User Readiness and AI Integration as Drivers of Smart Nano Learning in Mobile Environments

Gan Chanyawudhiwan; Kemmanat Mingsiritham

doi:10.3991/ijim.v20i10.60759

Authors

Gan Chanyawudhiwan Sukhothai Thammathirat Open University, Nonthaburi, Thailand https://orcid.org/0000-0001-9610-0425
Kemmanat Mingsiritham Sukhothai Thammathirat OSukhothai Thammathirat Open University, Nonthaburi, Thailandpen University https://orcid.org/0000-0002-3221-7154

DOI:

https://doi.org/10.3991/ijim.v20i10.60759

Keywords:

Smart nano-learning, Interactive mobile learning, Lifelong learning, User readiness and trust, AI support in education

Abstract

Lifelong learning has been undergoing a significant transformation driven by the development of digital learning platforms and the leveraging of artificial intelligence (AI) to personalize learning experiences. This study aims to examine the factors influencing the readiness of smart nano-learning platforms to support lifelong learning, with particular emphasis on user readiness, trust, and AI support as key determinants. Additional contributing factors considered include content quality, user experience, learning environment, and data systems and reporting. A quantitative research design was employed, with 378 undergraduate students using a validated and reliable questionnaire. The data were analyzed using structural equation modeling (SEM). The results indicate that user readiness, trust, and AI have significant direct effects on the smart nano-learning platform’s readiness. The findings suggest that the effective design of platforms for lifelong learning must integrate both human-centered factors and intelligent technological support. In particular, strengthening learners’ readiness and trust, alongside the strategic use of AI to enable scalable, personalized learning, is essential for developing sustainable, effective smart nano-learning platforms for real-world lifelong learning contexts.

Author Biographies

Gan Chanyawudhiwan, Sukhothai Thammathirat Open University, Nonthaburi, Thailand

Associate Professor Dr. Gan Chanyawudhiwan is a Lecturer at the Office of Educational Technology, Sukhothai Thammathirat Open University. His research and teaching interests focus on instructional design, learning design, universal design, user journey design, user experience design, user interface design, and human-computer interaction (E-mail: gancha@stou.ac.th)

Kemmanat Mingsiritham, Sukhothai Thammathirat OSukhothai Thammathirat Open University, Nonthaburi, Thailandpen University

Associate Professor Dr. Kemmanat Mingsiritham is a Lecturer at the Office of Educational Technology, Sukhothai Thammathirat Open University, Her primary interests include instructional design, virtual learning design, and distance learning (kemmanat.min@stou.ac.th)

References

[1] UNESCO, “Fostering a culture of lifelong learning in the digital era,” UNESCO, 2024. [Online]. Available: https://www.unesco.org/en/articles/fostering-culture-lifelong-learning-digital-era

[2] OECD, “OECD digital education outlook 2023: Towards an effective digital education ecosystem,” OECD Publishing, Paris, France, 2023. https://doi.org/10.1787/c74f03de-en.

[3] A. D. Samala, S. Papadakis, and S. Rawas, “Global insights into mobile learning in higher education: A PRISMA-guided bibliometric analysis from 2007 to 2023,” International Journal of Educational Reform, 2025. https://doi.org/10.1177/10567879251341869

[4] E. Ang, M. A. Abalos, J. L. Seril, K. M. Uy, F. M. Silvestre, R. Ebardo, and A. Pulumbarit, “Analyzing the factors affecting nano-learning behavior of college students on TikTok,” in Proceedings of the 33rd International Conference on Computers in Education. Asia-Pacific Society for Computers in Education, 2025. [Online]. Available: https://library.apsce.net/index.php/ICCE/article/view/6028

[5] N. Dunn, “TikTok statistics: The TikTok stats and facts you need to know about,” Charle Agency, Sep. 8, 2024. [Online]. Available: https://www.charleagency.com/articles/tiktok-statistics/

[6] W. Diteeyont and H.-Y. Ku, “Competency levels and influential factors of college students’ mobile learning readiness in Thailand,” Smart Learning Environments, vol. 10, no. 44, pp. 1-20, 2023. https://doi.org/10.1186/s40561-023-00266-6

[7] T. Nazaretsky, P. Mejia-Domenzain, V. Swamy, J. Frej, and T. Käser, “The critical role of trust in adopting AI-powered educational technology for learning: An instrument for measuring student perceptions,” Computers and Education: Artificial Intelligence, vol. 8, pp. 100368, 2025. https://doi.org/10.1016/j.caeai.2025.100368

