Does Delivery Model Matter? The Influence of Course Delivery Model on Teacher Candidates’ Self-Efficacy Beliefs Towards Inclusive Practices
Bibliographic record
Abstract
A causal-comparative research design was used to examine the influence of course delivery (face-to-face flipped or asynchronous online) on participants’ self-efficacy beliefs toward teaching in an inclusive classroom. The following research questions were used to guide the study: (a) Is there a relationship between completing an introduction of exceptionalities course and participants’ self-efficacy toward teaching an inclusive classroom? (b) Is there a relationship between completing an introduction of exceptionalities course in an asynchronous online or face-to-face flipped format on participants’ self-efficacy beliefs toward teaching in an inclusive classroom? The purpose of this study was to explore if there is a relationship between self-efficacy belief development and course delivery models. The results indicated a significant difference in self-efficacy beliefs towards teaching in an inclusive classroom after completing an introduction of exceptionalities course. However, there was no significant difference in the participants’ efficacy based on the course delivery model (face-to-face flipped or asynchronous online). Implications and suggestions for future research are discussed.
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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 | 0.017 | 0.063 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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 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".