MULTIPLE LINEAR REGRESSION MODEL OF UNDERGRADUATE STUDENTS’ ACADEMIC PERFORMANCE AT UEAB, KENYA
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Date
2019-09
Authors
Journal Title
Journal ISSN
Volume Title
Publisher
EPRA International Journal of Research and Development (IJRD)
Abstract
Generally, the University students have a vast variety of subjects in the core area which is sometimes problematic for the
students to comprehend. They have chosen social media or rather internet, where there is a lot of learning materials
concerning the area of their specialty. Predicting the academic performance of the students helps the instructor to
develop the virtuous understanding of student’s community and take the fit procedures to make their learning
comfortable. MLR was used to build a model which predicts the performance of the students in the discipline of
Statistics. Based on the collected data, the predictors of this model focused on how many hours spent on the social
media. The predicted Cumulative GPA at every academic semester period was the dependent variable. The results
revealed that the predicted model scores gives a better accuracy with
M
1
through
M
3
in the range of 5%
from the
original scores. Therefore, the instructors can analyze the performance of the students and can also extemporize the
teaching techniques used based on the result, of not only Statistics students, but also other areas they handle.