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Cited by 161Artificial Intelligence in EducationEFL/ESL Teaching and LearningEnglish Language Learning and Teaching

Enabling learner independence and self-regulation in language education using AI tools: a systematic review

Open access
Mohebbi, Ahmadreza·2025·Cogent Education
DOI 10.1080/2331186x.2024.2433814
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Abstract

In this study, a systematic review was conducted to explore the role of Artificial Intelligence (AI) in language learning, drawing insights from 18 peer-reviewed articles published between 2009 and 2024. The research utilised the PRISMA framework to ensure a comprehensive, structured approach to data collection and analysis. Articles were sourced from academic databases such as Google Scholar, ERIC, and PubMed, using targeted search terms including “AI and learning speaking,” “AI and learning writing,” and “AI and improving listening.” A meticulous screening process was applied, first by title and abstract, followed by full-text analysis to ensure relevance. The studies were then subject to a dual-round thematic analysis, with each round focusing on identifying patterns and cross-validating findings related to AI’s impact on language learning outcomes. The findings of the study revealed that AI-driven tools significantly enhance language learning outcomes by promoting engagement, providing immediate feedback, and facilitating personalised learning experiences. Specific AI tools like Virtual Reality (VR) applications, automated writing feedback systems, and chatbots were analysed for their effectiveness in enhancing speaking, writing, and grammar skills. By conducting a detailed thematic analysis, this study highlighted both the benefits and limitations of AI-driven language education, underscoring AI’s role in promoting self-regulated learning while noting areas needing cautious implementation, such as over-reliance on technology and equitable access.

AI snapshot

Written from the paper’s full text.

TL;DR

This systematic review of 18 peer-reviewed articles (2009–2024) finds that AI tools can support language learning and learner autonomy through immediate, personalised feedback and practice, especially in writing, speaking, grammar, and vocabulary. It also cautions about over-reliance, limited conversational depth, and unequal access.

Key findings

  • Writing was the most researched skill, followed by speaking, grammar, and vocabulary; reading and listening remained underexplored.
  • AI chatbots and VR reduced speaking anxiety and enabled stress-free practice, while automated writing feedback improved grammar, sentence structure, and coherence; automatic scoring supported grammatical accuracy and self-regulation.
  • AI promoted autonomy via real-time feedback, personalised learning paths, and flexible practice, but risks included over-reliance reducing critical thinking and creativity, and AI’s difficulty with nuanced, cultural, and contextual conversation.
  • Access inequality and the digital divide were identified as concerns that could exacerbate educational disparities.

Methods

  • Systematic review following the PRISMA framework, drawing on 18 peer-reviewed empirical articles published between 2009 and 2024 from Google Scholar, ERIC, PubMed, and high-impact Q1 journals.
  • Search terms included “AI and learning/teaching writing,” speaking, grammar, vocabulary, reading, and listening; initial screening reviewed over 100 articles, with full-text screening leaving 18.
  • Dual-round thematic analysis using Braun and Clarke’s six-phase approach, with AI tools aiding screening and thematic analysis; multiple independent reviewers resolved discrepancies by consensus.

Limitations

  • Stated in the paper: over-reliance on AI may bypass critical thinking, creativity, analysis, and synthesis; AI chatbots lack nuanced human-like conversation and cultural/contextual elements; digital divide/access inequality; privacy, bias, reduced human interaction, and need for teacher training.
  • Evident from the text: the synthesis is based on only 18 articles and reports no meta-analytic effect sizes or pooled quantitative outcomes; the search was restricted to selected databases and Q1 publishers, which may limit coverage and generalisability.

Model-written summary. Check it against the paper before relying on it.

Integrity signals

Registry

Crossref · 10.1080/2331186x.2024.2433814

Cites

19 of 19 references verified0 citation errors · 0 not checkable

Statistics

Nothing to recompute.

Claims the paper makes

0 of 41 cited sources checked · 0 supported · 0 flagged

  • Findingnone given

    AI writing feedback is especially effective in improving writing fluency, coherence, and grammatical accuracy.

    “This feedback is especially effective in improving writing fluency, coherence, and grammatical accuracy.”
    Quote in the paperNot a substantial claim
  • Findingcitation

    Learners who used AI writing tools showed significant improvement in organising ideas and writing structured, coherent essays.

