Cognitive load theory, learning difficulty, and instructional design

Information that is complicated and ambiguous entails high cognitive load. Trying to understand such information can involve a lot of cognitive effort. An alternative to expending a lot of cognitive effort is to engage in motivated cognition, which can involve selective attention to new information that matches existing beliefs. In accordance with principles of least action related to management of cognitive effort, another alternative is to give up trying to understand new information with high cognitive load. In either case, high cognitive load can limit potential for understanding of new information and learning from new information. Cognitive Load Theory (CLT) provides a framework for relating the characteristics of information to human cognitive load. Although CLT has been developed through more than three decades of scientific research, it has not been applied comprehensively to improve the explainability, transparency, interpretability, and shared interpretability (ETISI) of machine learning models and their outputs. Here, in order to illustrate the broad relevance of CLT to ETISI, it is applied to analyze a type of hybrid machine learning called Algebraic Machine Learning (AML). This is the example because AML has characteristics that offer high potential for ETISI. However, application of CLT reveals potential for high cognitive load that can limit ETISI even when AML is used in conjunction with decision trees. Following the AML example, the general relevance of CLT to machine learning ETISI is discussed with the examples of SHapley Additive exPlanations (SHAP), Local Interpretable Model-Agnostic Explanations (LIME), and the Contextual Importance and Utility (CIU) method. Overall, it is argued in this Perspective paper that CLT can provide science-based design principles that can contribute to improving the ETISI of all types of machine learning.

Aim/Purpose: This study aims to analyze the cognitive load experienced by secondary school students in Biology within m-learning environments and its impact on learning performance. Background: Cognitive load has become a critical issue that schools need to address to ensure students can excel in their learning without being overwhelmed. While principles for reducing cognitive load have been extensively discussed in previous research, studies focusing on mobile learning (m-learning) for Biology among students in Malaysia remain limited. This study employed Cognitive Load Theory (CLT) and Cognitive Theory of Multimedia Learning (CTML) to address this gap. By integrating four key principles—segmenting and pretraining, modality, redundancy, and seductive details—into m-learning tasks using the Successive Approximation Model (SAM1), this study aimed to reduce cognitive load and enhance students’ learning performance. Methodology: This study employed a quantitative approach using a randomized pre-test/post-test quasi-experimental design. Students were randomly assigned to either an intervention group (20 students) or a control group (18 students). The study was conducted over four weeks, comprising a three-week intervention period with a one-week interval. Statistical analyses, including independent t-tests, Mann-Whitney U tests, Quade ANCOVA, and Pearson correlation, were used to analyze the quantitative data. Qualitative feedback was analyzed using thematic analysis. Contribution: This study contributes by providing instructional design strategies that incorporate principles for reducing cognitive load in mobile learning for Biology. It also demonstrates how Cognitive Load Theory (CLT) and Cognitive Theory of Multimedia Learning (CTML) can be effectively integrated. By examining the cognitive load experienced by secondary school students in m-learning environments, the study offers valuable insights for designing and implementing effective instructional strategies. Identifying the factors influencing cognitive load enables educators to develop targeted interventions that enhance learning experiences and optimize performance. Findings: The study indicated that the adoption of mobile learning tasks not only significantly reduced cognitive load but also corresponded to enhanced learning performance. Participants engaging in m-learning experienced lower cognitive load, which was positively associated with superior performance in learning tasks, emphasizing the beneficial impact of mobile learning on cognitive load management and academic achievement. Recommendations for Practitioners: Educators and instructional designers are encouraged to incorporate cognitive load principles into their instructional strategies and learning material design to enhance student performance. Policymakers should consider similar strategies to reduce the cognitive load for students in educational settings to improve learning outcomes. Recommendation for Researchers: Researchers are encouraged to replicate the design elements used in this study when developing mobile or online learning materials to reduce learners’ cognitive load and enhance their performance. They should also consider expanding this research to other topics, subjects, and educational levels to provide further insights and validate the effectiveness of these design elements across different contexts. Impact on Society: The findings of this study have significant implications for society, particularly in addressing mental health and stress issues among the younger generation. By identifying strategies to manage cognitive load and reduce stress in online learning environments, the study provides valuable insights for educators, parents, and policymakers. These strategies can help mitigate the adverse effects of cognitive overload, improve learning experiences, and promote better mental well-being. Additionally, the study’s recommendations can guide the development of more effective and supportive learning environments, contributing to overall societal well-being and academic success. Future Research: Future studies could explore cognitive load beyond the intrinsic and extraneous components focused on in this study, examining additional elements within the frameworks of cognitive load theory and multimedia learning. In addition to using the cognitive load questionnaire, exploring other measurement tools could ensure a more comprehensive understanding of cognitive load. Future research might also consider enriching mobile learning tasks by diversifying subject matter and conducting longitudinal cohort studies. Such studies could provide valuable insights into memory retention over extended periods, aiding in optimizing mobile learning frameworks and enhancing educational experiences.

