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Record W2774050514 · doi:10.5539/elt.v11n1p46

On Reading Comprehension Teaching for English Majors under Relevance Theory

2017· article· en· W2774050514 on OpenAlexvenueno aff
Ping He

Bibliographic record

VenueEnglish Language Teaching · 2017
Typearticle
Languageen
FieldPsychology
TopicLanguage, Metaphor, and Cognition
Canadian institutionsnot available
Fundersnot available
KeywordsRelevance theoryRelevance (law)Reading (process)Reading comprehensionInferencePsychologyCognitionContext (archaeology)ComprehensionCognitive psychologyOstensive definitionFocus (optics)LinguisticsCognitive scienceComputer scienceArtificial intelligence

Abstract

fetched live from OpenAlex

Relevance Theory from the perspective of cognitive psychology argues that human communication is an ostensive-inferential process, and emphasizes the function of the optimal relevance for communication. In this sense, reading comprehension could be considered as a kind of communication in which the writer manifests his/her communication intention and the reader infers from the discourse codes; thereinto, the optimal relevance between the textual information and the reader’s cognition is essential to the optimal contextual effects. This paper sets out to discuss the explanatory power of relevance theory to reading comprehension, with focus on differences among readers with different reading abilities in grasping the optimal relevance with the discourse and the cognitive context. Through the reading teaching experiment undertaken for a semester, the result shows that the application of relevance theory to reading by pinpointing reading purpose, setting reading tasks and constructing cognitive contexts benefits greatly to students’ inference capability, hence their reading ability, which is also instructive for the teaching mode of reading courses.

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)0.003
metaresearch head score (Gemma)0.008
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.459
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.001
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 head0.019
GPT teacher head0.319
Teacher spread0.300 · 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

Citations4
Published2017
Admission routes1
Has abstractyes

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