Lifelong Learning

Introduction Informing science investigates how to provide clientele with information in a form, format, and schedule that maximizes its effectiveness (Cohen, 1999; 2009). According to its general, cross-disciplinary definition, information is a feature of objects of different nature that describes their structural aspects represented by patterns attributed to their organization (e.g., Stonier, 1997). Consequently, informing could be regarded as spreading structural patterns (patterns in form) among objects of different nature (Gackowski, 2009). In case of complex information systems such as living organisms (including humans), the aim of informing has been defined as expanding their control over environment (Gackowski, 2009) or, in evolutionary terms, enhancing their chances of survival. When informing is considered at the level of human information processing, the structure and characteristics of human cognitive architecture could have significant implications for the informing process. Cognitive aspects of human information processing may critically affect both the informing (informer) and perceiving (client) ends of the informing process. The intersection of cognitive and informing sciences has been related to the area of cognitive informatics (Cohen, 2009). Cognitive load theory as a branch of instructional psychology (see Sweller, 2003; Sweller, Ayres, & Kalyuga, 2011, for recent overviews) has applied cognitive science to enhance effectiveness and efficiency of instructional design. Since the major aim of instructional design is providing instructional formats and procedures that maximize learning, this could be regarded as a specific area of application of general principles of informing science with learners as clientele. Therefore, instructional and informing sciences are inherently connected. Theoretical frameworks and recommendations of informing science should be applied to instructional design, and established principles of cognitive load theory could also be potentially generalized to advance certain aspects of informing science. This paper explores a possibility of extending the established conceptual framework and principles of cognitive load theory to broader and more general situations than those in teaching and learning with the aim of enhancing the effectiveness of informing. The paper begins with an overview of major assumptions and principles of cognitive load theory based on a recently proposed evolutionary perspective, describes a corresponding model of human cognitive architecture, followed first by general implications of this architecture to informing science, and then by specific recommendations for improving processes of informing. Human Cognitive Architecture Cognitive load theory describes educational implications of human cognitive architecture (Sweller, 2003, 2004). In its basic assumptions, the theory uses the information processing aspects of biological evolution by natural selection as analogical to basic characteristics of human cognition (Sweller & Sweller, 2006). It considers both biological evolution and human cognition as examples of a broader category of natural information processing systems. It is assumed that such systems function based on the following five fundamental principles (Sweller, 2003; for an overview, see Sweller et al., 2011): * The information store principle: natural information processing systems include large stores of information that govern their activities. In human cognitive architecture, long-term memory provides this function. * The borrowing and reorganizing principle: information in the store is mostly borrowed from other information stores; however, it is reorganized in the process rather than copied exactly. For example, humans imitate other people, listen, and read in order to build long-term memory. * The randomness as genesis principle: all truly novel (not borrowed) information is acquired by a random generate-and-test process. …

Transaction analysis, the process of discerning which accounts are impacted (either increased or decreased) by a given transaction, is a fundamental accounting principle. While proficiency in this concept is vital for introductory accounting students, it poses a significant challenge for many. We addressed this hurdle using Excel and Excel VBA to develop a fully automated Journal Entry Learning Object (JELO) spreadsheet designed to aid first-year accounting students in grasping the intricacies of analyzing business transactions. Grounded in cognitive load theory (CLT), our spreadsheet based JELO provides a user-friendly interface that helps students develop their skills without becoming overwhelmed. Cognitive load theory, pioneered by John Sweller, suggests that learning is optimized when instructional materials reduce unnecessary cognitive load, allowing students to allocate their cognitive resources efficiently toward understanding and mastering the task at hand. CLT distinguishes between three types of cognitive load: intrinsic, extraneous, and germane (Sweller, Ayres, & Kalyuga, 2011). Intrinsic cognitive load refers to the inherent difficulty associated with a specific instructional topic (Sweller, J. 2010). In transaction analysis, the intrinsic load is naturally high due to the complexity of understanding the impact of transactions on various accounts. To manage this, JELO has three tiers of transaction questions. Students are allowed to progress to more complex transactions only after demonstrating proficiency with the lower levels. Extraneous cognitive load is generated by inefficient presentation of information to learners (Paas & Sweller, 2014). JELO minimizes extraneous load through its intuitive and interactive design. By providing clear instructions, a logical interface, and eliminating unnecessary information, JELO ensures that students can focus on the essential aspects of transaction analysis without being distracted by irrelevant information. Germane cognitive load refers to the mental effort required to create schemas and integrate new information into existing knowledge structures (Sweller et al., 2011). JELO enhances germane load by offering scaffolded and immediate feedback. This feedback is designed to reinforce correct responses and guide students through their errors with hints and explanations, facilitating deeper cognitive processing and better schema construction. Our goal was to make skill acquisition enjoyable and, more realistically, to reduce the pain of learning transaction analysis. The JELO offers an alternative to traditional “drill and practice” methods by providing an easy-to-use, interactive learning tool that dynamically adjusts the difficulty of its questions to match the student's skill level. This adaptive learning approach ensures that students are continually challenged just enough to promote learning without becoming overwhelmed. Additionally, JELO's feedback mechanism aligns with CLT principles by providing immediate positive reinforcement and corrective guidance. By doing so, it helps students build confidence and competence in transaction analysis, leading to a more effective and engaging learning experience. By incorporating principles of cognitive load theory, JELO ensures that students are neither under-challenged nor overwhelmed. This careful balancing of students’ overall cognitive load facilitates a more effective learning environment, fostering both proficiency and satisfaction in mastering transaction analysis.

