Cognitive Load and Challenges in Self-regulation: An Introduction and Reflection on the Topical Collection

Abstract

The effort monitoring and regulation (EMR) model integrates self-regulated learning and cognitive load theory to examine how students monitor, regulate, and optimize effort during learning. Since its introduction in 2020, it has inspired research that explores how to correct learners' misinterpretations of effort and metacognitive biases and how instructional interventions can improve learning strategies. The current topical collection titled Cognitive Load: Challenges in Self-regulation includes seven empirical papers, two review papers, one meta-analysis, and a discussion paper. These contributions build on the EMR model by testing its assumptions, linking it to motivation, and refining our understanding of the basis of effort ratings in learning. Among other findings, the findings in the topical collection (1) show that feedback valence can affect participants' perceived task effort and their willingness to invest effort via feelings of challenge and threat, (2) provide the first evidence of far metacognitive transfer, and (3) propose a novel categorization of effort based on the underlying psychological sources when experiencing and allocating mental effort. In this editorial introduction, we summarize the topical collection papers, connect their findings to the EMR model, and finally reflect on how these novel insights can further develop the model.