Integrative motivation and global language (English) acquisition in Poland
Bibliographic record
Abstract
This study investigated the consistency of a measure of integrative motivation in the prediction of achievement in English as a foreign language in 18 samples of Polish school students. The results are shown to have implications for concerns expressed that integrative motivation might not be appropriate to the acquisition of English because it is a global language and moreover that other factors such as the gender of the student or the environment of the class might also influence its predictability. Results of a hierarchical linear modeling analysis indicated that for the older samples, integrative motivation was a consistent predictor of grades in English, unaffected by either the gender of the student or class environment acting as covariates. Comparable results were obtained for the younger samples except that student gender also contributed to the prediction of grades in English. Examination of the correlations of the elements of the integrative motivation score with English grades demonstrated that the aggregate score is the more consistent correlate from sample to sample than the elements themselves. Such results lead to the hypothesis that integrative motivation is a multi-dimensional construct and different aspects of the motivational complex come into play for each individual. That is, two individuals can hold the same level of integrative motivation and thus attain the same level of achievement but one might be higher in some elements and lower in others than another individual, resulting in consistent correlations of the aggregate but less so for the elements.
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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 | 0.001 | 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 | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".