Australasian Journal of Educational Technology · 2023 · 84 citations · 41 references
EducationEducational TechnologyTeachingArtificial IntelligenceArtificial Intelligence In EducationInstruction In Higher EducationEngineering EducationGenerative Ai In EducationTechnology IntegrationAi-generated Learning MaterialsArtificial Intelligence EducationAssessment Through DialogueIntelligent Tutoring DialoguesTeaching With Chat Tools
This research explored the potential of artificial intelligence (AI)-assisted learning using ChatGPT in an engineering course at a university in South-east Asia. The study investigated the benefits and challenges that students may encounter when utilising ChatGPT-3.5 as a learning tool. This research developed an AI-assisted learning flow that empowers learners and lecturers to integrate ChatGPT into their teaching and learning processes. The flow was subsequently used to validate and assess a variety of exercises, tutorial tasks and assessment-like questions for the course under study. Introducing a self-rating system allowed the study to facilitate users in assessing the generative responses. The findings indicate that ChatGPT has significant potential to assist students; however, there is a necessity for training and offering guidance to students on effective interactions with ChatGPT. The study contributes to the evidence of the potential of AI-assisted learning and identifies areas for future research in refining the use of AI tools to better support students' educational journey. Implications for practice or policy Educators and administrators could review the usage of ChatGPT in an engineering technology course and study the implications of generative AI tools in higher education. Academics could adapt and modify the proposed AI-assisted learning flow in this paper to suit their classroom. Students can review and adopt the proposed AI-assisted learning flow in this paper for their studies. Researchers could follow up on the application of ChatGPT in teaching and learning: teaching quality and student experience, academic integrity and assessment design.
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Yogesh K. Dwivedi, Nir Kshetri, Laurie Hughes et al. · International Journal of Information Management · 2023 · 3.7K citations · Full text
Aidan Gilson, Conrad Safranek, Thomas Huang et al. · JMIR Medical Education · 2023 · 2K citations · Full text