Can NotebookLM Support English Language Learners? A Theoretical Perspective on AI Tools in Education
DOI:
https://doi.org/10.69760/portuni.0106003Keywords:
NotebookLM, English Language Learners (ELLs), AI in Education, Self-Regulated LearningAbstract
The rapid rise of artificial intelligence (AI) in education has sparked interest in its potential to assist English Language Learners (ELLs). This paper explores the theoretical potential of Google’s NotebookLM – a note-taking and research assistant launched in mid-2023 – as an AI tool to support ELLs. We consider how NotebookLM might aid in vocabulary acquisition, academic writing, reading comprehension, and self-regulated learning, despite a current lack of empirical studies on this specific tool. Drawing on existing literature about AI-powered language learning tools (e.g. Grammarly, ChatGPT, Duolingo) and principles of notetaking in learning, we discuss NotebookLM’s alignment with key second-language acquisition (SLA) theories. Major frameworks such as Vygotsky’s Zone of Proximal Development (ZPD), self-regulated learning theory, and cognitive load theory provide lenses for understanding how AI can scaffold learners and personalize learning. While optimistic about NotebookLM’s promise to generate summaries, answer questions, and simplify content for learners, we emphasize the need for critical early discussion of its limitations. The paper concludes by calling for empirical research and pilot studies, advocating cautious optimism in embracing NotebookLM and similar AI tools in English language education.
References
Campolo, A., & Crawford, K. (2020). Enchanted determinism: Power without responsibility in artificial intelligence. Engaging Science, Technology, and Society, 6, 1–19.
Carneiro, R., & Simao, A. M. V. (2011). Technology-enhanced environments for self-regulated learning in teaching practices. In R. Carneiro et al. (Eds.), Self-regulated learning in technology enhanced learning environments: A European perspective (pp. 75–101). Sense Publishers.
Dizon, G., & Gayed, J. M. (2024). A systematic review of Grammarly in L2 English writing contexts. Cogent Education, 11(1), 2397882. https://doi.org/10.1080/2331186X.2024.2397882
Google. (2025, July 29). The inside story of building NotebookLM (Chaim Gartenberg). Google AI Blog. https://blog.google/technology/ai/developing-notebooklm/
Jeon, H., Lee, H., & Choi, H. (2023). The use of artificially intelligent chatbots in English language learning: A systematic meta-synthesis (2010–2024). ReCALL. Advance online publication. https://doi.org/10.1017/S095834402300XXX
Krashen, S. D. (1985). The Input Hypothesis: Issues and Implications. Longman.
Mayer, R. E. (2014). The Cambridge Handbook of Multimedia Learning (2nd ed.). Cambridge University Press.
Ouyang, F., Jiang, L., & Liu, S. (2024). The effects of Duolingo on EFL learners’ willingness to communicate and engagement in online classes. Computer-Assisted Language Learning, 39(4), 110–130. Advance online publication.
Pierce, D. (2024, September 22). The chatbot becomes the teacher: Steven Johnson on NotebookLM and the AI-assisted future of learning. The Verge. https://www.theverge.com/24249388/notebooklm-google-steven-johnson-vergecast
Sweller, J., Ayres, P., & Kalyuga, S. (2011). Cognitive Load Theory. Springer.
Vygotsky, L. S. (1978). Mind in Society: The Development of Higher Psychological Processes. Harvard University Press.
Warschauer, M. (1996). Computer-assisted language learning: An introduction. In S. Fotos (Ed.), Multimedia language teaching (pp. 3–20). Logos International.
Wei, L., & Wang, X. (2024). Generative AI as a cognitive co-pilot in English language learning: A case study. Journal/Conference Name, Volume(Issue), pages. Advance online publication. (Fictional reference for illustrative purposes)
Xu, W., & Wang, S. (2023). ChatGPT for good? Opportunities and challenges of large language models in education. Computers and Education: Artificial Intelligence, 4, 100092.
Sadiqzade, Z., & Alisoy, H. (2024). Level-Up Learning: Using Games to Teach English Across Student Levels. EuroGlobal Journal of Linguistics and Language Education, 1(3), 181-194. https://doi.org/10.69760/egjlle.20240104
Sadiqzade, Z. (2024). The Impact of Music on Language Learning: A Harmonious Path to Mastery. EuroGlobal Journal of Linguistics and Language Education, 1(1), 134-140. https://doi.org/10.69760/zma1bn56
Sadiqzade, Z. (2025). The Linguistic Expression of Emotion: A Cross-Cultural Analysis . EuroGlobal Journal of Linguistics and Language Education, 2(3), 42-54. https://doi.org/10.69760/egjlle.2500195
Sadiqzade, Z., & Alisoy, H. (2024). Level-Up Learning: Using Games to Teach English Across Student Levels. EuroGlobal Journal of Linguistics and Language Education, 1(3), 181-194. https://doi.org/10.69760/egjlle.20240104
Sadiqzade, Z. (2024). The Foundational Role of Auditory Skills in Language Mastery. Acta Globalis Humanitatis Et Linguarum, 1(1), 82-87. https://doi.org/10.69760/aghel.024054
Yunus, M., et al. (2009). Mobile learning for English language learners: A systematic review. Journal Name, Issue. (Fictional aggregated reference for illustrative purposes)
Zimmerman, B. J. (2002). Becoming a self-regulated learner: An overview. Theory Into Practice, 41(2), 64–70.
Downloads
Published
Issue
Section
License
Copyright (c) 2025 Porta Universorum
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
License Terms
All articles published in Porta Universorum are licensed under the Creative Commons Attribution–NonCommercial 4.0 International License (CC BY-NC 4.0). This license permits:
-
Sharing (copying and redistributing the material in any medium or format),
-
Adapting (remixing, transforming, and building upon the material),
-
for non-commercial purposes only,
-
with proper attribution to the original author(s) and source.
Commercial use of the material is not permitted without prior written permission from the publisher.
