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Record W4416302641 · doi:10.5539/ijel.v15n6p57

The Impact of the Duolingo App on Improving Listening Comprehension Skills in EFL High School Saudi Students

2025· article· W4416302641 on OpenAlexvenueno aff
Shahad Dyieb Almuatiri, Khaled Besher Albesher

Bibliographic record

VenueInternational Journal of English Linguistics · 2025
Typearticle
Language
FieldComputer Science
TopicMobile Learning in Education
Canadian institutionsnot available
FundersQassim University
KeywordsListening comprehensionVocabularyActive listeningComprehensionVocabulary learningPerception

Abstract

fetched live from OpenAlex

Listening comprehension is a fundamental language acquisition component, underpinning vocabulary development, grammatical understanding, and cultural awareness. This study examined the effectiveness of the Duolingo app in improving EFL students’ listening comprehension skills and their attitudes toward its use. Forty-six third-grade students from the Qassim region participated in a quantitative, quasi-experimental study, divided into an experimental group using Duolingo and a control group following traditional instruction. Data was collected through pre- and post-listening comprehension tests and a questionnaire. Two independent rates were used to evaluate the students’ performance, and statistical analyses were conducted using SPSS version 20. The findings revealed that students who used Duolingo showed a notable improvement of 18.5% in listening comprehension scores compared to the control group, and 82% of participants reported positive perceptions toward the app. These results suggest integrating mobile-assisted learning tools like Duolingo can significantly enhance students’ engagement and listening proficiency, offering valuable insights for technology-enhanced language pedagogy.

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)0.166
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.536
Threshold uncertainty score0.910

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.166
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0050.001
Research integrity0.0000.002
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 head0.319
Teacher spread0.312 · 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 designObservational
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
Published2025
Admission routes1
Has abstractyes

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