Conceptual and Psychometric Properties of a Foreign Language Learning Motivation Questionnaire
Bibliographic record
Abstract
This paper investigates the conceptual and psychometric properties of an instrument that measures the foreign language motivation of Filipino learners. The results of this study suggest that there are six factors that compose the motivation orientation of Filipino learners. The factors identified in the questionnaire have the psychometric properties of internal consistency and construct validity. Some further validation, modifications and improvements are also suggested. Since the studies of two Canadian psychologists, Robert Gardner and Wallace Lambert in the 1950s, the study of concept and role of motivation in learning a second language (L2) or foreign language (FL) has continually been explored focusing on its multiple dimensions (Crookes & Smith, 1991; Dornyei, 1991; Gardner & Smythe, 1975; Gardner & Tremblay, 1994a, 1994b; Schmidth, Boraie & Kassagby, 1996). Gardner and Lambert defined motivation as the learner's orientation toward the goal of learning either FL or L2. They view motivation in FL and L2 in social-psychological perspective, which according to them, it is the drive or desire of an individual to learning a language that is directed towards culture and linguistic integration. With this, the concept of integrative and instrumental motivation emerged.
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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 | 0.016 | 0.044 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".