    “studies by Tseng and Warschauer (Citation2023) and Alharbi (Citation2023) revealed that learners who used these tools showed significant improvement in organising ideas and writing structured, coherent essays.”
    Quote in the paperNot a substantial claim0 of 2 sources checked
    • cites Tseng and Warschauer, Citation2023

      Not checked in the free run.

    • cites Alharbi, Citation2023

      Not checked in the free run.

  • Findingown data
    § Abstract

    AI-driven tools enhance language learning outcomes by facilitating personalised learning experiences.

    “The findings of the study revealed that AI-driven tools significantly enhance language learning outcomes by promoting engagement, providing immediate feedback, and facilitating personalised learning experiences.”
    Quote in the paperSubstantial claim
  • Findingown data
    § Abstract

    AI-driven tools enhance language learning outcomes by promoting engagement.

    “The findings of the study revealed that AI-driven tools significantly enhance language learning outcomes by promoting engagement, providing immediate feedback, and facilitating personalised learning experiences.”
    Quote in the paperSubstantial claim
  • Findingnone given

    AI writing tools such as ChatGPT, automated writing feedback systems, and AI-based writing assistants provide instant, personalised feedback.

    “Tools like ChatGPT, automated writing feedback systems, and AI-based writing assistants have demonstrated their ability to provide instant, personalised feedback.”
    Quote in the paperSubstantial claim
  • May combine two claims. 15
  • Classified as probably not a substantial claim. 21

  • May combine two claims.

    Findingnone given

    In AI-enhanced language education research, writing, grammar, speaking, and vocabulary have been most frequently studied, while reading and listening remain underexplored.

    “Among these, writing, grammar, speaking, and vocabulary have been most frequently studied, while reading and listening remain underexplored.”
    Quote in the paperSubstantial claim
    • Rests on an assumption: The findings of the included primary studies are reliable and valid enough to support the review's conclusions.
    • Rests on an assumption: The selected databases, journals, and search terms captured the relevant literature on AI in language education.

  • May combine two claims.

    Findingnone given

    AI chatbots are frequently used to simulate conversational practice, making speaking the second-most researched skill.

    “AI chatbots, particularly those powered by natural language processing (NLP), are frequently used to simulate conversational practice, making speaking the second-most researched skill.”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Findingcitation

    Learners who used AI chatbots benefited from stress-free, repetitive conversational exercises, leading to reduced speaking anxiety and increased frequency of practice.

    “Studies like Jeon (Citation2022) and Lin and Mubarok (Citation2021) found that learners benefitted from AI chatbots by engaging in stress-free, repetitive conversational exercises. This led to reduced speaking anxiety and increased frequency of practice, key factors in improving speaking proficiency.”
    Quote in the paperNot a substantial claim0 of 2 sources checked
    • cites Jeon, Citation2022

      Not checked in the free run.

    • cites Lin and Mubarok, Citation2021

      Not checked in the free run.

  • Probably not a substantial claim: may not pass S3 (load-bearing), S4 (based).

    Findingnone given

    Writing has consistently been the most researched skill in AI-enhanced language education.

    “Writing has consistently been the most researched skill in AI-enhanced language education.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Findingcitation

    Grammar correction is an area where AI excels.

    “Grammar correction is another area where AI excels.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Findingown data
    § Abstract

    The systematic review drew insights from 18 peer-reviewed articles published between 2009 and 2024.

    “In this study, a systematic review was conducted to explore the role of Artificial Intelligence (AI) in language learning, drawing insights from 18 peer-reviewed articles published between 2009 and 2024.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S4 (based). May combine two claims.

    Findingnone given
    § 6. Discussion

    AI's ability to provide personalised learning experiences, immediate feedback, and adaptive learning pathways has proven to be highly effective in enhancing language proficiency, especially in skills such as speaking, writing, grammar, and vocabulary.

    “AI’s ability to provide personalised learning experiences, immediate feedback, and adaptive learning pathways has proven to be highly effective in enhancing language proficiency, especially in skills such as speaking, writing, grammar, and vocabulary.”
    Quote in the paperNot a substantial claim
    • Rests on an assumption: The findings of the included primary studies are reliable and valid enough to support the review's conclusions.

