The school of hard knocks: Pre-service teachers’ mindset and motivational changes during their practicum
Bibliographic record
Abstract
The mindset and motivation that teachers demonstrate are likely to influence their students’ mindset and motivation. While mindset and motivation of in-service teachers have been investigated thoroughly, the same cannot be said of pre-service teachers. Pre-service teachers’ mindset and motivation are likely developed during in-class experiences or practicum, the latter seen as the defining experience of pre-service teachers’ preparation. Understanding the changes that pre-service teachers undergo during their practicum experiences in terms of theories of intelligence, teaching efficacy, resilience, and grit is therefore crucial. This study used these constructs as examples of mindsets, self-beliefs, capacities, and personality traits. A cross-sectional design compared American and Canadian pre-practicum versus post-practicum pre-service teachers’ growth mindset and motivation and illustrated that similar effects occur across national contexts through a primarily quantitative questionnaire with open-ended questions. Triangulated statistical and thematic analyses illustrated that post-practicum students were less idealistic about the incremental nature of intelligence and reported higher resilience and a more pragmatic approach to teaching than their pre-practicum peers. The study’s findings extended other studies’ findings illustrating that changes occur specifically in teacher mindset as well as their strategies. Teacher education programs informed by these specific changes can capitalize on the pragmatic shift of teachers’ strategy selection while also coaching them to retain an incremental view of intelligence for their students’ benefit.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| 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".