Artificial intelligence-enhanced self-paced learning in English as a foreign language: A nonlinear dynamic and self-determination framework for optimizing postgraduate linguistic proficiency—a mixed-methods randomized controlled trial

Abstract

This empirical study examines the effectiveness of artificial intelligence-enhanced personalized language learning interventions—tailored content adaptation, self-paced progression, and targeted weakness intervention—on academic writing proficiency, vocabulary acquisition, and grammatical accuracy among 540 Chinese postgraduate learners of English as a foreign language. Utilizing a pretest–posttest randomized controlled design, participants were assigned to three experimental groups (each receiving a distinct artificial intelligence-driven intervention) or a control group (traditional instruction). Quantitative analyses (multivariate analysis of covariance/analysis of covariance) demonstrated significant improvements across all learning outcomes for artificial intelligence groups compared with controls (p < .001), with the most pronounced effect sizes observed in the self-paced learning group (Cohen’s d = 2.71–16.43). Posttest indicated this group were substantially higher (academic writing: M = 7.09; vocabulary: M = 57.36; grammar: M = 48.21) compared with controls (M = 5.16, 29.72, 18.22, respectively), accounting for 68.3–98.0% of variance (partial η²). Thematic analysis of qualitative data (surveys, interviews) corroborated these findings, with 89% of participants in the self-paced group reporting enhanced autonomy and reduced cognitive load, in alignment with self-determination theory. Triangulation revealed robust associations between quantitative gains and qualitative themes of motivation, adaptability, and learner satisfaction. These results highlight the superiority of artificial intelligence-driven self-paced learning over static interventions, challenging the prevailing emphasis on content adaptation as the primary driver of proficiency. The study offers practical recommendations for integrating AI to optimize learner-centered language education while addressing technical and pedagogical challenges.

Keywords

artificial Intelligence-enhanced language learning personalized learning self-paced learning academic writing proficiency vocabulary acquisition grammatical accuracy

Get full access to this article

View all access options for this article.

References

Almuhanna

M.A.

(2025). Teachers’ perspectives of integrating AI-powered technologies in K-12 education for creating customized learning materials and resources. Education and Information Technologies, 30, 10343–10371. https://doi.org/10.1007/s10639-024-13257-y

Alzahrani

S.A.

(2025). The future of AI in language education: Trends and predictions. In Naseer

Dulloo

Abdul Kader Jilani

Shaheen

(Eds.), Bridging global divides for transnational higher education in the AI era (pp. 309–332). IGI Global Scientific Publishing.

American Educational Research Association, American Psychological Association, & National Council on Measurement in Education. (2014). Standards for educational and psychological testing. American Educational Research Association.

Chai

C.S.

Zhou

Shen

Zheng

Chen

(2023). Modeling English teachers’ behavioral intention to use artificial intelligence in middle schools. Education and Information Technologies, 28(5), 5187–5208. https://doi.org/10.1007/s10639-022-11286-z

Bahari

(2019). FonF practice model from theory to practice: CALL via focus on form approach and nonlinear dynamic motivation to develop listening and speaking proficiency. Computers & Education, 130(3), 40–58. https://doi.org/10.1016/j.compedu.2018.11.009

Bahari

Han

Strzelecki

(2025). Integrating CALL and AIALL for an interactive pedagogical model of language learning. Education and Information Technologies, 30, 14305–14333. https://doi.org/10.1007/s10639-025-13388-w

Bax

(2003). CALL—past, present and future. System, 31(1), 13–28.

Bond

T.G.

Fox

C.M.

(2015). Applying the Rasch model: Fundamental measurement in the human sciences (3rd ed.). Routledge.

Braun

Clarke

(2006). Using thematic analysis in psychology. Qualitative Research in Psychology, 3(2), 77–101.

10.

Brown

J. D.

Coombe

(2015). The Cambridge guide to research in language teaching and learning. Cambridge University Press.

11.

Cao

T.X.L.

(2023). Benefits and challenges of using LMS in blended learning: Views from EFL teachers and students at a Vietnamese public university. International Journal of TESOL & Education, 3(3), 78–100. https://doi.org/10.54855/ijte.23335

12.

Chapelle

C. A.

(2001). Computer applications in second language acquisition. Cambridge University Press.

13.

Chen

Gong

(2025). The role of AI-assisted learning in academic writing: A mixed-methods study on Chinese as a second language students. Education Sciences, 15(2), 141. https://doi.org/10.3390/educsci15020141

14.

