The Validation and Further Development of the Multidimensional Cognitive Load Scale for Physical and Online Lectures (MCLS-POL)

Abstract

Cognitive load theory (CLT) has been widely used to help understand the process of learning and to design teaching interventions. The Cognitive Load Scale (CLS) developed by Leppink and colleagues has emerged as one of the most validated and widely used self-report measures of intrinsic load (IL), extraneous load (EL), and germane load (GL). In this paper we investigated an expansion of the CLS by using a multidimensional conceptualization of the EL construct that is relevant for physical and online teaching environments. The Multidimensional Cognitive Load Scale for Physical and Online Lectures (MCLS-POL) goes beyond the CLS's operationalization of EL by expanding the EL component which originally included factors related to instructions/explanations with sub-dimensions including EL stemming from noises, and EL stemming from both media and devices within the environment. Through three studies, we investigated the reliability, and internal and external validity of the MCLS-POL using the Partial Credit Model, Confirmatory Factor Analysis, and differences between students either attending a lecture physically or online (Study 2 and 3). The results of Study 1 (N = 250) provide initial evidence for the validity and reliability of the MCLS-POL within a higher education sample, but also highlighted several potential improvements which could be made to the measure. These changes were made before re-evaluating the validity and reliability of the measure in a new sample of higher education psychology students (N = 140, Study 2), and psychological testing students (N = 119, Study 3). Together the studies provide evidence for a multidimensional conceptualization cognitive load and provide evidence of the validity, reliability, and sensitivity of the MCLS-POL and provide suggestions for future research directions.

Comparing Two Subjective Rating Scales Assessing Cognitive Load During Technology-Enhanced STEM Laboratory Courses

“…In contrast, the subscales for ICL and GCL of the adapted CLS show a good internal consistency. Except for ECL, the values are in the range of the original work by Leppink et al (2013) or former adaptions of the scale (Thees et al, 2020;Makransky, 2021a, Andersen andMakransky, 2021b). Here again, the insufficient reliability for ECL casts doubt on whether the items of this specific subscale are appropriate to measure the intended type of cognitive load.…”

“…These are the cognitive load scale (CLS; 10-item questionnaire) developed by Leppink et al (2013) and the (second version of the) naïve rating scale (NRS; 8-item questionnaire) by Klepsch et al (2017). Both scales were applied in various learning contexts (Leppink et al, 2014;Altmeyer et al, 2020;Andersen and Makransky, 2021a;Andersen and Makransky, 2021b;Becker et al, 2020;Kapp et al, 2020;Seufert, 2020, Klepsch andSeufert, 2021;Skulmowski and Rey, 2020;Thees et al, 2020), while the reliability of the subscales and the valid measurement of the three load types were confirmed multiple times (Klepsch et al, 2017;Becker et al, 2020;Klepsch and Seufert, 2020;Thees et al, 2020;Andersen and Makransky, 2021a;Andersen and Makransky, 2021b). However, their application in different contexts usually requires moderate adaptations.…”

COVID-19 Disruptions in Health Professional Education: Use of Cognitive Load Theory on Students' Comprehension, Cognitive Load, Engagement, and Motivation

“…Nevertheless, the potential impact of the CLT-based lecture model on the design and delivery of online lectures has yet to be explored. Indeed, Andersen and Makransky ( 30 ) raised concerns over the potential increase in their students' EL, which could have been imposed from noises, media, and devices within the online environment. Research has proven that handling online devices during learning requires students to multitask, thus imposing higher EL ( 31 ).…”

A Synthetic Review of Cognitive Load in Distance Interpreting: Toward an Explanatory Model

“…In the general field of cognitive load measurements, an instrument is usually developed and validated in one study, and further validated in other studies under different conditions. A typical example is that the cognitive load scale (CLS) developed by Leppink et al (2013) was widely used as a subjective measurement tool of three types of cognitive load at large, and was further validated and expanded by Andersen and Makransky (2021) to measure the cognitive load for physical and online lectures. In DI, the lack of internal reliability of the instruments is a noteworthy concern, since the instruments are mostly formulated by the investigators to answer their own specific questions, and therefore require further validation.…”