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Cited by 93EFL/ESL Teaching and LearningArtificial Intelligence in EducationEnglish Language Learning and Teaching

Investigating the integration of artificial intelligence in English as foreign language classes for enhancing learners’ affective factors: A systematic review

Open access
AlTwijri, Lujain, Alghizzi, Talal Musaed·2024·Heliyon
DOI 10.1016/j.heliyon.2024.e31053PMC PMC11109823
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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.

AI snapshot

Written from the paper’s full text.

TL;DR

This systematic review synthesizes 21 studies published between 2017 and 2023 on integrating AI into higher-education EFL classes to enhance learners’ affective factors—motivation, engagement, attitude, and anxiety. It finds generally positive effects on motivation, engagement, and attitude, with anxiety reduction in most but not all studies, and concludes that AI integration in EFL is still in its early stages.

Key findings

  • Of 64 retrieved articles, 21 met inclusion criteria; the most commonly used AI technologies were chatbots and AI-powered language-learning platforms, serving as teaching assistants, personal tutors, and learning partners.
  • Motivation and engagement were generally positive: Al-Abdullatif et al. (2023) reported total motivation means of 4.03 for the experimental group vs. 3.34 for the control group; Moybeka et al. (2023) reported a high motivation mean of 4.60; Kim (2018) found significant differences for motivation (t = 5.216, p = 0.000), interest (t = 7.882, p = 0.000), and confidence (t = 3.616, p = 0.001); Xie et al. (2021) found MOCA significantly improved engagement scores (p < .001).
  • Attitude was positive in most reviewed studies, including toward AI-integrated EFL learning, grammar translation AI tools, SIRI, and chatbots; however, Li and Peng (2021) found positive attitudes toward an AI language-learning platform but no significant difference in language performance between experimental and control groups.
  • Anxiety reduction was promising in most studies, with Bao (2019) reporting a cumulative anxiety reduction of −31; however, El Shazly (2021) found the opposite, with mean anxiety increasing from 15.3 pre-intervention to 16.8 post-intervention, indicating learners became more anxious.

Methods

  • Systematic review using the five-step grounded-theory-based method of Wolfswinkel et al., involving scope identification, database searching, final sample selection, sample evaluation, and results presentation.
  • Searches were conducted in IEEE, Wiley, Web of Science, Sage, ProQuest, Springer, and Science Direct using terms such as “AI,” “artificial intelligence,” “EFL,” “ESL,” “motivation,” “attitude,” “learning engagement,” “learning anxiety,” “affective factors,” and “higher education”; 64 publications were retrieved and 21 were included.
  • Inclusion required empirical, English-language journal articles integrating an AI application into EFL classes in higher education and focused on learners’ affective factors; exclusions included non-English articles, no AI integration, K–12 settings, studies focused on the four basic skills, grammar, or vocabulary, and editorials or opinion articles. Analysis was carried out in Microsoft Excel, categorizing studies into motivation, attitude, learning engagement, and learning anxiety.

Limitations

  • The paper states that most previous studies do not specify the teaching approach implemented, some articles did not clearly present validity and reliability of data collection methods, and only a few conducted pilot studies before implementation.
  • The paper states that there is a lack of longitudinal studies, most experiments were brief (from two 50-min experiments to a three-month quasi-experimental study), quantitative methods predominated, and AI integration into EFL education remains in its early stage with scarce research on affective factors.
  • The text makes evident that the review is limited to 21 English-language higher-education studies published between 2017 and 2023, excluding K–12 and skill-focused studies, which restricts generalizability; it is also a qualitative synthesis rather than a meta-analysis.

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

Integrity signals

Registry

Crossref · 10.1016/j.heliyon.2024.e31053

Cites

54 of 54 references verified0 citation errors · 0 not checkable

Statistics

Claims the paper makes

0 of 89 cited sources checked · 0 supported · 0 flagged

  • Findingnone given

    Systematic reviews investigating the effectiveness of AI technologies in promoting EFL learners' affective factors are scarce.

    “However, systematic reviews investigating the usefulness of AI technologies in higher education to enhance EFL learners' affective factors are scarce.”
    • Also stated in: § Purpose of the study · plain
      “Although there are significant advantages to AI applications, systematic reviews investigating their effectiveness in promoting EFL learners' affective factors are scarce.”
    • Also stated in: § Purpose of the study · plain
      “Furthermore, studies analyzing the effectiveness of AI technology in fostering learners' affective factors are scarce.”
    Quote in the paperSubstantial claim
    • Rests on an assumption: The search terms and databases used identified all relevant studies on AI integration in EFL higher education.
  • Findingown data

    21 studies were included in the final analysis.

    “Of the 64 articles analyzed only 21 articles published between 2017 and 2023 were determined to be relevant to the research topic.”
    • Also stated in: § Selecting the final sample · plain
      “This resulted in the inclusion of 21 studies in the final analysis see Table 1.”
    Quote in the paperNot a substantial claim
  • Findingnone given

    Very few AI tools have been specifically designed to create interactive activities to enhance learners' motivation, engagement, and attitude and reduce anxiety toward language learning.

