Navigating Chinese international students’ inquiry learning in a multilingual and multicultural environment
Bibliographic record
Abstract
In the past few decades, inquiry learning, as a research-based learning approach, has been increasingly emphasised in developed Western countries. This study examined the inquiry learning experiences of 17 Chinese international students at their host universities in the USA, the UK, Australia, and Canada, along with their achievements and challenges. Through two rounds of one-on-one semi-structured interviews, this study found a close relationship between the emphasis on inquiry learning in host universities and neoliberal demands for students to acquire knowledge and diverse practical competences. Urged by the learning demands in the host universities, participants advanced in knowledge acquisition, acquired active, passionate, responsible, and inclusive learning attitudes, as well as English language competence, intercultural competence, and other practical competences through inquiry learning. They also faced additional workload and challenges regarding language difficulties and sociocultural factors mediated by home and host educational, social, and cultural contexts. This study advises international and domestic staff and students to engage in constant, candid dialogue, try to understand the specific learning challenges that international students face, and the support they desire. Collaborative efforts from all relevant stakeholders are necessary to create a diversified, caring, inclusive, and supportive inquiry learning environment conducive to mutual learning and thriving.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.003 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.005 |
| 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".