Huettel, L., & Gustafson, M. R., & Nadeau, J. C., & Schaad, D. E., & Barger, M. M., & Linnenbrink-Garcia, L. (2014, June), Evidence for the Effectiveness of a Grand Challenge-based  Framework for Contextual Learning  Paper presented at 2014 ASEE Annual Conference & Exposition, Indianapolis, Indiana. 10.18260/1-2--20443

\bibitem{asee_peer_20443}
  Huettel, L., \& Gustafson, M. R., \& Nadeau, J. C., \& Schaad, D. E., \& Barger, M. M., \& Linnenbrink-Garcia, L. (2014, June), \emph{Evidence for the Effectiveness of a Grand Challenge-based  Framework for Contextual Learning}
  Paper presented at 2014 ASEE Annual Conference \& Exposition, Indianapolis, Indiana.
  10.18260/1-2--20443

Lisa Huettel, Michael R. Gustafson II, Joseph C. Nadeau, David E. Schaad, Michael M. Barger, and Lisa Linnenbrink-Garcia.  "Evidence for the Effectiveness of a Grand Challenge-based  Framework for Contextual Learning".  2014 ASEE Annual Conference & Exposition, Indianapolis, Indiana, 2014, June.  ASEE Conferences, 2014.  https://peer.asee.org/20443 Internet.  26 Jul, 2024

\bibitem{asee_peer_20443}
  Lisa Huettel, Michael R. Gustafson II, Joseph C. Nadeau, David E. Schaad, Michael M. Barger, and Lisa Linnenbrink-Garcia.
  "Evidence for the Effectiveness of a Grand Challenge-based  Framework for Contextual Learning".
  \emph{2014 ASEE Annual Conference \& Exposition, Indianapolis, Indiana, 2014, June}.
  ASEE Conferences, 2014.
  https://peer.asee.org/20443 Internet.  26 Jul, 2024

@INPROCEEDINGS{asee_peer_20443
author = "Lisa Huettel, Michael R. Gustafson II, Joseph C. Nadeau, David E. Schaad, Michael M. Barger, and Lisa Linnenbrink-Garcia"
title = "Evidence for the Effectiveness of a Grand Challenge-based  Framework for Contextual Learning"
booktitle = "2014 ASEE Annual Conference \& Exposition"
year = "2014"
month = "June"
address = "Indianapolis, Indiana"
publisher = "ASEE Conferences"
note = {https://peer.asee.org/20443}
number = {10.18260/1-2--20443}
}

TY  - CPAPER
AB  -             Evidence for the Effectiveness of a Grand Challenge-based                      Framework for Contextual LearningStudent motivation – and associated educational outcomes – can be influenced by the degree towhich course material connects to recognizable societal problems. The National Academy forEngineering has established the “Engineering Grand Challenges”, a set of 14 fundamentalproblems whose solution will require integrated contributions from engineers, scientists, andpolicy-makers. The current work builds the Engineering Grand Challenges (EGC) into apedagogical framework integrated into courses in several engineering disciplines, assessingwhether this framework increased student motivation and, if so, what sorts of students benefitfrom this approach.The EGC framework, as implemented here, follows a series of six stages that progress fromstatement of the problem, through exercises that teach a foundational concept using an EGCexample, to reflection on the role of engineering in addressing the problem. The framework wasimplemented in three diverse courses: a computational methods course taken by all first-yearengineering students, an upper-level signal-processing elective in electrical engineering, and adesign course for upper-level students in environmental engineering. Instructors for each of thesecourses implemented the EGC framework in a manner appropriate for their course. For example,students in the signal processing course investigated the EGC of “Reverse-Engineering theBrain”, which included a lecture/discussion led by a neuroscientist who uses signal processing,followed by a project assignment that applied spectral analysis and filter design to publiclyavailable data from a brain-computer interface contest. For all courses, baseline data werecollected from the same classes taught by the same instructors in the previous year.Results from the first year of implementation indicated significant benefits for the EGCframework, as well as differences in effectiveness across settings. Each student provided datathat included self-reported ratings of ABET criteria and standard psychological measures ofmotivation, and those measures were included in structural equation models that predicted inter-student differences in grades. The EGC framework was associated with significantly higher self-reported class effectiveness, as indexed by ABET criteria. Furthermore, in advanced classes theEGC framework enhanced a key measure of student motivation (i.e., situational interest), whichin turn was a positive predictor of student grades. This effect was not present in the introductoryclass examined. No differences between EGC and baseline groups were found in other measuresof self-reported motivation (e.g., perceived competence). Collectively, these results providestrong initial evidence that framing course activities around large-scale, societally relevantchallenges can have salutary effects upon students’ motivation and course performance. Ongoingwork examines these effects across multiple semesters of the same courses as well as acrossadditional courses from throughout engineering curricula.
AU  - Lisa Huettel
AU  - Michael R. Gustafson II
AU  - Joseph C. Nadeau
AU  - David E. Schaad
AU  - Michael M. Barger
AU  - Lisa Linnenbrink-Garcia
CY  - Indianapolis, Indiana
DA  - 2014/06/15
PB  - ASEE Conferences
TI  - Evidence for the Effectiveness of a Grand Challenge-based  Framework for Contextual Learning
UR  - https://peer.asee.org/20443
DO  - 10.18260/1-2--20443
ER  -