    “However, very few of them have been specifically designed to create interactive activities to enhance learners’ motivation, engagement, and attitude and reduce anxiety toward language learning.”
    Quote in the paperNot a substantial claim
  • Findingcitation

    The use of chatbots in higher education encouraged learners to invest time and effort in language learning.

    “increased their intrinsic and extrinsic motivation in language learning; and encouraged them to invest time and effort ([42,43]).”
    Quote in the paperSubstantial claim0 of 2 sources checked
    • cites [42] Ayedoun E. Hayashi Y. Seta K. Toward personalized scaffolding and fading of motivational support in L2 learner–dialogue agent interactions: an exploratory study IEEE Transactions on learning technologies 13 3 2020 604 616 10.1109/TLT.2020.2989776 source

      Not checked in the free run.

    • cites [43] Ali J.K.M. Shamsan M.A.A. Hezam T.A. Mohammed A.A. Impact of ChatGPT on learning motivation: teachers and students' voices Journal of English Studies in Arabia Felix 2 1 2023 41 49 10.5539/elt.v14n6p135 Learners. English Language Teaching, 14(6), 135–157

      Couldn’t be matched to a paper in Crossref, so it can’t be checked.

    • Rests on an assumption: The affective outcomes reported in the included studies can be attributed to the AI applications rather than other instructional or contextual factors.
  • Findingcitation

    The use of chatbots in higher education fostered learners' motivation, eagerness, and confidence.

    “The use of chatbots in higher education fostered learners' motivation, eagerness, and confidence ([[25], [26], [27],31,41,42]);”
    Quote in the paperSubstantial claim0 of 1 sources checked
    • cites [[25], [26], [27],31,41,42]

      Not checked in the free run.

    • Rests on an assumption: The affective outcomes reported in the included studies can be attributed to the AI applications rather than other instructional or contextual factors.
  • Classified as probably not a substantial claim. 39
  • May combine two claims. 38

  • Probably not a substantial claim: may not pass S4 (based).

    Findingnone given

    Studies investigating the impact of AI applications on EFL learners in higher education have extensively pursued motivation, engagement, attitude, and anxiety.

    “studies investigating the impact of AI applications on EFL learners in higher education have extensively pursued motivation, engagement, attitude, and anxiety.”
    Quote in the paperNot a substantial claim

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

    Findingown data

    A total of 64 publications were retrieved from the selected databases.

    “A total of 64 publications were retrieved.”
    Quote in the paperNot a substantial claim

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

    Findingreasoning

    Two dimensions were identified: integrated technology and task design.

    “Hence, two dimensions were identified: integrated technology and task design see Table 1.”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Findingcitation

    In a study by Yin et al. (2019), the experimental group was more competent in learning and attained significantly higher intrinsic motivation.

    “More specifically, the experimental group in a study conducted by Yin et al. (2019) was more competent in learning and attained significantly higher intrinsic motivation.”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites Yin et al. (2019)

      Not checked in the free run.

    • Rests on an assumption: The affective outcomes reported in the included studies can be attributed to the AI applications rather than other instructional or contextual factors.

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

    Findingnone given

    Little is known about how AI technology is implemented in higher educational systems, how well L2 learners engage with AI technology, and how their engagement with AI fosters their motivation and attitude toward learning the language.

    “Furthermore, little is known about how AI technology is implemented in higher educational systems, how well L2 learners engage with AI technology, and how their engagement with AI fosters their motivation and attitude toward learning the language.”
    Quote in the paperNot a substantial claim

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

    Findingown data

    Some studies fell into more than one domain, such as motivation and learning engagement or motivation and attitude.

    “Some studies fell into more than one domain, such as motivation and learning engagement or motivation and attitude.”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Findingcitation

    Chatbots that operated as teaching assistants provided academic knowledge, offered formative feedback, and enabled scaffolded learning.

    “The chatbots that operated as teaching assistants provided academic knowledge ([41,[48], [49], [50]]), offered formative feedback to EFL learners [45], and enabled scaffolded learning ([22,27,31,42,51]).”
    Quote in the paperNot a substantial claim0 of 7 sources checked
    • cites [41,[48], [49], [50]]

      Not checked in the free run.

    • cites [45] Xie T. Liu R. Chen Y. Liu G. MOCA: a motivational online conversational agent for improving student engagement in collaborative learning IEEE Transactions on Learning Technologies 14 5 2021 653 664 source

      Not checked in the free run.

    • cites [22] Kim N.Y. Chatbots and Korean EFL students' English vocabulary learning Journal of Digital Convergence 16 2 2018

      Not checked in the free run.

    • cites [27] Ebadi S. Amini A. Examining the roles of social presence and human- likeness on Iranian EFL learners' motivation using artificial intelligence technology: a case of csiec chatbot Interact. Learn. Environ. 2022 1 19

      Not checked in the free run.