Chen

Lin

C. H.

Chen

(2024). Extramural ICT factors impact adolescents’ academic performance and well-being differently: Types of self-regulated learners also matter. Education and Information Technologies, 29(15), 20459–20491.

15.

Chen

Lin

(2020). Artificial intelligence in Education: A review. IEEE Access, 8, 75264–75278.

16.

Cizrelioğlu

İ.

Aydin

. (2025). Using artificial intelligence in EFL learning among multilingual young learners. In Sanmugam

Edwards

Mohd Barkhaya

Khlaif

(Eds.), Fostering inclusive education with AI and emerging technologies (pp. 303–322). IGI Global Scientific Publishing.

17.

Dan

Mohamed

Yue

(2023). A review on the effect of integrating AI-based technology into flipped learning. Innovative Teaching and Learning Journal, 7(2), 41–50. https://doi.org/10.11113/itlj.v7.133

18.

Dandachi

I. E.

(2024). AI‑powered personalized learning: Toward sustainable education. In El‑Chaarani

Dandachi

I. E.

El Nemar

El Abiad

(Eds.), Navigating the intersection of business, sustainability and technology (pp. 109–118). Springer Nature Singapore.

19.

Darwin Rusdin

Mukminatien

Suryati

Laksmi

E.D.

Marzuki . (2024). Critical thinking in the AI era: An exploration of EFL students’ perceptions, benefits, and limitations. Cogent Education, 11(1), 2290342. https://doi.org/10.1080/2331186X.2023.2290342

20.

Daulay

S.F.

Ginting

(2024). Transforming English language teaching through AI: Evaluation of the strategies and potential of artificial intelligence applications in EFL. IDEAS: Journal on English Language Teaching and Learning, Linguistics and Literature, 12(1), 376–395. https://doi.org/10.24256/ideas.v12i1.4907

21.

Deci

E. L.

Ryan

R. M.

(1985). The general causality orientations scale: Self-determination in personality. Journal of Research in Personality, 19(2), 109–134.

22.

Deci

E. L.

Olafsen

A. H.

Ryan

R. M.

(2017). Self-determination theory in work organizations: The state of a science. Annual Review of Organizational Psychology and Organizational Behavior, 4, 19–43.

23.

Deci

E.L.

Ryan

R.M.

(2000). The “what” and “why” of goal pursuits: Human needs and the self-determination of behavior. Psychological Inquiry, 11(4), 227–268. https://doi.org/10.1207/S15327965PLI1104_01

24.

Denzin

N. K.

(1978). The research act: A theoretical introduction to sociological methods (2nd ed.). McGraw-Hill.

25.

Ding

Zou

(2024). Automated writing evaluation systems: A systematic review of Grammarly, Pigai, and Criterion with a perspective on future directions in the age of generative artificial intelligence. Education and Information Technologies, 29, 14151–14203. https://doi.org/10.1007/s10639-023-12402-3

26.

Eswaran

Murali

Eswaran

(2025). AI‑powered language teaching and learning: Innovations and challenges. In Stevkovska

Klemenchich

Kavaklı Ulutaş

(Eds.), Reimagining intelligent computer‑assisted language education (pp. 55–92). IGI Global.

27.

Godwin-Jones

(2011). Mobile apps for language learning. Language Learning & Technology, 15(2), 2–11.

28.

Godwin-Jones

(2017). Smartphones and language learning. Language Learning & Technology, 21(2), 3–17.

29.

Holmes

Porayska-Pomsta

Holstein

, et al. (2022). Ethics of AI in education: Towards a community-wide framework. International Journal of Artificial Intelligence in Education, 32, 504–526.

30.

Huang

Dou

(2024). AI-enhanced task-based language teaching: Fostering personalized college English learning. Frontiers in Educational Research, 7(10), 204–209. https://doi:10.25236/FER.2024.071033

31.

Han

(2023). A systematic review of conversational AI in language education: Focusing on the collaboration with human teachers. Journal of Research on Technology in Education, 55(1), 48–63. https://doi.org/10.1080/15391523.2022.2142873

32.

Karimi

M. N.

Ashkani

(2022). Situation-model representations of conflicting textual information in L2 readers: The effects of prior beliefs and L2 proficiency. Language Awareness, 32(2), 323–341.

33.

