Promoting Language Learners’ Awareness of Autonomy Through Goal Setting—An Alternative Approach of Assessing Goal Setting Effects
Bibliographic record
Abstract
This article aims at proposing a new measurement to assess the effects of language learners’ goal-setting behavior, as an alternative to the traditional open-ended questionnaire. This goal-setting instrument was carefully developed through three phases. In the first phase, an item pool was generated. In the second phase, a pilot study was carried out with a view to modifying the weak points of the questionnaire. In the third phase, a final version of the questionnaire was distributed among participants for evaluating the practicality. The evaluation of the psychometric properties of the final instrument was made using confirmatory factor analyses (CFA), with the validity and reliability being evaluated. The results indicate that the proposed instrument yields satisfactory characteristics and that the theoretical model bears a good fit with the data. The researcher proposes that the instrument presented in this study can provide a more psychometrically sound measure of goal-setting in learning a second language than traditional open-ended questionnaires.
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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 | 0.006 | 0.025 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.001 | 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".