Staff profile

Adam Wynn is a PhD student in the Department of Computer Science at Durham University. He completed an integrated Masters degree in Computer Science from Durham University in 2022. He is interested in AI in education, automatic feedback, adaptive learning and educational technology. Adam's research is currently focused on using technology to enhance the learning experience and aims to develop systems that provide personalised feedback and support to students in real-time.

• AI in Education
• Automatic Feedback
• Speech Processing

Chapter in book

• Wynn, A., & Wang, J. (2023). BETTER: An Automatic feedBack systEm for supporTing emoTional spEech tRaining. In Artificial Intelligence in Education. https://doi.org/10.1007/978-3-031-36272-9_66
• Wynn, A. T., Wang, J., Umezawa, K., & Cristea, A. I. (2022). An AI-Based Feedback Visualisation System for Speech Training. In M. Mercedes Rodrigo, N. Matsuda, A. I. Cristea, & V. Dimitrova (Eds.), Artificial Intelligence in Education. Posters and Late Breaking Results, Workshops and Tutorials, Industry and Innovation Tracks, Practitioners’ and Doctoral Consortium (510-514). Springer Verlag. https://doi.org/10.1007/978-3-031-11647-6_104

Conference Paper

• Wynn, A., Wang, J., & Valente, A. (2024, July). Simplifying Multimedia Programming for Novice Programmers: MediaLib and Its Learning Materials. Presented at ITiCSE 2024: Innovation and Technology in Computer Science Education, Milan, Italy
• Wynn, A., Wang, J., Sun, Z., & Shimada, A. (2024, March). Analysing Learner Behaviour in an Ontology-Based E-learning System: A Graph Neural Network Approach. Paper presented at LAK '24: The 14th Learning Analytics and Knowledge Conference, Kyoto, Japan
• Wynn, A., Wang, J., Han, R., & Hsu, T.-C. (2023, October). Multiplayer Serious Games Supporting Programming Learning. Presented at ECGBL 2023: 17th European Conference on Games Based Learning, Enschede, Netherlands

Journal Article

• Wang, J., Wynn, A., Mendori, T., & Hwang, G.-J. (2024). A topic map based learning management system to facilitate meaningful grammar learning: the case of Japanese grammar learning. Smart Learning Environments, 11(1), Article 53. https://doi.org/10.1186/s40561-024-00338-1