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Advancing Personalized Engineering Learning via an Adaptive Concept Map

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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

12

Page Numbers

25.137.1 - 25.137.12

Permanent URL

https://peer.asee.org/20897

Download Count

24

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Paper Authors

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Christopher B. Williams Virginia Tech

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Jacob Preston Moore Virginia Tech

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Jacob Moore is a Ph.D. candidate in the Department of Engineering Education at Virginia Tech.

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Aditya Johri Virginia Tech Orcid 16x16 orcid.org/0000-0001-9018-7574

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Robert Scott Pierce Sweet Briar College

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Chris North Virginia Tech

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Chris North is an Associate Professor of computer science at Virginia Tech. He leads the Information Visualization research group in the Center for Human-Computer Interaction, and directs the GigaPixel Display Laboratory, one of the most advanced display and interaction facilities in the world. He was General Chair of the IEEE Information Visualization (InfoVis) Conference and Associate Editor of IEEE Transactions on Visualization and Computer Graphics. He was awarded Faculty Fellow of the College of Engineering at Virginia Tech. He regularly teaches graduate courses on Information Visualization and undergraduate courses on human-computer interaction. His research expertise is in human-computer interaction, information visualization, evaluation methods, and large high-resolution displays.

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Abstract

ADVANCING PERSONALIZED ENGINEERING LEARNING VIA AN ADAPTIVE CONCEPT MAP There is a well recognized need to produce innovative engineers that have a strongfundamental understanding of engineering but are equally adept at applying their knowledge innovel domains. Concept maps are effective interventions in providing students with a holisticunderstanding of a domain while also allowing understanding of relationships among parts andacross the engineering curricula. Yet when the domain of application is large, concept mapsbecome overburdened with too much information and complexity. A function of the individuallearners’ cognitive load abilities, this phenomenon (termed “map shock”) results in studentdisengagement and reduction of expected learning gains. This limitation prevents the creation ofconcept maps that provide a unified framework for engineering knowledge across courses andcurricula. Thus, existing approaches to implementing expert-generated concept maps as contentrepositories are limited by: (i) an inability to effectively convey a large quantity of informationand (ii) an inability to adapt the presentation of information for each learner’s individualcognitive needs. To address these limitations, we apply theoretical research on adaptive expertise, conceptmaps, and information visualization to design, develop and assess a cyberlearning tool thatadvances personalized learning and helps students develop deep and broad conceptualknowledge. The proposed visualization tool, the “adaptive concept map,” overcomes theproblem of map shock by providing the user control over the quantity and level of detail ofinformation displayed, thus providing a means for navigating content in a manner that isadaptable to their personal cognitive load needs. The adaptive concept map tool is being developed initial for engineering statics content. Itwill be provided to students at two universities to be used as a supplemental “digital textbook.”The tool will be evaluated by comparing measures of conceptual understanding and cognitiveload between experimental groups (those with access to the adaptive map tool) and controlgroups (those without access to the adaptive map tool). This poster presents the progress that has been made with this project thus far. The contentand software development processes is outlined and a working prototype of the tool isshowcased. A section of the content development process, the development of a concept map ofall engineering statics content, will be discussed in more detail in another paper at thisconference. Preliminary results from pilot testing will also be presented.

Williams, C. B., & Moore, J. P., & Johri, A., & Pierce, R. S., & North, C. (2012, June), Advancing Personalized Engineering Learning via an Adaptive Concept Map Paper presented at 2012 ASEE Annual Conference & Exposition, San Antonio, Texas. https://peer.asee.org/20897

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