Learning from example : exploring immigrant language minority students’ perceptions of what it takes to "make it" as an ESL student
Bibliographic record
Abstract
Successful students who are immigrant language minority students (ILMS) and who were once identified as ESL learners tend to standout in the Greater Vancouver area since academic achievement tends to be the exception rather than the rule for these students. Only a small proportion appears to graduate from high school and/or pursue studies at a post-secondary level (Gunderson, 2000). If one believes that, in general, all children have what it takes to discover and learn about the world that surrounds them, and how to become an active participant in it, then one has to wonder why so many are failing. Moreover, one can ask what the few who are making it are actually doing that allows them to "beat the odds". This study attempted to explore this question through a series of qualitative iridepth interviews with fifteen 'ex-ESL students' from the Greater Vancouver area. The interviews focused on their perceptions of the factors having influenced their successful academic achievement and integration process as defined by their ability to enter a Canadian university. The importance of the special challenges that the education of ILMS presents for all involved is stressed, followed by a discussion of how these challenges were perceived, faced and overcome by the ILMS in this study. Special emphasis is put on the importance of sociocultural aspects such as the establishment of a strong sense of selfworth, strong relationships with family and friends, the preservation of home language(s) and culture(s) and prior school experiences as keys to social and academic achievement. This thesis also identifies interesting paradoxes in the way the informants perceived their educational experiences. Informants commented, for example, on the safe, yet segregating ESL classrooms and the importance of both individual and collective effort. In summarizing and discussing the comments and advice given by ILMS it is hoped that more people may gain a greater understanding of what ILMS have to face and what it takes to help make success the rule rather than the exception.
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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 | 0.004 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.018 | 0.010 |
| Scholarly communication | 0.007 | 0.002 |
| Open science | 0.003 | 0.006 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.003 | 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".