Instructional Video Design: Investigating the Impact of Monologue- and Dialogue-style Presentations
Bibliographic record
Abstract
Instructional videos are frequently used in online courses and websites. Such videos may include an instructor delivering a monologue-style presentation, or alternatively, engaging in a dialogue with a student who appears in the video alongside of the instructor. We compared three instructional video designs (N = 77), including monologue and dialogue style presentations. To obtain a comprehensive view of the impact of video design, we used a variety of measures, including eye tracking data, learning gains, self-efficacy, cognitive load, social presence, and interest. Despite eye tracking data showing that participants in speaker-visible conditions spent significantly less time on the domain content, learning and related variables were similar in all three conditions, a result we confirmed with Bayesian statistics that provided substantial evidence for the null model. Altogether, we provide evidence that learning and interest are not enhanced by a dialogue-style presentation or visual presence of the instructor. However, further work is needed to investigate the effect of other domains, speaker persona and saliency, and configuration of the speakers in the instructional video.
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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 | 0.003 | 0.043 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".