From EFL Teachers’ Perspective: Impact of EFL Learners’ Demotivation on Interactive Learning Situations at EFL Classroom Contexts
Bibliographic record
Abstract
For some reason, EFL students lose their motivation and interests and become more demotivated as time goes by. Many of the conducted studies focus on the factors that cause EFL learners’ demotivation rather than how EFL learners’ demotivation impact on classroom learning processes. Thus, the study will focus on the impact of EFL learners’ demotivation on the procedures and processes employed for EFL classroom interaction. The data are collected and statistically analyzed. The findings revealed the processes and the procedures that adopted for developing classroom interaction are negatively affected by the low quality of the participation that EFL demotivators do. These results negatively reflected EFL classroom interaction processes, EFL teachers’ performance, and EFL classroom group dynamics. In the light of these results, it recommended that the interactive classroom activities should be carefully designed and appropriately adapted to stimulate EFL demotivators’ interests. For example, the characteristics of these interactive classroom activities are in their content that reflects EFL learners’ cultural backgrounds and connects them to their every day actions.
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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 | 0.005 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.004 | 0.006 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".