Cognitive Load Theory describes the concept of limited working memory capacity for information processing and cognitive tasks requiring mental effort. Cognitive load is affected by the difficulty levels involved in the learning process and mental tasks. The present meta-analysis examines the effect of difficulty levels in educational tasks based on cognitive load using fixation duration, number of fixations, and pupil dilation. The present study is based on 21 articles containing 34 comparisons between high and low cognitive load conditions in education settings. We evaluated Cohen's d for effect size, the I 2 statistic and Q-test to estimate heterogeneity, and Egger's regression test for publication bias. The heterogeneity of the experimental settings was relatively high, nevertheless, we observed meaningful differences in pupil metrics. Pupil dilation significantly increased in hard compared to easy task conditions ( d = 0.72, CI = 0.3672; 1.072, p -value < 0.0001), serving as an indicator of cognitive load level in various educational settings. Fixation duration and number of fixations did not differentiate between the easy and hard levels.

Effects of inhibitory control capacity and cognitive load on involuntary past and future thoughts: A laboratory study

Research has shown that people prefer the letters in their names to letters that are not in their names. This name-letter effect seems to influence important life decision such as where one chooses to live or whom one chooses to marry. The authors' laboratory study investigated whether this effect generalizes to individuals' job-choice intentions under specific conditions. Furthermore, the authors hypothesized that name-letter preferences in job-choice intentions would be stronger under conditions of high cognitive load than under conditions of low cognitive load. Two experiments with final-year students attending a university in Belgium showed support for name-letter preferences in job-choice intentions. There was no support for the hypothesized moderating role of cognitive load. The authors discuss the implications of these results for theory and research on name-letter preferences and job choice.

Cognitive load theory (CLT) provides a rich framework to inform instructional design. Despite the applicability of CLT to simulation-based medical training, findings from multimedia learning have not been consistently replicated in this context. This lack of transferability may be related to issues in measuring cognitive load (CL) during simulation. The authors conducted a review of CLT studies across simulation training contexts to assess the validity evidence for different CL measures. PRISMA standards were followed. For 48 studies selected from a search of MEDLINE, EMBASE, PsycInfo, CINAHL, and ERIC databases, information was extracted about study aims, methods, validity evidence of measures, and findings. Studies were categorized on the basis of findings and prevalence of validity evidence collected, and statistical comparisons between measurement types and research domains were pursued. CL during simulation training has been measured in diverse populations including medical trainees, pilots, and university students. Most studies (71%; 34) used self-report measures; others included secondary task performance, physiological indices, and observer ratings. Correlations between CL and learning varied from positive to negative. Overall validity evidence for CL measures was low (mean score 1.55/5). Studies reporting greater validity evidence were more likely to report that high CL impaired learning. The authors found evidence that inconsistent correlations between CL and learning may be related to issues of validity in CL measures. Further research would benefit from rigorous documentation of validity and from triangulating measures of CL. This can better inform CLT instructional design for simulation-based medical training.

