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Record W2578503053 · doi:10.5539/ijel.v7n2p134

MPhil Scholars’ Views about the Use of Humor in English Language Classroom in Quetta, Balochistan, Pakistan

2017· article· en· W2578503053 on OpenAlexvenueno aff
Rabbia Nayyar, Muhammad Zeeshan

Bibliographic record

VenueInternational Journal of English Linguistics · 2017
Typearticle
Languageen
FieldPsychology
TopicHumor Studies and Applications
Canadian institutionsnot available
Fundersnot available
KeywordsNonprobability samplingEnglish languagePsychologyData collectionQualitative researchMathematics educationSample (material)PedagogySociologySocial scienceChemistryPopulation

Abstract

fetched live from OpenAlex

The element of humor is one of the important elements in a person’s social life and when used in the English language classroom by teachers, it could affect the students’ learning. This study investigated MPhil scholars’ views being student and teacher regarding the use of humor in English language classroom. The research was qualitative using purposive sampling. The sample consisted of eight female MPhil scholars of English department of two universities in Quetta, Balochistan, Pakistan. Interviews and observations were the instruments used for data collection. The data were analyzed through content analysis and for this purpose NVivo (Version 10) was used. The participants’ views and teaching practices suggested humor to be beneficial in the English language classrooms to motivate students. The results of this study recommend using humor in English language classroom as it may make teaching more effective. The future research directions are also suggested.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.065
Threshold uncertainty score0.130

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0110.007
Scholarly communication0.0040.001
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.063
GPT teacher head0.397
Teacher spread0.333 · 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 source (direct Gemma or distilled Codex), 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

Citations4
Published2017
Admission routes1
Has abstractyes

Explore more

Same venueInternational Journal of English LinguisticsSame topicHumor Studies and ApplicationsFrench-language works237,207