Enhancing Student Engagement through an Institutional Blended Learning Initiative: a Case Study
Bibliographic record
Abstract
Tertiary education institutions grapple with how to better engage students in their learning in high-enrolment, introductory courses. This paper presents a case study that examines a large-scale, faculty-level course redesign project in which this challenge was addressed through the use of blended learning models. The main research question was: Are students in blended formats engaged in their learning differently than those in the traditional formats? The first part of this paper describes the institutional policies, processes, and practices that were established to implement the course redesign project. The second part of the paper focuses on the effectiveness of the project, presenting the results of a longitudinal research study that examined changes in student engagement using the Classroom Survey of Student Engagement (CLASSE). The implications of the longitudinal evaluation and institutional strategy, structure, and support components are examined critically, as well as the project’s impact on students and on the larger university.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.012 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.009 | 0.003 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.003 | 0.007 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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 source (direct Gemma or distilled Codex), 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".