Socio-motivational moderators—two sides of the same coin? Testing the potential buffering role of socio-motivational relationships on achievement drive and test anxiety among German and Canadian secondary school students
Bibliographic record
Abstract
The current cross-national study investigates the potential buffering role of socio-motivational relationships for the association of achievement drive (AD) and test anxiety (TX) in secondary school students from Canada and Germany. One thousand and eighty-eight students (54% girls, M age = 13.71, SD = 0.53, age span 12-15 years) from the state of Brandenburg and 389 students from Quebéc (55.9% girls, M age = 13.43, SD = 0.82, age span 12-16 years) were asked about their socio-motivational relationships with their teachers and peers, their drive for achievement, and TX. Multigroup latent moderated structural equations were conducted to test for the moderator role of socio-motivational relationships that would buffer feelings of TX related to the drive for achievement. The analyses revealed the two-sided role socio-motivational relationships can have for students with different levels of AD; intensifying or mitigating feelings of TX. Thereby, the results of this study extend the buffering hypothesis by Cohen and Wills (1985). Cross-national differences between Canada and Germany were found concerning the studied moderators on the association of AD and TX: While for German students teacher-student relationships acted as moderator, for Canadian students student-student relationships and teachers acting as positive motivators displayed a moderator role.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.003 | 0.001 |
| 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".