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Record W4298146470 · doi:10.5430/wjel.v12n8p86

Students’ Perceptions of Social Networking Sites for English Language Learning: A Study in an Indonesian Higher Education Context

2022· article· en· W4298146470 on OpenAlexvenueno aff
Anna Riana Suryanti Tambunan, Winda Setia Sari, Rasmitadila Rasmitadila

Bibliographic record

VenueWorld Journal of English Language · 2022
Typearticle
Languageen
FieldComputer Science
TopicMobile Learning in Education
Canadian institutionsnot available
FundersUniversitas Negeri Medan
KeywordsIndonesianComputer scienceContext (archaeology)PerceptionMobile deviceM-learningMultimediaMathematics educationSocial mediaWorld Wide WebPsychology

Abstract

fetched live from OpenAlex

This study explores the use of Social Networking Sites (SNS) as a performance-enhancing method of teaching and learning of English in the classroom via cell phones and mobile devices, as well as its effect on students' motivation to learn. A survey was disseminated to 176 students. The analysis showcases that Instagram is the most useful learning tool that students enjoy, and its use on mobile devices has the potential to become a significant teaching tool in the classroom. Because the most popular social networking sites, such as Instagram, are predominantly accessible via mobile devices, this is the case. Given that students currently utilize social networking sites to boost their learning informally, their acknowledgment of social networking sites as learning tools demonstrates their understanding of the learning potential given by technology.

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)0.000
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 score0.029
Threshold uncertainty score0.652

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.015
GPT teacher head0.315
Teacher spread0.300 · 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

Citations5
Published2022
Admission routes1
Has abstractyes

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