Chinese EFL student perceptions of their learning through reflections on web-based learning
Bibliographic record
Abstract
English, as a foreign language, is a compulsory course for all students in their university study journey since the 1990s in China (MOE, 1994). The significant status of English was re-affirmed by the reform of English in higher education since 2007, which was further improved in 2016 by new guidelines by the Ministry of Education in China (MOE, 2007, 2016). English has become a tool for communication acquired by students to use in their daily life, for example when studying, living, and for social communication and future work (MOE, 2016), rather than being a foreign language used to merely read English articles to understand the Western world (in China, ‘Western world’ refers to developed countries, for example, the United Kingdom, the United States, or Canada, etc., which have a high-level development in economic, technology and living standards (Zhang, 2018)). Standardised uniform education will be gradually replaced by individualised education to satisfy each student’s needs in their daily life (Ma, 2017). The Internet, as a medium, brings a potentially revolutionary change in the way both learning and teaching take place inside and outside of class. Its use is suggested by the Ministry of Education to promote students’ English learning ability, particular in learning outside of the classroom (MOE, 2016). \n \nThis research explored 19 university students’ perceptions of EFL learning outside of class by accessing their ideas of and motivation for learning English, and investigating their English learning activities on websites out of class during the research conducted. It draws on a case study approach, based on the constructivist viewpoint, to analyse students’ English learning by themes. Results were obtained through a combination of weekly group meetings, individual interviews, and reflective written reports completed by students. Moreover, this study discusses the relationship between perceptions and practices, it reflects on the relationship between beliefs and the learning process (Ellis, 2008).
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".