ArticleBMC psychology2024
AI-empowered applications effects on EFL learners' engagement in the classroom and academic procrastination.
Article in BMC psychology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers, 1 of them a synthesis that pooled it.
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Who cites it
11 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Learner emotions in AI-assisted English as a second/foreign language learning: a systematic review of empirical studies.Frontiers in psychology · 2025Pooled it
- Belonging in Uncertain Times: An Ecological Perspective on the Identification of LOTE Majors.Behavioral sciences (Basel, Switzerland) · 2026Article
- Article
- How generative AI enhances self-regulated learning in EFL learners: a chain mediation model of "intention to use" and "learning engagement".Frontiers in psychology · 2026Article
- Academic procrastination and academic engagement among dentistry students at a Peruvian university: a cross-sectional study.Frontiers in psychology · 2026Article
- An associative model of Chinese university teachers' personality traits and students' classroom engagement from the teacher's perspective: the mediating role of emotional regulation.Frontiers in psychology · 2026Article
- Rethinking foreign language boredom in AI-assisted learning: the hidden roles of growth mindset, AI literacy, and AI self-efficacy.Frontiers in psychology · 2026Article
- Article
- Article
- AI acceptance and Chinese EFL learners' behavioral engagement with mediating effects of motivation.Scientific reports · 2025Article
- Exploring the factors influencing the adoption of artificial intelligence technology by university teachers: the mediating role of confidence and AI readiness.BMC psychology · 2025Article
Corrections and comments
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Authors and funding
2 authors.
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Abstract
backgroundIn today's rapidly evolving educational landscape, AI-powered applications like ChatGPT, POE, and Duolingo are revolutionizing language education, offering personalized learning experiences in EFL. However, challenges such as student engagement and academic procrastination persist. This study delves into how these AI tools impact EFL learners' engagement and procrastination tendencies, aiming to inform effective technology integration in language instruction.
objectivesThe primary goals of this research are to assess the influence of AI-empowered applications on affective, cognitive, and behavioural engagement and academic procrastination among EFL learners. By considering both the affective and cognitive aspects of engagement, the study aims to provide insights into optimizing EFL instruction through AI-driven tools while addressing academic procrastination challenges. METHODOLOGY: A quasi-experimental research method was employed, involving ten intact classes comprising 350 students divided into two groups. Engagement and procrastination scales were administered before and after the treatment. T-tests were utilized to analyze the data, comparing pre- and post-treatment scores between the groups.
findingsThe results indicate that the experimental group, exposed to AI-empowered applications, demonstrated significantly higher levels of affective, cognitive, and behavioural engagement than the control group. KEYWORDS: AI-empowered applications, Academic procrastination, engagement, Chinese EFL learners' engagement. Moreover, a substantial reduction in academic procrastination was observed among students exposed to AI-empowered applications.
conclusionsThe study underscores the potential of AI-empowered applications to enhance learner engagement and mitigate academic procrastination. The findings contribute to the pedagogical discourse surrounding technology integration and advocate adopting learner-centred approaches. The incorporation of AI-empowered applications in diverse educational settings is recommended.
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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.