In this episode of the Culture Compute Podcast: Learning in the Digital Age, I, Sai Gattupalli from the Advanced Learning Technologies Lab at the University of Massachusetts Amherst, review my personal notes from three recent, peer-reviewed research papers that are reshaping our understanding of educational technology. These studies—published in the British Journal of Educational Technology, Learning, Media and Technology, and a work by Salmaan Khan—offer fresh insights into AI literacy frameworks, the evolving role of algorithmic authorship in academia, and innovative approaches to interactive digital pedagogy.

In our discussion, I explore how Chee, Ahn, and Lee’s comprehensive framework for AI literacy provides a developmental pathway that spans from basic digital skills to advanced data-driven decision-making. I reflect on my own journey in learning technology, emphasizing the importance of continuous professional development and robust institutional support.

Next, I delve into Gretzky and Dishon’s thought-provoking examination of algorithmic authorship. Their work challenges traditional notions of creativity and intellectual contribution as AI tools increasingly participate in scholarly writing. I share my personal insights on the balance between human ingenuity and machine assistance, a theme that has profound implications for the future of academic work.

Finally, I review Salmaan Khan’s study on interactive digital pedagogy, which highlights how adaptive digital platforms can transform classrooms by engaging students as active, collaborative participants. This research underscores the practical benefits of technology when thoughtfully integrated into teaching practices—a vision that resonates deeply with my own experiences in the field.

Join me as we synthesize these groundbreaking studies and discuss how their collective insights can redefine teaching and learning in our increasingly digital world.

References:
Chee, H., Ahn, S., & Lee, J. (2024). A Competency Framework for AI Literacy: Variations by Different Learner Groups and an Implied Learning Pathway. British Journal of Educational Technology. https://bera-journals.onlinelibrary.wiley.com/doi/10.1111/bjet.13556?af=R

Gretzky, M., & Dishon, G. (2025). Algorithmic-authors in academia: blurring the boundaries of human and machine knowledge production. Learning, Media and Technology. https://www.tandfonline.com/doi/full/10.1080/17439884.2025.2452196

Khan, S. (2024). From Passive Receptors to Engaged Participants: Addressing the Limits of Generative AI and Knowledge Sharing in the Digital Age. https://cuny.manifoldapp.org/read/from-passive-receptors-to-engaged-participants-addressing-the-limits-of-generative-ai-and-knowledge-sharing-in-the-digital-age/section/2b6f966a-0830-42bd-b705-3f0ddb26e6a7

For inquiries or further discussion, please email sgattupalli@umass.edu. Visit CultureComputePod.com for more information.