What Makes Reform Work?–School-Based Conditions as Predictors of Teachers’ Changing Practice after a National Curriculum Reform
Bibliographic record
Abstract
Educational change initiatives, whether they involve the implementation of new policies or curriculum reforms, often fail to reach the level of teachers’ classroom practices. In the search for explanations, numerous studies have either characterized teachers as resistant to change or focused on how schools’ workplace conditions have failed to influence teacher change. This study draws attention to these issues by investigating teachers’ perceptions of the degree to which a national curriculum reform has brought about changes in their teaching. The study also proposes a model of how teachers’ perceptions of school-based conditions (i.e., school leadership, teacher collaboration, and development of school-based curricula) are related to teachers’ general orientations towards change and teachers’ perceptions of change as a result of the reform. The participants were 738 Norwegian teachers in public primary and lower secondary schools, and the data were analyzed using descriptive data, correlation analysis and structural equation modeling (SEM).The results indicate that the overall influence of the reform on teachers’ teaching was moderate. The results also revealed positive relationships between teachers’ perceptions of school-based conditions, teachers’ general orientations towards change and the degree of perceived reform changes in teachers’ teaching. However, a surprising finding is that school leadership and teacher collaboration were only indirectly related to teachers’ perceptions of reform changes, mediated through teachers’ general orientations towards change. The article highlights important relationships between educational reform, school-based conditions and teachers. It also contributes knowledge that is relevant to consider for successful reform of schools and education.
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 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 | 0.004 | 0.022 |
| 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 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".