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Record W2357002108 · doi:10.5430/jct.v5n1p87

Needs Analysis of Saudi EFL Female Students: A Case Study of Qassim University

2016· article· en· W2357002108 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueJournal of Curriculum and Teaching · 2016
Typearticle
Languageen
FieldArts and Humanities
TopicEFL/ESL Teaching and Learning
Canadian institutionsnot available
Fundersnot available
KeywordsSyllabusActive listeningNeeds analysisCurriculumPreferenceMathematics educationReading (process)PsychologyMedical educationPedagogyMedicineLinguisticsMathematics

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.756
Threshold uncertainty score0.287

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.022
GPT teacher head0.276
Teacher spread0.254 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it