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Record W2594659362 · doi:10.5539/elt.v10n4p35

An Analysis of Learners’ Motivation and Attitudes toward Learning English Language at Tertiary Level in Turkish EFL Context

2017· article· en· W2594659362 on OpenAlexvenueno aff
Zübeyde Sinem Genç, Fulya Aydin

Bibliographic record

VenueEnglish Language Teaching · 2017
Typearticle
Languageen
FieldArts and Humanities
TopicEFL/ESL Teaching and Learning
Canadian institutionsnot available
Fundersnot available
KeywordsTurkishPsychologyContext (archaeology)GeneralizationMathematics educationEnglish as a foreign languageLanguage acquisitionForeign languageAcademic achievementSocial psychologyLinguistics

Abstract

fetched live from OpenAlex

The purpose of this study is to investigate Turkish students’ (n=462) motivation and attitudes toward learning English as a foreign language at a state university in Turkey and the relation between their attitudes, motivation and the variables such as gender, parental involvement, their fields of study at university, and academic achievement. It was important to explore and comprehensively look at the issue through a range of variables because the findings of the previous studies have revealed inconsistent attitudinal profiles toward learning English language. The study adopted quantitative research paradigm and used a questionnaire for data collection. The results indicated that the participants’ instrumental and intrinsic motivation were at moderate level while the mean of parental involvement was at a high level. It was also shown that the learners’ attitude changed according to their gender, fields of study and academic achievement. Alternative solutions at individual and institutional levels have been proposed in order to develop motivation and more favourable attitudes toward learning English language, and to prevent the generalization of stereotypes, which may have great impact on the success of learning English language at tertiary level.

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)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.108
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0010.001
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 head0.035
GPT teacher head0.288
Teacher spread0.253 · 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

Citations43
Published2017
Admission routes1
Has abstractyes

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