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

被引:7
|
作者
Odukoya, Jonathan A. [1 ]
Popoola, Segun, I [2 ]
Atayero, Aderemi A. [2 ]
Omole, David O. [3 ]
Badejo, Joke A. [2 ]
John, Temitope M. [2 ]
Olowo, Olalekan O. [2 ]
机构
[1] Covenant Univ, Dept Psychol, Ota, Nigeria
[2] Covenant Univ, Dept Elect & Informat Engn, Ota, Nigeria
[3] Covenant Univ, Dept Civil Engn, Ota, Nigeria
来源
DATA IN BRIEF | 2018年 / 17卷
关键词
Smart campus; Learning analytics; Sustainable education; Nigerian university; Education data mining; Engineering;
D O I
10.1016/j.dib.2018.02.025
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
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. (C) 2018 The Authors. Published by Elsevier Inc.
引用
收藏
页码:998 / 1014
页数:17
相关论文
共 50 条
  • [1] ON THE USE OF ENTRY REQUIREMENTS FOR UNDERGRADUATE ACCOUNTING PROGRAMS
    DOCKWEILER, RC
    WILLIS, CG
    [J]. ACCOUNTING REVIEW, 1984, 59 (03): : 496 - 504
  • [2] Open University Learning Analytics dataset
    Kuzilek, Jakub
    Hlosta, Martin
    Zdrahal, Zdenek
    [J]. SCIENTIFIC DATA, 2017, 4
  • [3] Open University Learning Analytics dataset
    Jakub Kuzilek
    Martin Hlosta
    Zdenek Zdrahal
    [J]. Scientific Data, 4
  • [4] Learning analytics for smart campus: Data on academic performances of engineering undergraduates in Nigerian private university
    Popoola, Segun, I
    Atayero, Aderemi A.
    Badejo, Joke A.
    John, Temitope M.
    Odukoya, Jonathan A.
    Omole, David O.
    [J]. DATA IN BRIEF, 2018, 17 : 76 - 94
  • [5] Engineering Requirements with Desiree: An Empirical Evaluation
    Li, Feng-Lin
    Horkoff, Jennifer
    Liu, Lin
    Borgida, Alex
    Guizzardi, Giancarlo
    Mylopoulos, John
    [J]. ADVANCED INFORMATION SYSTEMS ENGINEERING (CAISE 2016), 2016, 9694 : 221 - 238
  • [6] Pharmacy Students' Approaches to Learning in Undergraduate and Graduate Entry Programs
    Smith, Lorraine
    Krass, Ines
    Sainsbury, Erica
    Rose, Grenville
    [J]. AMERICAN JOURNAL OF PHARMACEUTICAL EDUCATION, 2010, 74 (06) : 1 - 6
  • [7] ORGANIZATION OF UNDERGRADUATE PROGRAMS IN NUCLEAR ENGINEERING AT OREGON STATE UNIVERSITY
    BUPP, LP
    [J]. ENGINEERING EDUCATION, 1969, 60 (01): : 61 - &
  • [8] Open Learning Analytics: A Systematic Review of Benchmark Studies using Open University Learning Analytics Dataset (OULAD)
    Alhakbani, Haya A.
    Alnassar, Fatema M.
    [J]. PROCEEDINGS OF 2022 7TH INTERNATIONAL CONFERENCE ON MACHINE LEARNING TECHNOLOGIES, ICMLT 2022, 2022, : 81 - 86
  • [9] UNIVERSITY MANAGEMENT TRAINING PROGRAMS - EMPIRICAL EVALUATION
    LEE, SM
    DEAN, CC
    [J]. TRAINING AND DEVELOPMENT JOURNAL, 1971, 25 (01): : 32 - 37
  • [10] Learning Analytics of Outcomes-Based Engineering Programs’ Data
    Yahya, Anwar Ali
    [J]. Computers in Education Journal, 2021, 13 (03):