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A Team Based, Student Guided Approach to Learning Computer Algorithms Utilizing Video Game Programming

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Conference

2020 ASEE North Central Section conference

Location

Morgantown, West Virginia

Publication Date

March 27, 2020

Start Date

March 27, 2020

End Date

May 20, 2020

Page Count

6

Permanent URL

https://peer.asee.org/35722

Download Count

24

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Paper Authors

biography

Robert Allen Langenderfer The University of Toledo

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Robert Langenderfer is a Professor in the Computer Science and Engineering Technology program at the University of Toledo. He received his M.S. at the University of Toledo and is currently pursing his Doctorate. Robert has developed software for a variety of organizations, including Microsoft, Dana, Pilkington, the University of Michigan, and the University of Pittsburg.

Robert has researched and implemented neural networks, expert systems, image processing, and industrial control. His most recent interests are in deep learning neural networks applied to autonomous vehicles and AI assisted STEM education.

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Hong Wang The University of Toledo

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Dr. Hong Wang is a Professor Professor in Computer Science and Engineering Technology program in the Department of Engineering Technology program in the University of Toledo. He received his M.A and Ph.D in Computer Science from Kent State University (Kent, OH, USA). His research has covered parallel system design, smart building design, unmanned vehicle navigation under GPS denied environment and secure robot communications. His recent research interest is in data science field and STEM education.

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Abstract

"Play" and "fun" are words not usually associated with learning computer algorithms, but by directing students to design and develop a game during a semester course, students are kept engaged and given a sense of accomplishment. This paper discusses a team based, student guided approach to learning computer algorithms utilizing video game programming. At the beginning of the course, students are asked to deliver a game that meets a list of basic requirements. The game requirements are designed to coincide with the student outcomes for the Computer Science and Engineering Technology course curriculum. While students dictate the specifics of the game design, implementation, testing and even the timing of those activities, the instructor maintains an active role insuring a reasonable pace and consistent participation by all students. Interlaced with student guided sessions, the lectures cover the basic concepts and terminology to accelerate understanding of the standard language vital to communicating by the underlying concepts inherent in game programming. Students take turns engaging in the various roles necessary to develop a game; lead, architect, programmer and tester. By participating in these roles and working together, students also develop social and team skills that are often missing from the normally solitary programming tasks.

Students are assessed with traditional testing focusing on base knowledge covered in the lectures, but are also evaluated on the quality of the completed games, as well as by other students in their rotating roles. The inspiration behind this pedagogical approach is the difficulty maintaining student engagement when approaching the concepts and principles of computer algorithms and related theories. Since many students neglect their studies for the feelings of control and escapism provided by computer games, this approach incentivizes students by cross-linking their studies with preexisting free time behavior. Students often find a standard sorting algorithm uninspiring but are very interested when these methods are approached from the vantage point of conquering a series of digital enemies. Additionally, by examining the techniques utilized by their favorite video games, students infuse the enjoyment excitement of their play-time activities into their coursework.

Langenderfer, R. A., & Wang, H. (2020, March), A Team Based, Student Guided Approach to Learning Computer Algorithms Utilizing Video Game Programming Paper presented at 2020 ASEE North Central Section conference, Morgantown, West Virginia. https://peer.asee.org/35722

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