English Development Sustainability for English as Second Language College Transfer Students: A Case Study from a University in Hong Kong
Bibliographic record
Abstract
The sustainability of English development plays a crucial role in higher education. However, the language needs of community college transfer students have not been well studied. This paper examined the language needs and support measures for vertical transfer (VT) English as a Second Language (ESL) students after admission to the university. A qualitative approach was adopted. Thirty-nine focus groups and seven individual interviews were conducted with 124 VT ESL students. The results found that, while community college studies might have prepared VT students for basic written assignments in universities, these students needed support with advanced academic writing skills, and general speaking and listening skills. It is only if the needs and challenges of VT ESL students are clear to higher education administrators that effective strategies can be developed. For instance, the participants were not content with the current measures provided to them and required short, fun, and purpose-driven interventions. This is the first of its kind to explore the English needs and support measures among VT ESL to sustain their English development should be strengthened.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.002 |
| Scholarly communication | 0.003 | 0.001 |
| 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".