Application of Ordinal Logistic Regression in the Study of Students’ Performance

Adejumo, A. O., Adetunji, A. A.


The problem of incessant decline in academic performance of Nigeria students in recent years cannot be over emphasized. Despite importance attached to academic performance, researchers have shown that students’ performance is declining. Researches had also shown that there are a lot of factors responsible for this trend. Using data obtained from records of graduated students from the Faculty of Science, University of Ilorin for 2011/2012 academic session, mode of entry, age at entry, department, and sex of students are examined as factors that could contribute to students’ performance. Ordinal Logistic Regression (Proportional Odds Model) is used to model the data and the results reveal that only sex of students is not a determinant factor of final grade that students may attained at graduation. This research also finds that there is equal chance for both male and female students to graduate from a university with First Class, hence, governments’ policy on education should be focused on both gender instead of special attention usually given to female students. It has also been established that younger students perform better than the older ones; hence, age of students at entry into any of educational level should not be of major concerned but the ability of such student to cope with the demand of such level. It is also established that the highest odds of graduating with First Class is obtained by students who were admitted through Direct Entry (DE). Most of these students are educationally matured as they have spent at least two academic sessions in their previous school mostly Polytechnics, hence, in order to ensure that we have better graduates in our tertiary institutions, a policy that encouraged programmes such as Higher School Certificate (HSC) should be re-introduced into the system to ensure that only set of academically matured students get in different universities.

Keywords: Ordinal Logistic Regression, Odds Ratio, Link Function, Students’ Performance

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ISSN (Paper)2224-5804 ISSN (Online)2225-0522

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