Assessment of Self-Regulation in Ontario Secondary Schools
Bibliographic record
Abstract
Self-regulation is positively associated with better academic, and life, outcomes. Consequently, many school systems aim to develop self-regulation, or related constructs. Thus, many teachers are asked to assess and report upon students’ self-regulation (or related constructs). How secondary teachers in Ontario, Canada accomplish this task was investigated using mixed methods research. Phase 1 involved semi-structured interviews with 26 secondary teachers. The second phase of the study involved the analysis of report card data to examine large scale trends in self-regulation grades. The third phase employed an online survey whose development was informed by the interviews of the first phase. The overall findings are that Ontario secondary teachers vary in their definitions of self-regulation, but the strongest influences on teachers' self-regulation assessments are negative student behaviours. Report card data suggest that teachers struggle to assess self-regulation independently from other constructs such as initiative or collaboration. Implications for practice are discussed. Keywords: Classroom Assessment, Self-regulation, Learning skills, Grading, Report Cards L'autorégulation est positivement associée à de meilleurs résultats scolaires et personnels. Par conséquent, de nombreux systèmes scolaires visent à développer l'autorégulation, ou des concepts connexes. Ainsi, on demande à de nombreux enseignants d'évaluer et de rendre compte de l'autorégulation des élèves (ou des concepts connexes). La manière dont les enseignants du secondaire de l'Ontario (Canada) accomplissent cette tâche a été étudiée à l'aide de méthodes de recherche mixtes. La première phase a consisté en des entretiens semi-structurés avec 26 enseignants du secondaire. La deuxième phase de l'étude a consisté à analyser les données des bulletins scolaires afin d'examiner les tendances à grande échelle des notes d'autorégulation. La troisième phase a fait appel à une enquête en ligne dont l'élaboration a été guidée par les entretiens de la première phase. Les conclusions générales sont que les enseignants du secondaire de l'Ontario n'ont pas tous la même définition de l'autorégulation, mais que les comportements négatifs des élèves sont ceux qui influencent le plus l'évaluation de l'autorégulation par les enseignants. Les données des bulletins scolaires suggèrent que les enseignants ont du mal à évaluer l'autorégulation indépendamment d'autres concepts tels que l'initiative ou la collaboration. Les implications pour la pratique sont discutées. Mots clés : évaluation en classe, autorégulation, compétences d'apprentissage, notation, bulletins scolaires
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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 | 0.009 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.026 | 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".