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Record W2170902342 · doi:10.11648/j.ijalt.20150104.12

Investigating Language Learning Context Influence: An Approach to Iranian EFL Students’ Critical Thinking Ability

2015· article· en· W2170902342 on OpenAlexvenueno aff
Saeid Malek Mohammadi

Bibliographic record

VenueJournal of academic and applied studies · 2015
Typearticle
Languageen
FieldSocial Sciences
TopicEducation and Critical Thinking Development
Canadian institutionsnot available
Fundersnot available
KeywordsContext (archaeology)Critical thinkingMathematics educationPsychologyAffect (linguistics)Session (web analytics)Language learning strategiesLanguage acquisitionControl (management)PedagogyComputer scienceCognitionMetacognitionArtificial intelligenceWorld Wide WebCommunication

Abstract

fetched live from OpenAlex

Investigating to which extent language learning context affect Iranian EFL students’ critical thinking, this study was conducted to clarify the relationship between the variables. To achieve this purpose 90 EFL students in upper intermediate level of Payamnoor University selected, and equally divided to two groups of 45 person, the experimental group (n=45) with modern context of language learning by a web 2.0 environment on the internet and control group (n=45) with traditional context of language learning in regular classes. Sandra Lee M.C. Kay’s Researching Second Language Classroom book, published in 2008, was given to the both groups during 10 session of 120 minutes of study as a material. Pretest/posttest assessments and statistical package of social science (SPSS) t-test analyzed procedures clarified that experimental group’s language learner have a stronger critical thinking ability than control group ones. Confirming positive relation between language learning context and critical thinking ability of EFL learners, the results also show a strong willing of students to use modern, technological, more accessible, and new ways of learning.

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)0.004
metaresearch head score (Gemma)0.005
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 score0.060
Threshold uncertainty score0.622

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
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 head0.096
GPT teacher head0.435
Teacher spread0.339 · 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

Citations0
Published2015
Admission routes1
Has abstractyes

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