Kasneci

Sessler

Küchemann

Bannert

Dementieva

Fischer

Gasser

Groh

Günnemann

Hüllermeier

Krusche

Kutyniok

Michaeli

Nerdel

Pfeffer

Poquet

Sailer

Schmidt

Seidel

Stadler

Weller

Kuhn

Kasneci

(2023). ChatGPT for good? On opportunities and challenges of large language models for education. Learning and Individual Differences, 103, 102274.

34.

Park

Ryu

Kim

(2024). Alone but not isolated: Social presence and cognitive load in learning with 360 virtual reality videos. Frontiers in Psychology, 15, 1305477.

35.

Kim

(2024). Leading teachers’ perspective on teacher-AI collaboration in education. Education and Information Technologies, 29, 8693–8724. https://doi.org/10.1007/s10639-023-12109-5

36.

Law

(2024). Application of generative artificial intelligence (GenAI) in language teaching and learning: A scoping literature review. Computers and Education Open, 6, 100174. https://doi.org/10.1016/j.caeo.2024.100174

37.

Levy

(1997). Computer-assisted language learning: Context and conceptualization. Oxford University Press.

38.

Lin

C.C.

Huang

A.Y.

O.H.

(2023). Artificial intelligence in intelligent tutoring systems toward sustainable education: A systematic review. Smart Learning Environments, 10(1), 41. https://doi.org/10.1186/s40561-023-00260-y

39.

Luckin

Cukurova

Kent

du Boulay

(2022). Empowering educators to be AI-ready. Computers and Education: Artificial Intelligence, 3, 100076. https://doi.org/10.1016/j.caeai.2022.100076

40.

Marzuki Widiati

Rusdin

Darwin Indrawati

. (2023). The impact of AI writing tools on the content and organization of students’ writing: EFL teachers’ perspective. Cogent Education, 10(2), 2236469. https://doi.org/10.1080/2331186X.2023.2236469

41.

Mohamed

A.M.

(2024). Exploring the potential of an AI-based Chatbot (ChatGPT) in enhancing English as a Foreign Language (EFL) teaching: Perceptions of EFL Faculty Members. Education and Information Technologies, 29(3), 3195–3217. https://doi.org/10.1007/s10639-023-11917-z

42.

Mohebbi

(2025). Enabling learner independence and self-regulation in language education using AI tools: A systematic review. Cogent Education, 12(1), 2433814. https://doi.org/10.1080/2331186X.2024.2433814

43.

Morady Moghaddam

Esmaeilpour

Ranjbaran

(2024). Insights into mobile assisted language learning research in Iran: A decade review (2010–2023). Education and Information Technologies, 30(2), 2155–2181.

44.

Muftah

(2023). Data-driven learning (DDL) activities: do they truly promote EFL students’ writing skills development?. Education and Information Technologies, 28, 13179–13205. https://doi.org/10.1007/s10639-023-11620-z

45.

Muthmainnah

Cardoso

Alsbbagh

Y. A. M. R.

Al Yakin

Apriani

(2024). Advancing sustainable learning by boosting student self‑regulated learning and feedback through AI‑driven personalized in EFL education. In Al‑Abrrow

Valeri

Bayram

G. E.

Muhsen

Y. R.

(Eds.), Explainable artificial intelligence in the digital sustainability administration: Proceedings of the 2nd international conference on explainable artificial intelligence in the digital sustainability administration (AIRDS 2024) (Lecture Notes in Networks and Systems, Vol. 1033, pp. 36–54). Springer Nature Switzerland.

46.

Nation

I. S. P.

(2022). Learning vocabulary in another language (3rd ed.). Cambridge University Press.

47.

Piaget

(1970). Science of education and the psychology of the child. Orion Press.

48.

Qian

(2025). Pedagogical applications of generative AI in higher education: A systematic review of the field. TechTrends, 69, 1105–1120.

49.

Rintaningrum

(2023). Technology integration in English language teaching and learning: Benefits and challenges. Cogent Education, 10(1), 2164690. https://doi.org/10.1080/2331186X.2022.2164690

50.

Ross

J.A.

Bruce

C.D.

(2007). Teacher self-assessment: A mechanism for facilitating professional growth. Teaching and teacher Education, 23(2), 146–159. https://doi.org/10.1016/j.tate.2006.04.035

51.

Saadé

R.G.

