Are Chinese Students Really Quiet, Passive and Surface Learners? – A Cultural Studies Perspective
Bibliographic record
Abstract
Research has indicated that Chinese students experience considerable challenges in their academic studies at North American universities. This paper explores Chinese students’ academic learning through cultural studies perspectives by examining the concept of identity; cultural and linguistic context; Chinese students as quiet and passive learners; different classroom teaching methods experienced in both cultures; surface learners vs. deep learners; different culture worlds; and the concept of social communicative competence. It is argued that quiet, passive and surface learners are perhaps incorrect descriptors of Chinese students who are studying at North American Universities. Important educational implications are discussed. Plusieurs recherches montrent que les étudiants chinois doivent relever des défis considérables quand ils étudient dans des universités nord américaines. Le but de cet article est d’explorer l’apprentissage académique des étudiants chinois à partir d’une vision d’études culturelles. Ceci nous mènera à examiner le concept d’identité, de contexte culturel et linguistique, ainsi que des notions telles que le calme et la passivité des étudiants chinois, les différences entre méthodologies d’enseignement dans les deux cultures, les apprenants superficiels en opposition avec les apprenants réfléchis, les différences culturelles, et enfin, le concept de compétence communicative sociale. description des étudiants chinois comme étant des apprenants calmes, passifs et superficiels sont des descripteurs qui peuvent s’avérer incorrects si l’on prend en compte toutes les implications culturelles qui seront discutées dans cet article.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.005 | 0.008 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".