Advancing Science and Technology-Based Distance Learning through Artificial Intelligence, Interactive Navigation, and Cluster-Based Learning for Sustainable and Inclusive Education

Authors

  • Gavhar Saparovna Abdullayeva Chirchik State Pedagogical University, Chirchik, Uzbekistan
  • Zebunniso Bakhtiyor Atamirzayeva Chirchik State Pedagogical University, Chirchik, Uzbekistan
  • Abdimumin Ibragimovich Rasulov Uzbekistan National Pedagogical University, Tashkent, Uzbekistan
  • Dilshoda Chorshanbievna Mamatraimova Termez State Pedagogical Institute, Termez, Uzbekistan
  • Muhammadrasul Abdimumin Ibragimov Uzbekistan National Pedagogical University, Tashkent, Uzbekistan
  • Hemlata Gaikwad Symbiosis Institute of Management Studies, Symbiosis International (Deemed University), MH, India
  • Gulruh Shoikrom Buvorayeva Tashkent Institute of Irrigation and Agricultural Mechanization Engineers National Research University, Tashkent, Uzbekistan
  • Abduvali Abdullayevich Burxanov Tashkent Institute of Irrigation and Agricultural Mechanization Engineers National Research University, Tashkent, Uzbekistan
  • Odina Kobil Ozodova Uzbekistan National Pedagogical University, Tashkent, Uzbekistan
  • Prayoga Bestari Universitas Pendidikan Indonesia, Bandung, Indonesia

DOI:

https://doi.org/10.16920/jeet/2026/v40is1/26148

Keywords:

Artificial Intelligence, Cluster-based Learning, Distance Learning, Ict Competence, Inclusive Education, Interactive Navigation, Sustainable Development Goals.

Abstract

This study aims to advance science and technology-based distance learning by integrating artificial intelligence (AI), interactive navigation, cluster-based learning, and inclusive educational approaches within a sustainable education framework. A mixed-methods approach combining pedagogical experimentation, system-based implementation, and evaluation of technology-supported learning activities was applied. The main pedagogical experiment involved 444 university students in higher education environments associated with teacher preparation, with experimental and control groups used to compare ICT competence development and learning performance. Additional learning-interaction data from an AI-supported interactive distance-learning platform were adopted from a previous study to extend the evaluation of student engagement, theoretical learning, practical activities, and assessment processes. The data were analysed using descriptive and comparative approaches, including comparison of competence-level distributions, participation frequencies, response submissions, assessment completion, and practical learning activities between the experimental and control groups. The findings demonstrate improvements in ICT competence, professional readiness, learning autonomy, and the integration of theoretical and practical learning. AI-enabled feedback and structured navigation also enable adaptive learning pathways and more responsive assessment processes. The combination of educational clusters, smart technologies, interactive navigation, and inclusive pedagogical methods offers a holistic view of technology-enhanced education. The proposed framework supports the Sustainable Development Goals (SDGs), particularly on education, and contributes to the development of inclusive, equitable, and sustainable digital education.

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References

Abdullayeva, G. S. (2024). Features of inclusive education with children with special educational needs in Uzbekistan. Journal of Engineering Science and Technology (The Bioscan), 19(2), 827–830.

Al Husaeni, D. F., Al Husaeni, D. N., Ragadhita, R., Bilad, M. R., Al-Obaidi, A. S. M., Abduh, A., & Nandiyanto, A. B. D. (2022). How language and technology can improve student learning quality in engineering? Definition, factors for enhancing students' comprehension, and computational bibliometric analysis. International Journal of Language Education, 6(4), 445–476.

Ayinde, O. M., Salami, A. O., Ademola, M. A., Nnanna, O. M., & Anosike, C. O. (2026). Empowering information and communication technology (ICT) teachers through a behavioral approach to computer-aided design (CAD) for curriculum-oriented instruction: A community-based approach to pedagogical challenges. ASEAN Journal of Community Service and Education, 5(2), 121–136.

Haristiani, N. (2019). Artificial intelligence (AI) chatbot as language learning medium: An inquiry. Journal of Physics: Conference Series, 1387(1), 012020.

Haristiani, N., & Kusumawati, M. (2026). Integrating information and communication technology (ICT) and language in vocational education: A bibliometric and qualitative perspective toward workforce readiness and Sustainable Development Goals (SDGs). 19, 55–63.

Ibrahim, A., Bolaji, H. O., & Abdulraheem, A. J. (2025). Accessibility and utilization of artificial intelligence (AI)-based intelligent tutoring systems (ITS) and information and communication technology (ICT) in enhancing biology education. ASEAN Journal for Science Education, 4(2), 93–104.

