Special Issue on Cognitive Load Theory: Editorial

Paul Ginns,Jimmie Leppink

doi:10.1007/s10648-019-09474-4

Abstract

For over three decades, cognitive load theory (CLT) has drawn on models of cognitive architecture—including a working memory whose capacity and duration limits can be substantially reduced when domain-specific schemas are activated from long-term memory—to generate and test instructional design hypotheses. The cognitive load construct refers to the load placed on working memory by a range of cognitive processes, including comprehension, schema construction, schema automation, and problem solving. When working memory is overloaded by the competing demands of these processes, CLT argues, student learning is impaired. Using CLT, researchers have (typically) used experimental methods to test a range of instructional designs that variously target obstructions to learning (e.g., split attention) or develop strategies to circumvent these issues (e.g., worked examples; for summaries of CLT designs, see Kalyuga 2015; Sweller et al. 2011). This Special Issue presents 10 articles, including theoretical reviews, meta-analyses, and intervention studies, that all focus on a unique aspect of advancement of CLT or cognate theories such as Mayer’s cognitive theory of multimedia learning (CTML). Drawing in part on ongoing research presented at the 2017 and 2018 International Cognitive Load Theory Conferences, the Special Issue also reflects on the impact of a key review of CLT published in Educational Psychology Review by Sweller et al. (Educational Psychology Review, 10(3), 251-296, 1998), “Cognitive architecture and instructional design.” The impact of this review of CLT is clearly seen in citation counts as of 8 January 2019 (1862 citations in Web of Science; 5092 citations in Google Scholar).

Highlights

There have been recurrent calls to expand instructional design theories such as cognitive load theory (CLT) and cognitive theory of multimedia learning (CTML) (e.g., Brünken et al 2011; Moreno and Mayer 2007) to specify the role of affective factors
EVCT may provide us with a perspective to better understand the role of motivation and selfregulation in learning and in CLT
Building on the interval theory view of cognitive load presented by Kalyuga and Singh (2016) and drawing scholarship from affective neuroscience, educational psychology, cognitive psychology, and positive psychology, Plass and Kalyuga suggest four distinct ways in which emotions may relate to cognitive load during learning

Summary

Introduction

There have been recurrent calls to expand instructional design theories such as CLT and CTML (e.g., Brünken et al 2011; Moreno and Mayer 2007) to specify the role of affective factors. In the third review, Feldon et al (2019) propose an Expectancy-Value-Cost TheoryCognitive Load Theory (EVCT-CLT) model in which motivational beliefs and changes therein can result directly from cognitive load and manipulations thereof.

Results

Conclusion