Looking at Mental Effort Appraisals through a Metacognitive Lens: Are they Biased?

Abstract

A central factor in research guided by the Cognitive Load Theory (CLT) is the mental effort people invest in performing a task. Mental effort is commonly assessed by asking people to report their effort throughout performing, learning, or problem-solving tasks. Although this measurement is considered reliable and valid in CLT research, metacognitive research provides robust evidence that self-appraisals of performance are often biased. In this review, we consider the possibility that mental effort appraisals may also be biased. In particular, we review signs for covariations and mismatches between subjective and objective measures of effort. Our review suggests that subjective and most objective effort measures appear reliable and valid when evaluated in isolation, because they discriminate among tasks of varying complexity. However, not much is known about their mutual correspondence—that is, whether subjective measures covariate with objective measures. Moreover, there is evidence that people utilize heuristic cues when appraising their effort, similar to utilization of heuristic cues underlying metacognitive appraisals of performance. These cues are identified by exposing biases—mismatch in effects of cue variations on appraisals and performance. The review concludes with a research agenda in which we suggest applying the well-established methodologies for studying biases in self-appraisals of performance in metacognitive research to investigating effort appraisals. One promising method could be to determine the covariation of effort appraisals and objective effort measures as an indicator of the resolution of effort appraisals.

Making an Effort Versus Experiencing Load

“…In study 1, the overall pattern is also similar, but we found a simple main effect of prompts in the worked-example group. As the prompt was new for the learners, it might have resulted in passive rather than active load-as intended by us-because the prompt belongs to the task-centered dimension (Paas and van Merriënboer, 1994) or can be seen as data-driven (Scheiter et al, 2020). Further studies should have a closer look at prompts and other active load-enhancing techniques, like asking learners to use special learning strategies.…”

“…While mental load is not controllable and due to Paas and van Merriënboer "constant for a given task in a given environment," mental effort is the "amount of controlled processing the individual is engaged in" (1994). Scheiter et al (2020) referred to this distinction in their review on how to measure cognitive load and link it to an analog distinction which is made in the metacognitive literature. When learners rate their mental effort while metacognitively monitoring their learning process, they can also take these two perspectives as outlined by Koriat et al (2006).…”

When Cognitive Proximity Leads to Higher Evaluation Decision Quality: A Study of Public Funding Allocation

“…Conversely, decreasing evaluation experience will likely exacerbate cognitive dissonance with lower decision-making quality ( Kotha et al, 2013 ). For the inverted U shape, this implies that when evaluation experience is high, evaluators are allowed to correctly identify the objectively maximizing option ( Scheiter et al, 2020 ). This means that in our context, the curve flattens when evaluators’ evaluation experience is high.…”

“…Individuals with evaluation experience suggest that they can understand the underlying structural features of a problem, have superior pattern recognition skills, and develop more robust solutions to problems ( North et al, 2009 ). On the other hand, the cognitive effort is the amount of attention devoted to creating a solution related to the intensity aspect of attention ( Scheiter et al, 2020 ). It increases one’s cognitive-processing capacity to notice connections between different elements and make sense of these connections ( Acar and Van den Ende, 2016 ).…”

Validation of Cognitive Load During Inquiry-Based Learning With Multimedia Scaffolds Using Subjective Measurement and Eye Movements

“…Therefore, the processing of information that is relevant to learning should be optimized and loads irrelevant to learning are to be minimized (among others van Merriënboer et al, 2006 ; Paas and van Merriënboer, 2020 ). Another assumption claims the processing of information in two different channels – the verbal and the visual channel (dual channel assumption; Skuballa et al, 2019 ; Sweller et al, 2019 ; Scheiter et al, 2020 ). Furthermore, it is assumed that CL is composed of three distinct categories – intrinsic (ICL), extraneous (ECL), and germane cognitive load (GCL; among others Sweller, 1994 ; Zu et al, 2020 ).…”