Online course design perspectives, a new normal? Student and teacher perceptions of online engagement in rural Québec
Bibliographic record
Abstract
Abstract: The recent pandemic has accentuated the need to understand what online teaching techniques work to motivate students. Research indicates a more inclusive online student-centered approach creates new course design demands on teachers but provides greater student motivation. At the center of the issue is a lack of student engagement, frequently caused by learners feeling disconnected from other participants and/or the teacher in most online settings. Aside from technological issues, the problem is often accentuated by continued implementation of instructional design methodology that is based on conventional classroom models as opposed to inclusive approaches. Also tied into this, is a lack of teacher training to support learner-centered course design. Since virtual hybrid online learning using videoconferencing has started to offer an increase in course diversity that would otherwise not be possible for some locations with fewer educational resources and distance limitations, the need to understand learner-centered approaches has intensified. This study focused on professional programs given by Cégep de la Gaspésie et des Îles, a rurally situated Cegep (community college) in Québec, Canada, spanning a vast territory. Both students and instructors were asked to respond to separate, but corresponding surveys adapted from the Community of Inquiry framework and questionnaire developed by Garrison et al. (2000). Understanding the relationship between the participant responses and selected learner-centered approaches, either currently in use or viewed as useful, sheds light on what keeps students actively engaged. Results suggest that learner centered approaches are appreciated by both students and teachers to potentially increase student engagement, but the pedagogical possibilities are not always fully understood, or utilized. This information provides new directions for online course design because of the comparison factor between what teachers believe should get students engaged and what students report as being engaging.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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".