MULTILEVEL REGRESSION ANALYSIS OF LEARNING DISTRACTIONS AMONG HIGHER EDUCATION STUDENTS

Authors

DOI:

https://doi.org/10.20535/2410-8286.323075

Keywords:

Academic Resilience, Learning Distractions , Learning Outcomes , Multilevel Models , University Students

Abstract

Learning distractions, both internal and external, disrupt students’ focus and academic performance. Understanding these distractions is crucial for developing effective strategies to mitigate their effects and enhance learning outcomes for university students. Little literature is available on assessing students' learning distractions in Ethiopian universities. The current study aims to identify learning distractions of university students and their correlates using a multilevel regression analysis. A cross-sectional survey with a self-administered questionnaire, quantitative approach grounded in postpositivist and connectivism philosophies, is used to collect data from a sample of 1,380 students at the Addis Ababa Science and Technology University. The data are analyzed using SPSS version 27.0, Winsteps version 5.7.1.0, and R version 4.3.2. The multilevel model with random intercept and random-fixed slopes is used to analyze the learning distraction score of the students. The results show that the average learning distractions score is 33.70 out of 100, indicating moderate learning distraction levels among the students. Most (79.20%) students are in a good state, and 5.07% are academically resilient. About 15.44% of the students need help facing academic problems, and 0.29% require urgent university assistance due to early burnout. A significant portion (51.86%) of the variation in distraction score is due to differences between students’ years of stay at the university. Factors affecting learning distraction score include gender, age, income, time spent on social media, and academic resilience. Female students experience lower learning distraction as compared to males. Learning distraction score decreases with an increase in age. An increase in monthly income increases their learning distraction. Student learning distraction increases as the time spent on social media daily increases. Higher academic resilience reduces their distraction score. Interventions based on behavioral, cognitive, and social cognitive learning theories and self-regulated strategies are crucial for managing learning distractions at the university. The intervention may include well-planned training and awareness creation programs for the university students.

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Author Biographies

Endalkachew Debelu, Kotebe University of Education,Addis Ababa,Ethiopia

Ph.D Student of Statistics, Department of Mathematics

Ayele Goshu, Kotebe University of Education,Addis Ababa

Ph.D, Associate Professor, Department of Mathematics

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Published

2025-08-30

How to Cite

Debelu, E., & Goshu, A. (2025). MULTILEVEL REGRESSION ANALYSIS OF LEARNING DISTRACTIONS AMONG HIGHER EDUCATION STUDENTS. Advanced Education, 18(26), 122–141. https://doi.org/10.20535/2410-8286.323075

Issue

2025: Issue 26

Section

ARTICLES

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Copyright (c) 2025 Endalkachew Debelu, Ayele Goshu. The article cover was designed with the assistance of ChatGPT

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