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Text Mining-based Qualitative Student Assessment of Interactive Simulation Learning Using SIMIO Tool – A Work in Progress

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2020 ASEE Virtual Annual Conference Content Access


Virtual On line

Publication Date

June 22, 2020

Start Date

June 22, 2020

End Date

June 26, 2021

Conference Session

Student Learning Assessment Methods

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Aditya Akundi University of Texas Rio Grande Valley Orcid 16x16

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Dr. Satya Aditya Akundi is currently affiliated to the Department of Manufacturing and Industrial Engineering, at the University of Texas Rio Grande Valley. He earned a Bachelor of Technology in Electronics and Communication Engineering from Jawaharlal Nehru Technological University, India. He earned a Master of Science in Electrical and Computer Engineering at the University of Texas at El Paso (UTEP). and a Ph.D. in Electrical and Computer Engineering, with a concentration in Industrial and Systems Engineering (ISE) in 2016. His research is focused on understanding Complex Technical and Socio-Technical Systems from an Information Theoretic approach. He has worked on a number of projects in the field of Electrical & Computer Engineering, Systems Engineering, Additive Manufacturing, and Green Energy Manufacturing. His research interests are in Systems Engineering & Architecture, Complex systems, Systems testing and Application of Entropy to Complex Systems.

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Immanuel Edinbarough P.E. University of Texas Rio Grande Valley

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Immanuel A. Edinbarough received his B.Sc. (Applied Sciences) degree from PSG College of Technology, University of Madras, India, his B.E.. (M.E.) degree from the Institution of Engineers, India, M.E. (Production Engineering) degree from PSG College of Technology, Bharathiar University, India, and his Ph.D. in mechanical engineering from the Bharathiar University, India. He is currently a professor and director of engineering technology at the University of Texas, Brownsville (UTB). Prior to joining the UTB faculty he was a visiting professor at the Rochester Institute of Technology and an associate professor of production engineering technology at PSG College of Technology, Bharathiar University, India, where he served as the director of the Computer Vision Laboratory and National Cadet Corps – Engineering Division Director. With over 26 years of teaching and research experience in manufacturing/mechanical engineering and engineering technology, he currently teaches in the areas of CAD/CAM/CIM, robotics and automation, product and process design, materials and manufacturing processes, machine design, renewable energy and micro-manufacturing. His current research interests include robotics, CIM, sustainable manufacturing, micro machining and engineering and technology education. He has published several papers in these areas in various national and international conferences and journals. He has worked in heavy and light manufacturing industries, manufacturing pumps, motors, and CNC machine tools in the areas of system design, production planning, and control and manufacturing. Edinbarough also served in paramilitary forces and in the Air Force. He is a Life Member of the ISTE, a senior life member of the IE (India), a member of ASEE and SME, and a licensed Professional Engineer (P.E.) in the state of Texas.

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Computer simulations complement and extend the real-world components of industries and manufacturing organizations. Teaching simulation-based tools helps students in modeling and analyzing the behavior of real time systems. With the increased demand observed in products and technology consumption, manufacturing industries are evolving to embrace new technologies and initiatives. To keep the emerging workforce technically competent in current tools to understand and interpret manufacturing processes, this paper portrays an effort by the authors in introducing SIMIO i.e. a tool on Simulation of intelligent objects to undergraduate students at University of Texas Rio Grande Valley and in understanding the influence of using a hands-on tool to stimulate student learning. With the help of SIMIO, students were introduced to the concepts of Basics of Simulations, Logics and Methodologies, Developing Simulation Models, Analysis of Simulation Data, applications to Industrial and service system designs. To understand student learning and the grasp of the concepts discoursed during the course, Natural Language Processing techniques have been used to qualitatively measure concept association by the students.

Akundi, A., & Edinbarough, I. (2020, June), Text Mining-based Qualitative Student Assessment of Interactive Simulation Learning Using SIMIO Tool – A Work in Progress Paper presented at 2020 ASEE Virtual Annual Conference Content Access, Virtual On line . 10.18260/1-2--35291

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