AI-powered Literature Review with Notebook LM: Implications for Educational Technology and Older Adults

Abstract

With the rapid expansion of research on educational technology for older adults, conductingcomprehensive literature reviews has become increasingly complex. Artificial Intelligence (AI) tools suchas Google’s NotebookLM offer the potential to streamline this process by enabling researchers tointeractively query and summarize large document collections. This study presents a methodologicalevaluation of NotebookLM as an AI-assisted literature review tool and explores its implications forresearch in educational technology targeting older adult learners. A critical, tool-focused evaluation ofNotebookLM’s interaction with a curated corpus assesses its research value for age-sensitive educationaltechnologies. The tool was applied to a curated corpus of 20 academic sources, revealing its strengths inautomation, speed, and thematic synthesis. A SWOT analysis was employed to assess its capabilities,highlighting strengths (e.g., efficiency, breadth), opportunities (e.g., mapping emerging trends), but alsoweaknesses such as occasional hallucinated references and limited capacity for critical appraisal. Toaddress these limitations, we applied a human-in-the-loop approach, including manual verification ofsources, prompt refinement, and triangulation with traditional review methods, ensuring reliability andscholarly rigor. Ethical considerations, especially the need for human oversight, were emphasized due tothe potential for misinformation and bias in AI-generated outputs. Findings suggest that whileNotebookLM can accelerate the process of identifying key themes (e.g., digital inclusion, lifelong learning,assistive technologies), it cannot substitute for rigorous, human-led analysis. Instead, a human-AIpartnership is recommended, where AI performs the labor-intensive groundwork and researchers ensurethe quality and validity of results. This work contributes to the growing body of scholarship onintegrating AI into academic research workflows and highlights the importance of transparency andethical responsibility in the use of AI in literature reviews.

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