Asynchronous Delivery of a 400 Level, Partially Peer-Graded, Oral Presentation and Discussion Course in Systems Neuroscience for 60 Students during the COVID-19 Pandemic
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
A 400-level undergraduate oral presentation and discussion course in Systems Neuroscience was delivered asynchronously online during the COVID-19 pandemic. Enrolled students banked their narrated oral presentations in video format online then engaged in peer evaluation in virtual classrooms through the course website. Student delivered their oral presentation and responded to peer questions at their leisure and convenience, without the stress and anxiety associated with a “live” performance delivery in front of their peers. A remote and asynchronously delivered course facilitated much more peer contact than “live” versions of the course, which included a total of 62 uploaded presentations, 301 video responses uploaded to 1985 questions posed by peers, a total of 1159 feedback questionnaires submitted, 1066 rankings submitted of viewed oral presentations, and 1091 scores submitted evaluating the quality of questions posed by reviewers of oral presentations. A major drawback in the remote, asynchronous deliver was the enormity of peer engagement through the course website portal, which was mostly blind to the instructor because of the inability to effectively cross-index data linked between the student entries in the LEARN course website and the uploaded videos stored within BONGO Video Assignment tool. Nonetheless, a consistent engagement of students, and the positive feedback from enrolled students, indicate that a future version of this oral/written discussion course will be delivered, in part, remotely and asynchronously, even without a mandated delivery of the course by a remote and asynchronous method due to the COVID-19 pandemic restrictions in 2020–2021.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.013 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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