Modeling of students’ cumulative grade-point average (CGPA): A Markov chain approach
DOI:
https://doi.org/10.64497/jssci.119Keywords:
Markov chain, states, probability, transition, absorption, transientAbstract
This paper focuses on applying some basic concepts in discrete-time Markov chains to the modeling of students’ Cumulative Grade-Point Average (CGPA), using records of their first year in school. The primary focus is on forecasting the proportion of students that transit from one grade to another, as they journey through their academic semesters. The Fundamental matrix is obtained for the absorbing Markov chain, and other indices like the initial distributions, expected sojourn times for the transient states, the n-step transition probabilities and the absorption probabilities are obtained for the process. The results show that state 1(First class) is an absorbing state, which makes its expected sojourn time to be infinity. The expected sojourn times for states 2, 3, 4, 5, 6 have respectively been found to be 6.67, 10.00, 3.45, 1.67, 1.54. the probability of absorption to state 1, from the other (transient) states are all zeros.
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[1] M. A. Guerry and T. D. Feyter, "Markovian approaches in modeling workforce systems.," Journal of current issues in Fianace, Business and Economics, vol. 2, no. 4, pp. 1 - 20, 2009.
[2] R. Belhaj and M. Tkiouat, "A markov model for human resource supply forecast: dividing the HR system into subgroups.," Journal of Service Science and Management, vol. 6, no. 3, 2013. DOI: https://doi.org/10.4236/jssm.2013.63023
[3] A. U. Udom and U. G. Ebedoro, "On multinomial hidden Markov model for hierarchical manpower systems," Communications in Statistics - Theory and Methods, 2019. DOI: https://doi.org/10.1080/03610926.2019.1650185
[4] C. H. Nwankwo and E. U. George, "Optimization of a network of queues in a university teaching hospital," African Journal of Mathematics and Statistics Studies, vol. 3, no. 1, pp. 35 - 53, 2020.
[5] A. E. Usoro, E. U. George, I. N. Ikpang, N. Ekong and N. M. Edem, "Multivariate analysis of academic performance of undergraduate students admitted through unified ertiary matriculation examination and direct entry: a case study of Akwa Ibom State University, Akwa Ibom State, Nigeria," Researchjournali's Journal of Mathematis, vol. 7, no. 2, pp. 2 - 10, 2020.
[6] K. J. Adebayo, I. O. Adisa, A. O. Dele-rotimi, M. F. Akinmuyise, S. O. Ayinde, A. O. Adedeji and T. E. Olaosebikan, "On application of absorbing Markov chain model to determine students' academic progress: A case study of Mathematics Department, Ekiti State University, Nigeria," European Modern Studies Journal, vol. 8, no. 3, pp. 730 - 744, 2024. DOI: https://doi.org/10.59573/emsj.8(3).2024.45
[7] B. O. Yekeen, Y. Yakubu and N. Muhammad, "Modeling students' academic performance and progress: A discrete-time Markov chain approach," FUDMA Journal of Sciences, vol. 8, no. 6, pp. 444 - 449, 2024. DOI: https://doi.org/10.33003/fjs-2024-0806-3049
[8] P. G. Doyle and J. L. Snell, Random Walks and Electric Networks, Washington DC: The Mathematical Association of America, 1984. DOI: https://doi.org/10.5948/UPO9781614440222
[9] O. C. Ibe, Markov Processes for Stochastic Modeling, New York: Elsevier, 2013. DOI: https://doi.org/10.1016/B978-0-12-407795-9.00015-3
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Copyright (c) 2026 Ekemini U. George, Ikpang N. Ikpang, Akaninyene O. Ekong
This work is licensed under a Creative Commons Attribution 4.0 International License.
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