This study explored the impact of online lectures that were developed using principles of cognitive load theory (CLT) and cognitive theory of multimedia learning (CTML) on health profession students' lecture comprehension, cognitive load, cognitive engagement, and intrinsic motivation in learning. A total of 215 first-year undergraduate students in medical, dentistry, and nutrition programs participated in this pre-post quasi experimental study. The students attended a typical face-to-face lecture on Day-1 of the intervention, followed by a CLT-based online lecture 8 weeks thereafter. Their comprehension of the lecture topics was measured through pre- and post-lecture assessments, and their cognitive load, cognitive engagement, and motivation were measured immediately after each lecture session. The analysis revealed that the CLT-based online lectures promoted the students' comprehension of the lecture content (p < 0.001), self-perceived learning (p < 0.001), engagement toward the learning material, and motivation to learn (p = 0.025). It was also effective at reducing the students' intrinsic and extraneous cognitive loads (p < 0.001). Hence, designing online lectures using CLT and CTML principles could be an effective method to promote students' knowledge and comprehension, cognitive engagement, and learning motivation. However, further research is needed to investigate the applicability and impact of CLT-based online lectures in non-health profession disciplines.

The COVID-19 pandemic caused an unprecedented and highly threatening, constrained, and confusing social and educational environment, we decided to expand the traditional focus of the extraneous load in Cognitive Load Theory (CLT) acknowledging the psychological environment in which learning occurs. We therefore adapted and implemented principles of the CLT to reduce extraneous load for our students by facilitating their educational activities. Given previous empirical support for the principles of CLT, it was expected that the adoption of these principles might enable our students to cultivate attitudes and skills across multiple domains such as online learning and presentation technologies, implementing and maintaining a “classroom atmosphere” in a virtual environment, participating in discussions among large online groups of students, facilitating group work, providing virtual office hours for students, and proactively planning for upcoming semesters.

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.

In two experiments, the principles of cognitive load theory were applied to the design of alternatives to conventional music instruction hypothesised to facilitate learning. Experiment 1 demonstrated that spatial integration of visual text and musical notation, and dual‐modal delivery of auditory text and musical notation, were superior to the spatially separated placement of the same visual materials, demonstrating the split‐attention and modality effects respectively. In Experiment 2 there were four conditions differentiated by the presence or absence of musical notation and the simultaneous or successive presentation of auditory music, written explanations, and musical notation. Results indicated that the presence of music notation had no effects, but that the simultaneous presentation of either two or three information sources was superior to successive presentation. These results provide further empirical support for the need to consider cognitive load theory when designing instruction in any domain.

Cognitive load theory, learning difficulty, and instructional design

Managing cognitive load—recent trends in cognitive load theory

The design principles of cognitive load theory and learning by analogy has independently contributed to our understanding why an instruction will or will not work. In an experimental study involving 97 Year 9 Australian students conducted in regular classrooms, we evaluated the effect of the unguided problem-solving approach, worked examples approach and analogy approach on learning to solve two types of trigonometry problem. These trigonometry problems (sin40° = frac{x}{6} vs. cos50° = frac{14}{x}) exhibited two levels of complexity owing to the location of the pronumeral (numerator vs. denominator). The solution procedure of worked examples provided guidance, whereas the unguided problem-solving was without any guidance. Analogical learning placed emphasis on comparing a pair of isomorphic examples to facilitate transfer. Across the three approaches, solving practice problems contributed towards performance on the post-test. However, the worked examples approach and analogy approach were more efficient than the unguided problem-solving approach for acquiring skills to solve practice problems regardless of their complexity. Therefore, the worked examples approach and analogy approach that emphasizes algebraic transformation skills have the potential to reform instructional efficiency for learning to solve trigonometry problems.