    • cites [31] Moybeka A.M. Syariatin N. Tatipang D.P. Mushthoza D.A. Dewi N.P.J.L. Tineh S. Artificial intelligence and English classroom: the implications of AI toward EFL students' motivation Edumaspul: Jurnal Pendidikan 7 2 2023 2444 2454 source

      Not checked in the free run.

    • cites [42] Ayedoun E. Hayashi Y. Seta K. Toward personalized scaffolding and fading of motivational support in L2 learner–dialogue agent interactions: an exploratory study IEEE Transactions on learning technologies 13 3 2020 604 616 10.1109/TLT.2020.2989776 source

      Not checked in the free run.

    • cites [51] Lee Y. Hwang G. Chen P. Impacts of an AI-based chabot on College students' after-class review, academic performance, self-efficacy, learning attitude, and motivation Educ. Technol. Res. Dev. 70 5 2022 1843 1865 source

      Not checked in the free run.

  • May combine two claims.

    Findingcitation

    A study found that chatbots enabling interactive activity resulted in significant improvement in linguistic gains but did not reduce learners' anxiety.

    “Nonetheless, a study that investigated the role of chatbots in enabling interactive activity to reduce EFL learning anxiety resulted in a significant improvement in linguistic gains, but did not reduce learners’ anxiety [48] see Table 2.”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites [48] El Shazly R. Effects of artificial intelligence on English speaking anxiety and speaking performance: a case study Expet Syst. 38 3 2021 e12667

      Not checked in the free run.

  • May combine two claims.

    Findingcitation

    Learners were enthusiastically involved in the learning process and actively motivated to use SIRI to learn EFL.

    “In addition, learners were enthusiastically involved in the learning process and actively motivated to use SIRI to learn EFL [44].”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites [44] Haryanto E. Ali R.M. Students' attitudes towards the use of artificial intelligence SIRI in EFL learning at one public university BKS-PTN Wilayah Barat 1 1 2019

      Not checked in the free run.

    • Rests on an assumption: The affective outcomes reported in the included studies can be attributed to the AI applications rather than other instructional or contextual factors.

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

    Findingcitation

    Japanese and Chinese scholars account for 50% of published articles in the fields of AI and EFL learning.

    “It is evident that Japanese and Chinese scholars account for 50 % of published articles in the fields of AI and EFL learning [55].”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites [55] Koff L. Mullis R. Nutrition education and technology: can delivering messages via new media technology effectively modify nutrition behaviors of pre-schoolers and their families? J. Nutr. Educ. Behav. 43 4 2011 S40 S40 source

      Not checked in the free run.

  • May combine two claims.

    Findingcitation

    Interactive tools such as chatbots kept learners motivated and engaged, while allowing them to learn EFL in an exciting and relaxing atmosphere.

    “Interactive tools such as chatbots kept learners motivated and engaged, while allowing them to learn EFL in an exciting and relaxing atmosphere ([26,41,42,45]).”
    Quote in the paperSubstantial claim0 of 4 sources checked
    • cites [26] Ayedoun E. Hayashi Y. Seta K. Adding communicative and affective strategies to an embodied conversational agent to enhance second language learners' willingness to communicate Int. J. Artif. Intell. Educ. 29 1 2019 29 57 10.1007/s40593-018-0171-6 source

      Not checked in the free run.

    • cites [41] Al-Abdullatif A.M. Al-Dokhny A.A. Drwish A.M. Implementing the bashayer chatbot in Saudi higher education: measuring the influence on students' motivation and learning strategies Front. Psychol. 14 2023 1129070 PMC10226531 37255522 source

      Not checked in the free run.

    • cites [42] Ayedoun E. Hayashi Y. Seta K. Toward personalized scaffolding and fading of motivational support in L2 learner–dialogue agent interactions: an exploratory study IEEE Transactions on learning technologies 13 3 2020 604 616 10.1109/TLT.2020.2989776 source

      Not checked in the free run.

    • cites [45] Xie T. Liu R. Chen Y. Liu G. MOCA: a motivational online conversational agent for improving student engagement in collaborative learning IEEE Transactions on Learning Technologies 14 5 2021 653 664 source

      Not checked in the free run.

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

    Findingown data

    Some of the articles reviewed needed to clearly present whether the researchers examined the validity and reliability of the data collection methods.

    “Some of the articles reviewed in this study needed to clearly present whether the researchers examined the validity and reliability of the data collection methods, which included questionnaires, pre- and post-tests, and integrated AI technologies.”
    Quote in the paperNot a substantial claim

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

    Findingcitation

    The lack of longitudinal studies, the pervasiveness of quantitative methods, and the prevalence of quasi-experimental designs emphasize that there is still an abundance of opportunities for educators to pursue novel and valuable research using AI technologies in different fields of higher education and English language education.

    “Additionally, the lack of longitudinal studies, the pervasiveness of quantitative methods, and the prevalence of quasi-experimental designs emphasize that there is still an abundance of opportunities for educators to pursue novel and valuable research using AI technologies in different fields of higher education and, more specifically, English language education [35].”
    Quote in the paperSubstantial claim0 of 1 sources checked
    • cites [35] Zawacki-Richter O. Marín V.I. Bond M. Gouverneur F. Systematic review of research on artificial intelligence applications in higher education–where are the educators? International Journal of Educational Technology in Higher Education 16 1 2019 1 27 source

      Not checked in the free run.

