NSF Grantees Poster Session

Page Count

15

Page Numbers

25.1121.1 - 25.1121.15

DOI

10.18260/1-2--21878

Permanent URL

https://peer.asee.org/21878

Download Count

203

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Paper Authors

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Gamze Ozogul Arizona State University

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Gamze Ozogul is an Assistant Research Scientist in the Department of Electrical Engineering at Arizona State University (ASU). She received the undergraduate degree in Curriculum and Instruction in 2000 from Hacettepe University, and the M.S degree in Computer Education and Instructional Technology in 2002 from Middle East Technical University. She received her Ph.D. in Educational Technology in 2006 from ASU. She completed a Postdoctoral Research fellowship in the Department of Electrical Engineering at ASU in 2011.

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Amy M. Johnson Arizona State University

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Amy Johnson is an Assistant Research Scientist in the School of Electrical, Computer, and Energy Engineering at Arizona State University (ASU). She received her master of science degree in psychology from University of Memphis in 2008 and her Ph.D. in cognitive psychology from the University of Memphis is 2011. Her research interests include learning with multiple external representations, computer-based learning environments, self-regulated learning, and engineering education. She has authorship and co-authorship in several leading educational and cognitive psychology journals.

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Martin Reisslein Arizona State University Orcid 16x16 orcid.org/0000-0003-1606-233X

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Martin Reisslein is a professor in the School of Electrical, Computer, and Energy Engineering at Arizona State University, Tempe. He received his Ph.D. in systems engineering from the University of Pennsylvania in 1998. He has published more than 90 journal articles and more than 50 conference papers in the areas of multimedia networking over wired and wireless network, video traffic characterization, optical networking, and engineering education. He serves currently as Associate EiC for the IEEE Communications Surveys and Tutorials and as Associate Editor for the IEEE/ACM Transactions on Networking and Computer Networks. He is a member of the ASEE and a senior member of the ACM and the IEEE.

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Kirsten R. Butcher University of Utah

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Kirsten Butcher is interested in the impact of multimedia, visual representations, and interactive educational technologies on students’ comprehension processes and learning outcomes. She is an Assistant Professor at the University of Utah in the Department of Educational Psychology’s Learning Sciences and Instructional Design & Educational Technology programs.

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Abstract

Representation guidance with abstract and contextualized representation: effects on engineering learning performance in technological literacy educationIntroduction: Engineering instruction materials typically employ schematic diagrams, such aselectrical circuit diagrams, to represent engineering concepts and problems. The impact ofabstract diagrammatic representations using conventional engineering symbols vs.contextualized life-like depictions in diagrammatic representations has just recently begun toattract research interest (see e.g., Reisslein, Moreno, & Ozogul, J. Engineering Education, July2010). However, the existing studies have not considered the impact of explicit guidance(explanations) on the use of abstract symbols or life-like depictions to represent engineeringproblems. The present study examines the impact of guiding learners in the use of abstract orcontextualized representations of engineering problems.Method: The study had a 4 (representation conditions: abstract text with abstract diagrams (AA),contextualized text with contextualized diagram (CC), contextualized text with combinedcontextualized-abstract diagrams (CCA), and contextualized text with abstract diagrams (CA)) x2 (no guidance or guidance) design. Participants were a total of 195 undergraduate psychologystudents, who were learning basic electrical circuit analysis in the context of technologicalliteracy education. Instruction was provided by a computer-based module teaching the analysisof parallel electrical circuits using the respective combination of representation and guidance/noguidance on the representation of the electrical circuit components. Learning was measured witha near-transfer problem solving posttest that required the subjects to transfer the acquiredelectrical circuit analysis skills to a novel set of problem posed in contextualized form (i.e., life-like settings).Results: An initial ANOVA on pretest scores showed no significant differences among groups.A 2x4 ANOVA on the near-transfer posttest scores indicated that while there was no significantmain effect of representation type, nor a significant main effect of guidance, there was amarginally significant interaction between the representation and guidance factors, F(3, 187) =2.22, p = .09, ηp2 = .03. Separate independent sample t-tests among the eight conditions revealedthe following differences: First, among the conditions without guidance, the AA representationhad significantly higher near-transfer posttest scores compared to the CC representation, t (47) =2.73, p = .009, and compared to the CA representation, t (45) = 2.79, p = .008. Next, the CCrepresentation with guidance significantly outperformed the CC representation without guidance,t (48) = 2.12, p = .04. No other differences were found.Discussion: The results for the conditions without guidance replicate recent results obtained withhigh school students learning basic electrical circuit analysis (Reisslein, Moreno, & Ozogul, J.Engineering Education, July 2010). Taken together, the results for the present study and theReisslein et al. (2010) study indicate that although novices to engineering (such as high schoolstudents and undergraduate non-engineering majors) are unfamiliar with the abstract engineeringsymbols, they learn better with abstract symbol representations than with representations withlife-like depictions of engineering system components. Turning to the effect of guidance, the main focus on this study, the results indicate thatthe contextualized (CC) representation which employed life-like depictions of engineeringsystems, e.g., the life-like image of a battery and light bulb in an electrical circuit, benefittedsignificantly from explicit explanation of this contextualized representation of the circuitcomponents. In contrast, the abstract representation (AA) did not benefit from explicitexplanation of the abstract representation, e.g., voltage source symbol and resistor symbol. Thisinitially counterintuitive result indicates that novice engineering learners readily assimilate theabstract engineering symbols and their transfer of problem solving skills to novel problems is notaided by explicit explanation of the use of the abstract representation. On the other hand, thelearners in the contextualized representation condition benefitted significantly from explicitexplanation of the use of the life-like depictions to represent electrical circuit components.Apparently, by making the representation of the circuit components more explicit theseexplanations aided in generating problem solving schemata that allowed the learners then tomore effectively transfer their problem solving skill to novel contextualized problem settings.

Ozogul, G., & Johnson, A. M., & Reisslein, M., & Butcher, K. R. (2012, June), Representation Guidance with Abstract and Contextualized Representation: Effects on Engineering Learning Performance in Technological Literacy Education Paper presented at 2012 ASEE Annual Conference & Exposition, San Antonio, Texas. 10.18260/1-2--21878

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