Seattle, Washington
June 14, 2015
June 14, 2015
June 17, 2015
978-0-692-50180-1
2153-5965
Mechanical Engineering
Diversity
17
26.978.1 - 26.978.17
10.18260/p.24315
https://peer.asee.org/24315
539
Dr. Tseng is a Professor and Chair of Industrial, Manufacturing and Systems Engineering at UTEP. His research focuses on the computational intelligence, data mining, bio- informatics and advanced manufacturing. Dr. Tseng published in many refereed journals such as IEEE Transactions, IIE Transaction, Journal of Manufacturing Systems and others. He has been serving as a principle investigator of many research projects, funded by NSF, NASA, DoEd, KSEF and LMC. He is currently serving as an editor of Journal of Computer Standards & Interfaces.
Aditya Akundi is currently a doctoral student at the University of Texas at El Paso in the Electrical and Computer Engineering Department, Industrial and Systems Engineering (ISE) track. He earned a Master of Science in Electrical and Computer Engineering at the University of Texas at El Paso (UTEP) in 2012. He has worked on a number of projects in the field of Electrical & Computer Engineering, Systems Engineering, Additive Manufacturing and Green Energy Manufacturing. He is the current president of INCOSE UTEP student chapter along with being involved in UTEP Green Fund committee. His research interests are in Systems Engineering & Architecture, Complex systems, Systems testing and Application of Entropy to Complex Systems.
Email: sakundi@miners.utep.edu
Norman D. Love, Ph.D.is an Assistant Professor in the Department of Mechanical Engineering. Dr. Love, an El Paso native and UTEP alumnus, earned a B.S. and M.S. in Mechanical Engineering from the University of Texas El Paso and completed his Ph.D. at the University of Oklahoma in the same field. Dr. Love’s research interests lie in the areas of combustion and energy conversion processes and engineering education. He has developed flipped classroom modules and also implements project based learning activities in his class activities.
Instructional Setting on Student Learning Effectiveness Using Flipped Classroom in an Engineering Laboratory AbstractImproving Engineering Education, which plays an important role in shaping the future engineers,has always been a major concern. However, until recently more engineering educators have beeninvolved with the implementation of various different educational and learning techniques. Aspart of this movement, this paper is aimed at analyzing and thereby assessing how differentmethods used in a flipped classroom setting will impact student-learning effectiveness. The studycompares flipped classroom instruction to a traditional teaching method which is used as acontrol study. Data gathered for the analysis is based on a non-biased uniformly distributed labsetting focused on using smart materials to determine the vibration frequency of a cantileverbeam. The lab setup is a part of a Green Energy Materials & Engineering course offered in thesummer 2014 semester. This class introduced students to the concepts of Green Manufacturing,Green Technologies in industries, and Fabricating advanced Green Energy devices. Theframework used for gathering unbiased data, identifying a learning approach, and on quantifyingthe student learning is explained in detail. It is found that the instructional setting plays asignificant role in flipped classroom learning effectiveness. Flipped classroom learning setupdoes not guarantee better learning effectiveness if not set up appropriately in a laboratory setting.
Tseng, T. B., & Akundi, A., & Love, N. (2015, June), Instructional Setting on Student Learning Effectiveness Using Flipped Classroom in an Engineering Laboratory Paper presented at 2015 ASEE Annual Conference & Exposition, Seattle, Washington. 10.18260/p.24315
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