  • May combine two claims.

    Findingnone given

    Most studies have focused on employing conversational chatbots and automated writing-evaluation systems, ignoring the significance of affective factors.

    “Most studies have focused on employing conversational chatbots (to strengthen listening and speaking skills) and automated writing-evaluation systems (to improve writing skills and to correct vocabulary and grammar usage), ignoring the significance of affective factors that might negatively or positively affect the overall learning performance.”
    Quote in the paperSubstantial claim

  • Classified as probably not a substantial claim.

    Findingnone given

    There has been insufficient elaboration on the correct instructional method to implement when integrating AI technologies into EFL classrooms.

    “Furthermore, there has been insufficient elaboration on the correct instructional method to implement when integrating AI technologies into EFL classrooms.”
    Quote in the paperSubstantial claim

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

    Findingreasoning

    The use of such chatbots resulted in better academic achievement, enhanced motivation and engagement, reduced anxiety, and increased attention and collaboration.

    “The use of such chatbots resulted in better academic achievement, enhanced motivation and engagement, reduced anxiety, and increased attention and collaboration.”
    Quote in the paperNot a substantial claim

  • Classified as probably not a substantial claim.

    Findingnone given

    The papers reviewed supported the significance of AI technology in enhancing EFL learners' affective factors.

    “The papers reviewed supported the significance of AI technology in enhancing EFL learners’ affective factors.”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingcitation

    In a study conducted by El Shazly (2021), interactions with a chatbot did not reduce learners' anxiety; it only resulted in a significant improvement in linguistic gains.

    “However, in a study conducted by El Shazly (2021), interactions with a chatbot did not reduce learners’ anxiety; it only resulted in a significant improvement in linguistic gains.”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites El Shazly (2021)

      Not checked in the free run.

  • May combine two claims.

    Findingreasoning

    AI has had a positive impact by optimizing English language skills and learners' motivation, engagement, and attitudes.

    “AI has had a positive impact by optimizing English language skills and learners’ motivation, engagement, and attitudes.”
    Quote in the paperNot a substantial claim

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

    Findingnone given

    The mixed data collection method was employed in six studies and included questionnaires, pre-and post-tests, semi-structured interviews, and audio recordings.

    “The mixed data collection method was employed in six studies and included questionnaires, pre-and post-tests, semi-structured interviews, and audio recordings.”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Findingnone given

    Most of the reviewed studies indicated that AI applications can motivate students and foster their learning engagement.

    “Most of the reviewed studies indicated that AI applications can motivate students and foster their learning engagement.”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingnone given

    Studies have actively delineated productive and receptive skills, while affective factors are covered the least in recent studies.

    “Studies have actively delineated productive and receptive skills. In contrast, affective factors, such as motivation and attitude toward language learning, which facilitate or hinder the learning process, are covered the least in recent studies.”
    Quote in the paperSubstantial claim

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

    Premisecitation

    In higher education, AI can significantly improve learning outcomes across various fields of study.

    “In higher education, AI can significantly improve learning outcomes across various fields of study.”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites [14] Han L. Analysis of new advances in the application of artificial intelligence to education 2018 3rd International Conference on Education, E-Learning and Management Technology (EEMT 2018) 2018 Atlantis Press 608 611

      Not checked in the free run.

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    Premisecitation

    AI-based learning environments encourage L2 learners to achieve higher proficiency levels, thus accelerating the learning process and decreasing teachers' workload.

    “AI-based learning environments encourage L2 learners to achieve higher proficiency levels, thus accelerating the learning process and decreasing teachers' workload [18].”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites [18] Haenlein M. Kaplan A. A brief history of artificial intelligence: on the past, p present, and future of artificial intelligence Calif. Manag. Rev. 61 4 2019 5 14 source

      Not checked in the free run.

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

    Premisecitation

    AI holds the promise of enhancing students' academic performance by providing personalized learning opportunities and identifying areas needing improvement.

    “AI holds the promise of enhancing students' academic performance by providing personalized learning opportunities and identifying areas needing improvement [14].”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites [14] Han L. Analysis of new advances in the application of artificial intelligence to education 2018 3rd International Conference on Education, E-Learning and Management Technology (EEMT 2018) 2018 Atlantis Press 608 611

      Not checked in the free run.

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

    Premisecitation

    Various AI tools have been utilized in learning foreign languages, including automated writing-evaluation system, machine translation tool, intelligent learning management system, chatBot, and virtual learning environment.

    “Various AI tools have been utilized in learning foreign languages [19], including automated writing-evaluation system, machine translation tool, intelligent learning management system, chatBot, and virtual learning environment [20].”
    Quote in the paperNot a substantial claim0 of 2 sources checked
    • cites [19] Zhai C. A systematic review on artificial intelligence dialogue systems for enhancing English as foreign language students' interactional competence in the university Comput. Educ.: Artif. Intell. 2023 100134

      Not checked in the free run.

