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Record W2291111687 · doi:10.5539/ies.v9n2p89

The Relationship between Socio-Economic Status, General Language Learning Outcome, and Beliefs about Language Learning

2016· article· en· W2291111687 on OpenAlexvenueno aff
Mohsen Ghasemi Ariani, Narjes Ghafournia

Bibliographic record

VenueInternational Education Studies · 2016
Typearticle
Languageen
FieldSocial Sciences
TopicMultilingual Education and Policy
Canadian institutionsnot available
Fundersnot available
KeywordsSocioeconomic statusPsychologyLanguage assessmentTest of English as a Foreign LanguageLanguage proficiencyLanguage acquisitionSecond-language attritionMathematics educationComprehension approachLanguage learning strategiesLanguage educationTest (biology)Descriptive statisticsMetacognitionMedicinePopulationCognition

Abstract

fetched live from OpenAlex

<p class="apa">The objective of this study is to explore the probable relationship between Iranian students’ socioeconomic status, general language learning outcome, and their beliefs about language learning. To this end, 350 postgraduate students, doing English for specific courses at Islamic Azad University of Neyshabur participated in this study. They were grouped in terms of their socioeconomic status. They answered a questionnaire in which they indicated their beliefs about language learning in different contexts of language use. Besides, a general language test of proficiency (a Practice test of a TOEFL Test) was administered to all the participants to homogenize them in terms of general language proficiency or general language learning outcome. The quantitative data were subjected to a set of parametric statistical analyses, including descriptive statistics and factor analysis. The findings manifested a positive relationship between the students’ economic status and general language learning outcome. Besides, the findings manifested a significant relationship between the participants’ language learning outcome and their beliefs about language learning. The findings suggest if language instructors are equipped with the necessary information to assist language learners in coping with their negative beliefs, the process of language learning is not only accelerated, but also probable measurement errors may decrease.</p>

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)0.008
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.352
Threshold uncertainty score0.987

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.131
GPT teacher head0.532
Teacher spread0.402 · 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 designObservational
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

Citations20
Published2016
Admission routes1
Has abstractyes

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