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Record W3039674378 · doi:10.5539/elt.v13n8p12

The Impact of Using Cambly on EFL University Students’ Speaking Proficiency

2020· article· en· W3039674378 on OpenAlexvenueno aff
Maram S. Alshammary

Bibliographic record

VenueEnglish Language Teaching · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicEducation and Technology Integration
Canadian institutionsnot available
Fundersnot available
KeywordsPsychologyLanguage proficiencyMultimethodologyIntercultural communicationCultural diversityAutonomyTest (biology)Qualitative researchSocial psychologyPedagogySocial science

Abstract

fetched live from OpenAlex

This study sought to investigate the impact of using Cambly, a computer-mediated communication tool, on the speaking proficiency of English as a foreign language (EFL) learners. Further, it aimed to explore the participants’ perceptions of using Cambly. The study employed an experimental design featuring a mixed-methods approach to data collection that involved pre- and post-testing of the participants’ speaking proficiency as well as semi-structured face-to-face interviews. The study sample consisted of 28 EFL university students who were divided into the control and experimental groups. The participants in the experimental group used Cambly to conduct audio calls with native speakers of English over a period of 4 weeks. The quantitative analysis of the participants’ speaking proficiency tests revealed no significant differences between the experimental and control groups’ post-test scores. Moreover, no significant differences were found between the experimental group’s pre- and post-test scores. The qualitative analysis of the participants’ interviews revealed that the use of Cambly had a positive influence on their speaking proficiency, motivation, anxiety level, speaking opportunities, autonomy, social relationships, and cultural awareness.

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)0.002
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 score0.089
Threshold uncertainty score0.650

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
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 head0.026
GPT teacher head0.363
Teacher spread0.337 · 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

Citations4
Published2020
Admission routes1
Has abstractyes

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