Irmayanti, H., Iskandar, M. M., & Achilov, T. S. (2026). Designing a transparent AI system using SHAP and LIME. Journal of Engineering Science and Technology, 21(2), 81–88.

Jadhav, P., Gaikwad, H., & Patil, K. S. (2022). Teaching and learning with technology: Effectiveness of ICT integration in schools. ASEAN Journal for Science Education, 1(1), 33–40.

Karin, J., Dharmayanty, D., Luckyardi, S., Soegoto, E. S., Ximmataliyev, D., Yusof, M. K., Chochole, T., & Zangana, H. M. (2025). Evolution of artificial intelligence (AI)-driven information systems in higher education: A review. ASEAN Journal of Educational Research and Technology, 4(3), 523–530.

Karmaker, R. (2027). Community-based artificial intelligence (AI) empowerment for rural girls: A framework for digital literacy, cybersecurity, and sustainable community development. ASEAN Journal of Community Service and Education, 6(2), 97–116.

Khimmataliev, D. O., Salomova, R. N. V., Makhsumov, R. M., Khakimov, Z. O., Normurodova, A. K. Q., Togaev, B. E. U., Obidjanov, U. I., Omonova, N. P. Q., & Fitrilia, T. (2025). Enhancing ICT competence of future computer science teachers through cluster-based education models. Journal of Engineering Science and Technology, 20(4), 24–30.

Mulyana, A., Djatna, T., Wahjuni, S., & Sucoko, H. (2025). Towards an adaptive edge computing framework for computation offloading: ABC-MDP approach. NED University Journal of Research, 22, 403–411.

Nandiyanto, A. B. D. (2026). How to read and interpret FTIR spectra for materials: A master dataset with step-by-step guided peak-correlation analysis, representative examples, and a foundation for future artificial intelligence (AI)-assisted analysis. ASEAN Journal for Science and Engineering in Materials, 5(2), 323–356.

Pikhart, M., Klimova, B., Cierniak-Emerych, A., & Dziuba, S. (2023). A comparative analysis of perceived advantages and disadvantages of online learning. Behavioral Sciences, 13, 262.

Samiyeva, S. K., Olimov, S. S., Barnoeva, S. U. K., Ibragimov, U. M., Aslanova, N. K., Egamova, G. I. K., Mirzoeva, S. S. K., & Khusniddinova, Z. K. (n.d.). Advancing science and technology-based distance learning through artificial intelligence, interactive navigation, and Sustainable Development Goals (SDGs) integration [Manuscript accepted with revisions].

Sanni, A. M. (2023). ICT tools for teaching the Arabic language. ASEAN Journal of Religion, Education, and Society, 2(2), 67–74.

Stecuła, K., & Wolniak, R. (2022). Advantages and disadvantages of e-learning innovations during the COVID-19 pandemic in higher education in Poland. Journal of Open Innovation: Technology, Market, and Complexity, 8, 159.

Talebian, S., Mohammadi, H. M., & Rezvanfar, A. (2014). Information and communication technology in higher education: Advantages, disadvantages, conveniences and limitations of applying e-learning to agricultural students in Iran. Procedia - Social and Behavioral Sciences, 152, 300–305.

Usarov, J. E., Qahramonovna, R. M., Meyliyeva, M. S., Rustamov, B. K., & Allayorova, S. B. (2025). Development of inclusive learning of students with a social orientation in the environment of an educational cluster based on a competence-based approach. ASEAN Journal of Community and Special Needs Education, 4(1), 87–94.

Yuhanna, I., Alexander, A., & Kachik, A. (2020). Advantages and disadvantages of online learning. Journal Educational Verkenning, 1(2), 13–19.

Zaki, M. S. (2022). Advantages and disadvantages of online learning. The Journal of International Social Research, 15(92), 1.

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Published

2026-10-23

How to Cite

Abdullayeva, G. S., Atamirzayeva, Z. B., Rasulov, A. I., Mamatraimova, D. C., Ibragimov, M. A., Gaikwad, H., … Bestari, P. (2026). Advancing Science and Technology-Based Distance Learning through Artificial Intelligence, Interactive Navigation, and Cluster-Based Learning for Sustainable and Inclusive Education. Journal of Engineering Education Transformations, 40(1), 43–51. https://doi.org/10.16920/jeet/2026/v40is1/26148

Issue

Volume 40, Special Issue 1, September 2026

Section

Articles
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