Enhancing Transdisciplinary Tutoring in Analog Electronics and Embedded Systems Using Generative AI, Game-Based Learning (GBL) and Moodle
This paper presents a novel method for enhancing active learning and outcomes in electronic engineering by combining Generative AI for Game-Based Learning (GBL), and transdisciplinary tutoring in Moodle LMS. The approach bridges Analog Electronics (3rd semester) and Digital Design with Microcontrollers (6th semester, embedded systems) engineering courses, fostering collaboration through game-based projects focused on real-world analog-digital integration. Generative AI supports this by generating adaptable game scenarios, problems, and feedback, tailored to each student's learning progress. By incorporating popular game mechanics like Monopoly (for technological evolution), Trivial Pursuit (for component knowledge), and Settlers of Catan (for system design), the approach engages students in key topics like diodetransistor circuits, microcontroller programming, and analogdigital system design. Games are supervised in Moodle using workshop and other activities for peer review, allowing students to submit solutions, review peers' work, and track progress through quizzes, forums, journals, and peer feedback. Analog Electronics students learn Arduino microcontroller applications for lab instrumentation, while Digital Design students explore analog components' roles in embedded systems, deepening understanding of analog-digital interactions. A pilot case study shows increased engagement, collaboration, and practical application of concepts, highlighting the potential for AI, GBL, and Moodle-based transdisciplinary tutoring to personalize learning and deepen comprehension in complex engineering topics. Future research will refine GBL AI-generated content and assess scalability across other STEM, career, and engineering fields.
Authors
- Francisco Javier Zamora Navarro
Institutions
- Universidad Distrital Francisco José de Caldas (CO)
Publication Details
- Published
- 2025-04-22
- DOI
- https://doi.org/10.1109/educon62633.2025.11016465
- Primary Topic
- Intelligent Tutoring Systems and Adaptive Learning
- Type
- article
- Field-Weighted Citation Impact
- 0.00