Needs Analysis of Saudi EFL Female Students: A Case Study of Qassim University
Bibliographic record
Abstract
This research study analyzes the target needs of EFL female Saudi students to choose EFL as their specialization.The population of the research is the female students enrolled in Bachelors in English program, at the Department ofEnglish Language and Translation, Qassim University Saudi Arabia. Adapting the Hutchinson And Waters model ofNeeds Analysis, the study covers the Target needs( i.e. Necessities, Lacks and Wants) and the Learning needs. Itaims to suggest certain amendments in the curriculum on the basis of needs analysis. The sample for study consistedof 150 students, the data was collected through questionnaire and analyzed by using SPSS. Overall assessment of thedata shows that the learners show their weakness in oral skills i.e. Listening and Speaking as compared to literaryskills i.e. Reading and Writing. Students have shown their preference for the incorporation of practical activities andmedia based teaching material in their syllabus.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.006 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".