Past Expectations, Current Experiences, and Imagined Futures: Narrative Accounts of Chinese International Students in Canada
Bibliographic record
Abstract
The internationalization of higher education has led to the influx of Chinese international students in Canada. The literature on these students usually addresses the factors that drive them to Canada, their learning experiences, and the impact of the stereotypical constructions of “Chinese learners” on their language learning. But the literature does not connect the current learning experiences of these students to their past back in China and the futures in their imagination. This narrative study investigates the English learning and IELTS test-taking experiences of ten Chinese international students before and after they came to Canada to find out how their past and present experiences and imagined futures are interconnected in shaping their identities. In analyzing the storied, shared, and envisioned experiences of ten participants, I found that they came to Canada to escape Gaokao and learn English for a better future. While in Canada, they experienced tensions between learning in an English language Pathway Program and in university disciplinary classrooms, between learning in homestay and church settings, and navigating their identities of being Chinese, being Chinese international students, and being transnational. IELTS related stories showed that they observed discrepancies between the test-tackling strategies and their university learning, misconstrued IELTS preparation as English learning, and challenged the power of IELTS in shaping their English learning experiences and themselves as English learners. Drawing on Bourdieusian perspectives, sociocultural theorizing, Darvin and Norton’s (2015) investment model, and Chinese Ti-Yong logic guiding language learning, my analysis suggests that the current learning experiences of these students should be considered holistically with their past and future taken into account. The data reflects how the gate-keeping IELTS test has affected their perceptions about learning English, emotions, and identities as test-takers. The study brings implications to the systematic contradictions in the education system in China dominated by Gaokao as a compulsory exam for university admission, and the need for universities in Canada to view international students holistically as individuals with histories, and as complex subjects with flexible and multiple identities. Institution- and discipline-specific measures of supporting international students and faculty members working with them are suggested.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.029 | 0.018 |
| Scholarly communication | 0.010 | 0.005 |
| Open science | 0.003 | 0.008 |
| Research integrity | 0.002 | 0.007 |
| Insufficient payload (model declined to judge) | 0.004 | 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".