Academic performance data of undergraduate students׳ in 23 programmes from a private University in Nigeria

Azubuike, Ezenwoke and Oluwadamilola, Ogunwale and Matiluko, Opeyemi E. and Igbekele, Emmanuel Academic performance data of undergraduate students׳ in 23 programmes from a private University in Nigeria. Data in Brief.

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Abstract

The quality of teaching and learning in higher education in many developing countries can be improved as institutions in this region adopt evidence-based practices that emphasize empirical mea- surements, observations, analysis and reports of learning out- comes. This article presents and analyses data on the academic performances of undergraduate students for duration of three semesters across the three major colleges of Landmark University, a private University in Nigeria. The colleges include the college of Agricultural Sciences (CAS), college of Business and Social Sciences (CBSS), and the college of Science and Engineering (CSE). Furthermore, population samples of 82, 577 and 812 under- graduates were selected randomly from CAS, CBSS and CSE respectively; totaling a population of sample of 1471 under- graduates from all academic levels (200L–500L) with the exception of first year students. The random selection was drawn from three consecutive semesters- the first and second semesters of academic 2016/2017 session and first semester of 2017/2018 academic session. The cumulative GPA of the sample population of students for the semester highlighted was obtained from the Centre for Systems and Information Services Units of the University. Moti- vated by the need to promote evidence-based research in aca- demic excellence, a spread-sheet containing the detailed dataset is attached to this article. The descriptive statistics and frequency distributions of academic performance data are presented in with the use of tables and graphs for easy data interpretations. The data provided in this article supports the goal of a regional policy towards the realization of qualitative sustainable education.

Item Type: Article
Subjects: Q Science > Q Science (General)
Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Q Science > QA Mathematics > QA76 Computer software
Divisions: Faculty of Engineering, Science and Mathematics > School of Electronics and Computer Science
Depositing User: DR EMMANUEL IGBEKELE
Date Deposited: 15 Jan 2024 16:03
Last Modified: 15 Jan 2024 16:03
URI: https://eprints.lmu.edu.ng/id/eprint/5194

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