Repairing Misconceptions: A Case Study With Advanced Engineering Students On Their Use Of Schema Training Modules
- Conference
- Location
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Austin, Texas
- Publication Date
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June 14, 2009
- Start Date
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June 14, 2009
- End Date
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June 17, 2009
- ISSN
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2153-5965
- Conference Session
- Tagged Division
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Educational Research and Methods
- Page Count
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10
- Page Numbers
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14.1023.1 - 14.1023.10
- DOI
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10.18260/1-2--4857
- Permanent URL
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https://strategy.asee.org/4857
- Download Count
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474
Paper Authors
Dazhi Yang Purdue University
Dazhi Yang is a postdoctoral researcher in the School of Engineering Education at Purdue University, West Lafayette, IN. She obtained both her master’s and Ph.D. degrees in Educational Technology from Purdue in 2004 and 2008, respectively. Prior to joining the School of Engineering Education, Dr. Yang worked on a variety of interdisciplinary research projects in instructional design, distance and online learning, assessment and evaluation, technology integration, and information security and assurance in K12 schools. She is the 2009 Young Researcher Award winner from the American Educational Research Association (AERA) Special Interest Group: Instructional Technology. Her current research interests are innovative instructional strategies for helping students learn difficult engineering concepts, assessment and evaluation, and technology-enhanced learning.
Ruth Streveler Purdue University
Ruth A. Streveler is an Assistant Professor in the School of Engineering Education at Purdue University. Before coming to Purdue she spent 12 years at Colorado School of Mines, where she was the founding Director of the Center for Engineering Education. Dr. Streveler earned a BA in Biology from Indiana University-Bloomington, MS in Zoology from the Ohio State University, and Ph.D in Educational Psychology from the University of Hawaii at M?noa. Her primary research interest is investigating students’ understanding of difficult concepts in engineering science.
Ronald Miller Colorado School of Mines
Dr. Ronald L. Miller is professor of chemical engineering and Director of the Center for Engineering Education at the Colorado School of Mines where he has taught chemical engineering and interdisciplinary courses and conducted engineering education research for the past 23 years. Dr. Miller has received three university-wide teaching awards and has held a Jenni teaching fellowship at CSM. He has received grant awards for education research from the National Science Foundation, the U.S. Department of Education FIPSE program, the National Endowment for the Humanities, and the Colorado Commission on Higher Education and has published widely in the engineering education literature. He won the Wickenden Award from the American Society for Engineering Education for best paper published in the Journal of Engineering Education during 2005.
Aidsa Santiago Roman
Aidsa I. Santiago-Román is a PhD candidate in the School of Engineering Education at Purdue University, West Lafayette, IN. Aidsa has been teaching math and engineering courses to undergraduate students in Puerto Rico for about 12 years. Since 2000 she has been an instructor in the Department of Engineering Science and Materials at the University of Puerto Rico in Mayaguez, which is considered the Leading Hispanic Engineering Institution in the US. In 2007, she started her doctoral studies and has
been a research assistant in the area of engineering student misconceptions in statics and thermal and transport sciences.
Abstract
NOTE: The first page of text has been automatically extracted and included below in lieu of an abstract
Repairing Misconceptions: A Case Study with Advanced Engineering Students on Their Use of Schema Training Modules Key words: misconceptions, difficult concepts, schema training
Abstract
The case study described in this paper was a formative evaluation on the adapted schema training modules and materials. The study was intended to gather feedback and suggestions from the intended audience in order to revise the training modules. The study also assessed students’ overall experiences and performance regarding the tryout of the modules. Both qualitative and quantitative data were collected from the participants. Based on the case of four participants, (1) the training materials were well adapted for undergraduate engineering students; (2) the training models were effective, (3) the training modules would be more effective for students with less coursework in the engineering subjects covered by the modules.
Introduction and Background
Misconceptions
Previous studies reported that misconceptions related to heat transfer, fluid mechanics, thermodynamics, and other engineering and science concepts persist among engineering students even after they completed college-level courses in the subjects.1- 2- 3 These misconceptions are not simple confusion or misunderstanding due to inaccurate or incomplete pieces of knowledge of the concepts.4-5 Such misconceptions are fundamental misconceptions about differences in the way that some molecular-scale engineering processes such as the diffusion differ from other observable and macro level processes such as the blood circulation.6
Such misconceptions are also robust and resistant to traditional instruction because the correct understanding of some challenging concepts not only requires students' knowledge of the differences in the way they behave from commonsense conceptions but also “overcome their (perhaps even innate) predisposition to conceive” them differently.6 To repair these misconceptions, Chi and her colleagues proposed an innovative instructional approach, ontological schema training methods, which focus on helping students develop appropriate schemas or conceptual frameworks for learning difficult engineering concepts.7- 8- 6-9
Ontological schema training method
The ontological schema training methods were based on assumptions about how students learn. One of the assumptions about how students learn new concepts is that students assimilate or encode new information into an existing schema or category.10 Assimilating new information into an existing schema help students make inferences about and assign attributes to a new concept or phenomenon.11 However, when students learn some particularly new challenging engineering concepts or processes, which are fundamentally different from their commonsense observable conceptions, they can make the wrong inference or assign incorrect attributes to the new concepts based on their existing commonsense schema. A simple everyday example is that
Yang, D., & Streveler, R., & Miller, R., & Santiago Roman, A. (2009, June), Repairing Misconceptions: A Case Study With Advanced Engineering Students On Their Use Of Schema Training Modules Paper presented at 2009 Annual Conference & Exposition, Austin, Texas. 10.18260/1-2--4857
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