June 23, 2013
June 23, 2013
June 26, 2013
NSF Grantees Poster Session
23.51.1 - 23.51.14
A Grand Challenge-based Framework for Contextual Learning in EngineeringA key finding within the current engineering education literature is that exposure to real-worldapplications – especially when presented in an active, experiential learning environment –increases both student interest and pedagogical effectiveness. This idea of contextual learning,learning designed so that students can carry out activities and solve problems in ways that reflectthe real-world nature of such tasks, is based on cognitive learning theory and current research incognitive psychology and neuroscience. Such research suggests that initial learning, transfer ofthat learning to other contexts, and retention of learned material is facilitated when concepts arepresented in a familiar or relatable context. That is, students are motivated when learning hasmeaning.The National Academy of Engineering recently outlined twelve Grand Challenges forEngineering (e.g., “Reverse Engineering the Brain”) that collectively constitute some of thelargest and most pressing real-world issues facing engineering research and practice. We havedevleoped an instructional framework for engineering education that utilizes these GrandChallenges as the context for teaching a wide range of concepts. The framework comprises sixstages, each building upon its predecessor. Students first progress from thinking about the grand,overarching theme from a multitude of perspectives to focusing on a discipline-specific view ofthe challenge (Stages 1-3). Then, they concentrate on learning the specific course content andapplying what they have learned to a specific, real-world problem inspired by the overarchingGrand Challenge (Stages 4-5). Finally, they analyze what they have learned from the hands-onactivities and reflect back on how this can inform their understanding of, and solutions to, theGrand Challenge (Stage 6).This paper begins with a description of the framework including its foundation in contextuallearning theory and the motivation for using the Grand Challenges. Subsequently, theimplementation of the framework in two engineering courses is described: ComputationalMethods in Engineering, which is required of all freshman engineers, and Fundamentals ofDigital Signal Processing, which is an elective course taken by junior and senior students inElectrical and Computer Engineering and Biomedical Engineering. Details of the learningmodules and activities corresponding to the six stages of the framework are presented for eachcourse. Similarities and differences in implementation are highlighted, illustrating how acommon framework can be applied to seemingly very different courses. Finally, the use of theframework is evaluated in terms of its impact on student motivation and learning usingpsychologically rigorous measures..
Huettel, L. G., & Gustafson, M. R., & Nadeau, J. C., & Schaad, D., & Barger, M. M., & Linnenbrink-Garcia, L. (2013, June), A Grand Challenge-based Framework for Contextual Learning in Engineering Paper presented at 2013 ASEE Annual Conference & Exposition, Atlanta, Georgia. 10.18260/1-2--19065
ASEE holds the copyright on this document. It may be read by the public free of charge. Authors may archive their work on personal websites or in institutional repositories with the following citation: © 2013 American Society for Engineering Education. Other scholars may excerpt or quote from these materials with the same citation. When excerpting or quoting from Conference Proceedings, authors should, in addition to noting the ASEE copyright, list all the original authors and their institutions and name the host city of the conference. - Last updated April 1, 2015