Development and Validation of a Measure to Assess Early Adolescents’ Perceptions of Caring Student-Teacher Relationships
Bibliographic record
Abstract
There is accruing evidence documenting the importance of caring student-teacher relationships in fostering students’ social and emotional competence (SEC), well-being, and school success, particularly during early adolescence. However, few studies have investigated dimensions of caring student-teacher relationships from the perspective of early adolescents. This study describes the development and validation of the Caring Student-Teacher Relationship (CSTR) scale. Participants included 222 sixth and seventh grade middle school students who completed the CSTR and self-report measures of classroom supportiveness, prosociality, well-being, and school functioning. Students also assessed their teachers’ SEC. Classroom teachers (n = 14) completed self-report measures of mindfulness in teaching and burnout, reported on closeness and conflict in their relationships with students, and rated students’ SECs and academic success. Results from an Exploratory Factory Analysis (EFA) indicated high internal consistency of the CSTR and a two-factor solution: Teacher Support and Attunement and Caring Teacher Qualities. Further analyses revealed that the two factors of the CSTR were related in expected directions to measures of teacher support (e.g., academic and personal) and SEC, and to students’ reports of classroom supportiveness, prosociality, well-being, and school functioning. Positive associations of the two CSTR factors to teacher reports of students’ SEC and academic success were also found. The two factors of the CSTR were positively associated with teachers’ reports of mindfulness in teaching and negatively associated with teachers’ burnout. These findings have implications for understanding the role that students’ perceptions of student-teacher relationships may play in promoting their positive adaptation and success in school.
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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 | 0.011 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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 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".