  • Probably not a substantial claim: may not pass S3 (load-bearing), S4 (based).

    Findingnone given

    AI's use in enhancing listening skills is limited by its current inability to capture nuances of spoken language, including accent variation and emotional tone.

    “Additionally, AI’s use in enhancing listening skills is limited by its current inability to capture the nuances of spoken language, including accent variation and emotional tone ().”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Findingcitation

    Vocabulary tools that adapt to individual learning levels encouraged learners to actively manage their vocabulary learning, setting personalised learning paths based on immediate feedback from AI systems.

    “Similarly, vocabulary tools that adapt to individual learning levels, like those in Divekar et al. (Citation2021), encouraged learners to actively manage their vocabulary learning, setting personalised learning paths based on immediate feedback from AI systems ().”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites Divekar et al., Citation2021

      Not checked in the free run.

  • May combine two claims.

    Findingcitation

    AES systems provide consistent and scalable feedback, which is often difficult for human instructors to manage in large groups.

    “The AES systems studied by Mizumoto and Eguchi (Citation2023) were particularly useful in providing consistent and scalable feedback, which is often difficult for human instructors to manage in large groups.”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites Mizumoto and Eguchi, Citation2023

      Not checked in the free run.

  • May combine two claims.

    Findingcitation

    AI-driven writing tools provided learners with instant feedback on grammar, structure, and coherence, empowering them to make independent corrections and adjustments.

    “Tseng and Warschauer (Citation2023) and Alharbi (Citation2023) found that these tools provided learners with instant feedback on grammar, structure, and coherence, which empowered them to make independent corrections and adjustments.”
    Quote in the paperSubstantial claim0 of 2 sources checked
    • cites Tseng and Warschauer, Citation2023

      Not checked in the free run.

    • cites Alharbi, Citation2023

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  • May combine two claims.

    Findingcitation

    AI-driven conversations lack depth and natural flow, limiting their effectiveness in advancing learners beyond basic fluency levels.

    “However, the main limitation, as highlighted by Hapsari and Wu (Citation2022), lies in the lack of depth and natural flow in AI-driven conversations. While AI tools excel at providing structured, predictable dialogues, they struggle with more nuanced, unpredictable elements of human conversation, limiting their effectiveness in advancing learners beyond basic fluency levels.”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites Hapsari and Wu, Citation2022

      Not checked in the free run.

  • May combine two claims.

    Findingreasoning

    AI grammar tools enable learners to identify and correct errors autonomously, fostering greater self-regulation.

    “These tools enable learners to identify and correct errors autonomously, fostering greater self-regulation.”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingcitation
    § 6. Discussion

    AI-driven tools like VR and chatbots reduced learners' anxiety and facilitated more consistent practice.

    “Chen (Citation2024) and Jeon (Citation2022) both found that AI-driven tools like VR and chatbots reduced learners’ anxiety and facilitated more consistent practice, which is often difficult to achieve in traditional classrooms.”
    Quote in the paperSubstantial claim0 of 2 sources checked
    • cites Chen, Citation2024

      Not checked in the free run.

    • cites Jeon, Citation2022

      Not checked in the free run.

    • Rests on an assumption: The findings of the included primary studies are reliable and valid enough to support the review's conclusions.

  • May combine two claims.

    Findingcitation

    AI writing tools helped learners improve grammar, sentence structure, and coherence.

    “Tseng and Warschauer (Citation2023) and Alharbi (Citation2023) both observed that AI writing tools, such as ChatGPT and automated writing feedback systems, helped learners improve their grammar, sentence structure, and coherence.”
    Quote in the paperSubstantial claim0 of 2 sources checked
    • cites Tseng and Warschauer, Citation2023

      Not checked in the free run.

    • cites Alharbi, Citation2023

      Not checked in the free run.

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Study design and conductnone given

    The search used specific keywords combined with Boolean operators such as AND.

    “To ensure a comprehensive search, a set of specific keywords was used, combined with Boolean operators such as AND.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Study design and conductnone given
    § Abstract

    The research utilised the PRISMA framework to ensure a comprehensive, structured approach to data collection and analysis.

