Comparative Review of Selected Adaptive e-Learning Platforms

Alkhalaf, S., Nguyen, A., & Draw, S. (2010). Assessing e-learning system in the kingdom of saudi arabia’s higher education sector: an explanatory analysis. 2010 International Conference on Intelligent Network and Computing, 284-287. https://www.academia.edu/941587/ Arovo, L., Dolog, P., Houben, G., Kravcik, M., Naeve, A., Nilsson, M., & Wild, F. (2006). Interoperability in personalised adaptive learning. Educational Technology and Society, 9(2), 4-18. https://www.researchgate.net/publication/220374558 BaitiAfini, N., Shuib, N., Nasir, H., Bimba, A., Idris, N., & Balakrishnan, V. (2019). Identification of personal traits in adaptive learning environment: systematic literature review. Computers and Education. 130, 168-190. https://www.sciencedirect.com/science/article/abs/pii/S0360131518303026 Balasubramania, V., & Annocia, S. (2016). Learning style detection based on cognitive skills to support adaptive learning environment: a reinforcement approach. Ain Shams Engineering Journal, 9(4), 1-8. https://www.researchgate.net/publication/304493930 Ben-Naim, D., Bain, M., & Marcus, N. (2009). A user-driven and data-driven approach for supporting teachers in reflection and adaptation of adaptive tutorials. Proceedings of the 2nd International Conference on Educational Data Mining, Spain. https://www.researchgate.net/publication/221570376 Ben-Naim, D., Marcus, N., & Bain, M. (2007). Virtual apparatus framework approach to constructing adaptive tutorials. Proceedings of the 2007 International Conference on E-Learning, E-Business, Enterprise Information Systems and E- Government EEE 2007, Nevada. https://www.researchgate.net/publication/221186398 Ben-Naim, D., Marcus, N., & Bain, M. (2008). Visualisation and analysis of student interactions in an adaptive exploratory learning environment. ResearchGate. 138, 1-10. http://ceur- ws.org/Vol-381/paper01.pdf Brooks, C., Greer, J., Melis, E., & Ullrich, C., (2014). Combining its and e-learning technologies opportunities and challenges. Researchgate, 28, 1-11. https://www.researchgate.net/publication/200166244_ Budiharto, W., Chayani, D., Rumordon, P., & Suhartono, D. (2017). Edurobot: intelligent humanoid robot with natural interaction for education and entertainment. Procedia Computer Science, 116, 564-570. https://www.sciencedirect.com/science/article/pii/S1877050917321142 Ciloglugil, B. (2016). Adaptivity based on felder-silverman learning styles modeling e-learning. 4th International Symposium on Innovative Technologies in Engineering and Science (ISITES 2016) Turkey, 1523-1532. https://www.researchgate.net/publication/311597011_ Cingi, C. (2013). Computer aided education. Social and Behavioural Sciences, 103, 220-229. https://www.sciencedirect.com/science/article/pii/S1877042813037749 Dina, D., Cofini, V., Mascio, T., & Cecilia, M. (2016). The silent reading supported by adaptive learning technology: influence in the children outcomes. Computers in Human Behaviours, 55, 1125-1130. https://www.academia.edu/19922299/ Elumalai, V., Shankar, J., Kalaichelvi, R., John, J., Menon, N., Salem, M., & May, A. (2020). Factors affecting the quality of e-learning during the covid-19 pandemic from the perspectie of higher education students. Journal of Information Technology Education Research, 19, 731-751. http://www.jite.org/documents/Vol19/JITE-Rv19p731- Farashahi, S., Donahue, C.H., Khorsand, P., Seo, H., Lee, D., & Soltani, A. (2017). Metaplasticity as a neural substrate for adaptive learning and choice under uncertainty. Neuron, Elsevier, 94, 401- 414. https://pubmed.ncbi.nlm.nih.gov/28426971/ Forsyth, B., Kimble, C., Birch, J., Deel, G., & Brauer, T. (2016). Maximizing the adaptive learning technology experience. Journal of Higher Education Theory and Practice, 16(4), 80-88. https://www.jurispro.com/files/articles/ Hedberg, B. (1981). How organisation learning and unlearn. The Learning Organisation, 24(1), 30-38. https://www.researchgate.net/publication/313682988_Organizational_learning_and_unle arning Huang, Q., Yang, D., Jiang, L., Zhang, H., Liu, H., Kotani, K., (2017). An improved k-means algorithm based on association rules. International Journal of Computer Theory and Engineering 6(2), 146-149. http://www.ijcte.org/papers/853-IT143.pdf. Kim, H., Hong, A., & Song, H. (2019). The roles of academic engagement and digital readiness in students’ achievement in university e-learning environment. Journal of Educational Technology in Higher Education, 21, 16-21. https://www.researchgate.net/publication/333931838 Koukopoulos, Z., & Koukopoulos, D. (2017). Integrating educational theories into a feasible digital environment. Applied Computing and Informatics, 15, 19-26. https://www.researchgate.net/publication/319934395 Leahy, M., Holland, C., & Ward, F. (2019). The digital frontier: envisioning future technologies impact in the classroom. Futures Elsevier, 113, 1-10. https://reader.elsevier.com/reader/sd/pii/ Liu, L., Jiang, H., Chen, W., He, P., Gao, J., Liu, X., & Han, J. (2020). On the variance of the adaptive learning rate and beyond. International Conference on Learning Representation. 23-31. https://arxiv.org/pdf/1908.03265.pdf Liu, M., Kang, J., Zou, W., Pan, Z., & Corliss, S. (2019). Using data to understand how to better design adaptive learning. Technology, Knowledge and Learning Journal, 22, 271-298. https://doi.org/10.1007/s10758-017-9326-z Liu, M., McKelroy, E., Corliss, S.B., & Carrigan, J. (2017). Investigating the effect of an adaptive learning intervention on students’ learning. Educational Technology Research and Development, 65, 1605-1625. https://link.springer.com/article/10.1007/ Luaran, J., Samsuri, N., Nadzri, A., Baharen, K., & Rom, M. (2014). A study on the student perspective on the effectiveness of using e-learning. Social and Behavioral Sciences, Elsevier,123, 139-144. https://www.researchgate.net/publication/275543572_ Machado, M., Moreira, T., Gomes, L., Caldeira, A., & Santos, D. (2016). A fuzzy logic application in virtual education. Procedia computer science, 19, 19-26. https://cyberleninka.org/article/n/676534/viewer Mainemelis, C., Boyatzis, R., & Kolb, D. (2002). Learning styles and adaptive flexibility: testing experiential learning theory. Management Learning, 33 (1), 5-33. https://www.researchgate.net/publication/275714431_ Mehta, A., Morris, A., Swinnerton, B., & Homer, M. (2019). The influence of values on e- learning adoption. Computers and Education, 141, 231- 240. https://doi.org/10.1016/j.compedu.2019.103617 Mirata, V., Hirt, F., Bergamin, P., & Westhizen, C. (2020). Challenges and contexts in establishing adaptive learning in higher education: findings from a delphi study. International Journal of Educational Technology in Higher Education, 17, 1-25. https://educationaltechnologyjournal.springeropen.com/ Murray, M., & Perez, J. (2015). Informing and performing: a study comparing adaptive learning to traditional learning. Informing Science: The International Journal of an Emerging Transdicipline, 18, 111-125. https://www.inform.nu/Articles/Vol18 Paramythis, A., & Loidi-Reisinger, S. (2004). Adaptive learning environment and e-learning standard. Electronic Journal on e-Learning, 2(1), 181-194. https://www.bibsonomy.org/bibtex/ Popenici, S., & Kerr, S. (2017). Exploring the impact of artificial intelligence in teaching and learning in higher education. Research and Practice in Technology, 22, 1-13. https://telrp.springeropen.com/articles/10.1186/s41039-017-0062-8 Prusty, G., Russell, C., Ford, R., Ben-Naim, D., Ho, S., Vrcelj, Z., Marcus, N., Mccarthy, T., Goldfinch, T., Ojeda, R., Gardner, A., Tom, M., & Roger, H. (2011). Adaptive tutorials to target threshold concepts in mech