Ordinal Logistic Regression for Predicting the Effects of Some Variables Affecting Student’s Academic Performance

dc.contributor.authorSidi, Shamasu
dc.contributor.authorMaijamaa, Bilkisu
dc.date.accessioned2023-12-14T08:14:43Z
dc.date.available2023-12-14T08:14:43Z
dc.date.issued2019-09-11
dc.description.abstractThe difficulty that leads to failure of students to attain a good higher performance in University lately can’t be overstressed. Regardless of the benefit connected to student’s performance, academic analysts have shown it in their different papers that there is a decline in students’ achievement. Explorers had additionally demonstrated that there are great deals of components dependable for this pattern. Utilizing the information gotten from a questionnaire from students of a University. Sex, Communication skills, Guidance, Proximity of student to school, Learning facilities, Pear group, Lack of learning materials and Family stress of students are inspected to the components that seem to contribute to student’s execution. Ordinal Logistic Regression (proportional odds model) is utilized to model the information and the output reveal that sex, communication, proximity to school, Peer group, Learning Facilities of understudies isn’t a determinant component of final grade that students may accomplished at graduation. This research finds that there is equal chance for both male and female students to graduate from university with best class of degree, hence. It is also established that the highest chance of graduating with best Class of degree is gotten by students who were giving proper guidance. Most of these students are giving a well proper care both academically, and financially which contribute to their high performances in their various departments. It has also seen that the model for family stress has the highest clarification for the variations in the CGPA (final grade of students). Hence a policy should be recommended to encourage students with various understanding of different disciplines to study at their own course of interest and government’s strategy on education should be centered on the two sexual orientations rather than exceptional consideration generally given to female students.en_US
dc.identifier.citation1. Ali S. Haider, Z., Munir, F. Khan, H. & Ahmed, A. (2013). Factors Contributing to the Students’ Academic Performance. A case study of Islamia University, Sub-Campus.’’ American Journals of Education Journal, Vol. 1 8, (pp1-10). 2. Ali, Norhidayah, Jusoff, Kamaruzaman, Ali, Syukriah, Mokhtar, Najah and Salamt, Azni Syafena Andin. (20 December 2009). ‘The Factors Influencing Students’ Performance at Universiti Teknologi MARA Kedah, Malaysia’. Canadian Research & Development Center of Sciences and Cultures, Vol.3 No.4. 3. Norhidayah, A, Kamaruzaman, J Syukriah, A, Najah, M and Azni, S, Andin, S. (2009). ‘The Factors Influencing Students’ Performance at UniversitiTecknology MARA Kedah, Malaysia’. Canadian Research & Development Center of Sciences and Cultures,3 (4), (pp 81-99) 4. Hijazi, Syed Tahir and Naqvi, S.M.M. Raza. (2006). ‘Factors Affecting Students’ Performance. A Case of Private Colleges’. Bangladesh e- Journal of Sociology. Volume 3, Number 1, (pp 1-10) 5. Harb, Nasri and El-Shaarwi, Ahmed. (July 2006). ‘Factors Affecting Students' Performance’. MPRA Paper No. 1362. 6. Kombo, D. K. & Tromp, D. L. (2006). Proposal and thesis writing, An Introduction. Pauline Publication Nairobi, Africa. Laws, S. & Harper, C. & Marcus, R. (2003). Research for Development. A Practical Guide. London. Sage Publication. 7. Yamane, Taro 1967. Statistics, An Introductory Analysis, 2nd Ed., New York: Harper and Row. 8. Mushtaq I., & khan, S.N. (2012). Factors affecting student academic performance. Global journal of management and business research Vol 12 No 9.en_US
dc.identifier.urihttps://keffi.nsuk.edu.ng/handle/20.500.14448/6225
dc.language.isoenen_US
dc.publisherDepartment of Statistics, Nasarawa State University Keffi.en_US
dc.subjectOrdinal Logistic Regression, Odds Ratio, Link Function, Students’ Performanceen_US
dc.titleOrdinal Logistic Regression for Predicting the Effects of Some Variables Affecting Student’s Academic Performanceen_US
dc.typeArticleen_US

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