Motivating Students in the EFL Classroom: A Case Study of Perspectives
Bibliographic record
Abstract
Motivating EFL students to develop in the target language is quite complex. In many cases, these students face difficulties in learning English and are often demotivated to learn. Research in classroom motivation has found that certain strategies can help these students adopt more positive attitudes and become more motivated in the learning process. This exploratory study investigates the perceptions through interviewing students and surveying teachers’ views in an EFL Program of the problems that hinder these students’ learning in the English classes related to motivation. Findings show that learners are not motivated to learn English because of an over-focus on writing skills with very little new learning experiences, uninteresting materials, and unclear links between language courses and their majors or future careers. Results also indicate that teachers complain of unmotivated students and pre-structured syllabi leaving little room for communicative methods. Implications are made for the classroom
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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 | 0.007 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.020 | 0.006 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.003 | 0.007 |
| Research integrity | 0.005 | 0.007 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".