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Record W4386520416 · doi:10.19173/irrodl.v24i3.7185

Effects of Using the WhatsApp Application on Iranian Intermediate EFL Learners’ Vocabulary Learning and Autonomy

2023· article· en· W4386520416 on OpenAlexvenueno aff
Kamran Janfeshan, Asmaa Nader Sharhan, Mohamad Mahdi Janfeshan

Bibliographic record

VenueThe International Review of Research in Open and Distributed Learning · 2023
Typearticle
Languageen
FieldComputer Science
TopicMobile Learning in Education
Canadian institutionsnot available
Fundersnot available
KeywordsVocabularyBlended learningPsychologyMathematics educationControl (management)Vocabulary learningSignificant differenceAutonomyTest (biology)Language acquisitionAnalysis of covarianceLearner autonomyVocabulary developmentTeaching methodEducational technologyPedagogyComputer scienceLanguage educationLinguisticsMathematicsComprehension approachArtificial intelligence

Abstract

fetched live from OpenAlex

The current study was planned to find out if the use of blended learning as a combination of face-to-face instruction and mobile-assisted language learning using WhatsApp contributed to the vocabulary learning and autonomy of Iranian EFL learners compared to the traditional method. To assess their English skills, PET was given to 80 homogenous intermediate learners at the beginning of the study. The study's intended participants were fifty EFL learners with scores that were within the intermediate competency level. Then, the participants were divided randomly to experimental and control groups to see how successful blended learning vs traditional education is at improving learners' vocabulary knowledge. One-way between-groups analysis of covariance was run. On post-test scores, the findings indicated a statistically significant difference between the experimental and control groups. Another one-way between-groups analysis of covariance was performed to assess the impact of two distinct blended learning vs traditional teaching treatments on EFL learners' autonomy. In post-test results, a significant difference between the control and experimental groups' performance was observed. This study provided insights into how technology may be applied to teach language components and skills.

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)0.006
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.798
Threshold uncertainty score0.363

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.001
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 head0.046
GPT teacher head0.409
Teacher spread0.363 · 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 designOther design
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

Citations2
Published2023
Admission routes1
Has abstractyes

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