Students’ Self and Group-Driven Motivation on Target-Oriented Activity in Grammar Learning
Bibliographic record
Abstract
The article investigated students’ self and group-driven motivation in learning Grammar & Structure 03 on target oriented activity. It aimed at exploring what factors influence the participants and their higher motivation between self and group-driven motivation are, and how their motivation progress is toward the target-oriented activity. This article applied three phases of motivation theory (Dornyei and Otto, 1998) and language learning strategies (Dornyei, 2005). The results show that self-motivation is more dominant than group-driven motivation. Several factors influenced the motivational components which inhibit and enhance motivation on task. Considering the learning strategies, the participants tend to be more effective by subjective values and norms, however, emphasizing the task, they can manage both motivation types to be interdependence. Moreover, the participants’ motivation stages show that group-driven motivation progress is capable of enhancing motivation. Whereas, the downward scale of self-motivation as the result of the motivational disposition failed in generating enactment.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| 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".