The Role of Motivational Teaching Strategies Used by English Language Teachers in Urdu Medium Secondary Schools in Pakistan
Bibliographic record
Abstract
A number of strategies are used by English language teachers to get the desired outcomes from the language learners. The strategies prove useful when implemented in accordance with the level of the students and the environment of the L2 classroom. The prime focus of the teachers is to keep the learners motivated in learning English language. This particular research is conducted with the objectives and reasons for which the English teachers in Urdu medium secondary schools and students make use of motivational teaching strategies in their L2 classroom and similarly to indicate the situations where these strategies would be more helpful and crucial. Interview questions were distributed among English teachers and the students of matriculation. They were asked to read the questions and spell comprehensive answers. A comparison is made between the results obtained by the answers of Urdu medium secondary schools’ teachers and students. The data were collected and interpreted qualitatively that reflected the views of teachers and students of Urdu medium schools about the use of motivational teaching practices in ELT classroom in relation to students’ proficiency of L2 learning.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".