Lecture Capture as Universal Design for Learning, A Post-Pandemic Scoping Review

universal design for learning
digital research
higher education policy
lecture recording
project-qaa-wp
technology enhanced learning
Authors

Emily Nordmann

Jill R. D. MacKay

Published

January 21, 2026

Doi
Abstract
Lecture capture is frequently justified as an inclusive technology, yet its alignment with Universal Design for Learning (UDL) in post-pandemic practice has not been empirically considered. We conducted a scoping review of post-pandemic lecture capture research, identifying 12 studies that considered live lecture recording in higher education. Using the UDL guidelines as an analytic framework, we found that lecture capture primarily supports Engagement and, to a lesser extent, Representation through flexible access, replay and player controls. Action and Expression and higher-level executive functions were rarely addressed. Demographic reporting was limited, with few analyses for disabled, neurodivergent or commuting students. We argue that lecture capture is necessary, but insufficient as a sole adjustment for inclusive design and prioritise future research.

Behind the Paper

Emily and I have increasingly been interested in the claim that lecture recording can be a mainstreaming adjustment. While we both agree, many researchers (ourselves included!) can be a bit vague as to exactly how this happens. We are also firmly of the opinion that the post-pandemic education landscape is different, and we can’t necessarily draw the same generalisations from the pre-pandemic literature.

In this scoping review, we explored how lecture recording is used as learning adjustment, using the Universal Design for Learning guidelines as a framework. Unsurprisingly, we found that many of the mainstreaming possibilities had not been researched or evaluated.

There’s still plenty to do in this field, and plenty more to understand about how students can utilise tools like recordings in their learning.

AI Use

This was the first paper where I actually used AI. We used AI to review our codes and suggest where we may have missed some. We then reviewed its suggestions, and I acted as the ‘AI naive’ reviewer, sense checking the process without looking at what had been suggested by the AI tool. I don’t think I personally would hurry to use it again in this fashion, but its worth noting here!

Citation

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