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Record W2572751428 · doi:10.5539/ijel.v7n2p117

Exploring the Motivational Strategies Practiced by Pakistani EFL Teachers to Motivate Students in Learning English Language

2017· article· en· W2572751428 on OpenAlexvenueno aff
Sehrish Khan Kakar, Zahid Hussain Pathan

Bibliographic record

VenueInternational Journal of English Linguistics · 2017
Typearticle
Languageen
FieldArts and Humanities
TopicEFL/ESL Teaching and Learning
Canadian institutionsnot available
Fundersnot available
KeywordsPsychologyEnglish languageContext (archaeology)Mathematics educationSignificant differenceAutonomyMotivation to learnEnglish as a foreign languagePedagogy

Abstract

fetched live from OpenAlex

The purpose of this study was to investigate motivational strategies which EFL teachers employ to motivate students in learning English language and to determine the significant difference if any across male and female teachers in practicing motivational strategies in an EFL classroom. A quantitative research design was employed. An adopted questionnaire by Cheng & Dornyei (2007) comprising of 48 close-ended items ranging from “Hardly ever” to “very often” was administered among 96 male and female EFL teachers who were teaching in government secondary schools in Quetta, Balochistan, Pakistan. To answer the two research questions of the study, both descriptive and inferential statistics were performed in SPSS (version, 21). The findings of the first research questions revealed that to promote learners’ autonomy emerged as the most influential source of motivational strategy practiced by EFL teachers followed by Familiarization learners with L2-related values as the second most practiced motivational strategy. The findings of second research question revealed no statistical significant difference between male and female EFL teachers in terms of practicing motivational strategies. The findings of the present study have implications on effective English language teaching and enhancing teachers’ experience and knowledge in order to motivate EFL learners by using different motivational strategies in learning English in context of Pakistan.

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)0.120
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Scholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.701
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.120
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0020.001
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 head0.057
GPT teacher head0.340
Teacher spread0.283 · 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

Citations23
Published2017
Admission routes1
Has abstractyes

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