Learner Agency in China’s Program for Interdisciplinary English Talents: A Sociocultural Perspective
Bibliographic record
Abstract
Aiming to develop a sociocultural understanding of learner agency as defined by Ahearn (2001), this study asks the questions: How do English majors under the Program for Interdisciplinary English Talents in Chinese universities with international or regional orientations experience their English learning and exert learner agency differently? Which factors influence learners’ agentive activities and what differences exist in the influencing strength of those factors? Interview data were collected from 14 student participants from two representative universities in the eastern part of China. Analyzing the data using the framework proposed by Dang and Marginson (2013) revealed that learners’ agentive activities are mediated by the sociocultural context, in which the global, national and local factors exert great influences and their influencing strength varies. Among all the factors, the influence of the microgenetic domain, to be specific, the institutional context is the greatest. Implications and suggestions are provided based on the results.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.043 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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 teacher head, 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".