Mitigating Information Overload in an Online Undergraduate Learning Environment

Abstract

Information overload (IO) is a concern becoming increasingly pertinent in education over the past few years, further amplified by the transition towards using more technology in the classroom. While there is currently no set definition for IO, it is often defined as an excess of information that disrupts knowledge processing. As the effects of the COVID-19 pandemic intensified in March of 2020, post-secondary institutions transitioned to online learning. Elements including learning management systems and software such as Zoom or Microsoft Teams heighten the effects of IO online. As such, it is of utmost importance that instructors find ways to optimize their online course design to ensure student success. While course content may not be able to change drastically, the modes of delivery have potential to alleviate some IO.

The main objective of this research is to investigate different strategies undergraduate instructors can employ to mitigate IO in online learning. Cognitive load theory is examined to identify instructional strategies that can be used to mitigate IO. This review will describe the construction of: (1) a review of cognitive load theory and the need for mitigating IO and (2) a practice guide purposed with providing undergraduate instructors with strategies to mitigate IO in online courses. The strategies presented in the practice guide are be based on ways to reduce extraneous load within cognitive load theory. This research is extremely important and currently especially relevant as the optimization of online courses has the potential to directly benefit students and improve their academic performance.