Development of the Online Course Overload Indicator and the Student Mental Fatigue Survey

Keywords: mental fatigue, cognitive overload, online learning, online course design, student support, online course development


The purpose of this study is to develop and examine the psychometric properties of the Online Course Overload Indicator (OCOI) and the Student Mental Fatigue Survey (SMFS). The OCOI was designed to measure students’ perceptions of cognitive overload in online courses. The SMFS was used to assess students’ perceptions of mental fatigue while taking online courses. An exploratory factor analysis was conducted on a sample of 378 undergraduate students from various institutions offering online courses across the United States. Results of a factor and reliability analyses confirmed that the instruments are valid and reliable measures of students’ perceived mental fatigue and overload from online course elements. The analysis supported the model that students’ perceptions of overload in online courses consist of four constructs—information relevance, information overload, course design, and facilitation—in addition to the one-factor structure of the SMFS, which consists of the student mental fatigue construct.

Author Biographies

Gail Alleyne Bayne, Texas Tech University

Gail Alleyne Bayne received an Ed.D. degree from Texas Tech University in Instructional Technology. Dr. Alleyne Bayne is currently an Adjunct Instructor at Texas Tech University teaching undergraduate and graduate synchronous and asynchronous courses. Her research interests are online learning and mental fatigue, cooperative and project-based learning in online environments.

Fethi A. Inan, Texas Tech University

Fethi A. Inan is a President's Excellence in Teaching Professor of Instructional Technology. He has a diverse background and experience in learning intelligent tutoring systems, instructional multimedia, and data analytics. Dr. Inan's research interests are online learning, individual differences, adaptive systems, and technology integration.


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How to Cite
Alleyne Bayne, G., & Inan, F. A. (2022). Development of the Online Course Overload Indicator and the Student Mental Fatigue Survey. The International Review of Research in Open and Distributed Learning, 23(4), 75-92.
Research Articles