    • cites [20] Chu T. Wang W. Chen X. Visual analysis of research trends on language teachers in the era of artificial intelligence Advances in Educational Technology and Psychology 7 8 2023 71 76

      Not checked in the free run.

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    Premisecitation

    AI chatbots fostered learners' motivation, engagement, and positive attitudes toward learning EFL.

    “Furthermore, AI chatbots fostered learners' motivation, engagement, and positive attitudes toward learning EFL ([[25], [26], [27], [28]]).”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites [[25], [26], [27], [28]]

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    Premisecitation

    AI enhances the higher education sector by motivating educators and students to engage profoundly.

    “AI enhances the higher education sector by motivating educators and students to engage profoundly [17]”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites [17] Fahimirad M. Kotamjani S.S. A review on application of artificial intelligence in teaching and learning in educational contexts Int. J. Learn Dev. 8 4 2018 106 118 source

      Not checked in the free run.

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    Premisecitation

    The human brain rarely, if ever, remembers things that do not have emotional connections because without emotions, there will be no curiosity, awareness, and attention, which are critical components in learning processes.

    “it is neurobiologically believed that human brain rarely, if ever, remembers things that do not have emotional connections because without emotions, there will be no curiosity, awareness, and attention, which are all critical components in the learning processes [3].”
    Quote in the paperSubstantial claim0 of 1 sources checked
    • cites [3] Nishant R. Kennedy M. Corbett J. Artificial intelligence for sustainability: challenges, opportunities, and a research Agenda Int. J. Inf. Manag. 53 2020 102104

      Not checked in the free run.

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    Premisecitation

    Intrinsic motivation is linked with higher levels of achievement as it originates from personal interest and self-derived satisfaction.

    “It is linked with higher levels of achievement as it originates from personal interest and self-derived satisfaction [9].”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites [9] Noels K.A. Pelletier L.G. Clément R. Vallerand R.J. Why are you learning a second language? Motivational orientations and self‐determination theory Lang. Learn. 50 1 2000 57 85 source

      Not checked in the free run.

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

    Premisecitation

    There is no separation of mind and emotions; emotions, thinking and learning are all linked.

    “there is no separation of mind and emotions; emotions, thinking and learning are all linked” (4, p.71).”
    Quote in the paperSubstantial claim0 of 1 sources checked
    • cites [4] Lai E.R. Motivation: a literature review Person Research’s Report 6 2011 40 41

      Not checked in the free run.

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    Premisecitation

    AI applications play a significant role in supporting L2 learners by bridging gaps between their existing and new knowledge to adjust knowledge to the learner's current understanding or facilitate the acquisition of new knowledge.

    “AI applications play a significant role in supporting L2 learners by bridging gaps between their existing and new knowledge to adjust knowledge to the learner's current understanding or facilitate the acquisition of new knowledge.”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites [18] Haenlein M. Kaplan A. A brief history of artificial intelligence: on the past, p present, and future of artificial intelligence Calif. Manag. Rev. 61 4 2019 5 14 source

      Not checked in the free run.

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    Premisecitation

    The integration of AI enhances affective factors, attributed to personalized and constant feedback, an interactive learning environment, accessibility and flexibility in terms of place and time, and autonomous learning opportunities.

    “It has been found that the integration of AI enhances affective factors and this attributed to different reasons, such as personalized and constant feedback, an interactive learning environment, accessibility and flexibility in terms of place and time, and autonomous learning opportunities.”
    Quote in the paperSubstantial claim0 of 1 sources checked
    • cites [31] Moybeka A.M. Syariatin N. Tatipang D.P. Mushthoza D.A. Dewi N.P.J.L. Tineh S. Artificial intelligence and English classroom: the implications of AI toward EFL students' motivation Edumaspul: Jurnal Pendidikan 7 2 2023 2444 2454 source

      Not checked in the free run.

  • May combine two claims.

    Premisecitation

    AI has the potential to customize language learning and meet different learners' needs by creating optimal learning opportunities.

    “AI has the potential to customize language learning and meet different learners’ needs by creating optimal learning opportunities [3].”
    Quote in the paperSubstantial claim0 of 1 sources checked
    • cites [3] Nishant R. Kennedy M. Corbett J. Artificial intelligence for sustainability: challenges, opportunities, and a research Agenda Int. J. Inf. Manag. 53 2020 102104

      Not checked in the free run.

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

    Study design and conductreasoning

    The review included only empirical journal articles published in English, integrating an AI application into EFL classes, applicable in higher education, focused on learners' affective factors, and published recently.

    “For inclusion, journal articles needed to be empirical, published in English, integrated with an AI application into EFL classes, applicable in the higher education sector, focused on learners' affective factors, and published recently owing to the rapid evolution of AI.”
    Quote in the paperSubstantial claim

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

    Study design and conductreasoning

    The databases chosen were IEEE, Wiley, Web of Science, Sage, ProQuest, Springer, and Science Direct, selected based on their contributions to language education and AI.

