1st Australian International Conference on Industrial Engineering and Operations Management

A Multiple Regression Analysis of Academic Workload, Stress Level, Procrastination, and Academic Performance of 4th year Architecture and Industrial Engineering Students A.Y 2022-2023

Jussell Joe Pizarro
Publisher: IEOM Society International
0 Paper Citations
Track: Undergraduate Student Paper Competition

Many students, particularly 4th-year Architecture and Industrial Engineering students, have been influenced by the change to e-learning in the Philippines as a result of the COVID-19 pandemic. This puts a strain on college students’ efforts to fulfill daily academic demands, which can negatively impact their well-being and motivation to study. Due to the effects of the Covid-19 pandemic, the education sector adopted a new normal in the form of Online Learning. This paper addresses different factors affecting students academic performance such as academic workload, stress level, and procrastination in online classes. The study aims to establish the multiple regression  relationship between  academic workload, academic stress, academic procrastination and academic performance.This study benefits and serve awareness for students, faculty teachers,Commission of Higher Education(CHED), and future researchers towards the factors that could affects the students academic performance based on the level of workload, stress, and academic procrastination.The number of participants of architecture students with 107 and industrial engineering students with 71 with a total of 178 students. The results shows , the average level of procrastination is 26.75(High)  for architecture students and 28.4(High) for industrial engineering students. While the average academic workload for architecture students is 16.95(High) and for industrial engineering students is 17.49(High), the average academic stress for architecture students is 26.75(High) and for industrial engineering is 17.75(Moderate). The results showed that academic workload and procrastination had a significant relationship with students' academic performance based on the indicated coefficients with a 95% confidence interval. In the model summary, R-squared = 47.84% variance shows that the independent variable a had a significant relationship in students' academic performance, which is normal since predictive analysis of human behavior tends to give a value of less than 50%.

Published in: 1st Australian International Conference on Industrial Engineering and Operations Management, Sydney, Australia

Publisher: IEOM Society International
Date of Conference: December 21-22, 2022

ISBN: 979-8-3507-0542-3
ISSN/E-ISSN: 2169-8767