Storage interference in working memory cannot be removed by attention

The objective of this cross-sectional study was to determine the neural signature of dual-tasking deficits in idiopathic rapid eye movement sleep behavior disorder using a validated gait paradigm. Fifty-eight participants (28 controls; 30 idiopathic rapid eye movement sleep behavior disorder patients) were recruited; 52 participants had functional MRI scans as they performed a validated dual-task virtual reality gait paradigm using foot pedals. Forty-one participants completed single- and dual-task "overground walking" on a pressure sensor carpet. Idiopathic rapid eye movement sleep behavior disorder patients showed deficits in dual-tasking (i.e., greater mean step time) compared to controls during "overground walking." Functional MRI revealed that idiopathic rapid eye movement sleep behavior disorder patients had reduced blood-oxygen-level-dependent signal change in the dorsal caudate nucleus, and significantly different corticostriatal functional connectivity patterns from controls, when dual-tasking in high versus low cognitive load. While controls showed greater connectivity between frontoparietal and motor networks, idiopathic rapid eye movement sleep behavior disorder patients exhibited less change in this connectivity as a function of cognitive load. These findings demonstrate evidence of dual-task gait deficits in idiopathic rapid eye movement sleep behavior disorder patients, underpinned by disrupted corticostriatal connectivity. Minimal differences in the level of functional connectivity between dual-tasking conditions of high and low cognitive load suggest that idiopathic rapid eye movement sleep behavior disorder patients recruit cognitive networks to control gait even when the cognitive demands are low. This may indicate a compensatory strategy for early cognitive decline in idiopathic rapid eye movement sleep behavior disorder. © 2020 International Parkinson and Movement Disorder Society.

This chapter outlines the cognitive architecture used by cognitive load theory, and provides a general indicator of its relevance to instructional design issues associated with multimedia instruction. Cognitive load theory has been one of the theories used to integrate our knowledge of human cognitive structures and instructional design principles. It is concerned with the elements of that theory and its general implications for multimedia learning, specifically words presented in spoken or written form along with pictures or diagrams. The chapter considers categories of knowledge from an evolutionary perspective, followed by an outline of those aspects of human cognitive architecture relevant to instructional concerns, also considered from an evolutionary perspective. The chapter discusses three categories of cognitive load: intrinsic cognitive load, extraneous cognitive load and germane cognitive load. All categories of cognitive load are concerned with the acquisition, storage and use of biologically secondary information.

To test the hypothesis that racial biases in opioid prescribing would be more likely under high levels of cognitive load, defined as the amount of mental activity imposed on working memory, which may come from environmental factors such as stressful conditions, chaotic workplace, staffing insufficiency, and competing demands, one's own psychological or physiological state, as well as from demands inherent in the task at hand. Two (patient race: White vs Black) by two (cognitive load: low vs high) between-subjects factorial design. Ninety-eight primary care physicians from the Veterans Affairs Healthcare System. Web-based experimental study. Physicians were randomly assigned to read vignettes about either a Black or White patient, under low vs high cognitive load, and to indicate their likelihood of prescribing opioids. High cognitive load was induced by having physicians perform a concurrent task under time pressure. There was a three-way interaction between patient race, cognitive load, and physician gender on prescribing decisions (P = 0.034). Hypotheses were partially confirmed. Male physicians were less likely to prescribe opioids for Black than White patients under high cognitive load (12.5% vs 30.0%) and were more likely to prescribe opioids for Black than White patients under low cognitive load (30.8% vs 10.5%). By contrast, female physicians were more likely to prescribe opioids for Black than White patients in both conditions, with greater racial differences under high (39.1% vs 15.8%) vs low cognitive load (28.6% vs 21.7%). Physician gender affected the way in which patient race and cognitive load influenced decisions to prescribe opioids for chronic pain. Future research is needed to further explore the potential effects of physician gender on racial biases in pain treatment, and the effects of physician cognitive load on pain treatment.

Pupillometric and saccadic measures of affective and executive processing in anxiety

Multiple-choice questions (MCQs) are a common form of assessment in medical science education. The traditional MCQ format involves students picking a single best answer (SBA) from four or five options. There are concerns about the ability of SBA formats to reward partial knowledge and their susceptibility to guessing. An alternative to SBA is elimination testing (ET), wherein students eliminate all the incorrect answer options, with negative marking to deter guessing. Cognitive load theory (CLT) is an approach to education that prioritises strategies to minimise the amount of unnecessary ‘load’ placed upon working memory. The cognitive load imposed by assessment design has received little attention. We evaluated the cognitive load of SBA and ET MCQ formats, using an online participant pool and a survey of students at a UK Medical School. We found that partial knowledge was rewarded with the ET format. However, students strongly preferred the SBA format and reported both that it was easier and imposed a lower cognitive load. Removing negative marking reduced the cognitive load of ET style questions and improved the student experience, but the improvement was insufficient to change student preference for SBA questions.

