Leveraging Video Presentation Coursework to Enhance Engineering Education Assessment Amidst the Rise of Generative AI Tools
In the evolving landscape of educational technology, particularly with the advent of AI language models, there is a pressing need to re-evaluate traditional student assessment methods to maintain their relevance and effectiveness. This paper presents a ground-breaking pilot study that examines the integration of video presentation coursework into the assessment framework of engineering education. The aim is to explore the significant effects of embedding video presentation production coursework alongside conventional assessments within engineering education to counteract the potential adverse effects of AI language models on assessments. How does this integrated assessment method impact students' communication abilities, critical thinking, and active engagement in learning? The study also aims to promote active learning, encourage lifelong learning, and better prepare students for their future careers by instilling engineering students with vital skills often neglected in standard classroom environments. To address student experience, a survey was conducted among final-year engineering students enrolled in an elective module at The University of Nottingham Ningbo China. The survey comprised both Likert scale and open-ended questions, facilitating a dual analysis approach. This methodology combines quantitative data for statistical analysis with qualitative insights from participants' responses to open questions, using tools such as Excel and SPSS for data analysis. The outcomes of integrating video presentation into the assessment showed that incorporating video presentation into assessment strategies can significantly enrich the skill set of engineering students, encompassing research, presentation, rehearsal, and self-evaluation. At the same time, it can cultivate critical thinking and serve as a proactive measure against the risk of academic dishonesty in an educational context influenced by AI.
Authors
- Sherif Welsen (ORCID: https://orcid.org/0000-0002-2614-813X)
Institutions
- University of Nottingham Ningbo China (CN)
Publication Details
- Published
- 2024-12-02
- DOI
- https://doi.org/10.1109/weef-gedc63419.2024.11151832
- Citations
- 2
- Primary Topic
- Educational Assessment and Pedagogy
- Type
- article
- Field-Weighted Citation Impact
- 4.19