EXPLORING AUTONOMOUS LANGUAGE LEARNING STRATEGIES AMONG EFL UNIVERSITY STUDENTS IN DIGITAL ERA
Downloads
Digital technologies have reshaped language learning by providing EFL university students with access to online resources, mobile applications, artificial intelligence tools, and interactive platforms. This study aimed to identify the autonomous language learning strategies employed by EFL university students in the digital era and examine the factors associated with their use. A quantitative cross-sectional survey was conducted with 250 undergraduate students selected through proportionate stratified random sampling. Data were collected using a validated questionnaire covering cognitive, metacognitive, memory, compensation, affective, social, and digital-resource management strategies, then analyzed through descriptive statistics, correlation, t-tests, analysis of variance, and multiple regression. The findings showed that students used autonomous learning strategies at a high level, with metacognitive strategies receiving the highest mean score, followed by digital-resource management and cognitive strategies. Affective strategies were the least frequently employed. Digital literacy, motivation, and daily digital-learning duration were significantly related to strategy use, while digital literacy emerged as the strongest predictor. The study concludes that learner autonomy in digital contexts depends not only on technological access but also on students’ capacity to plan, evaluate, regulate, and ethically integrate digital resources. Universities should therefore provide explicit instruction in strategic learning, critical digital literacy, and responsible artificial intelligence use.
Al-Bogami, R. M., & Alahmadi, N. A. (2025). Effects of an AI-based reading progress tool on third-grade EFL learners’ oral reading fluency. Computers and Education Open, 9, 100283. https://doi.org/https://doi.org/10.1016/j.caeo.2025.100283
Al Fraidan, A., & Al-Harazi, E. M. (2023). Using social media platforms to prepare for examinations post Covid-19: The case of saudi university EFL learners. Heliyon, 9(11), e21320. https://doi.org/https://doi.org/10.1016/j.heliyon.2023.e21320
Alrashdan, I., El-Migdady, L., & Mitib Altakhaineh, A. R. (2024). Attitudes of Jordanian school students toward dictionaries. Heliyon, 10(21), e39499. https://doi.org/https://doi.org/10.1016/j.heliyon.2024.e39499
Arani, S. M. N. (2025). Enhancing communication and reducing anxiety: The role of problem-based learning in EFL learners’ psychological development. Ampersand, 15, 100245. https://doi.org/https://doi.org/10.1016/j.amper.2025.100245
Bailey, D. R., Almusharraf, N., Almusharraf, A., du Plessis, W., & Hatcher, R. (2023). Activity choice and perceptions: Influencing factors to learning outcomes within videoconference-enhanced LMS courses. System, 116, 103079. https://doi.org/https://doi.org/10.1016/j.system.2023.103079
Bobrowicz, K., López-Pernas, S., Teuber, Z., Saqr, M., & Greiff, S. (2024). Prospects in the field of learning and individual differences: Examining the past to forecast the future using bibliometrics. Learning and Individual Differences, 109, 102399. https://doi.org/https://doi.org/10.1016/j.lindif.2023.102399
Chang, W.-L., & Sun, J. C.-Y. (2024). Evaluating AI’s impact on self-regulated language learning: A systematic review. System, 126, 103484. https://doi.org/https://doi.org/10.1016/j.system.2024.103484
Chu, X. (2025). More ICT, more creativity? A fsQCA study on configurational pathways to students’ creative thinking in PISA 2022. International Journal of Educational Research, 134, 102802. https://doi.org/https://doi.org/10.1016/j.ijer.2025.102802
Cui, Y., Ma, Z., Wang, L., Yang, A., Liu, Q., Kong, S., & Wang, H. (2023). A survey on big data-enabled innovative online education systems during the COVID-19 pandemic. Journal of Innovation & Knowledge, 8(1), 100295. https://doi.org/https://doi.org/10.1016/j.jik.2022.100295
Dahri, N. A., Yahaya, N., Al-Rahmi, W. M., Aldraiweesh, A., Alturki, U., Almutairy, S., Shutaleva, A., & Soomro, R. B. (2024). Extended TAM based acceptance of AI-Powered ChatGPT for supporting metacognitive self-regulated learning in education: A mixed-methods study. Heliyon, 10(8), e29317. https://doi.org/https://doi.org/10.1016/j.heliyon.2024.e29317