[8] W. K. Monib, A. Qazi, R. A. Apong, J. H. Santos, and M. M. Mahmud., “The MIND model: A microlearning AI-integrated instructional design for enhanced learning outcomes,” Scientific Reports, vol. 15, no. 41020, pp. 1-14, 2025. https://doi.org/10.1038/s41598-025-24910-y

[9] A. Baillifard, M. Gabella, P. B. Lavenex, and C. S. Martarelli, “Effective learning with a personal AI tutor: A case study,” Education and Information Technologies, vol. 30, pp. 297–312, 2025. https://doi.org/10.1007/s10639-024-12888-5

[10] L. Sun and L. Zhou, “Does generative artificial intelligence improve the academic achievement of college students? A meta-analysis,” Journal of Educational Computing Research, vol. 62, no. 7, pp. 1676–1713, 2024. https://doi.org/10.1177/07356331241277937

[11] M. M. Soares, T. Ahram, and C. Falcão, “Usability and user experience,” in Handbook of Usability and User-Experience. Boca Raton, FL, USA: CRC Press, 2022, pp. 3–22. https://doi.org/10.1201/9780429343490-2

[12] P. Vivekananth, “Nanolearning: A new paradigm shift in teaching and learning,” International Journal of Engineering and Management Research, vol. 12, no. 1, pp. 112–114, 2022. https://doi.org/10.31033/ijemr.12.1.14

[13] R. Li and M. Li, “Teaching strategies and implementation paths for interactive mobile learning platforms in higher education,” International Journal of Interactive Mobile Technologies, vol. 19, no. 20, pp. 84–98, 2025. https://doi.org/10.3991/ijim.v19i20.58433

[14] L. M. Hasani, I. D. Sensuse, and R. R. Suryono, “User-centered design of e-learning user interfaces: A survey of the practices,” in 3rd International Conference on Computer and Informatics Engineering (IC2IE), 2020. https://doi.org/10.1109/IC2IE50715.2020.9274623

[15] A. M. Alterkait and Y. M. Alduaij, “Impact of information quality on satisfaction with e-learning platforms: Moderating role of instructor and learner quality,” Sage Open, vol. 14, no. 1, pp. 1–13, 2024. https://doi.org/10.1177/21582440241233400

[16] F. Gao, C. Wang, H. Xie, and J. Hong, “Social interaction and online learning efficiency for middle school students: The mediating role of social presence and learning engagement,” Behavioral Sciences, vol. 14, no. 10, pp. 1-18, 2024. https://doi.org/10.3390/bs14100896

[17] T. V. Nguyen, S. Yaghmour, C. S. Trinh, and T. H. Ngo, “Pedagogical design patterns in educational mobile apps: A comparative analysis of learning effectiveness across K–12, higher education, and professional training,” Journal of Interactive Mobile Technologies, vol. 19, no. 22, pp. 4–21, 2025. https://doi.org/10.3991/ijim.v19i22.58511

[18] Y. B. Limbu and L. Pham, “Impact of e-learning service quality on student satisfaction during the COVID-19 pandemic: A systematic review,” Knowledge Management & E-Learning, vol. 15, no. 4, pp. 523–538, 2023. https://doi.org/10.34105/j.kmel.2023.15.030

[19] N. Shehzad and T. Charles, “Exploring the impact of instructor social presence on student engagement in online higher education,” Contemporary Educational Technology, vol. 15, no. 4, ep484, 2023. https://doi.org/10.30935/cedtech/13823

[20] C. Cabi and H. Türkoglu, “The impact of a learning analytics-based feedback system on students’ academic achievement and self-regulated learning in a flipped classroom,” International Review of Research in Open and Distributed Learning, vol. 26, no. 1, pp. 175–196, 2025. https://doi.org/10.19173/irrodl.v26i1.7924

[21] L. Cabral, R. Pinto, and G. Gonçalves, “AI-powered learning analytics dashboards: a systematic review of applications, techniques, and research gaps,” Discovery Education, vol. 4, no. 525, pp. 1-27, 2025. https://doi.org/10.1007/s44217-025-00964-y

[22] Q. Xia, W. Li, Y. Yang, X. Weng, and T. Chiu, “A systematic review and meta-analysis of the effectiveness of Generative Artificial Intelligence (GenAI) on students’ motivation and engagement,” Computers and Education: Artificial Intelligence, vol. 9, no. 100455, pp. 1-16, 2025. https://doi.org/10.1016/j.caeai.2025.100455

