Shadow Podcasts: Student Perspectives on AI-Generated Audio Content as a Supplementary Learning Tool
DOI:
https://doi.org/10.56433/k04zqd46Keywords:
AI-generated podcasts, learning experiences, supplementary learning toolsAbstract
This paper explores the use of AI-generated “Shadow Podcasts” as a supplementary learning tool in higher education. Developed using Google’s NotebookLM, the podcasts transformed lecture transcripts into short audio summaries, offering students an alternative means of engaging with course content. Deployed across five modules in two academic Schools within the Robert Gordon University, the podcasts were evaluated through a mixed-method survey of 85 students, combining quantitative ratings with thematic analysis of open-ended responses.
Analysis suggests the podcasts were well-received, with most students rating them as good or excellent and noting improvements in their own engagement, understanding, and revision. The tool's conversational tone and ability to support multitasking distinguished it from traditional materials. Critiques centred on the artificial delivery, and lack of visual or detailed content. Students expressed interest in improvements such as more expressive voices, subtitles, video integration, and stronger alignment with assessments.
The study highlights the potential of generative AI to enhance educational experiences when used transparently and reflectively. While Shadow Podcasts are not being positioned as a replacement for live teaching, they offer a flexible, scalable, and engaging complement to existing resources. Future work will involve cross-institutional research and further exploration of the podcasts’ impact on learning outcomes and curriculum design. This study contributes to the growing dialogue on pedagogically-grounded uses of generative AI in computing and business education.
References
Arkün-Kocadere, S., & Çağlar-Özhan, Ş. (2024). Video lectures with AI-generated instructors: Low video engagement, same performance as human instructors. International Review of Research in Open and Distributed Learning, 25(3), 350–369.
Becker, B. A., Craig, M., Denny, P., Keuning, H., Kiesler, N., Leinonen, J., Luxton-Reilly, A., Prather, J., & Quille, K. (2023). Generative AI in introductory programming. Association for Computing Machinery.
Becker, B. A., Denny, P., Finnie-Ansley, J., Luxton-Reilly, A., Prather, J., & Santos, E. A. (2023). Programming Is Hard—Or at Least It Used to Be: Educational Opportunities and Challenges of AI Code Generation. Proceedings of the 54th ACM Technical Symposium on Computer Science Education V. 1, 500–506. https://doi.org/10.1145/3545945.3569759
Beluzzi, F., Condorelli, V., & Giuffrida, G. (2024). Does It Really Work? Perception of Reliability of ChatGPT in Daily Use. Italian Sociological Review, 14(10S), 625–655.
Braun, V., & Clarke, V. (2021). Thematic analysis: A practical guide. SAGE publications Ltd.
Carvalho, A. A., Aguiar, C., Santos, H., Oliveira, L., Marques, A., & Maciel, R. (2009). Podcasts in Higher Education: Students’ and Lecturers’ Perspectives. In A. Tatnall & A. Jones (Eds), Education and Technology for a Better World (pp. 417–426). Springer Berlin Heidelberg.
Ciampa, K., Wolfe, Z. M., & Bronstein, B. (2023). ChatGPT in education: Transforming digital literacy practices. Journal of Adolescent & Adult Literacy, 67(3), 186–195.
Creswell, J. W., & Poth, C. N. (2016). Qualitative inquiry and research design: Choosing among five approaches. Sage publications.
Denny, P., Prather, J., Becker, B. A., Finnie-Ansley, J., Hellas, A., Leinonen, J., Luxton-Reilly, A., Reeves, B. N., Santos, E. A., & Sarsa, S. (2024). Computing Education in the Era of Generative AI. Commun. ACM, 67(2), 56–67. https://doi.org/10.1145/3624720
Do, T. D., Shafqat, U. B., Ling, E., & Sarda, N. (2024). PAIGE: Examining Learning Outcomes and Experiences with Personalized AI-Generated Educational Podcasts. https://arxiv.org/abs/2409.04645
Edirisingha, P., Rizzi, C., Nie, M., & Rothwell, L. (2007). Podcasting to provide teaching and learning support for an undergraduate module on English Language and Communication. Turkish Online Journal of Distance Education, 8.
Fernandez, V., Simo, P., & Sallan, J. M. (2009). Podcasting: A new technological tool to facilitate good practice in higher education. Computers & Education, 53(2), 385–392. https://doi.org/10.1016/j.compedu.2009.02.014
Field, A. (2024). Discovering statistics using IBM SPSS statistics. Sage publications limited.
Finnie-Ansley, J., Denny, P., Becker, B. A., Luxton-Reilly, A., & Prather, J. (2022). The Robots Are Coming: Exploring the Implications of OpenAI Codex on Introductory Programming. Proceedings of the 24th Australasian Computing Education Conference, 10–19. https://doi.org/10.1145/3511861.3511863
Gabriel, I., Manzini, A., Keeling, G., Hendricks, L. A., Rieser, V., Iqbal, H., Tomašev, N., Ktena, I., Kenton, Z., Rodriguez, M., & others. (2024). The ethics of advanced ai assistants. arXiv Preprint arXiv:2404.16244.
Google. (n.d.). NotebookLM Privacy Policy. Retrieved 24 September 2025, from https://support.google.com/notebooklm/answer/16164461
Google. (2023). NotebookLM: How to try Google’s experimental AI-first notebook. https://blog.google/technology/ai/notebooklm-google-ai/
Hernandez-Lopez, M., & Mendoza-Jimenez, J. (2025). Podcasts Created by University Students: A Way to Improve Subject Understanding, Connection with Peers, and Academic Performance. Education Sciences, 15(3), 284.
