Data analytics : an exploration of quality control to determine students’ academic performance
Balogun, Oluwafemi Samson; Olaleye, Sunday Adewale; Agjei, Richard Osei; Adusei, Akwasi Gyamerah (2020-11-04)
Oluwafemi Samson BALOGUN, Sunday Adewale OLALEYE, Richard Osei AGJEI and Akwasi Gyamerah ADUSEI “Data Analytics: An Exploration of Quality Control to Determine Students’ Academic Performance” Proceedings of the 36th International Business Information Management Association (IBIMA), ISBN: 978-0-9998551-5-7, 4-5 November 2020, Granada, Spain.
© 2020 The Autrhos. Published by International business information management association. Creative Commons Attribution License 4.0 Unported.
https://creativecommons.org/licenses/by/4.0/
https://urn.fi/URN:NBN:fi-fe20201217101207
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Abstract
Quality control and improvement is a crucial process development of any institution that craves growth. One part of the SPC approach is to aid the constant improvement of performance by further reducing unexplained variability. Another aspect of Statistical Process Control (SPC) is that planned and unplanned changes signaled as fast as considering the natural process variability. This paper aimed to determine whether students’ performance is significantly distributed according to academic patterns using the quality control procedure. This study found that one of the notable Nigerian Private University student academic performances drawn from three engineering departments based on the mean chart is in control and out of control, indicating excellent, intermediate, and lower results. The study also shows upper, average, and lower results with a close margin. This insight is an interdepartmental issue. The school managers need to formulate a holistic policy that will improve the existing academic performance to move the outlier students from worst to better and from better to best.
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