Personal goals as predictors of intended classroom goals: Comparing elementary and secondary school pre‐service teachers
Bibliographic record
Abstract
BACKGROUND AND AIMS: The literature documents fewer classroom mastery goal structures in secondary school compared to elementary. However, little is known about how personal achievement goals may influence classroom goal structures. This is especially true at the level of pre-service teachers. Our objective was to investigate if pre-service teachers' personal goals predicted their intended classroom goal structures. SAMPLE: Participants were 125 elementary and 175 secondary school pre-service teachers from two Western Canadian universities. METHOD: Structural equation modelling was used to examine if the structural relationships and latent means of personal and intended classroom goal structures differed for elementary and secondary school pre-service teachers. RESULTS: The results revealed that personal goals predicted the goal structures that pre-service teachers intended to establish; however, the relationships and means differed between elementary and secondary school pre-service teachers. Specifically, personal mastery-approach goals positively predicted classroom mastery goals much more strongly at the elementary than the secondary level. Furthermore, elementary pre-service teachers had significantly higher latent mean scores on personal mastery-approach goals than their secondary counterparts. CONCLUSIONS: It seems possible that the currently documented differences between classroom goal structures noted for elementary compared to secondary school may be based on the personal goals endorsed as pre-service teachers. The results are further discussed in terms of alignment with research on practising teachers' personal and classroom goals and implications for teacher education.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".