Generative AI in Reflective Learning

Abstract

In further education, barriers to scientific knowledge often arise due to limited competence in reading and comprehending complex academic literature. This study investigates the potential of generative artificial intelligence (AI) to scaffold reflective practice-based learning by assisting learners in overcoming these barriers by embedding generative AI within professional training. This research highlights a pathway for re-engaging adult learners with academic discourse, offering scalable solutions for lifelong learning in an era of rapid technological change. Specifically, we explore whether generative AI can enhance the accessibility of scientific literature, thereby supporting professional development through improved technological literacy. The research employed a mixed-methods approach, combining questionnaires and semi-structured interviews. The questionnaire assessed the learners perceived difficulty in engaging with academic papers. At the same time, the interviews delved into the effectiveness of generative AI assistance and its integration into their professional practice. Initial findings suggest that generative AI can act as a scaffolding mechanism, providing simplified translations and interpretations of complex texts. This support helps learners to understand and apply scientific content in their contexts. These results highlight the potential of generative AI in enhancing reflective practice-based learning by bridging gaps in scientific literacy, ultimately contributing to the future of practice-oriented education in an era shaped by disruptive technologies.

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