    “The research utilised the PRISMA framework to ensure a comprehensive, structured approach to data collection and analysis.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing), S4 (based).

    Interpretationnone given
    § Abstract

    There is a risk of over-reliance on AI in language education.

    “It also explores challenges, including the risk of over-reliance on AI and the disparity in access to advanced technologies.”
    Quote in the paperNot a substantial claim

  • Classified as probably not a substantial claim.

    Study design and conductnone given
    § 3. Methodology

    The review followed the PRISMA framework for literature selection, screening, and data extraction.

    “The methodology followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) framework, ensuring a transparent, structured, and rigorous approach to literature selection, screening, and data extraction.”
    Quote in the paperSubstantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Study design and conductnone given

    The screening process followed the PRISMA flowchart approach.

    “The screening process followed the PRISMA flowchart approach, which includes identification, screening, eligibility, and inclusion phases.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Study design and conductcitation

    Data were analysed using thematic analysis following Braun and Clarke's six-phase approach.

    “The thematic analysis process followed Braun and Clarke (Citation2021) six-phase approach:”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites Braun and Clarke, Citation2021

      Not checked in the free run.

  • Classified as probably not a substantial claim. May combine two claims.

    Study design and conductown data

    Screening was carried out independently by multiple reviewers, and discrepancies were resolved through discussion until consensus.

    “To minimise bias, the screening was carried out independently by multiple reviewers. Any discrepancies in article inclusion were resolved through discussion until consensus was reached.”
    Quote in the paperSubstantial claim

  • Classified as probably not a substantial claim.

    Premisecitation

    Metacognitive skills enable learners to take an active role in their learning, making informed decisions about their learning strategies and adjusting their approaches based on their progress and feedback.

    “These skills enable learners to take an active role in their learning, making informed decisions about their learning strategies and adjusting their approaches based on their progress and feedback (Zimmerman, Citation2002).”
    Quote in the paperSubstantial claim0 of 1 sources checked
    • cites Zimmerman, Citation2002

      Not checked in the free run.

  • Probably not a substantial claim: may not pass S3 (load-bearing), S4 (based). May combine two claims.

    Interpretationreasoning

    AI-driven interactions lack conversational depth and cultural nuances, suggesting learners may not fully develop communication skills for real-world, nuanced conversations.

    “The conversational depth and cultural nuances AI tools lack suggest that learners may not fully develop their communication skills for real-world, nuanced conversations.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing), S4 (based).

    Interpretationnone given
    § Abstract

    There is a disparity in access to advanced technologies in language education.

    “It also explores challenges, including the risk of over-reliance on AI and the disparity in access to advanced technologies.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Study design and conductnone given
    § Abstract

    A meticulous screening process was applied, first by title and abstract, followed by full-text analysis to ensure relevance.

    “A meticulous screening process was applied, first by title and abstract, followed by full-text analysis to ensure relevance.”
    Quote in the paperNot a substantial claim

  • Classified as probably not a substantial claim.

    Study design and conductnone given

    Data were collected from Google Scholar, ERIC, and PubMed.

    “The data for this review was collected from prominent academic databases such as Google Scholar, ERIC, and PubMed, which provide extensive coverage of educational, linguistic, and interdisciplinary research.”
    Quote in the paperSubstantial claim

  • Classified as probably not a substantial claim.

    Study design and conductnone given

    Inclusion and exclusion criteria were developed to ensure only high-quality, relevant studies were considered.

    “A clear set of inclusion and exclusion criteria was developed to ensure that only high-quality, relevant studies were considered for this review.”
    Quote in the paperSubstantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Study design and conductnone given
    § Abstract

    The studies were subject to a dual-round thematic analysis, with each round focusing on identifying patterns and cross-validating findings related to AI's impact on language learning outcomes.

    “The studies were then subject to a dual-round thematic analysis, with each round focusing on identifying patterns and cross-validating findings related to AI’s impact on language learning outcomes.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing), S4 (based). May combine two claims.

    Study design and conductnone given

    Constant comparison across studies ensured that identified themes were robust and reflected the full scope of available research.