Research on learning engagement and cognitive load theory have proceeded in parallel with little cross-over of ideas. The aim of this research was to test an integrative model that examines how prior knowledge influences learning engagement via cognitive load and help-seeking strategies. A sample of 356 students from two middle schools in the north of China participated in the study. Analyses using structural equation modeling revealed that prior knowledge was positively associated with learning engagement, and that this relationship was mediated by cognitive load and instrumental help-seeking. Cognitive load also mediated the impact of prior knowledge on instrumental help-seeking, executive help-seeking and avoidance of help-seeking. The study shows that students with more prior knowledge and lower cognitive load are able to exercise higher levels of instrumental help-seeking, leading to good quality learning engagement. On the other hand, students with less prior knowledge and higher cognitive load are less able to engage in instrumental help-seeking, leading to lower engagement. Based on the research findings, recommendations for how teachers can improve learning engagement through decreasing cognitive load are discussed.

Cognitive load theory (CLT) focuses on the limited bandwidth of working memory. Core to CLT is the concept of cognitive overload, which occurs when working memory demands exceed working memory capacity, and learning and performance suffer. Within health professions education (HPE), workplace learning settings are very complex, placing learners at high risk of cognitive overload. Although continuous monitoring of physiologic parameters can indicate states of high cognitive load, how to practically identify cognitively overloaded learners within everyday workplace settings is not well understood. We sought to characterise how attending physicians described their perceiving of cognitive overload among learners in two different workplace settings: the gastrointestinal endoscopy suite and the intensive care unit. We performed a secondary qualitative analysis of transcripts of interviews with workplace teachers that had been carried out during two previous studies. These studies had addressed different objectives but both were informed by CLT. Each included questions that prompted participants to reflect on how they perceived cognitive overload to manifest among learners in the workplace. To investigate the phenomenon of cognitive overload, we developed a new codebook and performed content analysis. We analysed 42 interview transcripts (22 endoscopists, 12 hospitalists, eight intensivists). Participants described four behaviours they had witnessed among learners they thought were cognitively overloaded: poor performance on workplace tasks; non-verbal physical manifestations (including posture, eye and body movements and autonomic functions); verbal utterances (words and sounds), and interpersonal interactions with team members. Endoscopists often described individually oriented examples, whereas intensivists and hospitalists tended to frame examples within an interpersonal context. We identified four overarching ways in which HPE workplace teachers perceived learners as appearing to be cognitively overloaded. Workplace teachers and learners should be mindful of and watch for these signs, which may signal states of cognitive overload. Earlier recognition of cognitive overload may facilitate timely action to reduce cognitive overload and promote learning.

The purpose of this study is to examine the methodology and thematic analysis of using Electronic Educational Resources (EERs) to teach mathematics at the university level. Using TPACK (Technological Pedagogical Content Knowledge) framework and Cognitive Load Theory as guiding principles, this research aims to investigate the impact of pedagogical strategies, as well as cognitive load, on the way EERs are utilized by teachers. There is increasing evidence that there are a variety of factors that can influence the effectiveness of EERs, and this is in relation to their effectiveness. A significant contribution to the effectiveness of EERs was found to be made by pedagogical strategies and cognitive load factors that played an important role in this study. In addition, existing pedagogical methodologies show varying degrees of alignment with TPACK and the Cognitive Load Theory in terms of their alignment with TPACK. There is a need for educators and instructional designers to apply a multifaceted approach to technology integration, while also taking into account the context of the lesson. These findings offer valuable insights for educators and instructional designers. As a result of this study, both theoretical and practical aspects of the use of technology in the teaching of mathematics at university level can be addressed