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Record W2547844401 · doi:10.5539/elt.v9n12p34

IPad Acceptance by English Learners in Saudi Arabia

2016· article· en· W2547844401 on OpenAlexvenueno aff
Barry Lawrence

Bibliographic record

VenueEnglish Language Teaching · 2016
Typearticle
Languageen
FieldDecision Sciences
TopicTechnology Adoption and User Behaviour
Canadian institutionsnot available
Fundersnot available
KeywordsUnified theory of acceptance and use of technologyPsychologyPerceptionSocial influenceVocational educationForeign languageMathematics educationEnglish as a foreign languageApplied psychologySocial psychologyPedagogy

Abstract

fetched live from OpenAlex

<p>This study used the Unified Theory of Acceptance and Use of Technology (UTAUT; Venkatesh, Morris, Davis, & Davis, 2003) model to investigate factors predicting the acceptance of iPad tablets by learners of English as a foreign language (EFL) at a technical vocational college in Saudi Arabia. An online survey was conducted on 199 male learners, and a simultaneous multiple regression analysis was conducted on the data. The results indicated that a belief in the device’s educational potential, a sense that it was straightforward to use, and the perception that the infrastructure would support usage were all significant predictors of the behavioral intention to use iPads. Social factors did not indicate an acceptance of the device. The findings highlighted areas of importance for educators intending to adopt mobile devices in second language instruction and partially supported the application of the UTAUT.</p>

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)0.020
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.429
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.020
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.030
GPT teacher head0.337
Teacher spread0.306 · 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.

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

Citations8
Published2016
Admission routes1
Has abstractyes

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