Moving Towards More Authentic Learning Experiences – Stream 3: Generative AI & Digital Learning Content Creation

Stream 3 Overview

The objective of this research stream is to investigate the various aspects of how we can take advantage of AI driven techniques to generate learning content that is grounded in sound pedagogical practices.

Topics that will be examined include:

• Content Generation and Adaptation
  • Possible ways to generate and structure content to align with learning objectives.
  • Investigating how generative AI can be used to rapidly and reliably create complex learning experiences and interactive scenarios, which can often be time consuming to create.
  • If and how learning content can be customised to specific industries, organisations. learning needs or cultural contexts.
  • How can the use of generative AI help learning developers and educators focus on creating high-quality learning activities.
• Content Validation
  Hallucinations and bias are a concern with generative AI. In this research stream we aim to gain an understanding of the likelihood and risks of generating biassed and invalid content.We will investigate if any instruments or models might be available to validate the generated content’s pedagogical quality to help avoid the risk that AI driven learning systems generate potentially damaging learning content.
• Metadata Generation and Interpretation
  Generative AI has the potential to deeply understand how an individual learns. Through an ongoing dialogue between learner and machine, highly personalised learning experience could be generated.
  Through our research, we aim to build a better understanding of the technical and pedagogical possibilities, limitations and shortcomings to generate and interpret data on how the learner learns. This work will complement the research activities of research stream 4 and aims to contribute to translation of learner data into highly personalised and authentic learning activities.