Personal and Academic Aspects that Contributed to the Development of the English Language Competence of Students from a Language Teacher Education Program
Bibliographic record
Abstract
Students from the English as a Foreign Language (EFL) Program targeted in the present study are expected to achieve a C1 level of English proficiency according to the Common European Framework (CEF). However, only a five per cent of the students has evidenced this level on the institutional English exam (Ileusco Test, henceforth IT) for the past five years. Through the present descriptive-exploratory qualitative study we have attempted to inquire about the personal and academic factors that may have contributed to the successful development of the L2 competence of those learners.We used a questionnaire, individual interviews and focus-group interviews to ask 12 students about learning strategies, experiences and actions they have implemented to develop their l2 competence. We concluded that it is mainly students’ commitment and self-discipline that helped them keep their L2 learning process successfully running; that despite the high quality of a school curriculum, a language program or a teaching methodology, it is students’ autonomous learning initiatives that mainly enhance their L2 proficiency; and that L2 instruction in higher education seems to convey a stronger impact than elementary and secondary education.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".