This paper investigates earlier research publications on personalized learning, exceptionally personalized e-learning, appearing in the World of Science Education and Educational Research categories. The researcher initially consults HistCite to identify the range of relevant articles and their citation links. The HistCite technique finds and isolates personalized e- learning studies. In addition, several articles are selected based on criteria and the EPPI guide for in-depth analysis to discover trends, design principles, and future research prospects.

Zhen Li. A System Literature Review of Personalized e-Learning. International Journal of Frontiers in Sociology (2021), Vol. 3, Issue 19: 91-97. https://doi.org/10.25236/IJFS.2021.031918.

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[2] Capuano, N., Mangione, G. R., Pierri, A., & Salerno, S. (2014a). Personalization and Contextualization of Learning Experiences based on Semantics. International Journal of Emerging Technologies in Learning (iJET), 9(7), 5. https://doi.org/10.3991/ijet.v9i7.3666

[3] Capuano, N., Mangione, G. R., Pierri, A., & Salerno, S. (2014b). Personalization and Contextualization of Learning Experiences based on Semantics. International Journal of Emerging Technologies in Learning (iJET), 9(7), 5. https://doi.org/10.3991/ijet.v9i7.3666

[4] Chen, C.-M. (2008). Intelligent web-based learning system with personalized learning path guidance. Computers & Education, 51(2), 787–814. https://doi.org/10.1016/j.compedu.2007.08.004

[5] Chen, C.-M., Lee, H.-M., & Chen, Y.-H. (2005). Personalized e-learning system using Item Response Theory. Computers & Education, 44(3), 237–255. https://doi.org/10.1016/j.compedu.2004.01.006

[6] Drissi, S., & Amirat, A. (2016). An Adaptive E-Learning System based on Student’s Learning Styles: An Empirical Study.

[7] International Journal of Distance Education Technologies, 14(3), 34–51. https://doi.org/10.4018/IJDET. 2016070103

[8] Dwivedi, P., Kant, V., & Bharadwaj, K. K. (2018). Learning path recommendation based on modified variable length genetic algorithm. Education and Information Technologies, 23(2), 819–836. https://doi.org/10.1007/s10639-017-9637-7

[9] Ellis, R. A., Han, F., & Pardo, A. (2019). When Does Collaboration Lead to Deeper Learning? Renewed Definitions of Collaboration for Engineering Students. IEEE Transactions on Learning Technologies, 12(1), 123–132. https://doi.org/10.1109/TLT.2018.2836942

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[11] Firat, M., & Bozkurt, A. (2020). Variables affecting online learning readiness in an open and distance learning university. Educational Media International, 57(2), 112–127. https://doi.org/10.1080/09523987. 2020.1786772

[12] Hariyanto, D., Triyono, M., & Koehler, T. (2020). Usability evaluation of personalized adaptive e-learning system using USE questionnaire. Knowledge Management and E-Learning, 12, 85–105. https://doi.org/10.34105/j.kmel.2020.12.005

[13] JuanYang, Zhi Xing Huang, Yue Xiang Gao, & Hong Tao Liu. (2014). Dynamic Learning Style Prediction Method Based on a Pattern Recognition Technique. IEEE Transactions on Learning Technologies, 7(2), 165–177. https://doi.org/10.1109/TLT.2014.2307858

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[15] Logue, A. W., Douglas, D., & Watanabe-Rose, M. (2019). Corequisite Mathematics Remediation: Results Over Time and in Different Contexts. Educational Evaluation and Policy Analysis, 41(3), 294–315. https://doi.org/10.3102/0162373719848777

[16] Melia, M., & Pahl, C. (2009). Constraint-Based Validation of Adaptive e-Learning Courseware. IEEE Transactions on Learning Technologies, 2(1), 37–49. https://doi.org/10.1109/TLT.2009.7

[17] Pardo, A., Gasevic, D., Jovanovic, J., Dawson, S., & Mirriahi, N. (2019). Exploring Student Interactions With Preparation Activities in a Flipped Classroom Experience. IEEE Transactions on Learning Technologies, 12(3), 333– 346. https://doi.org/10.1109/TLT.2018.2858790

[18] Pardo, A., Han, F., & Ellis, R. A. (2017). Combining University Student Self-Regulated Learning Indicators and Engagement with Online Learning Events to Predict Academic Performance. IEEE Transactions on Learning Technologies, 10(1), 82–92. https://doi.org/10.1109/TLT.2016.2639508

[19] Pardo, A., Jovanovic, J., Dawson, S., Gašević, D., & Mirriahi, N. (2019). Using learning analytics to scale the provision of personalised feedback. British Journal of Educational Technology, 50(1), 128–138. https://doi.org/10.1111/bjet.12592

[20] Park, C., Kim, D., Cho, S., & Han, H.-J. (2019). Adoption of multimedia technology for learning and gender difference.

[21] Computers in Human Behavior, 92, 288–296. https://doi.org/10.1016/j.chb.2018.11.029

[22] Santoso, H. B., Putra, P. O. H., & S, F. F. F. H. (2021). Development & Evaluation of E-Learning Module Based on Visual and Global Preferences Using a User-Centered Design Approach. International Journal of Emerging Technologies in Learning (IJET), 16(15), 139–151.

[23] Sergis, S., & Sampson, D. G. (2016). Learning Object Recommendations for Teachers Based On Elicited ICT Competence Profiles. IEEE Transactions on Learning Technologies, 9(1), 67–80. https://doi.org/10.1109/TLT.2015.2434824

[24] Thanyaphongphat, J., & Panjaburee, P. (2019). Effects of a personalised ubiquitous learning support system based on learning style-preferred technology type decision model on university students’ SQL learning performance.

[25] International Journal of Mobile Learning and Organisation, 13(3), 233. https://doi.org/10.1504/IJMLO. 2019.100379

[26] Wang, H.-C., & Huang, T.-H. (2013). Personalized e-learning environment for bioinformatics. Interactive Learning Environments, 21(1), 18–38. https://doi.org/10.1080/10494820.2010.542759

[27] Wang, T.-H. (2014). Developing an assessment-centered e-Learning system for improving student learning effectiveness.

[28] Computers & Education, 73, 189–203. https://doi.org/10.1016/j.compedu.2013.12.002

[29] Wongwatkit, C., Panjaburee, P., Srisawasdi, N., & Seprum, P. (2020). Moderating effects of gender differences on the relationships between perceived learning support, intention to use, and learning performance in a personalized e- learning. Journal of Computers in Education, 7(2), 229–255. https://doi.org/10.1007/ s40692-020-00154-9

[30] Yousuf, B., & Conlan, O. (2018). Supporting Student Engagement Through Explorable Visual Narratives. IEEE Transactions on Learning Technologies, 11(3), 307–320. https://doi.org/10.1109/TLT.2017.2722416