ACADEMIC PROGRESS OF STUDENTS IN QUANTITATIVE COURSES AT NIGDE UNIVERSITY VOCATIONAL SCHOOL OF SOCIAL SCIENCES: A PREDICTION USING MARKOV MODEL
Öz
This study analyzes and predicts the academic progress of vocational school of social sciences students in quantitative courses in order to improve student progress in education. A population of 232 students taking commercial mathematics and statistics courses in 2014/2015 academic year is selected. The academic progress of students are estimated by using final examination scores extracted from OGRIS student otomation system of Nigde University. Academic progress is classified with respect to the mean test score as “greater”, “stable” and “lower”. Chi-square test is used for statistical analysis and predictions are estimated by one step stochastic Markov chain model. Direction of academic progress is predicted by the product of the initial probability matrix and transition probability matrix. In 2028-2029 academic year, the probabilities of improvement, no change and decline become stable approximately at 28%, 20% and 52%, respectively. The results are discussed and interpreted.
Anahtar Kelimeler
Sayısal Yöntemler, Ak ademik Performans, Geçiş Olasılık ları Matrisi, Mark ov Analizi
Kaynakça
- Ma, X., & Kishor, N. (1997). Assessing the relationship between attitude toward mathematics and achievement in mathematics: A meta-analysis. Journal of Research in Mathematics Education, 28(1): 26-47.
- Taha H. A. (2000). Yöneylem Araştırması, 6.Baskıdan Çeviri, İstanbul: Literatür Yayıncılık.
- Anthony G. (2000). Factors influencing first-year students' success in mathematics, International Journal of Mathematical Education in Science & Technology, 31(1):3-14.
- Abu-Hilal, M. M. (2000). A structural model of attitudes toward school subjects, academic aspirations, and achievement. Educational Psychology, 20(1):75-84.
- Wainwright, P. (2006), Project Proposal: An Enrollment Retention Study Using A Markov Model For A Regional State University Campus In Transition, Indiana University
- Birch, E. & Miller, P. (2007). The Influence Of Type Of High School Attended On University Performance, Australian Economic Papers, 46(1):1-17
- Alawadhi, 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.
- Ilgan A. (2013). Predicting College Student Achievement in Science Courses, Journal of Baltic Science Education, 12(3): 322-336
- Öztürk A. (2014). Yöneylem Araştırması, 15.Baskı, Bursa: Ekin Kitabevi Yayınları.
- Bluman A.G. (2014). Elemantary Statistics, 9th Ed.,New York: McGraw Hill Education.