LogicHouse-v1: a digital game-based learning tool for enhanced teaching of digital electronics in higher education institutions

Abstract

A drastic decline in the number of students that are enrolled for Engineering is now being experienced in developed as well as developing countries. Learning is becoming boring as a generation brought up on technology is losing the ability to pay attention in traditional classes for a long stretch of time. This has led to the idea that other teaching methods do exist and can be applied in teaching/learning. This work leveraged the use of Digital Game-Based Learning (DGBL) in Engineering classrooms to develop a serious game named LogicHouse Version 1 (LogicHouse-V1 or LogicHouse for short). The game, is a web-based serious game prototype that targets selected topics in Digital Electronics course. This course is a core component of undergraduate curriculum in Electrical & Electronics Engineering, Computer Engineering, Information Technology, Communication Engineering, Computer Science and other related Science Technology Engineering and Mathematics (STEM) courses. LogicHouse involves a virtual broken house where the player has to play the various levels to fix the house and gain points along the way. This game was designed based on the Learning Mechanics-Game Mechanics (LM-GM) model and the Unified Modeling Language (UML). Furthermore, the design was implemented using Adobe Illustrator, Procreate, Unity Engine, C#, Microsoft Azure Playfab and deployed on itch.io. Preliminary evaluation results indicate that students are interested in the game and its application. Based on this, there is a prospect of improved performance in any course in which the game is implemented.

Keywords:

• DGBM
• LogicHouse
• LM-GM
• STEM
• UML

Reviewing Editor:

• Ai Qingsong
• Wuhan University of Technology
• China

SUBJECTS:

• Digital Game-Based Learning
• Digital Electronics
• Electrical & Electronics Engineering
• Computer Engineering
• Information Technology
• Computer Science

Acknowledgments

The authors acknowledge the Advanced Signal Processing and Machine Intelligence Research (ASPMIR) group, Covenant University, Ota, Nigeria for supporting the design and implementation of this project. The Covenant University Center for Research, Innovation and Discovery (CUCRID) is acknowledged for providing funding support towards the publication of this paper.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Author contribution

The authors of this paper are members and/or research collaborators of the Advanced Signal Processing and Machine Intelligence Research (ASP MIR) group, Covenant University, Ota, Nigeria. The group applies fundamental knowledge in scientific and engineering fields to address societal challenges in diverse domains such as education, telecommunication and etc.