Measuring Cognitive Load: Are There More Valid Alternatives to Likert Rating Scales?

Kim Ouwehand,Jacqueline Wong,Fred Paas,Avalon Van Der Kroef

doi:10.3389/feduc.2021.702616

Kim Ouwehand, Jacqueline Wong + Show 2 more

Open Access

https://doi.org/10.3389/feduc.2021.702616

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Abstract

Cognitive load researchers have used varying subjective techniques based on rating scales to quantify experienced cognitive load. Although it is generally assumed that subjects can introspect on their cognitive processes and have no difficulty in assigning numerical values to the imposed cognitive load, little is known about how visual characteristics of the rating scales influence the validity of the cognitive load measure. In this study we look at validity of four subjective rating scales (within groups) differing in visual appearance by participants rating perceived difficulty and invested mental effort in response to working on simple and complex weekday problems. We used two numerical scales (the nine-point Likert scale most often used in Cognitive load theory research and a Visual Analogue Scale ranging between 0–100%) and two pictorial scales (a scale consisting of emoticons ranging from a relaxed blue-colored face to a stressed red-colored face and an “embodied” scale picturing nine depicted weights from 1–9 kg). Results suggest that numerical scales better reflect cognitive processes underlying complex problem solving while pictorial scales Underlying simple problem solving. This study adds to the discussion on the challenges to quantify cognitive load through various measurement methods and whether subtleties in measurements could influence research findings.

Highlights

Cognitive load theory (CLT) centralizes the characteristics of human cognitive architecture, and especially the limitations of working memory in time and capacity (Baddeley, 1992, 2000), as a prerequisite for the optimization of learning
We propose that a subjective rating scale depicting affect from negative to positive, might represent the experience of mental effort of learners better than a more abstract numerical scale, and might be a more valid manner to measure invested mental effort and perceived task difficulty
Following up on the interaction effects between complexity and scale that was found for all dependent variables, we compared difference scores, i.e. instead of using a repeated measure for the performance and ratings on the simple and complex problems, we looked at Δ simple - complex

Summary

Introduction

Cognitive load theory (CLT) centralizes the characteristics of human cognitive architecture, and especially the limitations of working memory in time and capacity (Baddeley, 1992, 2000), as a prerequisite for the optimization of learning. Sweller, 2010), namely 1) intrinsic load that is imposed by the learning task itself, 2) extraneous load that is imposed by the design of the instruction, and 3) germane load that is related to the amount of cognitive resources that learners have available for learning. All three types of load have been proposed to be influenced by element interactivity (Sweller 2010); how many separate parts of information need to be integrated for learning to occur. Memory (Sweller, et al, 1998, 2019; van Merriënboer & Sweller, 2005) This process is called schematization and is a core mechanism underlying successful learning in CLT. Having a valid indication of cognitive load experienced/spent during a specific task or activity could provide crucial information on the development of a learning process and quality of an instruction

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