Learning attributes of summa cum laude students: Experience of a Nigerian university

This paper presents data on the academic performance of a particular set of accounting students from the year of inception into a Nigerian university to the year of graduation. Descriptive analysis was performed on the dataset and a regression model which is capable of making predictions was fitted to the dataset. From the dataset, 24 out of the students who started with a first class result (CGPA above 4.50) still maintained a first class result at graduation. 4 out of the students who started with a first class result dropped to second class upper division before graduation. 4 out of the students who started with a second class upper division result moved to first class result before graduation. 28 out of 35 students who started with a second class upper division maintained a second class upper division result at graduation.

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“…Some recent studies on learning analytics include the works of Refs. [1] , [2] , [3] , [4] , [5] and the references therein.…”

Section: Experimental Design Materials and Methodsmentioning

confidence: 99%

Learning analytics: Data sets on the academic record of accounting students in a Nigerian University

et al. 2018

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“…*Many variables are often considered as key in the choice of university education. Some of the factors are conducive environment for effective learning, high graduation rates, low attrition rates for tutors, course accreditation by regulatory bodies, feedback from industry, academic ranking, affordable fees for low income families and so on (Odukoya et al, 2018a;2018b;2018c;Popoola et al, 2018). This paper however describes in details, the perceived relationship between the final graduating grade of students and their previous results in the university.…”

Section: Introductionmentioning

confidence: 98%

Analysis of the inter-relationship between students’ first year results and their final graduating grades

Oguntunde¹

2018

Int. j. adv. appl. sci.

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There is a tendency for students to lose focus in tertiary institutions because of change in environment and peer pressure (among several others); hence, a need to monitor and study the trend of students' performance in the tertiary institution. This article, therefore, seeks to know the correlation between the first year results and in particular, the final graduating grade of students in a leading Nigerian University. Test of normality was performed for the final graduating results and multiple linear regression models were fitted to the data; this enables us to predict what a student can graduate with having known a previous result (or first year result). All the analyses were performed using Minitab software. The result established that there are strong linear relationships between the GPAs as a student progresses in his/her academic journey.

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“…Value of the data The data is highly imperative for empirical evaluation of the relationship between entry qualifications and the academic performance of engineering undergraduates in Nigerian universities. This will help in determining the suitability and appropriateness of the admission policy set by universities and the NUC to engineering education in Nigeria [1] , [2] . Sound exploration of the data provided in this data article will help Nigerian universities, the NUC, engineering regulatory bodies, and relevant stakeholders to objectively evaluate and subsequently improve the quality of engineering education in the country [3] , [4] , [5] , [6] .…”

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confidence: 99%

“…The data is highly imperative for empirical evaluation of the relationship between entry qualifications and the academic performance of engineering undergraduates in Nigerian universities. This will help in determining the suitability and appropriateness of the admission policy set by universities and the NUC to engineering education in Nigeria [1] , [2] .…”

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confidence: 99%

Learning analytics: Dataset for empirical evaluation of entry requirements into engineering undergraduate programs in a Nigerian university

et al. 2018

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In Nigerian universities, enrolment into any engineering undergraduate program requires that the minimum entry criteria established by the National Universities Commission (NUC) must be satisfied. Candidates seeking admission to study engineering discipline must have reached a predetermined entry age and met the cut-off marks set for Senior School Certificate Examination (SSCE), Unified Tertiary Matriculation Examination (UTME), and the post-UTME screening. However, limited effort has been made to show that these entry requirements eventually guarantee successful academic performance in engineering programs because the data required for such validation are not readily available. In this data article, a comprehensive dataset for empirical evaluation of entry requirements into engineering undergraduate programs in a Nigerian university is presented and carefully analyzed. A total sample of 1445 undergraduates that were admitted between 2005 and 2009 to study Chemical Engineering (CHE), Civil Engineering (CVE), Computer Engineering (CEN), Electrical and Electronics Engineering (EEE), Information and Communication Engineering (ICE), Mechanical Engineering (MEE), and Petroleum Engineering (PET) at Covenant University, Nigeria were randomly selected. Entry age, SSCE aggregate, UTME score, Covenant University Scholastic Aptitude Screening (CUSAS) score, and the Cumulative Grade Point Average (CGPA) of the undergraduates were obtained from the Student Records and Academic Affairs unit. In order to facilitate evidence-based evaluation, the robust dataset is made publicly available in a Microsoft Excel spreadsheet file. On yearly basis, first-order descriptive statistics of the dataset are presented in tables. Box plot representations, frequency distribution plots, and scatter plots of the dataset are provided to enrich its value. Furthermore, correlation and linear regression analyses are performed to understand the relationship between the entry requirements and the corresponding academic performance in engineering programs. The data provided in this article will help Nigerian universities, the NUC, engineering regulatory bodies, and relevant stakeholders to objectively evaluate and subsequently improve the quality of engineering education in the country.

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Learning attributes of summa cum laude students: Experience of a Nigerian university

Cited by 10 publications

References 10 publications

Learning analytics: Data sets on the academic record of accounting students in a Nigerian University

Learning analytics: Data sets on the academic record of accounting students in a Nigerian University

Analysis of the inter-relationship between students’ first year results and their final graduating grades

Learning analytics: Dataset for empirical evaluation of entry requirements into engineering undergraduate programs in a Nigerian university

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