Students Selecting Higher Face-to-Face Instructional Delivery Report Higher Levels of Learning Interactions and Outcomes
Bibliographic record
Abstract
This exploratory study examined the learning interactions of 303 undergraduate students who initially enrolled in seven traditional 200-level university criminal justice courses. Participants were offered the opportunity to choose between four different teaching modalities: 90% of a course (in face-to-face interactions; almost exclusively in the classroom) to 70%, 30% and 10% ratios (to almost exclusively online). Students who chose higher levels of blended face-to-face interactions were statistically more likely to report higher levels of learner–learner (LL), learner-instructor (LI) and learner-technology (LT) interactions. There was also no statistical impact on learner-content (LC) interactions suggesting that the amount or rigor of content did not seem to be impacted by a student’s decision on the teaching modality they selected.
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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 | 0.005 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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 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".