Investigating Changes in Demotivation among Chinese EFL Learners from an Activity Theory Perspective
Bibliographic record
Abstract
This paper reports on a study that investigated the changes of demotivation to learn English over the four college years among Chinese English as a Foreign Language Learners (EFL) from the perspective of Activity Theory. Semi-structured interviews were conducted on fifteen college EFL learners in China. The interview data were analyzed by means of content analysis to explore the changes in the demotivation among the participants and the reasons why their demotivation changed. The results revealed that: 1) the interviewees experienced changes in their demotivation during the four college years, with a stronger demotivation in the first and fourth year; 2) the dynamic disposition of the respondents’ demotivation is related to such factors as subject (Interest and future career), object (English examinations), tools (textbooks) and community (peers and teachers). The findings are implicative for teachers and students to tackle demotivation in English class for students at technological universities in China and other similar EFL contexts beyond.
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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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| 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 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".