    “The second step involved executing search queries in the chosen databases, which were IEEE, Wiley, Web of Science, Sage, ProQuest, Springer, and Science Direct. The databases were chosen based on their contributions to language education (e.g., Wiley) and AI (e.g., IEEE).”
    Quote in the paperNot a substantial claim

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    Study design and conductreasoning

    No limitations were set on the year of publication to broaden the initial search.

    “To broaden the initial search, no limitations were set on the year of publication.”
    Quote in the paperNot a substantial claim

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

    Study design and conductown data

    The analysis was carried out using Microsoft Excel, and studies were categorized into four domains: motivation, attitude, learning engagement, and learning anxiety.

    “To evaluate the chosen articles, the author developed criteria, and the analysis was carried out using Microsoft Excel. During the process, the studies were categorized into four domains: motivation, attitude, learning engagement, and learning anxiety.”
    Quote in the paperNot a substantial claim

  • Classified as probably not a substantial claim.

    Study design and conductnone given

    Studies were selected by searching for terms-'AI,' 'artificial intelligence,' 'EFL,' 'ESL,' 'motivation,' 'attitude,' 'learning engagement,' 'learning anxiety,' 'affective factors' and 'higher education'-in the articles' titles and abstracts.

    “Studies were selected by searching for suitable terms—“AI,” “artificial intelligence,” “EFL,” “ESL,” “motivation,” “attitude,” “learning engagement,” “learning anxiety,” “affective factors” and “higher education”—in the articles' titles and abstracts.”
    Quote in the paperSubstantial claim

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

    Study design and conductnone given

    The search was narrowed to include articles written in English, and titles and abstracts were scrutinized for relevance to AI applications used to enhance EFL learners' affective factors in higher education.

    “The search was narrowed to include articles written in English. Additionally, the titles and abstracts of the articles were scrutinized for their relevance to AI applications used to enhance EFL learners’ affective factors in higher education.”
    Quote in the paperSubstantial claim

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

    Study design and conductnone given

    The authors reviewed the methodology employed in each study and summarized the findings of the selected articles to develop an adequate analytical framework.

    “Furthermore, the authors reviewed the methodology employed in each study and summarized the findings of the selected articles to develop an adequate analytical framework.”
    Quote in the paperNot a substantial claim
    • Rests on an assumption: The included studies' findings are reliable enough to synthesize without a formal risk-of-bias assessment.

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

    Study design and conductcitation

    The review excluded articles not published in English, not integrating AI applications, applied in K-12 education, focused on developing the four basic skills, grammar, vocabulary, or editorials/opinion articles.

    “On the other hand, articles that were not considered were published in other languages; did not integrate any of the AI applications; were applied in K–12 education; focused on developing the four basic skills, grammar, vocabulary; or were editorials or opinion articles.”
    Quote in the paperSubstantial claim

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

    Study design and conductnone given

    The studies were organized into meaningful subcategories based on study purpose, the examined AI tools and applicability in higher education to learn EFL.

    “In addition, the studies were organized into meaningful subcategories based on study purpose, the examined AI tools and applicability in higher education to learn EFL.”
    Quote in the paperNot a substantial claim

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

    Study design and conductcitation

    Editorials and opinion articles were excluded because they present the author's subjective perspective and lack methodological rigor, and including them may affect the findings of the systematic review.

    “Editorials and opinion articles were excluded as they present the author's subjective perspective and lack methodological rigor [19]. Besides, [40] believes that including these potentially biased studies may affect the findings of the systematic review.”
    Quote in the paperNot a substantial claim0 of 2 sources checked
    • cites [19] Zhai C. A systematic review on artificial intelligence dialogue systems for enhancing English as foreign language students' interactional competence in the university Comput. Educ.: Artif. Intell. 2023 100134

      Not checked in the free run.

    • cites [40] Firmstone J. Editorial Journalism and Newspapers' Editorial Opinions 2019 Oxford research encyclopedia of communication 10.1093/acrefore/9780190228613.013.803

      Not checked in the free run.

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

    Premisecitation

    Attitude can help predict a person's acceptance of novel technologies and applications.

    “Attitude can help to predict his or her acceptance of novel technologies and applications [11].”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites [11] Brown H.D. Principles of Language Learning and Teaching vol. 4 2000 Longman New York

      Not checked in the free run.

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

    Premisecitation

    The use of AI in education is a cause of grave concern worldwide, especially after UNESCO's 2019 consensus.

    “However, the use of AI in education is a cause of grave concern worldwide, especially after UNESCO's 2019 consensus.”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites UNESCO's 2019 consensus

      Not checked in the free run.

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

    Interpretationnone given

    The introduction of chatbot systems in the educational sector has the potential to provide personalized EFL learning experiences by adapting to learners' needs and providing learning materials anywhere and anytime.

