How effective is online pre-service teacher education for inclusion when compared to face-to-face delivery?
Bibliographic record
Abstract
Research has recognized that enhancing pre-service teachers’ attitudes, efficacy, and decreasing concerns about inclusive education are essential factors in teacher preparation. However, no research has compared the relative ability of online courses to affect these factors when compared to traditional face-to-face instruction. The current study used pre–post survey methods to measure the effects of the online versus face-to-face formats of teaching inclusive education content to Canadian pre-service teachers. Moreover, we studied the relationships between these variables and the participants’ intentions for inclusive teaching practices. Results showed that while the face-to-face format influenced pre-service teachers’ attitudes and efficacy, it did not foster lower concerns or higher intentions. In contrast, the online course made no significant difference in any of the dependent variables. Given the well-established importance of affective as well as practical variables to effective inclusion, implications and limitations are discussed.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".