Sharing Student Projects

This dissertation explores the development and efficacy of a novel framework aimed at enhancing and promoting responsible student interaction with AI-based tools, specifically focusing on ChatGPT. Guided by the components of the Technology Acceptance Model (TAM), this study seeks to optimise user experience while using the framework, addressing usability and user satisfaction. Employing a mixedmethod approach that integrates both qualitative and quantitative data collection, the study analyses the framework's role in facilitating effective interactions with ChatGPT. Participants' experiences using the framework are analysed through survey responses, while their interactions with ChatGPT are qualitatively examined for a nuanced comprehension of the framework's impact. The findings reveal a positive impact of the framework on optimising interactions with ChatGPT. Additionally, they highlight pain points and areas of success. Qualitative insights point out the role of language in shaping these interactions with ChatGPT, independent of the framework's application. Notably, this study identifies factors that enhance interactions with ChatGPT with the help of the framework, offering valuable insights for refining future iterations of the framework.

This study has implications for the use of AI in education, offering insights into the role of guidelines to enable an effective and responsible use of AI.