Fereydoonfar, M. (2025). Constrained yet strategic linguistic investment: Iranian English learners navigating identities, ideologies and capital forms amid religious nationalism. English Teaching: Practice & Critique, 24(4), 522–539. https://doi.org/https://doi.org/10.1108/ETPC-04-2025-0075
Han, I. (2025). Development of self-directed learning readiness of English language learners through mobile-assisted problem-based learning. International Journal of Educational Research, 133, 102729. https://doi.org/https://doi.org/10.1016/j.ijer.2025.102729
Jiang, Y., & Vásquez, C. (2025). Sharing as informal teaching: Identity construction of an English learner/teacher microcelebrity on Douyin. Discourse, Context & Media, 65, 100888. https://doi.org/https://doi.org/10.1016/j.dcm.2025.100888
Lee, S., & Jeon, J. (2024). Teacher agency and ICT affordances in classroom-based language assessment: The return to face-to-face classes after online teaching. System, 121, 103218. https://doi.org/https://doi.org/10.1016/j.system.2023.103218
Li, X., Zhang, J., & Yang, J. (2024). The effect of computer self-efficacy on the behavioral intention to use translation technologies among college students: Mediating role of learning motivation and cognitive engagement. Acta Psychologica, 246, 104259. https://doi.org/https://doi.org/10.1016/j.actpsy.2024.104259
Lin, C.-C. (2024). Challenging the future: Development of students’ multimodal competencies by designing an online exhibition. Entertainment Computing, 48, 100614. https://doi.org/https://doi.org/10.1016/j.entcom.2023.100614
Lin, C.-H., Zhou, K., Li, L., & Sun, L. (2025). Integrating generative AI into digital multimodal composition: A study of multicultural second-language classrooms. Computers and Composition, 75, 102895. https://doi.org/https://doi.org/10.1016/j.compcom.2024.102895
Liu, H., Fan, J., & Xia, M. (2025). Exploring individual’s emotional and autonomous learning profiles in AI-enhanced data-driven language learning: An expanded sor perspective. Learning and Individual Differences, 122, 102753. https://doi.org/https://doi.org/10.1016/j.lindif.2025.102753
Liu, M., Zhang, L. J., & Zhang, D. (2025). Enhancing student GAI literacy in digital multimodal composing through development and validation of a scale. Computers in Human Behavior, 166, 108569. https://doi.org/https://doi.org/10.1016/j.chb.2025.108569
Liu, Y., & Chang, P. (2024). Exploring EFL teachers’ emotional experiences and adaptive expertise in the context of AI advancements: A positive psychology perspective. System, 126, 103463. https://doi.org/https://doi.org/10.1016/j.system.2024.103463
Long, Q., Li, S., An, R., Yasmin, F., & Akbar, A. (2025). Deep learning as a bridge between intercultural sensitivity and learning outcomes: A comparative study of English-medium instruction delivery modes in Chinese higher education. Acta Psychologica, 259, 105410. https://doi.org/https://doi.org/10.1016/j.actpsy.2025.105410
Mohammadi, R. R., Saeidi, M., & Abdollahi, A. (2023). Modelling the interrelationships among self-regulated learning components, critical thinking and reading comprehension by PLS-SEM: A mixed methods study. System, 117, 103120. https://doi.org/https://doi.org/10.1016/j.system.2023.103120
Molefi, R. R., Ayanwale, M. A., Kurata, L., & Chere-Masopha, J. (2024). Do in-service teachers accept artificial intelligence-driven technology? The mediating role of school support and resources. Computers and Education Open, 6, 100191. https://doi.org/https://doi.org/10.1016/j.caeo.2024.100191
Nam, B. H., Yang, Y., & Draeger, R. (2023). Intercultural communication between Chinese college students and foreign teachers through the English corner at an elite language university in Shanghai. International Journal of Intercultural Relations, 93, 101776. https://doi.org/https://doi.org/10.1016/j.ijintrel.2023.101776
Rezai, A., Soyoof, A., & Lee Reynolds, B. (2024). Ecological factors affecting students’ use of informal digital learning of English: EFL teachers’ perceptions. Teaching and Teacher Education, 145, 104629. https://doi.org/https://doi.org/10.1016/j.tate.2024.104629
Sabaté-Dalmau, M., & Moncada-Comas, B. (2023). Exploring the affordances of multimodal competence, multichannel awareness and plurilingual lecturing in EMI. System, 118, 103161. https://doi.org/https://doi.org/10.1016/j.system.2023.103161
