ReviewHeliyon2024
Investigating the integration of artificial intelligence in English as foreign language classes for enhancing learners' affective factors: A systematic review.
Review in Heliyon, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
7 citing papers in PubMed.
- Modelling Divergent Thinking as a Mediator Between Artificial Intelligence Cognitive Stimulation and EFL Learners' Cognitive Creativity.Journal of Intelligence · 2026Article
- Working Memory, Attention Control, and Vocabulary Retention in AI (ChatGPT)-Assisted Foreign Language Learning: A Structural Cognitive Modelling Approach.Journal of Intelligence · 2026Article
- Enhancing creative writing through AI-powered co-creation with cognitive and emotional outcomes.Scientific reports · 2026Article
- ChatGPT use and learner autonomy among EFL university students: the mediating role of English speaking anxiety.Frontiers in psychology · 2026Article
- Enhancing intercultural competence in technical higher education through AI-driven frameworks.Scientific reports · 2025Article
- Values characteristics of Chinese college students with upper-level learning engagement.Frontiers in psychology · 2025Article
- From literacy to learning: The sequential mediation of attitudes and enjoyment in AI-assisted EFL education.Heliyon · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Integrating Artificial Intelligence (AI) applications into language learning and teaching is currently a growing trend in higher education. Literature reviews have demonstrated the effectiveness of AI applications in improving English as a foreign language (EFL) and English as a second language (ESL) learners' receptive and productive skills, vocabulary knowledge, and intercultural competencies. However, systematic reviews investigating the usefulness of AI technologies in higher education to enhance EFL learners' affective factors are scarce. This study is a systematic review that investigates the effectiveness of integrating AI technologies to enhance EFL learners' motivation, engagement, and attitude, and reduce their learning anxiety. Articles from reputable journal databases such as IEEE, Wiley, Web of Science, Sage, ProQuest, Springer, and Science Direct were screened by examining titles and abstracts, and irrelevant articles were excluded from the search. Of the 64 articles analyzed only 21 articles published between 2017 and 2023 were determined to be relevant to the research topic. The findings suggest that the implementation of AI technologies in EFL contexts is in its early stages, and further research is required to establish the impact of AI-integrated classes on EFL learners' affective factors. This review also identifies the gaps in literature and recommends avenues for future research in this novel area.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.