AI-Driven Learning Environments and Learning Flow Experience: The Role of Technological Readiness in Supporting Sustainable Quality Education
DOI:
10.29303/jppipa.v12i2.14385Published:
2026-02-25Downloads
Abstract
This study examines the determinants of learning flow experience in AI-driven learning environments and its contribution to Sustainable Development Goal 4 (Quality Education). A quantitative approach was employed using survey data from 316 undergraduate students experienced in AI-integrated courses across four faculties at Universitas Negeri Padang, Indonesia. The data were analyzed using partial least squares structural equation modeling (SEM-PLS). The results indicate that AI technological readiness has a significant positive effect on learning flow experience and mediates the influence of instructor support, community support, and teaching platform quality on learning flow. In contrast, AI digital literacy does not have a significant effect on technological readiness, indicating that technical training alone is insufficient and cannot independently build learners’ readiness without strong pedagogical and contextual support. Furthermore, AI facilitating conditions slightly but significantly strengthen the relationship between technological readiness and learning flow, suggesting their role as a contextual boundary factor. These findings highlight the importance of integrating instructional, technological, and institutional support systems in AI-driven learning. In conclusion, fostering technological readiness through supportive learning ecosystems is essential for promoting meaningful and sustainable learning experiences aligned with SDG 4.
Keywords:
AI digital literacy AI-driven learning Facilitating conditions Learning flow experience Technological readinessReferences
Agyemang Adarkwah, M., Huang, R., Chen, Y., Oubibi, M., Tlili, A., Shehata, B., Wang, H., & Hosny Saleh Metwally, A. (2025). Identifying emerging learning spaces for future educational sustainability: a comprehensive literature review and Delphi survey. Interactive Learning Environments, 1–25. https://doi.org/10.1080/10494820.2025.2511253
Al-Fraihat, D., Joy, M., Masa’deh, R., & Sinclair, J. (2020). Evaluating e-learning systems success: An empirical study. Computers in Human Behavior, 102, 67–86. https://doi.org/10.1016/j.chb.2019.08.004
Al-Samarraie, H., Shamsuddin, A., & Alzahrani, A. I. (2020). A flipped classroom model in higher education: a review of the evidence across disciplines. Educational Technology Research and Development, 68(3), 1017–1051. https://doi.org/10.1007/s11423-019-09718-8
Arini, D., & Nursa’ban, M. (2024). Contribution of Artificial Intelligence (AI) in education to support the achievement of Sustainable Development Goals (SDGs) 2030. Jurnal Penelitian Pendidikan IPA, 10(SpecialIssue), 39–45. https://doi.org/10.29303/jppipa.v10iSpecialIssue.8321
Artha, B., Kurniyati, N. N., Ratnawati, E. T. R., & others. (2024). Artificial Intelligence: A New Paradigm in Human Resource Management. Jurnal Penelitian Pendidikan IPA, 10(SpecialIssue), 372–376. https://doi.org/10.29303/jppipa.v10iSpecialIssue.8609
Bond, M., Bedenlier, S., Marín, V. I., & Händel, M. (2020). Emergency remote teaching in higher education: Mapping the first global online semester. International Journal of Educational Technology in Higher Education, 17(1), 1–24. https://doi.org/10.1186/s41239-020-00282-x
Bond, M., Zawacki-Richter, O., & Nichols, M. (2021). Revisiting five decades of educational technology research: A content and authorship analysis of the British Journal of Educational Technology. British Journal of Educational Technology, 52(1), 12–32. https://doi.org/10.1111/bjet.13093