Shahini, G., Toroujeni, S. M. H., & Ebrahimi, M. R. (2025). Creative Reading’s Impact on EFL Learners’ Critical Thinking and Reading Comprehension. Thinking Skills and Creativity, 57, 101855. https://doi.org/https://doi.org/10.1016/j.tsc.2025.101855
Shen, L., Wang, S., & Xin, Y. (2025). EFL students’ writing engagement and AI attitude in GenAI-assisted contexts: A mixed-methods study grounded in SDT and TAM. Learning and Motivation, 92, 102168. https://doi.org/https://doi.org/10.1016/j.lmot.2025.102168
Shi, S., & Zhang, H. (2025). EFL students’ motivation predicted by their self-efficacy and resilience in artificial intelligence (AI)-based context: From a self-determination theory perspective. Learning and Motivation, 91, 102151. https://doi.org/https://doi.org/10.1016/j.lmot.2025.102151
Shi, Y., Shen, J., Wei, Y., Chen, M., Wu, M., & Dong, Q. (2025). Understanding the effects of teacher credibility on students’ cognitive engagement in online learning: The mediating roles of academic self-efficacy and motivational regulation strategies. Acta Psychologica, 261, 105896. https://doi.org/https://doi.org/10.1016/j.actpsy.2025.105896
Teng, M. F. (2025). Understanding EFL student writers’ metacognitive awareness in utilizing ChatGPT. System, 135, 103848. https://doi.org/https://doi.org/10.1016/j.system.2025.103848
Tomisu, H., Yamauchi, Y., Ueda, T., Ueda, J., & Yamanaka, T. (2025). Exploring Learner-Action Timing in a Generative AI Supported EFL Ideathon: A KPT Study in Japan. Procedia Computer Science, 270, 5128–5137. https://doi.org/https://doi.org/10.1016/j.procs.2025.09.640
Wang, C., & Canagarajah, S. (2024). Postdigital ethnography in applied linguistics: Beyond the online and offline in language learning. Research Methods in Applied Linguistics, 3(2), 100111. https://doi.org/https://doi.org/10.1016/j.rmal.2024.100111
Wang, X., & Wang, S. (2024). Exploring Chinese EFL learners’ engagement with large language models: A self-determination theory perspective. Learning and Motivation, 87, 102014. https://doi.org/https://doi.org/10.1016/j.lmot.2024.102014
Wang, Y., Xin, Y., & Chen, L. (2024). Navigating the emotional landscape: Insights into resilience, engagement, and burnout among Chinese High School English as a Foreign Language Learners. Learning and Motivation, 86, 101978. https://doi.org/https://doi.org/10.1016/j.lmot.2024.101978
Wuttiphan, N., & Kwangmuang, P. (2025). Designing a ubiquitous learning environment to enhance pre-service Chinese language teachers’ critical writing skills: A developmental research approach. Teaching and Teacher Education, 155, 104921. https://doi.org/https://doi.org/10.1016/j.tate.2024.104921
Yi-Ming Kao, G., Yeh, H.-C., Su, S.-W., Chiang, X.-Z., & Sun, C.-T. (2025). Advancing a Practical Inquiry Model with multi-perspective role-playing to foster critical thinking behavior in e-book reading. Computers & Education, 225, 105185. https://doi.org/https://doi.org/10.1016/j.compedu.2024.105185
Yuan, L., & Liu, X. (2025). The effect of artificial intelligence tools on EFL learners’ engagement, enjoyment, and motivation. Computers in Human Behavior, 162, 108474. https://doi.org/https://doi.org/10.1016/j.chb.2024.108474
Zafar, M. B., Ali, H., & Yasin, T. (2025). Reimagining human creativity and learning in the age of generative AI: A multi-method meta-thematic synthesis. Next Research, 2(4), 100802. https://doi.org/https://doi.org/10.1016/j.nexres.2025.100802
Zarrati, Z., Zohrabi, M., Abedini, H., & Xodabande, I. (2024). Learning academic vocabulary with digital flashcards: Comparing the outcomes from computers and smartphones. Social Sciences & Humanities Open, 9, 100900. https://doi.org/https://doi.org/10.1016/j.ssaho.2024.100900
Zhang, H. (2025). Investigating Chinese English learners’ readiness for Artificial Intelligence (AI) technologies: A theory of planned behavior (TPB) perspective. Learning and Motivation, 91, 102164. https://doi.org/https://doi.org/10.1016/j.lmot.2025.102164
Zhang, Y. (2025). Impact of digital literacy on college students’ English proficiency: The mediating role of learning motivation and the moderating effect of technological self-efficacy. Acta Psychologica, 259, 105452. https://doi.org/https://doi.org/10.1016/j.actpsy.2025.105452
Copyright (c) 2026 Andreas Aris Eko Mulyono, Miku Fujita, Daiki Nishida

This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.



















