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Record W3030112912 · doi:10.5539/elt.v13n6p127

An Investigation on the Effectiveness of the English Literary Elements in Improving English Language at Undergraduate Level

2020· article· en· W3030112912 on OpenAlexvenueno aff
Arshad Ali, Syed Hyder Raza Shah, Shahid Hussain Mughal, Ghulam Muhiuddin Solangi, Muhammad Arif Soomro

Bibliographic record

VenueEnglish Language Teaching · 2020
Typearticle
Languageen
FieldArts and Humanities
TopicShakespeare, Adaptation, and Literary Criticism
Canadian institutionsnot available
Fundersnot available
KeywordsActive listeningPsychologyFluencyCompetence (human resources)Lingua francaEnglish studiesLanguage assessmentPedagogyAffect (linguistics)LinguisticsLanguage educationLinguistic competenceMathematics education

Abstract

fetched live from OpenAlex

The English has become a lingua-franca language, thus to promote the English language’s interest in the people with the teachings of English literature is regarded as the competence of the learners in the Target Language(TL).Thus,the study aims to investigate the effectiveness of English literary elements in improving English language at undergraduate level. The qualitative method was preferred for collecting the data in which 15 participants were involved, 5 of them were university lecturers and rest of them were the students of English Department Shaheed Benazir Bhutto University, Sanghar Campus. Semi-structured interviews were conducted from the participants and the data was analyzed by the thematic process. The findings of the research indicated that the English literary elements are helpful in the favor of improving English language. It was also declared that movies and dramas affect the English language more effectively. English literary elements affect the learners’ language competence in the different areas as; Listening and speaking. These elements help the learners to learn the language more effectively, and these elements play important role in improving the comprehensions of the learners. The study suggests that there should be integration of movies and dramas in the favor of students as they could get more fluency in English and the study also suggests that the material in the class should be used related to the learning area of the students.

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)0.002
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 score0.049
Threshold uncertainty score0.704

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
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 head0.027
GPT teacher head0.237
Teacher spread0.210 · 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

Citations2
Published2020
Admission routes1
Has abstractyes

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