Collaborating with teachers to design and implement assessments for self-regulated learning in the context of authentic classroom writing tasks
Bibliographic record
Abstract
We present data from a larger longitudinal study, focusing on researchers’ and teachers’ collaborative design and implementation of assessments for learning (AfL), including student self-assessments, to support self-regulated learning (SRL) during classroom writing activities. We focus on students (N = 112) when they were in Grade 3. The study used a mixed method triangulation approach. Data include: detailed descriptions of classrooms with relatively high and low emphasis on SRL; students’ self-assessments of SRL; and students’ writing processes and products from a teacher-researcher co-constructed writing task. Students enrolled in classrooms with high emphases on SRL had more opportunities and support for SRL and AfL and, consequently, demonstrated more sophisticated self-assessments and higher levels of interest and task value than their peers in classrooms with low emphasis on SRL. Also, these learners demonstrated higher levels of self-regulation in writing tasks and higher quality writing products. Implications for research and practice 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 | 0.071 | 0.120 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.001 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".