Exploration EAL Learner Identity: Understanding Language-Related Challenges of Chinese International Students at University of Saskatchewan
Bibliographic record
Abstract
The purpose of this research was to explore the relationship between English language learning and identity of language learners. Most of the research related to language and identity began with Bonny Norton (Norton Peirce, 1995; Norton, 1997; Norton, 2000). Norton (1995) noted a comprehensive understanding of social identity with integration of the language learners and the language learning context. This research investigated how six Chinese international students at the University of Saskatchewan (U of S) constructed their own identities as EAL (English as additional language) learners using critical discourse analysis (CDA) of their ideological and linguistic choices through interviews and written responses concerning their challenges and frustrations of language learning and using in Canada. The study show that the construction of Chinese international students’ EAL learner identity are influenced both by their prior English learning experiences in China and the practical experiences of learning and using English in Canada. It also shows that despite full of challenges and struggles, Chinese international students are striving to build positive EAL learner identity instead of being marginalized.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.015 | 0.005 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.001 | 0.002 |
| 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".