Positive, complicated, distant, and negative: How different teacher‐student relationship profiles relate to students’ science motivation
Bibliographic record
Abstract
INTRODUCTION: Researchers note a consistent decline in adolescents' motivation and participation in science. It is important to examine factors vital to students' motivation in science, such as teacher-student relationships (TSRs). Limited research in science has examined TSRs from a multidimensional or person-centered perspective. The present investigation adopts Ang's tripartite relational framework to examine three dimensions of TSRs: socio-emotional support, instrumental help, and conflict. Such research is needed to better understand the diversity of relationships that exist within a science classroom and their impact on science motivation. METHODS: = 15.11 years; SD = 0.69). Data were collected via online sampling in the final quarter of 2020. The data are cross-sectional. Latent profile analysis was used to (1) determine if distinct student profiles based on the three dimensions of TSRs existed and (2) the extent to which these profiles were associated with varying levels of science motivation: self-efficacy, intrinsic value, utility value, and cost. RESULTS: Four distinct profiles were identified: Positive, Complicated, Distant, and Negative. Students in the Negative TSR profile reported the lowest adaptive motivation and highest cost. The associations between profile membership and motivation were more varied for the Positive, Complicated, and Distant TSR profiles. CONCLUSIONS: Findings indicate that dichotomous perspectives (positive vs. negative) may be insufficient to describe the diversity of relationships within science classrooms. Results also suggest that concurrent attendance to all dimensions of TSRs is needed to improve relationships.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".