Kurtz, B. L., Fenwick, J. B., & Ellsworth, C. C. (2007). Using podcasts and tablet PCs in computer science. Proceedings of the 45th Annual ACM Southeast Conference, 484–489. https://doi.org/10.1145/1233341.1233428
Laing, C., & Wootton, A. (2007). Using podcasts in higher education. Health Information on the Internet, 60.
Lonn, S., & Teasley, S. D. (2009). Podcasting in higher education: What are the implications for teaching and learning? The Internet and Higher Education, 12(2), 88–92. https://doi.org/10.1016/j.iheduc.2009.06.002
Mahon, J., Mac Namee, B., & Becker, B. A. (2024). Guidelines for the Evolving Role of Generative AI in Introductory Programming Based on Emerging Practice. In Proceedings of the 2024 on Innovation and Technology in Computer Science Education V. 1 (pp. 10–16).
Miles, M. B., Huberman, A. M., & Saldana, J. (2013). Qualitative Data Analysis: A Methods Sourcebook. SAGE Publications. https://books.google.co.uk/books?id=p0wXBAAAQBAJ
Pirie, E., Crawford, I., Pirie, T., Richardson, C., & Spadafora, A. (2025). Enhancing entrepreneurial skills through creativity, diversity and collaborative online learning. Journal of Perspectives in Applied Academic Practice, 13(1).
Pirie, E., & Keenan, J. (2025). Creative Practice, Collaboration and Industry Engagement: The Launch of the Digital Marketing Subject Discipline and the development of the 'Inverted T Curriculum'. Journal of Perspectives in Applied Academic Practice, 13(1).
QAA. (2023a, January). The rise of artificial intelligence software and potential risks for academic integrity: Briefing paper for higher education providers. In QAA advice and resources on Generative AI. https://www.qaa.ac.uk/docs/qaa/members/the-rise-of-artificial-intelligence-software-and-potential-risks-for-academic-integrity.pdf?sfvrsn=ebb0a981_6
QAA. (2023b, July). Reconsidering assessment for the Chat GPT era: QAA advice on developing sustainable assessment strategies. In QAA advice and resources on Generative AI. https://www.qaa.ac.uk/docs/qaa/members/reconsidering-assessment-for-the-chat-gpt-era.pdf?sfvrsn=38d3af81_6
QAA, A. A. for H. (2023c, May). Maintaining quality and standards in the ChatGPT era: QAA advice on the opportunities and challenges posed by Generative Artificial Intelligence. In QAA advice and resources on Generative AI. https://www.qaa.ac.uk/docs/qaa/members/maintaining-quality-and-standards-in-the-chatgpt-era.pdf?sfvrsn=2408aa81_10
Robert Gordon University. (2024). University Research Policies: Research Governance and Ethics. https://www.rgu.ac.uk/research/university-research-policies/research-governance-ethics
Rokeman, N. R. M. (2024). Likert measurement scale in education and social sciences: Explored and explained. EDUCATUM Journal of Social Sciences, 10(1), 77–88.
Salkind, N. J. (2010). Encyclopedia of research design (Vol. 1). SAGE Publications.
Siegel, A. A., & Zarb, M. (2016). Student concerns regarding transition into higher education CS. Proceedings of the 2016 ACM Conference on Innovation and Technology in Computer Science Education, 23–28.
Smith, C. E., Shiekh, K., Cooreman, H., Rahman, S., Zhu, Y., Siam, M. K., Ivanitskiy, M., Ahmed, A. M., Hallinan, M., Grisak, A., & Fierro, G. (2024). Early Adoption of Generative Artificial Intelligence in Computing Education: Emergent Student Use Cases and Perspectives in 2023. Proceedings of the 2024 on Innovation and Technology in Computer Science Education V. 1, 3–9. https://doi.org/10.1145/3649217.3653575
Zarb, M., Alshaigy, B., Bouvier, D., Glassey, R., Hughes, J., & Riedesel, C. (2018). An international investigation into student concerns regarding transition into higher education computing. Proceedings Companion of the 23rd Annual ACM Conference on Innovation and Technology in Computer Science Education, 107–129.
Zarb, M., Brown, J. N. A., Goodfellow, M., Liaskos, K., & Young, T. (2024). Ethical Implications of Gen-AI and LLMs in Computing Education. Proceedings of the 2024 on ACM Virtual Global Computing Education Conference V. 2, 293–294. https://doi.org/10.1145/3649409.3691074
Zarb, M., Brown, J. N. A., McDermott, R., McGowan, J., & Young, T. (2024). Assessing Faculty Perceptions of a Pass/Fail Grading Model in CS1. 2024 IEEE Frontiers in Education Conference (FIE), 1–8. https://doi.org/10.1109/FIE61694.2024.10893076
Zarb, M., & Siegel, A. A. (2018). An analysis of pupil concerns regarding transition into higher education. Higher Education for All. From Challenges to Novel Technology-Enhanced Solutions: First International Workshop on Social, Semantic, Adaptive and Gamification Techniques and Technologies for Distance Learning, HEFA 2017, Maceió, Brazil, March 20–24, 2017, Revised Selected Papers 1, 3–16.
Zyda, M. (2024). Generative AI changes the world, maybe. Computer, 57(09), 118–123.
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