Exploring Motivational Strategies Practiced by Saudi High School Female EFL Teachers
Bibliographic record
Abstract
This study looked into Saudi female English as a Foreign Language (EFL) teachers’ perception of their motivational practices in the actual classroom in public and private schools. Forty (n=40) EFL teachers filled out a questionnaire consisting of forty-four motivational strategies that were based on a five-point Likert scale ranging from "very important" to "not important." Descriptive statistics have been used to determine the most and the least important teaching strategies viewed by EFL teachers in private and public schools. To determine if there was any difference between private and public schools’ teachers on how they viewed each strategy in terms of importance, inferential statistics, t-test has been implemented. The study revealed that participants in both educational contexts indicate that “teachers’ proper behavior” is the most significant motivational strategy while “having an encouraging environment” in the EFL classroom was ranked the least important strategy. The findings show that there existed a striking similarity between the two sets of teachers in regard to their perceptions of the importance of motivational strategies. The study suggests that English-as-a-Second-Language book planners should keep textbook materials in harmony with motivational strategies practiced by EFL teachers.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".