    “In addition, the introduction of chatbot systems in the educational sector has the potential to provide personalized EFL learning experiences, by adapting to learners’ needs and providing learning materials anywhere and anytime.”
    Quote in the paperNot a substantial claim

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

    Premisecitation

    Zawacki-Richter et al. (2019) noted that more research is needed from educators and learning designers on how to integrate AI applications throughout the student lifecycle.

    “In a systematic review, Zawacki-Richter et al. (2019) noted, “More research is needed from educators and learning designers on how to integrate AI applications throughout the student lifecycle” (p. 22), which supports the findings of the current study.”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites Zawacki-Richter et al. (2019) source

      Not checked in the free run.

  • May combine two claims.

    Interpretationcitation

    The currently available AI applications provide pedagogical opportunities to design intelligent learning systems that scaffold learning; provide adaptive learning experiences; and enable interactive and personalized learning opportunities to foster motivation, engagement, and positive attitudes.

    “The currently available AI applications provide pedagogical opportunities to design intelligent learning systems that scaffold learning; provide adaptive learning experiences; and enable interactive and personalized learning opportunities to foster motivation, engagement, and positive attitudes [17].”
    Quote in the paperSubstantial claim0 of 1 sources checked
    • cites [17] Fahimirad M. Kotamjani S.S. A review on application of artificial intelligence in teaching and learning in educational contexts Int. J. Learn Dev. 8 4 2018 106 118 source

      Not checked in the free run.

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

    Interpretationreasoning

    Given the functions of AI tools, it is most likely that these technologies will significantly and positively influence language learning achievement, engagement, motivation, and attitudes.

    “Given the functions of AI tools, it is most likely that these technologies will significantly and positively influence language learning achievement, engagement, motivation, and attitudes.”
    Quote in the paperNot a substantial claim

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

    Interpretationcitation

    The absence of such details might have affected the results and is a major flaw affecting the accuracy and feasibility of the study.

    “The absence of such details might have affected the results and is a major flaw affecting the accuracy and feasibility of the study [58].”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites [58] Creswell J.W. Creswell J.D. Research Design: Qualitative, Quantitative and Mixed Methods Approaches fifth ed. 2018 SAGE Los Angeles

      Not checked in the free run.

  • Probably not a substantial claim: may not pass S2 (checkable). May combine two claims.

    Interpretationreasoning

    Considering EFL learners' positive attitude toward AI-integrated EFL classes, it is reasonable to suppose that learners will embrace the use of AI applications in learning EFL.

    “Considering EFL learners’ positive attitude toward AI-integrated EFL classes, it is reasonable to suppose that learners will embrace the use of AI applications in learning EFL.”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Interpretationreasoning

    AI technologies are effective in fostering the acquisition of knowledge and the development of language skills.

    “This indicates that AI technologies are effective in fostering the acquisition of knowledge and the development of language skills.”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Interpretationreasoning

    These AI technologies have the potential to positively impact various aspects of EFL learning, such as improving motivation, engagement, and attitudes and reducing anxiety in EFL higher education.

    “It is evident that these AI technologies have the potential to positively impact various aspects of EFL learning, such as improving motivation, engagement, and attitudes and reducing anxiety in EFL higher education.”
    Quote in the paperSubstantial claim

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

    Interpretationreasoning

    Students may become demotivated by the use of inappropriate learning resources or if they find using AI technologies challenging.

    “Students may become demotivated by the use of inappropriate learning resources or if they find using AI technologies challenging.”
    Quote in the paperSubstantial claim

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

    Interpretationreasoning

    These benefits have occurred for competent learners, as AI technology has not yet been well developed for integration into the learning process.

    “However, these benefits have occurred for competent learners, as AI technology has not yet been well developed for integration into the learning process.”
    Quote in the paperNot a substantial claim
56 of 56

  • The paper relies on this without support.

    The 21 included studies are representative of the literature on AI integration in EFL higher education.

    “This resulted in the inclusion of 21 studies in the final analysis see Table 1.”
    “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.”

  • The paper relies on this without support.

    The affective outcomes reported in the included studies can be attributed to the AI applications rather than other instructional or contextual factors.

    “The use of chatbots in higher education fostered learners' motivation, eagerness, and confidence ([[25], [26], [27],31,41,42]);”

  • The paper relies on this without support.

    The search terms and databases used identified all relevant studies on AI integration in EFL higher education.

    “Studies were selected by searching for suitable terms—“AI,” “artificial intelligence,” “EFL,” “ESL,” “motivation,” “attitude,” “learning engagement,” “learning anxiety,” “affective factors” and “higher education”—in the articles' titles and abstracts.”

  • The paper relies on this without support.

    The included studies' findings are reliable enough to synthesize without a formal risk-of-bias assessment.

    “Furthermore, the authors reviewed the methodology employed in each study and summarized the findings of the selected articles to develop an adequate analytical framework.”
4 of 4

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?

  • Twijri and Alghizzi's systematic review of 22 empirical studies found consistent evidence that AI applications-especially chatbots and intelligent tutors-can enhance emotional engagement and reduce anxiety when effectively implemented.

