Modeling Personalized Smart Teaching for Learner Needs

[1] Mehmood, R., Alam, F., Albogami, N. N., Katib, I., Albeshri, A., & Altowaijri, S. M. (2017). Utilearn: a personalised ubiquitous teaching and learning system for smart societies. IEEE Access, 5, 2615-2635. Search in Google Scholar

[2] Ilkou, E., & Signer, B. (2020). A Technology-enhanced Smart Learning Environment based on the Combination of Knowledge Graphs and Learning Paths. International Conference on Computer Supported Education. Search in Google Scholar

[3] Li, K. C., & Wong, T. M. (2019). Advancing teaching with massive open online courses: a review of case studies. International Journal of Innovation and Learning, 25(2), 141-155. Search in Google Scholar

[4] Huang, Y. (2022). Design of personalised english distance teaching platform based on artificial intelligence. Journal of Information & Knowledge Management. Search in Google Scholar

[5] Bianchini, D., Antonellis, V. D., Garda, M., & Melchiori, M. (2020). A methodological approach for enabling personalised smart city data exploration. IEEE. Search in Google Scholar

[6] Gisela Cebrián, Palau, R., & Mogas, J. (2020). The smart classroom as a means to the development of esd methodologies. Sustainability, 12. Search in Google Scholar

[7] Suraimi, A. S. M. A., & Hasan, M. (2022). Engineering students’ perceptions of blended learning during covid-19 pandemic: context of a developing country. International Journal of Smart Technology and Learning, 3(1), 67-. Search in Google Scholar

[8] Meleko, J., & Kurilovas, E. (2018). Adaptive tutoring system with application of intelligent agents. International Journal of Smart Education and Urban Society, 9(2), 1-11. Search in Google Scholar

[9] Tsatiris, G., & Karpouzis, K. (2021). Developing for personalised learning: the long road from educational objectives to development and feedback. Search in Google Scholar

[10] Merwe, H. J. V. D., & Brown, T. H. (2017). Mobile and contextual learning. International Journal of Mobile & Blended Learning, 9(2), vi-viii. Search in Google Scholar

[11] Venkatesh, M., & Sathyalakshmi, S. (2020). Smart learning using personalised recommendations in web-based learning systems using artificial bee colony algorithm to improve learning performance. Electronic Government an International Journal, 16(1/2), 101. Search in Google Scholar

[12] Kanellopoulou, C., & Giannakoulopoulos, A. (2021). Internet-assisted language teaching: the internet as a tool for personalised language exploration. Creative Education. Search in Google Scholar

[13] Agbo, F. J., Oyelere, S. S., Suhonen, J., & Tukiainen, M. (2019). Identifying potential design features of a smart learning environment for programming education in nigeria. International Journal of Learning Technology(4). Search in Google Scholar

[14] Wang, F. (2023). Iot for smart english education: ai-based personalised learning resource recommendation algorithm. Int. J. Comput. Appl. Technol., 71, 200-207. Search in Google Scholar

[15] Oliveira, E., Barba, P. G. D., & Corrin, L. (2021). Enabling adaptive, personalised and context-aware interaction in a smart learning environment: piloting the icollab system. Australasian Journal of Educational Technology(2). Search in Google Scholar

[16] Cheung, S. K. S., Wang, F. L., & Kwok, L. F. (2021). The continuous pursuit of smart learning. Australasian Journal of Educational Technology(2). Search in Google Scholar

[17] Folasade O. IsinkayeYetunde O. FolajimiAdesesan B. Adeyemo. (2020). On collaborative filtering model optimised with multi-item attribute information space for enhanced recommendation accuracy. International Journal of Intelligent Systems Technologies and Applications, 19(3). Search in Google Scholar

[18] Mcgreal, R. (2018). Hearables for online learning. International Review of Research in Open and Distance Learning, 19(4). Search in Google Scholar

[19] Malik, S. (2020). A study of parent’s opinion on online teaching in delhi-ncr schools. Indian Journal of Science and Technology, 13(42), 4351-4363. Search in Google Scholar

[20] Reddy, R., & Tiwari, M. (2020). Artificial Intelligence Based Personalised Adaptive Learning (PAL) In Education 4.0-An Exploratory Study. INTERNATIONAL RESEARCH CONFERENCE 2020 -BUSINESS ARCHITECTURE IN THE ERA OF INDUSTRY 4.0. Search in Google Scholar

[21] Alhasan, K., Chen, L., & Chen, F. (2018). Mining Learning Styles for Personalised eLearning. 2018 IEEE SmartWorld, Ubiquitous Intelligence & Computing, Advanced & Trusted Computing, Scalable Computing & Communications, Cloud & Big Data Computing, Internet of People and Smart City Innovation (SmartWorld/SCALCOM/UIC/ATC/CBDCom/IOP/SCI). IEEE. Search in Google Scholar

[22] Alisauskiene, S., Kaminskiene, L., Milteniene, L., Meliene, R., & Wozniczka, A. K. (2021). INNOVATIVE TEACHER EDUCATION THROUGH PERSONALISED LEARNING: DESIGNING TEACHING AND LEARNING SCENARIOS. 15th International Technology, Education and Development Conference. Search in Google Scholar

[23] Yari, S., Mses, S., & Maennel, O. (2020). A Method for Teaching Open Source Intelligence (OSINT) Using Personalised Cloud-based Exercises. 15th International Conference on Cyber Warfare and Security (ICCWS). Search in Google Scholar

[24] Adewale, O., Agbonifo, O., & Osajiuba, O. (2019). Development of a myers-briggs type indicator based personalised e-learning system. International Journal of Computer (IJC)(1). Search in Google Scholar

[25] William, E., Boyd, Airdre, & Grant. (2017). Individualised, tailored and personalised approach to the teacher-learner relationship in postgraduate staff development studies-a case study of postgraduate research supervision training. Creative Education, 08(3), 312-332. Search in Google Scholar