[Adam, R. Y. (2015). An Application of Markov Modeling to the Student Flow in Higher Education in Sudan. International Journal of Science and Research, 4(2), 49–54.]Search in Google Scholar
[Adeleke, R. A., Oguntuase, K. A. & Ogunsakin, R. E. (2014). Application Of Markov Chain To The Assessment Of Students ’ Admi ssion And Academic Performance In Ekiti State University. International Journal of Scientific & Technology Research, 3(7), 349–357.]Search in Google Scholar
[Al-Awadhi, S. A. & Ahmed, M. A. (2002). Logistic models and a Markovian analysis for student attrition. Kuwait Journal of Science and Engineering, 29(2), 25–40.]Search in Google Scholar
[Al-Awadhi, S. A. & Konsowa, M. (2007). An application of absorbing Markov analysis to the student flow in an academic institution. Kuwait Journal of Science & Engineering, 34(2A), 77–89.]Search in Google Scholar
[Al-Awadhi, S. & Konsowa, M. (2010). Markov Chain Analysis and Student Academic Progress: An Empirical Comparative Study. Journal of Modern Applied Statistical Methods, 9(2), 584–595.10.22237/jmasm/1288585500]Search in Google Scholar
[Arias Ortiz, E. & Dehon, C. (2013). Roads to Success in the Belgian French Community’s Higher Education System: Predictors of Dropout and Degree Completion at the Université Libre de Bruxelles. Research in Higher Education, 54(6), 693–723. http://doi.org/10.1007/s11162-013-9290-y10.1007/s11162-013-9290-y]Search in Google Scholar
[Aulck, L., Velagapudi, N., Blumenstock, J. & West, J. (2016). Predicting Student Dropout in Higher Education. Machine Learning; Computers and Society. Retrieved from http://arxiv.org/abs/1606.06364]Search in Google Scholar
[Auwalu, A., Mohammed, L. B. & Saliu, A. (2013). Application of Finite Markov Chain to a Model of Schooling. Journal of Education and Practice, 4(17), 1–10.]Search in Google Scholar
[Beichelt, F. (2006). Stochastic Processes in Science, Engineering and Finance. Boca Raton: Chapmna & Hall/CRC.10.1201/9781420010459]Search in Google Scholar
[Boath, E., Machin, R., Dixon, M., Thomas, N., Connell, P. O. & Taylor, L. (2016). Stop with the FLO : using text messaging to improve retention rates in University Students. Innovative Practice in Higher Education, 2(3), 29–39.]Search in Google Scholar
[Borgen, S. T. & Borgen, N. T. (2016). Student retention in higher education: Folk high schools and educational decisions. Higher Education, 71(4), 505–523. http://doi.org/10.1007/s10734-015-9921-710.1007/s10734-015-9921-7]Search in Google Scholar
[Brezavšček, A. & Baggia, A. (2015). Analysis of student’s flow in higher education study programmes using discrete homogeneous Markov chains. In L. Zadnik Stirn (Ed.), SOR ’15 proceedings, 13th International Symposium on Operational Research in Slovenia (pp. 473–478). Ljubljana: Slovenian Society Informatika, Section for Operational Research.]Search in Google Scholar
[Clarke, J. A., Nelson, K. J. & Stoodley, I. D. (2013). The place of higher education institutions in assessing student engagement, success and retention: a maturity model to guide practice. In Higher Education Research and Development Society of Australasia. AUT University, Auckland. Retrieved from http://eprints.qut.edu.au/60024/]Search in Google Scholar
[Clouder, L., Broughan, C., Jewell, S. & Steventon, G. (2012). Improving student engagement and development through assessment: Theory and practice in higher education. Routledge.]Search in Google Scholar
[Crippa, F., Mazzoleni, M. & Zenga, M. (2016). Departures from the formal of actual students’ university careers: an application of non-homogeneous fuzzy Markov chains. Journal of Applied Statistics, 43(1), 16–30. http://doi.org/10.1080/02664763.2015.109144610.1080/02664763.2015.1091446]Search in Google Scholar
[Hlavatý, R. & Dömeová, L. (2014). Students’ progress throughout examination process as a Markov chain. International Education Studies, 7(12), 20–29. http://doi.org/10.5539/ies.v7n12p2010.5539/ies.v7n12p20]Search in Google Scholar
[Hudoklin Božič, A. (2003). Stohastični procesi (6th ed.). Kranj: Moderna Organizacija.]Search in Google Scholar
[Mashat, A. F., Ragab, A. H. & Khedra, A. M. (2012). Decision Support System Based Markov Model for Performance Evaluation of Students Flow in FCIT-KAU. In roceedings of the ICCIT (pp. 409–414).]Search in Google Scholar
[Menéndez-Valdés, J. (2016). Current changes to the labour market may well define the future of Europe. Retrieved January 15, 2017, from https://www.eurofound.europa.eu/news/news-articles/labour-market-quality-of-life-social-policies/current-changes-to-the-labour-market-may-well-define-the-future-of-europe]Search in Google Scholar
[Moody, V. R. & DuClouy, K. K. (2014). Application of Markov Chains to Analyze and Predict the Mathematical Achievement Gap between African American and White American Students. Journal of Applied & Computational Mathematics, 3(161). http://doi.org/10.4172/2168-9679.100016110.4172/2168-9679.1000161]Search in Google Scholar
[Petty, T. (2014). Motivating first-generation students to academic success and college completion. College Student Journal, 48(2), 257–264.]Search in Google Scholar
[Rahim, R., Ibrahim, H., Kasim, M. M. & Adnan, F. A. (2013). Projection model of postgraduate student flow. Applied Mathematics and Information Sciences, 7(2 L), 383–387. http://doi.org/10.12785/amis/072L0110.12785/amis/072L01]Search in Google Scholar
[Rodríguez-Gómez, D., Meneses, J., Gairín, J., Feixas, M. & Muñoz, J. L. (2016). They have gone, and now what? Understanding re-enrolment patterns in the Catalan public higher education system. Higher Education Research & Development, 35(4), 815–828. http://doi.org/10.1080/07294360.2015.113788610.1080/07294360.2015.1137886]Search in Google Scholar
[Shah, C. & Burke, G. (1999). An undergraduate student flow model: Australian higher education. Higher Education, 37(4), 359–375.10.1023/A:1003765222250]Search in Google Scholar
[Symeonaki, M. & Kalamatianou, A. (2011). Markov Systems with Fuzzy States for Describing Students’ Educational Progress in Greek Universities. Isi, 1, 5956–5961. Retrieved from http://www.2011.isiproceedings.org/papers/950864.pdf]Search in Google Scholar
[Tijms, H. C. (2003). A First Course in Stochastic Models. Technometrics (Vol. 47). Chichester: John Wiley & Sons. http://doi.org/10.1198/tech.2005.s29310.1198/tech.2005.s293]Search in Google Scholar
[Watterson, C. A., Browne, W. N. & Carnegie, D. A. (2013). Steps to increase student engagement and retention in first year engineering. In Proceedings of 2013 IEEE International Conference on Teaching, Assessment and Learning for Engineering (TALE) (pp. 1–6). http://doi.org/10.1109/TALE.2013.665438810.1109/TALE.2013.6654388]Search in Google Scholar
[Wood, D., Gray-Ganter, G. & Bailey, R. (2016). Pre-commencement interviews to support transition and retention of first year undergraduate students. Student Success, 7(2), 21–31. Retrieved from https://student-successjournal.org/article/view/33810.5204/ssj.v7i2.338]Search in Google Scholar