Chiu, T. K. F., & Churchill, D. (2023). Exploring the characteristics of AI-supported learning environments and their impact on student engagement. Computers & Education: Artificial Intelligence, 4, 100112. https://doi.org/10.1016/j.caeai.2023.100112
Cunningham, J. B. (2023). Using demographic variables in educational technology research: Methodological considerations and implications. Educational Research Review, 38, 100501. https://doi.org/10.1016/j.edurev.2023.100501
Dede, C., Richards, J., & Saxberg, B. (2019). Learning engineering for online education: Theoretical contexts and design-based examples. Educational Technology Research and Development, 67(3), 597–621. https://doi.org/10.1007/s11423-018-9614-3
Dwivedi, Y. K. (2023). So what if ChatGPT wrote it? Multidisciplinary perspectives on opportunities, challenges and implications of generative conversational AI for research, practice and policy. International Journal of Information Management, 71, 102642. https://doi.org/10.1016/j.ijinfomgt.2023.102642
Eagly, A. H. (2013). Sex differences in social behavior: A social-role interpretation. Psychology Press. https://doi.org/10.4324/9780203781906
Efendi, E. (2025). Research Trends and Opportunities in Integrating Augmented Reality and Deep Learning into Science Education: A Bibliometric Analysis. Jurnal Penelitian Pendidikan IPA, 11(7), 1–11. https://doi.org/10.29303/jppipa.v11i7.11988
Falebita, O. A., & Kok, S. K. (2024). Assessing technological readiness for artificial intelligence adoption in higher education. Education and Information Technologies, 29(2), 1235–1256. https://doi.org/10.1007/s10639-023-11904-7
Feziyasti, A., & Ashel, H. (2025). Teaching Science Mapping Research on Integration of Augmented Reality Technology and Education for Sustainable Development: A Bibliometric Analysis. Jurnal Penelitian Pendidikan IPA, 11(7), 12–24. https://doi.org/10.29303/jppipa.v11i7.11985
Hafifah, H., Yerimadesi, Y., Alizar, A., & Kurniawati, D. (2025). Development of acid base e-module based on guided discovery learning to improve digital literacy skills of senior high school phase F students. Jurnal Penelitian Pendidikan IPA, 11(7), 789–796. https://doi.org/10.29303/jppipa.v11i7.11382
Hair, J. F., Risher, J. J., Sarstedt, M., & Ringle, C. M. (2019). When to use and how to report the results of PLS-SEM. European Business Review, 31(1), 2–24. https://doi.org/10.1108/EBR-11-2018-0203
Hamari, J., Shernoff, D. J., Rowe, E., Coller, B., Asbell-Clarke, J., & Edwards, T. (2016). Challenging games help students learn: An empirical study on engagement, flow and immersion in game-based learning. Computers in Human Behavior, 54, 170–179. https://doi.org/10.1016/j.chb.2015.07.045
Holmes, W., Bialik, M., & Fadel, C. (2022). Artificial intelligence in education: Promise and implications for teaching and learning. Center for Curriculum Redesign. Retrieved from https://discovery.ucl.ac.uk/id/eprint/10139722
Howard, S. K., Tondeur, J., Siddiq, F., & Scherer, R. (2021). Ready, set, go Profiling teachers’ readiness for online teaching in secondary education. Technology, Pedagogy and Education, 30(1), 141–158. https://doi.org/10.1080/1475939X.2020.1839543
Hwang, G. J., & Tu, Y. F. (2021). Roles and research trends of artificial intelligence in mathematics education: A bibliometric mapping analysis and systematic review. Educational Technology & Society, 24(2), 1–17. https://doi.org/10.3390/math9060584
Hwang, G. J., Tu, Y. F., & Tang, K. Y. (2023). AI literacy in education: Conceptualization, measurement, and implications for teaching and learning. Computers & Education: Artificial Intelligence, 4, 100114. https://doi.org/10.1016/j.caeai.2023.100114