    “Drawing from 22 empirical studies, they find consistent evidence that AI applications-especially chatbots and intelligent tutors-can enhance emotional engagement and reduce anxiety when effectively implemented.”

    From AI-Integrated Scaffolding to Enhance Agency and Creativity in K-12 English Language Learners: A Systematic Review (2025) · cites this paper as [15]

    The Discussion reports that AI chatbots improved EFL learners’ engagement and could reduce anxiety, but the Results (Learning anxiety) note a study in which anxiety did not decline. The Methods table lists 21 reviewed studies, not 22, and the review discusses learning engagement rather than measuring emotional engagement as a distinct outcome. Page numbers are unavailable in our copy. (LLM, conf=0.87)

    Experimental — accuracy not yet measured

  • Twijri and Alghizzi's review focuses primarily on general EFL instruction and affective outcomes, with minimal attention to the cognitive and compositional dimensions of writing.

    “While these findings underscore AI's value in shaping learners' emotional responses, the review focuses primarily on general EFL instruction and affective outcomes, with minimal attention to the cognitive and compositional dimensions of writing.”

    From AI-Integrated Scaffolding to Enhance Agency and Creativity in K-12 English Language Learners: A Systematic Review (2025) · cites this paper as [15]

Statistics recomputed

Every reported test result, recomputed from its test statistic and degrees of freedom. A result shows as not adding up only once an independent check has confirmed it.

  • ConsistentF(2, 24) = 3.48reported p < .05 · recomputed p = .047

    “F(2,24) = 3.48, p < .05”

  • ConsistentF(2, 24) = 4.97reported p < .05 · recomputed p = .016

    “F(2,24) = 4.97, p < .05”

  • ConsistentF(2, 24) = 2.88reported p < .1 · recomputed p = .076

    “F(2,24) = 2.88, p < .1”

  • ConsistentF(2, 36) = 7.139reported p < .05 · recomputed p = .002

    “F(2, 36) = 7.139, p < .05”

  • ConsistentF(2, 36) = 3.472reported p < .1 · recomputed p = .042

    “F(2, 36) = 3.472, p < .1”

  • ConsistentF(2, 36) = 6.466reported p < .05 · recomputed p = .004

    “F(2, 36) = 6.466, p < .05”

6 of 6

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.

  • Yin study is given conflicting publication years

    Minor

    The results identify the Yin et al. study as published in 2019, whereas both the reviewed-articles table and its reference list date it to 2021.

  • Chatbots are described both as learning partners and as only tutors or assistants

    Minor

    The limitations section says the specified AI agents, including chatbots, were used only as tutors and assistants. The discussion also assigns chatbots a distinct learning-partner role.

  • A reviewed study reports no integrated AI technology

    Minor

    The inclusion criteria require studies to integrate an AI application into EFL classes, but Table 1 records "No" for the integrated technology in the included Aljohani study.

3 of 3

Cites

Flagged first, then by citations

2 of the 56 references couldn’t be matched to a known paper.

Research works printed but not linked: 5

  1. Arnold, 2020, Affective factors and language learning, Language education and emotions: Research into emotions and language learners, language teachers and educational processes, 18
  2. Ormrod, 2010, How motivation affects learning and behavior, Educ. Week
  3. Brown, 2000, vol. 4
  4. Kim, 2021, vol. 21, 712
  5. Turan, 2018, Role of affective factors in foreign language learning, Journal of Educational & Instructional Studies in the World, 8

Cited by

Sorted by citations

Related

Authors
AlTwijri, L., & Alghizzi, T. M.
Affiliations
Imam Mohammad ibn Saud Islamic University (SA)
Corresponding author
  • AlTwijri, Lujain
  • Alghizzi, Talal Musaed
ORCID
Venue
Heliyon
Publisher
Elsevier BV
Published
2024-05
Volume
10
Issue
10
Pages
e31053
ISSN
2405-8440 (ISSN-L)
DOI
10.1016/j.heliyon.2024.e31053
PMC
PMC11109823
OpenAlex
W4396806090
Semantic Scholar
118622378682a60192cd83b86f7099306913c0b5
Cited by
93
References
56
Citations by year
2026: 43 · 2025: 41 · 2024: 9
FWCI
21.45
Type
journal article
Language
en
Open access
Licence
Locations
  • Heliyon (publishedVersion, cc-by-nc-nd)
  • PubMed Central (publishedVersion, cc-by-nc-nd)
  • PubMed (publishedVersion)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
Topics
  • Social Sciences › Arts and Humanities › Language and Linguistics › EFL/ESL Teaching and Learning
  • Physical Sciences › Computer Science › Information Systems › Artificial Intelligence in Education
  • Physical Sciences › Computer Science › Information Systems › English Language Learning and Teaching
Keywords
artificial intelligence in language teaching, English as a foreign language, emotional factors, student motivation, student engagement, student attitudes, student anxiety, higher education language learning

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Claims read by deepseek-v4.1-flash under definition version 3 (extract-v3) on 2026-10-09.

Classified by jev-1.13-20260917 (gold-guideline-v0.2) on 2026-10-09.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

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