Guidelines for Choosing Cognitive Load Measures in Perceptually Rich Environments

Abstract

Cognitive load measurement is a methodological issue of high importance in all learning settings involving a high perceptual richness, such as virtual and augmented reality. As a result of the growing number of cognitive load measurement methods and surveys, it can be difficult to choose the optimal measurement instrument for learning tasks in perceptually rich environments. Current research suggests that survey-based methods do not necessarily have to be less valid than physiological measures. Furthermore, in several studies, single-item measures of cognitive load have shown a high negative correspondence with learning outcomes. A trend toward a more fine-grained analysis of different components of cognitive load can be observed, but the ability to detect cognitive load depends on selecting an appropriate survey for the specific task. Based on this narrative overview on current developments in cognitive load measurement, recommendations for deciding on a cognitive load measurement method are given.Perceptually rich learning environments using technologies such as virtual reality and augmented reality are gaining traction within the field of education and learning. The increased availability of the required equipment, ever-improving methods of content creation, and a number of positive research results have caused a substantial increase in interest in this technology. Readily available computer systems can be used to present visualizations,

Cognitive load scale in learning formal definition of limit: A rasch model approach

“…Item with code GCL14, designated as the most challenging item to gain respondent agreement, falls under the code of germane cognitive load, which are the cognitive load resulting from cognitive processes relevant to the understanding of the material being studied and the knowledge construction process. If an individual does not have germane cognitive load, it means their working memory cannot organize, construct, elaborate, or integrate the concepts they are currently learning into long-term memory (Forsberg et al, 2021;Skulmowski, 2023). Conversely, individuals with issues related to germane cognitive load tend to attempt to connect new knowledge with their existing knowledge, hoping to store it in their memory & Seufert, 2020).…”

“…Cognitive load can be assessed over various methods including brain activity measures (functional MRI), physiological measurements (electrical skin conductivity), eye tracking, self-rating scales, and even cardiovascular metrics (Can et al, 2019;Katona, 2022;Ramakrishnan et al, 2021;Skulmowski, 2023). The most commonly approach employed is the utilization of cognitive load scale instruments (Huckaby et al, 2022;Jiang & Kalyuga, 2020;Klepsch et al, 2017).…”

How Learners’ Visuospatial Ability and Different Ways of Changing the Perspective Influence Learning About Movements in Desktop and Immersive Virtual Reality Environments

“…However, immersive VR environments might be perceptually more demanding than Desktop-VR environments (see Skulmowski, 2023a). Overall, it can be stated that Desktop-VR environments provide a lower level of immersion and, in line with that, a lower level of presence than immersive (headset) VR environments (Smith, 2019).…”

Learners Emphasize Their Intrinsic Load if Asked About It First: Communicative Aspects of Cognitive Load Measurement

“…Furthermore, there are parallels between instructional cognitive load measurement and human factors research (Hollender, Hofmann, Deneke, & Schmitz, 2010). The appropriate choice of methods for cognitive load measurement remains a controversial issue (Skulmowski, 2023a), with the easy‐to‐administer method of using surveys on the one side and more elaborate approaches using physiological measures on the other. As research suggests, surveys do not necessarily have to be an inferior alternative (Ayres, Lee, Paas, & van Merriënboer, 2021).…”