[Paper Review] Generative AI in Self-Directed Learning: A Scoping Review

Jasper Roe, Mike Perkins|arXiv (Cornell University)|Nov 12, 2024

Innovative Teaching and Learning Methods8 citations

TL;DR

This scoping review synthesizes 18 studies (2020–2024) on GenAI and SDL, identifying four themes: GenAI as an SDL enhancer, educators as guides, personalisation, and cautious adoption, while noting gaps in long-term impact and multimodal applications.

ABSTRACT

This scoping review examines the current body of knowledge at the intersection of Generative Artificial Intelligence (GenAI) and Self-Directed Learning (SDL). By synthesising the findings from 18 studies published from 2020 to 2024 and following the PRISMA-SCR guidelines for scoping reviews, we developed four key themes. This includes GenAI as a Potential Enhancement for SDL, The Educator as a GenAI Guide, Personalisation of Learning, and Approaching with Caution. Our findings suggest that GenAI tools, including ChatGPT and other Large Language Models (LLMs) show promise in potentially supporting SDL through on-demand, personalised assistance. At the same time, the literature emphasises that educators are as important and central to the learning process as ever before, although their role may continue to shift as technologies develop. Our review reveals that there are still significant gaps in understanding the long-term impacts of GenAI on SDL outcomes, and there is a further need for longitudinal empirical studies that explore not only text-based chatbots but also emerging multimodal applications.

Motivation & Objective

• Map the current knowledge at the intersection of Generative AI (GenAI) and Self-Directed Learning (SDL).
• Identify how GenAI tools can support on-demand, personalised SDL experiences.
• Assess the evolving educator role in GenAI-enabled SDL.
• Highlight gaps and future research needs, including long-term and multimodal studies.

Proposed method

• Synthesize findings from 18 studies published 2020–2024.
• Follow PRISMA-SCR guidelines for scoping reviews.
• Thematic synthesis to develop four key themes.
• Qualitative assessment of how GenAI tools like ChatGPT relate to SDL.

Experimental results

Research questions

• RQ1 What is the current state of knowledge on GenAI applications in SDL?
• RQ2 How can GenAI support personalised, on-demand SDL assistance?
• RQ3 What role do educators play in GenAI-enabled SDL, and how might that role evolve?
• RQ4 What gaps exist in understanding long-term impacts of GenAI on SDL outcomes, including multimodal tools?

Key findings

• GenAI tools show promise in supporting on-demand, personalised SDL assistance.
• Educators remain central to the learning process, even as their roles may shift with technology.
• There are significant gaps in understanding long-term SDL outcomes with GenAI.
• There is a need for longitudinal empirical studies and exploration of multimodal GenAI applications.
• The review synthesifies insights across four themes: GenAI as a potential SDL enhancer, educators as GenAI guides, personalisation of learning, and cautious adoption.