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Record W4315641089 · doi:10.5430/wjel.v13n1p346

Using Mobile Phone Based Tasks to Improve Jordanian Grade 7 EFL Students’ Composition Writing Skills

2023· article· en· W4315641089 on OpenAlexvenueno aff
Nofah Sameh Almawadeh

Bibliographic record

VenueWorld Journal of English Language · 2023
Typearticle
Languageen
FieldComputer Science
TopicMobile Learning in Education
Canadian institutionsnot available
Fundersnot available
KeywordsMobile phoneComposition (language)Test (biology)Computer scienceMathematics educationPhoneStatistical significanceStatistical analysisPsychologyStatisticsMathematicsLinguistics

Abstract

fetched live from OpenAlex

This study investigated the effectiveness of using mobile phone based tasks to improve the FL composition writing skills of 52 Jordanian grade 7 students. They were divided into two groups; control and experimental groups. The control group included 24 students, while the experimental group included 28 students. Data were collected through a pre-test and a post-test of FL composition writing. The mixed method of quantitative and qualitative analysis was used. Data were analyzed using the Paired-Samples T-Test. In addition, the use of the independent samples T-Test aimed to determine the statistical significance of the two tested groups’ performance in FL composition writing. The findings affirmed the effectiveness of using mobile phones in improving the FL composition writing skills of Jordanian grade 7 students.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.170
Threshold uncertainty score0.670

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.011
GPT teacher head0.306
Teacher spread0.295 · 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 designBench or experimental
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
Published2023
Admission routes1
Has abstractyes

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