Seattle, Washington
June 14, 2015
June 14, 2015
June 17, 2015
978-0-692-50180-1
2153-5965
Engineering Physics & Physics
13
26.614.1 - 26.614.13
10.18260/p.23952
https://peer.asee.org/23952
772
Yu Gong is a graduate student in the School of Engineering Education and School of Electrical and Computer Engineering at Purdue University. She holds B.S, M.S. degrees in electrical engineering from Jiangsu University in China. Her researches focus on model-based learning in nanotechnology education.
Tugba Yuksel is a Ph.D. candidate in curriculum and Instruction department at Purdue University. She has received her B.S and M.S degrees in physics education program from Hacettepe University in Turkey. She registered to a master program in department of physics at Ankara University in Turkey. At the end of the second semester, she leave her program and came to Purdue university. She holds another M.S degree in science education from Purdue University. Her research interest is mainly on examining how undergraduate level students use their model-based reasoning in the process of learning quantum mechanics and identifying new instructional strategies which helps to support visualization and model-based reasoning.
Alejandra Magana is an Assistant Professor in the Department of Computer and Information Technology and an affiliated faculty at the School of Engineering Education at Purdue University. She holds a B.E. in Information Systems, a M.S. in Technology, both from Tec de Monterrey; and a M.S. in Educational Technology and a Ph.D. in Engineering Education from Purdue University. Her research is focused on identifying how model-based cognition in STEM can be better supported by means of expert technological and computing tools such as cyberinfrastructure, cyber-physical systems, and computational modeling and simulation tools.
Lynn A. Bryan is a Professor and Director of the Center for Advancing the Teaching and Learning of STEM (CATALYST) at Purdue University. She holds a joint appointment in the Department of Curriculum and Instruction and the Department of Physics. She received her B.S. in Chemistry from the Georgia Institute of Technology and her Ph.D. in Science Education from Purdue University. Her research focuses on teachers’ development of knowledge and skills for teaching in instructionally innovative settings involving novel curriculum reform and technology enhanced environments.
Engineering and Physics Students’ Metacognitive Strategies with Computer SimulationsComputer simulation has great advantages on helping students test abstract conceptsand visualize complex phenomena resulting in conceptual understanding. Students’experiences and attitudes on computer simulations promote intrinsic motivation thatinfluences their engagement and learning outcomes. Understanding students’experiences and attitudes will be important for simulation tool design and delivery.However, there are very few research studies providing such kind of references forteachers in practice. To explore this gap, we will study the role of simulation inengineering and physics learning from students’ perspective. The main researchquestions include: 1. How do students think simulation could help or not help their learning? 2. Which features are favorable, and which are expected to be added in simulation?12 volunteer undergraduate students from engineering and physics disciplinesparticipated in a one-on-one interview. The interview questions were based on, butnot limited to the above research questions. Each interview lasted 30-45 minutes andwas audio recorded. The data analysis is proceeding in two phases. In the first phase,the interview responses were transcribed. Distinct phenomena were identified andgrouped using phenomenographic analysis by the first two authors individually. In thesecond phase, the first two authors will discuss finding results with the third authorand get consensus on group categories with each other.Preliminary results indicated that most students agreed that simulation is helpful fortheir learning. The positive feedback mainly focused on easy operation, directvisualization, and animated demonstration. Many students could understand that it isthe underlying mathematical model that used to describe abstract phenomena whenusing simulation. However, there was also negative feedback, mostly from upperlevel students. More details will be discussed in the final paper. Recommendations forimproving simulation based educational practice will also be provided.Simulation-based learning is a popular instructional tool in engineering and physicsclassroom. The implementation relies on educators’ design, teachers’ instruction andlast but not least, students’ engagement. Understanding students’ experiences andattitudes towards computer simulations is an important aspect in engineering andphysics education.
Gong, Y., & Yuksel, T., & Magana, A. J., & Bryan, L. A. (2015, June), Engineering and Physics Students’ Perceptions About Learning Quantum Mechanics via Computer Simulations Paper presented at 2015 ASEE Annual Conference & Exposition, Seattle, Washington. 10.18260/p.23952
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