Functions of L1 Use in the L2 Classes: Jordanian EFL Teachers’ Perspectives
Bibliographic record
Abstract
This qualitative study investigated teachers’ perspectives on the functions of first language (L1) use in the second language (L2) classroom. Data were collected from seven Jordanian English as foreign language (EFL) teachers, where each teacher participated in one classroom observation and two rounds of interviews, one pre-observation and one post-observation. Interviews were transcribed and coded for recurrent themes. Thematic analysis identified six functions of L1 use that teachers used to enhance teaching and learning: translating, explaining metalinguistic information, overcoming teaching challenges, giving instructions, improving motivation, and avoiding words in the L2 that sound taboo in the L1. This research contributes to a more complex picture of L2 teaching in Jordan and potentially other similar EFL settings. The findings could also guide L2 academics, policymakers, and practitioners in better understanding the role of the L1 in the L2 classroom, particularly in foreign language (FL) contexts.
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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 | 0.006 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.009 | 0.006 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| 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".