Examining teacher candidates’ self-determined motivation to develop self-regulated learning promoting practices
Bibliographic record
Abstract
The development of self-regulated learning leads to positive academic, social, and emotional outcomes for learners. For many educators, teaching towards self-regulated learning is challenging. This study investigated contextual and motivational features within teacher education programs that support or hinder teacher candidates' motivation to development self-regulated learning practices. Zimmerman's model of self-regulated learning (2008), along with Perry, Hutchinson, and Thauberger’s (2008) descriptions of self-regulated learning practices and Ryan and Deci's (2017) self-determination theory informed this process. Codes and categories drawn from interviews, documents, and in-class observations and reported upon in previously published work was analyzed to identify themes that are supportive or constraining of teacher candidates' motivation to develop practices that foster self-regulated learning in the classroom. Results reveal five themes: (a) opportunities for teacher candidates to see their school mentors' formation of classroom participation structures, (b) the provision of freedom for teacher candidates to experiment with practices along with in-situ scaffold support, (c) adequate support for teacher candidates to integrate self-regulated learning content into their practice, (d) teacher candidates' perceptions of alignment across their learning experiences, and (e) adequate time and support for teacher candidates to establish relationships in their practicum settings.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.010 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.003 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 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".