Exploring Formative Assessment and Co-Regulation in Kindergarten Through Interviews and Direct Observation
Bibliographic record
Abstract
Formative assessment practices have been theoretically connected to the development of self-regulation with mounting empirical evidence. Co-regulation is the process whereby a more capable individual (e.g., teacher or peer) attunes the behaviours, emotions, or cognitive processes of an individual (a student) to align with goals or expectations and is being recognized as a strategy for developing self-regulation. Formative assessment practices may facilitate co-regulation, however, much of the literature has focused on older student populations. This phenomenological study explored the relationship between formative assessment and co-regulation in eight Kindergarten classrooms. Eight Kindergarten teachers and four Early Childhood Educators (ECE) completed semi-structured interviews in 2019 during two time periods with each participant completing two interviews. To supplement the interviews, 56 h of classroom observations were completed in each classroom, totaling 448 h of observations across eight classrooms. Interviews were audio-recorded and transcribed verbatim. Qualitative data were analyzed thematically. Four themes emerged: 1) Authentic assessment and self-regulation practices, 2) Feedback as foundational, 3) Formative assessment and co-regulation have shared purposes, and 4) Connections between classroom assessment and co-regulation. Participants described their classroom assessment and self-regulation practices as authentic and natural for students while also providing examples of their interactions with students as a form of co-regulation. Feedback was articulated as foundational to both classroom assessment and co-regulation. Participants illustrated examples of feedback from peers (including through modified peer-assessment). Shared purposes between formative assessment and co-regulation placed students at the centre of the learning process, encouraging agentic behaviours, and scaffolding student thinking. The final theme underlined the need to broaden conceptualizations of assessment in Kindergarten. Findings suggested student agency as the bridge between classroom assessment and co-regulation, and a bidirectional, mutually supportive, relationship between formative assessment and co-regulation.
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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 | 0.014 | 0.032 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.003 | 0.009 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.001 | 0.002 |
| 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 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".