    “Constant comparison across studies ensured that the identified themes were robust and reflected the full scope of available research on the topic ().”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

    Premisecitation
    § 5. Overcoming challenges in AI-enhanced language education

    The role of teachers remains vital, particularly in providing emotional support, fostering critical thinking, and offering nuanced feedback that AI cannot replicate.

    “The role of teachers remains vital, particularly in providing emotional support, fostering critical thinking, and offering nuanced feedback that AI cannot replicate (Luckin & Holmes, Citation2016).”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites Luckin & Holmes, Citation2016

      Not checked in the free run.

31 of 31

  • The paper relies on this without support.

    The findings of the included primary studies are reliable and valid enough to support the review's conclusions.

    “The findings from the reviewed studies underscore the transformative potential of AI in language education, yet also highlight the critical need for a thoughtful and balanced integration of AI with traditional pedagogical methods.”

  • The paper relies on this without support.

    The selected databases, journals, and search terms captured the relevant literature on AI in language education.

    “The data for this review was collected from prominent academic databases such as Google Scholar, ERIC, and PubMed, which provide extensive coverage of educational, linguistic, and interdisciplinary research.”
2 of 2

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

  • AI can provide personalised feedback, guiding students towards ethical writing practices and self-regulated learning.

    “Additionally, AI can provide personalised feedback, guiding students towards ethical writing practices and self-regulated learning [ 37 ].”

    From Redefining student assessment in AI-infused learning environments: a systematic review of challenges and strategies for academic integrity (2026) · cites this paper as [37]

    The Results (section 4.3.1; page not provided) say AI writing tools give individualised feedback that helps learners make independent corrections and engage in self-regulated learning. The paper does not say this feedback guides students toward ethical writing practices; its discussion of ethics concerns matters such as privacy and bias. (LLM, conf=0.87)

    Experimental — accuracy not yet measured

  • AI presents risks to integrity but also offers opportunities for enhanced assessment, security, and personalised feedback.

    “While AI presents risks to integrity, it also offers opportu -nities for enhanced assessment, security, and personalised feedback [ 37 ].”

    From Redefining student assessment in AI-infused learning environments: a systematic review of challenges and strategies for academic integrity (2026) · cites this paper as [37]

    Section 2.2 describes AI-based assessment tools that provide immediate, personalised feedback. Section 5 discusses privacy and the need to secure learners’ data, but frames security as a challenge requiring safeguards, not an opportunity AI itself offers. The passages do not address risks to academic integrity. (LLM, conf=0.88)

    Experimental — accuracy not yet measured

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

Each contradiction between two passages listed here was confirmed by an independent check.

  • First research question is treated as an effectiveness question

    Minor

    The first research question asks which skills have been studied most frequently, not whether AI has been effective. The discussion attributes an effectiveness finding to that question; effectiveness is the subject of the second question.

  • Sottilare citation year differs from reference year

    Minor

    The in-text citation gives 2014, but the corresponding Sottilare reference is dated 2016.

2 of 2

Cites

1 retracted

Flagged first, then by citations

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Cited by

Sorted by citations

Authors
Mohebbi, A.
Affiliations
University of Auckland (NZ)
Corresponding author
Mohebbi, Ahmadreza
ORCID
Mohebbi, Ahmadreza
Venue
Cogent Education
Publisher
Informa UK Limited
Published
2024-12-23
Volume
12
Issue
1
ISSN
2331-186X (ISSN-L)
DOI
10.1080/2331186x.2024.2433814
OpenAlex
W4405706032
Cited by
161
References
19
Citations by year
2026: 101 · 2025: 60
FWCI
9.25
Type
journal article
Language
en
Open access
Licence
Locations
  • Cogent Education (publishedVersion, cc-by)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
  • ResearchSpace (University of Auckland) (submittedVersion, cc-by)
Topics
  • Physical Sciences › Computer Science › Information Systems › Artificial Intelligence in Education
  • Social Sciences › Arts and Humanities › Language and Linguistics › EFL/ESL Teaching and Learning
  • Physical Sciences › Computer Science › Information Systems › English Language Learning and Teaching
Keywords
artificial intelligence in language teaching, learner autonomy, student self-regulation, speaking skills, writing skills, listening skills, grammatical competence, virtual reality in language learning, automated writing feedback, chatbots, personalized learning, student engagement, equitable access to technology

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