Usability of an eLearning Professional Development Program for Elementary Classroom Teachers: ASSIST for Disruptive Classroom Behaviours
Bibliographic record
Abstract
An eLearning professional development (PD) program, ASSIST for Disruptive Classroom Behaviour, was developed using an iterative user-centred design approach. This program was designed to support teachers in the implementation of teacher-implemented in-class interventions for disruptive classroom behaviour (DCB). The objective of the current study was to determine the usability of this program. Overall, the results suggest that end-users (i.e., classroom teachers) and stakeholders (i.e., administrators, specialized teachers, school psychologists, and behaviour specialists) found the program to have high usability and reported that it was ready to be used by other teachers, that they found it flexible to adapt to their classroom setting; they provided high satisfaction ratings for this program. In addition to the positive findings, the primary constructive feedback was that tangible downloadable materials should be added to the ASSIST for Disruptive Classroom Behaviour program to meet classroom teachers’ needs better. Based on all results, the program, with a few minor modifications, was deemed ready for effectiveness testing.
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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 | 0.004 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".