Ifenthaler, D., & Yau, J. Y. K. (2020). Utilising learning analytics to support study success in higher education: A systematic review. Educational Technology Research and Development, 68(4), 1961–1990. https://doi.org/10.1007/s11423-020-09788-z
Karim, B. Q., Haryanto, H., & Susanti, E. Y. (2025). AI in Education: Transforming Student Engagement for the Digital Age. Jurnal Penelitian Pendidikan IPA, 11(2), 1127–1136. https://doi.org/10.29303/jppipa.v11i2.10469
Kim, J., Park, H., & Jang, M. (2022). Instructor support and student engagement in technology-enhanced learning environments. Computers & Education, 176, 104357. https://doi.org/10.1016/j.compedu.2021.104357
Kuswanti, E., Sukatmi, S., Gaol, L. L., Suryani, P., & Robiansyah, A. (2024). Transforming in the digital era: uncovering the potential of self-reliance and technology for the success of new ut students in distance learning. Jurnal Penelitian Pendidikan IPA, 10(8), 5919–5928. https://doi.org/10.29303/jppipa.v10i8.8178
Li, R., Meng, Z., Tian, M., Zhang, Z., & Xiao, W. (2021). Modelling Chinese EFL learners’ flow experiences in digital game-based vocabulary learning: The roles of learner and contextual factors. Computer Assisted Language Learning, 34(4), 483–505. https://doi.org/10.1080/09588221.2019.1619585
Li, Y., Wang, Q., & Liu, Z. (2021). Exploring students’ flow experience in online learning environments: The role of perceived enjoyment and concentration. Educational Technology Research and Development, 69(5), 2341–2361. https://doi.org/10.1007/s11423-021-10026-9
Mohd Rahim, N. I., A. Iahad, N., Yusof, A. F., & A. Al-Sharafi, M. (2022). AI-based chatbots adoption model for higher-education institutions: A hybrid PLS-SEM-neural network modelling approach. Sustainability, 14(19), 12726. https://doi.org/10.3390/su141912726
Ng, D. T. K., Leung, J. K. L., Chu, S. K. W., & Qiao, M. S. (2021). AI literacy: Definition, teaching, evaluation and ethical issues. Journal of Information Literacy, 15(1), 2–23. https://doi.org/10.11645/15.1.2891
Ouyang, F., & Jiao, P. (2021). Artificial intelligence in education: The three paradigms. Computers & Education: Artificial Intelligence, 2, 100020. https://doi.org/10.1016/j.caeai.2021.100020
Ouyang, F., Zheng, L., & Jiao, P. (2022). Artificial intelligence in online higher education: A systematic review. Computers & Education, 176, 104357. https://doi.org/10.1016/j.compedu.2021.104357
Puspitasari, A., Paradhita, A. N., Tineka, Y. W., Sulistyowati, V., Noriska, N. K. S., & others. (2024). Natural Language Processing (NLP) Technology for Chatbot Website. Jurnal Penelitian Pendidikan IPA, 10(SpecialIssue), 319–324. https://doi.org/10.29303/jppipa.v10iSpecialIssue.8241
Radianti, J., Majchrzak, T. A., Fromm, J., & Wohlgenannt, I. (2020). A systematic review of immersive virtual reality applications for higher education. Education and Information Technologies, 25(6), 4959–4980. https://doi.org/10.1007/s10639-020-10291-6
Riasani, B., Nisa, A. F., Zulfiati, H. M., & Wibawa, S. (2025). Ethnopedagogy of IPAS Armed with Pancasila and Artificial Intelligence as a 21st Century Learning Revolution. Jurnal Penelitian Pendidikan IPA, 11(6), 985–994. https://doi.org/10.29303/jppipa.v11i7.11638
Rovai, A. P. (2002). Development of an instrument to measure classroom community. The Internet and Higher Education, 5(3), 197–211. https://doi.org/10.1016/S1096-7516(02)00102-1
Scherer, R., Siddiq, F., & Tondeur, J. (2019). The technology acceptance model (TAM): A meta-analytic structural equation modeling approach. Computers & Education, 128, 13–35. https://doi.org/10.1016/j.compedu.2018.09.009