[23] S. Hijazi, M. N. Mokal, A. Halder, V. Victor, and G. John, “AI- and IoT-driven mobile learning environments: A framework for educational transformation, workforce development, and digital inclusion,” International Journal of Interactive Mobile Technologies, vol. 19, no. 24, pp. 4–17, 2025. https://doi.org/10.3991/ijim.v19i24.58959

[24] A. M. Al-Zahrani and T. M. Alasmari, “Exploring the impact of artificial intelligence on higher education: The dynamics of ethical, social, and educational implications,” Humanities and Social Sciences Communications, vol. 11, no. 912, pp. 1-12, 2024. https://doi.org/10.1057/s41599-024-03432-4

[25] C. Merino-Campos, “The impact of artificial intelligence on personalized learning in higher education: A systematic review,” Trends in Higher Education, vol. 4, no. 17, pp. 1-15, 2025. https://doi.org/10.3390/higheredu4020017

[26] S. V. Bentley, C. K. Naughtin, M. J. McGrath, J. L. Irons, and P. S. Cooper, “The digital divide in action: How experiences of digital technology shape future relationships with artificial intelligence,” AI and Ethics, vol. 4, pp. 901–915, 2024. https://doi.org/10.1007/s43681-024-00452-3

[27] Y. Walter, “Embracing the future of artificial intelligence in the classroom: The relevance of AI literacy, prompt engineering, and critical thinking in modern education,” International Journal of Educational Technology in Higher Education, vol. 21, no. 15, pp. 1–29, 2024. https://doi.org/10.1186/s41239-024-00448-3

[28] H. Y. Ahn, “AI-powered e-learning for lifelong learners: Impact on performance and knowledge application,” Sustainability, vol. 16, no. 20, pp. 9066, 2024. https://doi.org/10.3390/su16209066

[29] A. Fortuna, F. Prasetya, A. D. Samala, S. Rawas, S. Criollo-C, D. Kaya, M. Raihan, W. Andriani, D. Safitri, and R. A. Nabawi, “Artificial intelligence in personalized learning: A global systematic review of current advancements and shaping future opportunities,” Social Sciences & Humanities Open, vol. 12, no. 102114, pp. 1-17, 2025. https://doi.org/10.1016/j.ssaho.2025.102114

[30] U. Lah, J. R. Lewis, and B. Šumak, "Perceived Usability and the Modified Technology Acceptance Model," International Journal of Human–Computer Interaction, vol. 36, no. 13, p. 4811, 2020, https://doi.org/10.1080/10447318.2020.1727262

[31] D. Al-Fraihat, M. Joy, R. Masa'deh, and J. Sinclair, "Evaluating E-learning systems success: An empirical study," Computers in Human Behavior, vol. 102, pp. 67–86, 2020, https://doi.org/10.1016/j.chb.2019.08.004

[32] D. Y. Long, S. Wang, S. M. Rashid, and X. T. Lu, "Artificial intelligence in higher education: a systematic review of its impact on student engagement and the mediating role of teaching methods," Frontiers in Education, vol. 10, pp. 1-18, 2025, https://doi.org/10.3389/feduc.2025.1648661

[33] O. M. Chamorro, S. o. Zegarra, and C. Dávila-Ignacio, "Microlearning and Nanolearning in Higher Education: A Bibliometric Review to Identify Thematic Prevalence in the COVID-19 Pandemic and Post-Pandemic Context,” International Journal of Learning Teaching and Educational Research, vol. 23, no. 4, pp. 279-297, 2024, https://doi.org/10.26803/ijlter.23.4.15

[34] S. Kruger, and A. A. Steyn, “Navigating the fourth industrial revolution: a systematic review of technology adoption model trends,” Journal of Science and Technology Policy Management, vol. 16, no.10, pp. 24-56, 2025, https://doi.org/10.1108/JSTPM-11-2022-0188

[35] S. Papadakis, A. M. Striuk, H. M. Kravtsov, et al., “Embracing digital innovation and cloud technologies for transformative learning experiences,” in Proceedings of the 11th Workshop on Cloud Technologies in Education, CEUR Workshop Proceedings, vol. 3679, pp. 1-21, 2024. [Online]. Available: https://ceur-ws.org/Vol-3679/paper00.pdf