Instructor enthusiasm in online lectures: how vocal enthusiasm impacts student engagement, learning, and memory
Bibliographic record
Abstract
Across two studies we investigated the impact of instructor enthusiasm on student attentional engagement during an online undergraduate lecture, as well as their memory for lecture content and their motivation to watch additional lecture videos on the same topic (Study 2 only). In both studies participants were randomly assigned to watch a 22-min lecture, delivered with either high or low vocal enthusiasm by the instructor. Subjective ratings of instructor enthusiasm/energy confirmed that in both studies the manipulation of instructor enthusiasm was effective. More importantly, in both studies we found that students in the high enthusiasm condition were consistently more engaged over the course of the lecture compared to those in the low enthusiasm condition, and that overall, reports of engagement increased together with ratings of instructor enthusiasm. However, we found no evidence that instructor enthusiasm influenced quiz performance in either study. Nevertheless, Study 2 showed that those in the high enthusiasm condition were more motivated to watch the next lecture than those in the low enthusiasm condition. These findings make an important contribution to the study of online learning and indicate that instructor enthusiasm may be a viable strategy to increase student engagement and motivation in online courses.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".