Academic performance of engineering students: A predictive validity study of first‐year GPA and final‐year CGPA

Author:

Nurudeen Abdulhakeem Hassan1ORCID,Fakhrou Abdulnaser2,Lawal Nuruddeen3,Ghareeb Sara4

Affiliation:

1. Department of Mechanical Engineering University of Abuja Abuja Nigeria

2. College of Education Qatar University Al Rayyan Qatar

3. Educational Foundation University of Abuja Abuja Nigeria

4. College of Basic Education Kuwait City Kuwait

Abstract

AbstractStudents' academic achievement is regarded as the scholastic standing of students at the end of a given study period that is expressed in terms of grades. This study focused on students' first‐year GPA as a predictor of final‐year CGPA and the relationship between demographic attributes of the students to academic achievement. An ex‐post factor research approach was adopted, and Pearson's correlation and Regression Analysis were fitted with the data using Minitab software. The results of the study highlighted that first‐year GPA had a strong positive relationship with final‐year CGPA which is an indication that first‐year GPA greatly influences final‐year CGPA meanwhile, demographic characteristics have no significant correlation with students' final‐year CGPA. Finally, the correlations drawn from this study indicated that first‐year GPA had a strong positive relationship with final‐year CGPA. Therefore, the students should be properly guided, University administrators, Faculty members, policy‐makers and other stakeholders should effectively develop a monitoring blueprint for students' academic progress as poor performance has severe consequences on students, teachers should inculcate effective learning culture among students, while government and its supervisory agencies should provide adequate teaching and learning resources, create enabling learning environment for effective service delivery that focuses on improving students' performance in Engineering.

Funder

Qatar University

Publisher

Wiley

Subject

General Engineering,General Computer Science

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