Ahmad, S. F., Alam, M. M., Rahmat, M. K., Mubarik, M. S., & Hyder, S. I. (2022). Academic and administrative role of artificial intelligence in education. Sustainability, 14(1101). https://doi.org/10.3390/su14031101

Feng, W., Tang, J., & Liu, T. X. (2019). Understanding Dropouts in MOOCs. Proceedings of the AAAI Conference on Artificial Intelligence33(01), 517-524. https://doi.org/10.1609/aaai.v33i01.3301517

Lu, O. H. T., Huang, A. Y. Q., Lin, A. J. Q., Ogata, H., & Yang, S. J. H. (2018). Applying Learning Analytics for the Early Prediction of Students’ Academic Performance in Blended Learning. Educational Technology & Society, 21 (2), 220–232

Moreno-Marcos, P. M., Muñoz-Merino, P. J., Alario-Hoyos, C., Estévez-Ayres, I., & Delgado Kloos, C. (2018). Analyzing the predictive power for anticipating assignment grades in a massive open online course. Behaviour & Information Technology, 37(10-11), 1021-1036. https://doi.org/10.1080/0144929X.2018.1458904

Qian, Y., Li, C.-X., Zou, X.-G., Feng, X.-B., Xiao, M.-H., & Ding, Y.-Q. (2022). Research on predicting learning achievement in a flipped classroom based on MOOCs by big data analysis. Computer Applied Applications in Engineering Education, 30, 222–234.  https://doi.org/10.1002/cae.22452

Romero, C. & Ventura, S. (2013). WIREs Data Mining Knowl Discov 2013, 3(1), 12–27 https://doi.org/10.1002/widm.1075

Terras, M. M., & Ramsay, J. (2015). Massive open online courses (MOOCs): Insights and challenges from a psychological perspective. British Journal of Educational Technology, 46(3), 472–487. https://doi.org/10.1111/bjet.12274

Zawacki-Richter, O., Marín, V. I., Bond, M., & Gouverneur, F. (2019). Systematic review of research on artificial intelligence applications in higher education—Where are the educators? International Journal of Educational Technology in Higher Education, 16(1), 1–27. https://doi.org/10.1186/s41239-019-0171-4