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A Strategic Perspective on Using Symbolic Transformation in STEM Education: Robotics and Automation

Author

Listed:
  • Jack M. Rappaport

    (Brilliance Consulting, Ambler, PA, USA)

  • Stephen B. Richter

    (Computer Science Department,West Chester University, West Chester, PA, USA)

  • Dennis T. Kennedy

    (Business Systems and Analytics Department,La Salle University, Philadelphia, PA, USA)

Abstract

This paper describes and implements an innovative model for teaching Science, Technology, Engineering and Mathematics (STEM) that enhances the decision making process of students considering a major or a career in STEM fields. The model can also be used as a decision making tool for educators interested in stressing the importance of STEM for career enhancement and for society as a whole. The model creates analogies and metaphors for various STEM topics using the contents of popular music videos. Theories of neuroscience, the interdisciplinary study of the nervous system, are used to describe and validate our decision making model. Concepts such as, embodied cognition, mirror neurons and the connection between emotion and cognition, are used to explain how the brain processes the information and multi-modal stimuli generated by our model. The model was implemented using the topic of automated decision processes in robotics and automation with a group of university and high school students and teachers. The impact of the model was evaluated using the National Science Foundation (NSF) frameworks for evaluating informal science projects. The results indicate that the model using symbolic transformation to teach STEM can have a significant impact on students' attitude towards STEM and the decision making process about their careers.

Suggested Citation

  • Jack M. Rappaport & Stephen B. Richter & Dennis T. Kennedy, 2016. "A Strategic Perspective on Using Symbolic Transformation in STEM Education: Robotics and Automation," International Journal of Strategic Decision Sciences (IJSDS), IGI Global, vol. 7(1), pages 39-75, January.
    • Handle: RePEc:igg:jsds00:v:7:y:2016:i:1:p:39-75
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