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Record W2273154336 · doi:10.5539/elt.v9n3p74

Investigating the Application of Needs Analysis on EAP Business Administration Materials

2016· article· en· W2273154336 on OpenAlexvenueno aff
Saifalislam Abdalla Hajahmed Mohammed

Bibliographic record

VenueEnglish Language Teaching · 2016
Typearticle
Languageen
FieldArts and Humanities
TopicEFL/ESL Teaching and Learning
Canadian institutionsnot available
Fundersnot available
KeywordsNeeds analysisSyllabusEnglish for academic purposesContent analysisPsychologyMedical educationEnglish for specific purposesProcess (computing)Needs assessmentDescriptive statisticsSpecial needsAdministration (probate law)PedagogyMathematics educationSociologyComputer scienceMedicinePolitical science

Abstract

fetched live from OpenAlex

<p>This study is conducted to investigate the application of needs analysis in developing EAP materials for business administration students in two Sudanese universities. The subjects are 2 head departments of English language. To collect data, the researcher uses interview and content analysis. The study adopts the descriptive approach. The data of the study is analyzed qualitatively. The findings show that most of the business administration EAP materials in Sudanese universities are not based on needs analysis and are not relevant to the students' learning and target situation needs. The drawbacks in EAP materials, in Sudanese universities, are due to the absence of needs analysis practice in the process of syllabi design. Therefore, the researcher recommends the application of needs analysis in the process of course design to assure designing courses that are relevant to the students' actual needs. The EAP courses which are taught in Sudanese universities should be tailored to the students' specific needs.</p>

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.

How this classification was reachedexpand

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.236
Threshold uncertainty score0.305

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.015
GPT teacher head0.255
Teacher spread0.239 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
Domainnot available
GenreEmpirical

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".

Quick stats

Citations15
Published2016
Admission routes1
Has abstractyes

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