Bibliographic record
Abstract
This chapter examines factors influencing students' course delivery modality selection (fully online vs. blended) in the context of a LINC program and compares modalities with respect to digital skills acquisition, language learning progress, and participants' satisfaction, using data from assessments (pre and post) and end-of-term feedback surveys. While digital literacy was not a factor in modality selection or preference, given no statistical difference across modalities in digital skills test scores at the pretest, sociodemographic factors (e.g., gender, parental status, marital status, and time in Canada) were associated with being in the online modality, suggesting that selection of the online modality was more about flexibility and convenience. In addition, being in the fully online modality was negatively associated with the odds of improved test performance on writing tests (no difference for reading and digital literacy tests). On the other hand, end-of-term survey feedback from CLB 5 and above classes found higher satisfaction rates among students in the online modality.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.012 |
| 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 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".