Scripted Vicarious Dialogues: Educational Video Augmentation Method for Increasing Isolated Students’ Engagement
Bibliographic record
Abstract
Videos are convenient resources for asynchronous learning, but they lack interpersonal interactions found in synchronous classrooms. Due to missed social connectedness, the isolated video-based learners experience low emotional, behavioral, and cognitive engagement. This work presents "Scripted Vicarious Dialogues" (SVD), a technique for engaging students in a pseudo-social experience of witnessing scripted dialogues between virtual characters (teaching assistants and students) around a video. We conducted a participatory design study to derive design guidelines for SVD. The findings indicate the need to distinguish the virtual components and to give students control of the dialogue’s pace. We then implemented an interactive prototype of SVD and evaluated it (N=40) against a non-social, direct-learning baseline. The results show that the preference for SVD versus the baseline is polarized (25 of 40 preferred SVD; no neutral preferences), and those who preferred SVD had significantly higher emotional and behavioral engagement with SVD compared to the baseline.
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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 | 0.007 |
| 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 | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".