Special Issue on Cognitive Load Theory: Editorial INTRODUCTION

Paul Ginns, Jimmie Leppink*

*Corresponding author for this work

Research output: Contribution to journalEditorialAcademicpeer-review

7 Citations (Web of Science)

Abstract

For over three decades, cognitive load theory (CLT) has drawn on models of cognitive architectureincluding a working memory whose capacity and duration limits can be substantially reduced when domain-specific schemas are activated from long-term memoryto 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).

Original languageEnglish
Pages (from-to)255-259
Number of pages5
JournalEducational Psychology Review
Volume31
Issue number2
DOIs
Publication statusPublished - Jun 2019

Keywords

  • Cognitive load theory
  • Learning
  • Instruction

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