How does knowledge evolve using adaptive heuristics learning in an engineering game?

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Rani Deepika Balavendran Joseph
Gayatri Mehta


In this paper, the primary focus is on the performers whose learning process originate by solving simple or complex problems and perceiving the performers interest in solving advanced problems from the knowledge obtained. An open-source puzzle like a game UNTANGLED is used in our study. The game is developed to unravel the mapping/placement problems in electrical engineering by using human instincts. Telemetry data for the two groups of performers who solved simple and complex puzzles in the first attempt is considered to investigate the Kolb's Experiential Learning Theory (KELT) and fathom the adaptive heuristics for building knowledge from experience. From analysis performed it is evident that a similar learning process is followed by both performers who played initial and complex puzzles in first attempt. Also, results illustrate that the players who first played initial level puzzles are more interested in playing next level puzzles than the one who first played complex puzzles. Results illustrate that 18% of players who solved easy in first attempt played advanced puzzles in consecutive attempts. Apparently, conclusions advocate that to develop an indelible appetite to deal with advanced/complex problems, STEM education teachers need to structure the lab experiments or teach the complex concepts by starting from simple projects/concepts to complex one. By making learners to try a greater number of low-level abstraction problems will engage learners’ interest in solving high-level abstraction problems. Similarly, educational game designers can develop a game environment introducing more intermediate levels, which gives enough experience to deal with difficult levels

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How to Cite
Balavendran Joseph, R. D., & Mehta, G. (2018). How does knowledge evolve using adaptive heuristics learning in an engineering game?. Advances in Social Sciences Research Journal, 5(10).
Author Biography

Gayatri Mehta, University of North Texas

Gayatri Mehta is an Associate Professor in the department of Electrical Engineering at the University of North Texas. She received her Ph. D in Electrical and Computer Engineering from the University of Pittsburgh in 2009. Her research interests are broadly in the areas of  electronic design automation, reconfigurable computing, low-power VLSI design, system-on-a chip design, embedded systems, and portable/wearable computing. 

Dr. Mehta is the director of the Reconfigurable Computing Lab at UNT. She has received the 2017 UNT College of Engineering Faculty Research Award. She has designed an interactive mapping game UNTANGLED to uncover human mapping strategies. UNTANGLED received the People's Choice Award in the Games & Apps category of the 2012 International Science & Engineering Visualization Challenge conducted by Science and National Science Foundation. 


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