期刊名称：Journal of Theoretical and Applied Information Technology
印刷版ISSN：1992-8645
电子版ISSN：1817-3195
出版年度：2021
卷号：99
期号：3
页码：651
出版社：Journal of Theoretical and Applied
摘要：The automated examination result processing system (AERPS) which is currently used by many tertiary institutions in Nigeria and beyond for monitoring students� academic progression (from their first year of study till their possible graduation from school) is deficient to a large extent. This is because the AERPS uses only the CGPA of students as the yardstick for determining such progression out of several other factors like: (i) a student�s academic duration in school, (ii) a student�s CGPA benchmark, (ii) a student�s examination and moral misconducts in school, etc. These factors are very paramount in ascertaining a student�s true academic state so that an appropriate action can be taken on the student for proper academic and moral nurturing such as: promoting him/her to the next level of study, or placing him/her on one year probation, or suspending/expelling him/her from school, etc. The aim of this work, therefore, is to develop a finite state machine model that will incorporate all these multi-faceted factors affecting the academic progression of an undergraduate student for effective monitoring. A mixture of quantitative and qualitative research methodology was used in developing the mathematical models required for simulating the input data of students. The generated input data was used by the FSM model to simulate the academic progression of 25 first year students for one academic session. Results showed that, using the 95% confidence interval of the t-distribution, the FSM model is better than the AERPS technique in determining the true academic state of a student. This ensures that every student is properly screened in character and learning before graduating. It also helps course advisers/lecturers in counselling students properly during course registration as well as in writing unbiased referee reports about them when needed.
关键词：Finite State Machine; Model; Academic Progression; Automated Examination Result Processing System; Simulation
