Online Prelectures: An Alternative to Textbook Reading Assignments
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
To engage students in a more meaningful discussion of course material and prompt their higher thinking skills, most instructors expect students to read the course textbook for initial exposure to the course content before class. However, as many instructors are aware, most students do not read their textbook throughout the quarter.1,2 At California State Polytechnic University, Pomona (Cal Poly Pomona) we have adopted web-based multimedia learning modules (MLMs) as prelecture assignments to help students to prepare for the class activities. The MLMs place lecture contents into the hands and control of the learners; similar to “flipped”3 or “inverted”4 classroom approaches, this method allows students to receive key course content outside of class and apply and analyze the content actively during class. In addition to initial exposure to basic principle, the MLMs provide additional worked examples that cannot be thoroughly covered in class.
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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| 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