Disturbance is a recurring phenomenon in online education, not yet resolved. A particular sub-set of this are audiovisual disturbances, stemming from online education always being mediated by some sort of digital tool. Here, a research overview of current research on online higher education, hitting 884 articles and conference papers in the databases ERIC, Scopus and Google Scholar (after removing duplicates), found 266 relevant hits. Seven themes were identified as regarding audiovisual aspects of disturbances, and how to measure such aspects: communication (21), audiovisual perception and quality (20), fluidness (12), fatigue (13), cognitive load (86), measurements of these categories (99), and as a sub-set, eye-tracking (15).
Any kind of malfunction of a digital tool or connection causes disturbance in communication, which exists in numerous variants. Video is considered to provide better communication by students, than only sound or text, even though quality of sound is crucial to teaching and learning success. Quality of content is more important though, than the technical standard of video. Short, high-quality videos seem to render the better student engagement at lessons. Anyhow, students need to have technical readiness to sustain online education.
Key for student online learning success is the user-experience of seamlessness in teaching and e-tutorial situations. Such seamlessness allows for immersion, which supports a better personal situatedness, than during traditional teaching. Further, both gamification and interactivity support immersion and the sense of “flow” (Csikszentmihalyi, 1990) in the learning situation. However, the flow of information, at least in part, need to be adjustable for the student.
Online education also comes with the risk for several forms of fatigue: fatiguing course material, and solitude fatigue felt by students, compassion fatigue on behalf of teachers, and “Zoom fatigue” for all. Particular fatigue measurements have been developed.
Another effect of the online education situation is the vulnerability to cognitive load. Negative cognitive load arises as an effect from attention split, in turn caused by disturbing details, cueing and signals, and differences in information modalities. Particularly distracting is complex information presented in VR environments. Several studies consider cognitive load during use of video in the teaching/learning situations: for instance, the effects of video length, teacher presence, or external cognitive load. A few cognitive load measurements include objective data such as mouse clicks or time consumption, whereas most cognitive load measurements rely on subjective reporting of experience via questionnaires or scale indications. Not all cognitive load is negative though, so there is a differentiation between external, internal (both negative) and germane (positive) cognitive load. However, there are some indications that course content might be possible to improve by better design, taking cognitive load into regard.
Eye-tracking provides a particular non-intrusive means for objective attention measure. It is used to study attention to web-page layout, during video usage, or text reading as well as course assignment work – all online. Yet, I found no studies that use eye-tracking to examine cognitive load, although it is feasible to do so.
As for a future research initiative, I suggest to explore cognitive load in online education settings by means of eye-tracking.
IATED , 2024. p. 6869-6880
INTED2024 - 18th International Technology, Education and Development Conference, 4-6 March, 2024, Valencia, Spain