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Record W2804571174 · doi:10.5539/ells.v8n2p85

An Empirical Research on Application of Cohesion Theory in College Listening EFL Teaching

2018· article· en· W2804571174 on OpenAlexvenueno aff
Chunxia Fu

Bibliographic record

VenueEnglish Language and Literature Studies · 2018
Typearticle
Languageen
FieldNeuroscience
TopicCognitive Science and Education Research
Canadian institutionsnot available
Fundersnot available
KeywordsCohesion (chemistry)College EnglishMathematics educationActive listeningListening comprehensionEmpirical researchSignificant differenceReading comprehensionPsychologyTest (biology)Class (philosophy)The artsReading (process)Computer scienceLinguisticsMedicineMathematicsArtificial intelligence

Abstract

fetched live from OpenAlex

Cohesion Theory of Halliday and Hasan has been widely applied in different subjects of College EFL teaching, particularly in reading comprehension, writing and translation practice. It can also be a practical theory for College Listening EFL Teaching. Based on that theory, an empirical research is carried out among the freshmen from two classes in Yangtze University College of Arts and Sciences, and it lasts for 16 weeks. One of the classes is Control Group (CG) and the other is Experimental Group (EG). Both groups have the same amount of exercises from the same teaching materials but with different guidance in class: the subjects in CG are taught in traditional ways while those in EG are trained with the guidance of Cohesion Theory. After the experimental teaching period, the data collected from students’ pre-test and post-test scores is analyzed by the SPSS software program. The pre-test results show that there is no statistically significant difference between the scores of EG and CG before the experiment (P= 0.932>0.05). While the post-test results demonstrate that there is a considerable improvement on the scores of the subjects in EG than that of CG (P=0.009 < 0.05).

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)0.002
metaresearch head score (Gemma)0.006
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 score0.060
Threshold uncertainty score0.660

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.075
GPT teacher head0.484
Teacher spread0.408 · 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

Citations0
Published2018
Admission routes1
Has abstractyes

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