Student usage of short online single-topic videos in a first-year engineering chemistry class
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
This study explored students’ usage patternswith 5-10 minute single-topic (“short topic”) videosproduced solely for online use to support undergraduatestudents enrolled in a first-year introductory course toengineering chemistry and materials science at theUniversity of Toronto. The short topic videos were postedas unlisted YouTube videos and made available to studentsusing the Blackboard learning management system.Analytical data was collected from these unlisted YouTubevideos. In 2016, 142 student participants completed ananonymous survey that collected information on users’perceived usefulness and the reason for using the shorttopic videos. In the survey responses, 70.4% of studentsindicated a preference for using the short topic videos toreview specific content vs. full lecture captures. A total of76 short topic videos were created with an average videolength of 8:11 min. The videos were intentionally keptshort, with a maximum duration of 13:46 min. View counts and feedback from the survey responses suggested that students used the short topic videos to review contents and found the videos to be a valuable learning resource. The videos were re-used as the main learning content in the online equivalent course offered in 2017 and 2018. Datacollected from YouTube analytics demonstrated similarusage behavior and retention in the videos when used asthe main learning resource in the online courses to whenthe videos were provided as supplementary resources.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it