Zhang

Wang

Liu

Guan

(2023). Challenges and opportunities in the Internet of intelligence of things in higher education—towards bridging theory and practice. IoT, 4(3), 430–465. https://doi.org/10.3390/iot4030019

52.

Saimon

Mtenzi

Lavicza

Fenyvesi

Arnold

Diego-Mantecón

J. M.

(2024). Applying the 6E learning by design model to support student teachers to integrate artificial intelligence applications in their classroom. Education and Information Technologies, 29(17), 23937–23954.

53.

Salmanpour

Tabatabaei

Salehi

Yunus

M. M.

(2024). Impact of Duolingo language program as an artificial intelligence tool on Iranian EFL teachers’ work engagement. In 2024 10th International Conference on Artificial Intelligence and Robotics (QICAR) (pp. 350–358). IEEE.

54.

Santilli

Ceccacci

Mengoni

Giaconi

(2025). Virtual vs. traditional learning in higher education: A systematic review of comparative studies. Computers & Education, 227, 105214.

55.

Shadish

W. R.

Cook

T. D.

Campbell

D. T.

(2002). Statistical conclusion validity and internal validity. In Cook

T. D.

Campbell

D. T.

Shadish

(Eds.), Experimental and quasi-experimental designs for generalized causal inference (pp. 103–134). Houghton Mifflin.

56.

Skinner

B. F.

(1957). The experimental analysis of behavior. American Scientist, 45(4), 343–371

57.

Slamet

(2024). Potential of ChatGPT as a digital language learning assistant: EFL teachers’ and students’ perceptions. Discover Artificial Intelligence, 4(1), 46. https://doi.org/10.1007/s44163-024-00143-2

58.

Son

J.B.

Ružić

N.K.

Philpott

(2023). Artificial intelligence technologies and applications for language learning and teaching. Journal of China Computer-Assisted Language Learning, 5(1), 94–112. https://doi.org/10.1515/jccall-2023-0015

59.

Stockwell

(2008). Investigating learner preparedness for and usage patterns of mobile learning. ReCALL, 20(3), 253–270.

60.

Stockwell

(Ed.). (2012). Computer-assisted language learning: Diversity in research and practice. Cambridge University Press.

61.

Üstünbaş

. (2024). EFL learners’ views about the use of artificial intelligence in giving corrective feedback on writing: A case study. In Çetin Köroğlu

Çakır

(Eds.), Fostering foreign language teaching and learning environments with contemporary technologies (pp. 115–133). IGI Global.

62.

Vygotsky

L.S.

(1978). Mind in society: The development of higher psychological processes. Harvard University Press.

63.

Wang

(2024). AI-driven autonomous interactive English learning language tutoring system. Journal of Computational Methods in Science and Engineering, 25(2), 1155–1166. https://doi.org/10.1177/14727978241296719

64.

Warschauer

(1996). Comparing face-to-face and electronic discussion in the second language classroom. CALICO Journal, 13(2–3), 7–26.

65.

Warschauer

Healey

(1998). Computers and language learning: An overview. Language Teaching, 31(2), 57–71.

66.

Wei

(2023). Artificial intelligence in language instruction: impact on English learning achievement, L2 motivation, and self-regulated learning. Frontiers in Psychology, 14, 1261955. https://doi.org/10.3389/fpsyg.2023.1261955

67.

Yang

Chiu

M. M.

Yan

(2021). The power of teacher feedback in affecting student learning and achievement: insights from students’ perspective. Educational Psychology, 41(7), 821–824.

68.

Zhang

Lee

Ali

DiPaola

Cheng

Breazeal

(2023). Integrating ethics and career futures with technical learning to promote AI literacy for middle school students: An exploratory study. International Journal of Artificial Intelligence in Education, 33(2), 290–324. https://doi.org/10.1007/s40593-022-00293-3

69.

Zhang

Hyland

(2023). The role of digital literacy in student engagement with automated writing evaluation (AWE) feedback on second language writing. Computer Assisted Language Learning, 38(5–6), 1060–1085. https://doi.org/10.1080/09588221.2023.2256815

Supplementary Material

Please find the following supplemental material available below.

For Open Access articles published under a Creative Commons License, all supplemental material carries the same license as the article it is associated with.

For non-Open Access articles published, all supplemental material carries a non-exclusive license, and permission requests for re-use of supplemental material or any part of supplemental material shall be sent directly to the copyright owner as specified in the copyright notice associated with the article.

0.00 MB

0.08 MB