Motivation and the Support of Significant Others across Language Learning Contexts
Bibliographic record
Abstract
According to Self-Determination Theory, intrinsic and self-determined extrinsic motivation are maintained to the extent that learners feel that engagement in an activity is a personally meaningful choice, that the task can be performed competently, and that they share a social bond with significant others in the learning context. These perceptions are enhanced when significant others act or communicate in a way that encourages learner autonomy, provides informative feedback on how to improve task competency, and establishes a sense of connection with the learner. The present study used a focused essay technique to examine how the learning context impacts learners’ motivation and the kinds of support (or lack thereof) received from different people. Heritage (n = 34), modern (n = 34), and English-as-asecond-language (ESL; n = 36) learners described their reasons for language learning, and reported how teachers, family members, peers, and members of the language community encouraged or discouraged their engagement in language learning. The results indicated that heritage students are more included to learn the language because it is integral to their sense of self than the two other groups, whereas ESL students are generally more regulated by external contingencies. Although there were some commonalities, different people supported learners’ motivation in different ways depending upon the learning context. The results point to the importance of the language learning context for understanding students’ motivation and how others can support them.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.004 |
| 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".