An Eye Tracking Comparison of Instructional Videos Showing a Monologue Versus a Dialogue: Impacts On Visual Attention, Learning, and Psychological Variables
Bibliographic record
Abstract
The present study aimed to synthesize two disparate domains of instructional video research to investigate what impacts occurred from, on one hand, the visual presence of the speaker(s), and on the other hand, the format of a dialogue.Seventy-seven participants watched either a narrated control video without the instructor visible, a monologue video with the instructor visible, or a dialogue video between an instructor and student, both visible.To compare the conditions, we examined learning outcomes, visual attention, self-efficacy, mindset, cognitive load, social presence, and interest.Despite eye tracking data showing that participants in speaker-visible conditions spent significantly less time attending to the learning content, we found no conditional differences on measures of learning, social presence, cognitive load, selfefficacy, or mindset.These results suggest that neither speaker visual presence nor dialogue format affected learning or participants' perceptions of the videos.I would like to thank the countless people who supported, guided, and cheered me along my journey through this work.This project would have certainly never left the ground if not for Prof. Kasia Muldner, whose supervision cleared my path of many obstacles and brought invaluable direction and clarity to my ideas and writing.Thank you to Sara for volunteering to be on camera as our intrepid 'student', and to the participants for contributing their time and feedback.Thank you to the faculty, fellow students, staff, and others that I had the pleasure of meeting through the Carleton HCI program -being surrounded by the wealth of knowledge and passion for this field was a constant reminder of the meaningful challenge of awesome, empathetic, human-centred design.To my UOSalsa familia, thank you for bringing so much joy into my life and helping me nurture my love of dance.A regular dose of salsa, bachata, and kizomba was the perfect foil to long days spent reading and writing.Finally, thank you to my friends and family for encouraging me to pursue my dreams and for being there through both stress and celebration.And to Curtis,
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".