Relationship Between Academic Motivation and Mathematics Achievement Among Indian Adolescents in Canada and India
Bibliographic record
Abstract
This study examined the relationships between academic motivation-intrinsic motivation, extrinsic motivation, amotivation-and mathematics achievement among 363 Indian adolescents in India and 355 Indian immigrant adolescents in Canada. Results of hierarchical multiple regression analyses showed that intrinsic motivation, extrinsic motivation, and amotivation were not statistically significantly related to mathematics achievement among Indian adolescents in India. In contrast, both intrinsic motivation and extrinsic motivation were statistically significantly related to mathematics achievement among Indian immigrant adolescents in Canada. While intrinsic motivation was a statistically significant positive predictor of mathematics achievement among Indian immigrant adolescents in Canada, extrinsic motivation was a statistically significant negative predictor of mathematics achievement among Indian immigrant adolescents in Canada. Amotivation was not statistically significantly related to mathematics achievement among Indian immigrant adolescents in Canada. Implications of the findings for pedagogy and practice are discussed.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 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".