Setiaji, B., Fatmah, E. N., Pujianto, P., Perdana, R., Mas’ulah, N. F., Nauli, H., Pitono, A. P. C., Widyaningtyas, F. S., & Wiyatmo, Y. (2025). Development of Artificial Intelligence (AI)-Based Physics Learning Media Integrated with Bakpia: Expert Feasibility Test. Jurnal Penelitian Pendidikan IPA, 11(6), 965–975. https://doi.org/10.29303/jppipa.v11i6.10847
Shin, D., Park, Y. J., & Kim, H. (2019). The impact of flow on user satisfaction and loyalty in mobile learning environments. Computers in Human Behavior, 91, 136–145. https://doi.org/10.1016/j.chb.2018.09.030
Simatupang, N. I., Sormin, E., Purba, L. S. L., Harfa, N., & Nugroho, A. (2025). Development of Virtual Reality Laboratory Integrated with Artificial Intelligence for Acid-Base Titration Practicum. Jurnal Penelitian Pendidikan IPA, 11(7), 1157–1192. https://doi.org/10.29303/jppipa.v11i7.11587
Tsai, Y. S., Perrotta, C., & Gašević, D. (2020). Empowering learners with personalised learning approaches? Educational Technology Research and Development, 68(2), 753–775. https://doi.org/10.1007/s11423-019-09670-7
Venkatesh, V., Thong, J. Y. L., & Xu, X. (2016). Unified theory of acceptance and use of technology: A synthesis and the road ahead. Journal of the Association for Information Systems, 17(5), 328–376. Retrieved from https://shorturl.asia/nJbXz
Vygotsky, L. S., & Cole, M. (1978). Mind in Society: Development of Higher Psychological Processes. Harvard University Press.
Wulandari, C., Yeni, F., Hidayati, A., & Rahmi, U. (2025). Interactive Learning Media Development Based on Google Sites in Subjects Science Junior High School. Jurnal Penelitian Pendidikan IPA, 11(8), 91–98. https://doi.org/10.29303/jppipa.v11i8.11498
Zawacki-Richter, O., Marín, V. I., Bond, M., & Gouverneur, F. (2019). Systematic review of research on artificial intelligence applications in higher education. International Journal of Educational Technology in Higher Education, 16(1), 39. https://doi.org/10.1186/s41239-019-0171-0
Zhai, X., Chu, X., Chai, C. S., Jong, M. S. Y., Istenic, A., Spector, J. M., & Yuan, J. (2023). A review of artificial intelligence in education from 2010 to 2020. Education and Information Technologies, 28(1), 1–40. https://doi.org/10.1007/s10639-022-11164-9
Zhang, J., Wang, B., Yang, H. H., Chen, Z., Gao, W., & Liu, Z. (2022). Assessing quality of online learning platforms for in-service teachers’ professional development. Frontiers in Psychology, 13, 998196. https://doi.org/10.3389/fpsyg.2022.998196
Zhang, X., Dai, H., & Ardasheva, Y. (2022). Quality of online learning platforms and student engagement: Evidence from higher education. Computers & Education, 180, 104444. https://doi.org/10.1016/j.compedu.2022.104444
License
Copyright (c) 2026 Ani Nurhayati, Ulfia Rahmi, Abna Hidayati, Septriyan Anugrah, Indra Saputra

This work is licensed under a Creative Commons Attribution 4.0 International License.
Authors who publish with Jurnal Penelitian Pendidikan IPA, agree to the following terms:
- Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution 4.0 International License (CC-BY License). This license allows authors to use all articles, data sets, graphics, and appendices in data mining applications, search engines, web sites, blogs, and other platforms by providing an appropriate reference. The journal allows the author(s) to hold the copyright without restrictions and will retain publishing rights without restrictions.
- Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgment of its initial publication in Jurnal Penelitian Pendidikan IPA.
- Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work (See The Effect of Open Access).






