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Record W4223625160 · doi:10.5539/elt.v15n5p32

Insights from a Survey into Chinese University Graduates’ Perceptions Toward University-Level English Courses

2022· article· en· W4223625160 on OpenAlexvenueno aff
Liwei Wei, Chuan-Chi Chang

Bibliographic record

VenueEnglish Language Teaching · 2022
Typearticle
Languageen
FieldArts and Humanities
TopicSecond Language Learning and Teaching
Canadian institutionsnot available
Fundersnot available
KeywordsActive listeningCurriculumPsychologyChinaMedical educationNeeds analysisPublic universityPremisePerceptionPedagogyEnglish for specific purposesMathematics educationPolitical scienceMedicineLinguistics

Abstract

fetched live from OpenAlex

Needs analysis guides course and curriculum design. In addition to mandatory courses, it is necessary for intensive language schools and institutes. Recent university graduates in China are increasingly enrolling in language training at public and private language schools to hone their communication abilities. On the other hand, English courses as the workplace prerequisites for Chinese university graduates have been scientifically researched and found to be exceedingly rare. The research's fundamental premise serves that there is a substantial link between the demands of Chinese recent graduates and university English course design. The aim of this research is to assess the goals, needs, and perceived utility of university English courses among recent on-the-job Chinese graduates over an eight-month period. After evaluating the questionnaire and interview replies, it was concluded that these Chinese young graduates in China had similar learning demands, with listening and speaking skills taking primacy. Additionally, various characteristics were discovered that show why an English course designed for future workplace purposes is advantageous to university students. The results are examined in terms of their pedagogical importance for curriculum creation and classroom practice in English courses at the university.  

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 categoriesMeta-epidemiology (narrow), Science and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.113
Threshold uncertainty score1.000

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 studies0.0030.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0050.000

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 head0.225
Teacher spread0.203 · 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.

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

Citations1
Published2022
Admission routes1
Has abstractyes

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