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Record W4402724801 · doi:10.5539/elt.v17n10p36

Digital Literacy in Saudi Tertiary EFL Context: Perspectives of Students and Potentials for Listening Skills

2024· article· en· W4402724801 on OpenAlexvenueno aff
Rand K. Alduwayghiri, Saad Aljebreen

Bibliographic record

VenueEnglish Language Teaching · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicTechnology-Enhanced Education Studies
Canadian institutionsnot available
Fundersnot available
KeywordsPsychologyActive listeningContext (archaeology)LiteracyMathematics educationPedagogyTertiary levelCommunication

Abstract

fetched live from OpenAlex

Technology is regarded as a vital aspect in modern society, revolutionising various fields. Consequently, evolutionary knowledge and skills raise in this paradigm, referred to as digital literacy. The necessity to reveal the influence in EFL, English as a foreign language, context is fundamental. The exploration seeks to examine digital literacy perspectives of 117 Saudi undergraduate EFL learners enrolled in English Language and Translation bachelor’s programme at a Saudi university. It also scrutinises the prospects for improving English listening skills. To achieve the exploration objectives, mixed-method approach is integrated via adopted questionnaires from scholarly work (Mudra, 2020; Najmi & Navaee Lavasani, 2021; Ng; 2012a; Ng; 2012b; Yukselir & Yuvayapan, 2019) with minor adjustments. Findings demonstrate EFL learners’ confidence to their digital literacy skills. They reveal high confidence to solving technical difficulties; conversely, the least positive positioning denotes towards literacy to web relevant activities. Findings advocate for the benefits of listening skills, especially for pronunciation and vocabulary improvement, authentic materials for learning, language learning motivation, and access to entertaining educational materials. The exploration serves endeavour to subsequent academic and pedagogical implementations.

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)0.003
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 score0.134
Threshold uncertainty score0.407

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.007
GPT teacher head0.355
Teacher spread0.348 · 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
Published2024
Admission routes1
Has abstractyes

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