With the framework of the cognitive load theory, researchers have shown students in an experimental condition learned mathematics with worked-out examples significantly outperformed those learning mathematics in the control condition. The current consists of two experimental studies with 66 fifth grade students as participants. In Study 1, participants were divided into an experimental and a control condition, learning mathematics with the worked-out example instruction and traditional instruction, respectively. The result shows an aptitude-treatment interaction, that is, the worked-out example method was more beneficial for students for students with lower prior achievement, while the traditional method was more beneficial for students with higher prior achievement in mathematics. In Study 2, students were assigned to three conditions to learn mathematics, a condition with worked-out examples presented with PowerPoint, a condition with worked-out examples presented with hard copies, and a condition with traditional instruction. The results indicated that the students who received instruction with the worked-out example presented via PowerPoint gained significantly higher grades in a posttest of the mathematical achievement test than those who received the traditional instruction.

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.

Introduction: Patient handoffs remain a significant patient safety challenge. Researchers have used cognitive load theory (CLT) to unpack the complexity of health professions workplace learning tasks including handoffs. 1 When the cognitive load of a handoff exceeds the working memory capacity of the trainee, learning and performance suffer. CLT focuses on the development of instructional strategies that match intrinsic load (IL) to the developmental stage of the learner, decrease extraneous load (EL), and optimize germane load (GL). CLT strategies have traditionally focused on modifying the complexity of the task, the knowledge of the learner, and/or the design of the instruction. CLT researchers have given little attention to how the learner’s emotions influence cognitive load. 2 Yet, we know that emotion modulates learning through numerous cognitive processes including motivation, attention, working memory, and long-term memory. 3 To address this gap, this study explores how emotion influenced the IL, EL, and GL imposed upon the working memory of trainees performing patient handoffs. Methods: From January to March 2019, we administered a cross-sectional survey to 1,807 residents and fellows from a large 24-hospital health system in the United States. Participants completed the survey after performing a handoff. The survey included questions about features of the learner, task, and instructional environment. IL, EL, and GL were measured with the 16-item Cognitive Load Inventory for Handoffs. 4 Emotions were assessed with an 8-item scale based on the circumplex model of affect. 5 The authors used factor analysis to identify the core dimensions of emotion and then explored the relationship between emotion and cognitive load with 3 types of analyses. First, bivariate correlational analyses examined the relationship between the emotion factors and learner, task, and environment features known to predict cognitive load. Second, we conducted univariate regression analyses to investigate whether emotion factor scores predicted IL, EL, and GL. Third, multivariate regression determined whether the addition of the emotion factors to models including these previously established predictors of cognitive load types increased the variance explained (Δ R2). Results: Six hundred and ninety-three (38.7%) of 1,807 residents and fellows completed a survey. Exploratory and confirmatory factor analysis identified 2 dimensions of emotion representing positive activation (labeled invigoration) and positive deactivation (labeled tranquility). The correlational analyses revealed that higher invigoration was associated with higher levels of training and use of a standardized verbal protocol, while lower levels of invigoration were associated with interruptions, difficulty obtaining essential information, and fatigue. Higher tranquility was associated with higher levels of training and lower levels of tranquility with interruptions, difficulty obtaining information, fatigue, longer handoffs, and greater number of patients. In univariate regression analyses, higher levels of invigoration, tranquility, and their interaction were independently associated with lower intrinsic load and extraneous load. The interaction of invigoration and tranquility predicted lower germane load. Finally, in the multivariate models of predictors for each type of cognitive load, the addition of the emotion term increased the amount of variance explained from 0.10 to 0.16 for IL, 0.15 to 0.27 for EL, and 0.11 to 0.14 for GL. Discussion: Emotion significantly influenced the cognitive load experienced by trainees while performing in vivo handoffs. Like studies in the simulation context, the structure of emotion during patient handoffs consisted of 2 factors. Higher invigoration/tranquility predicted lower IL, El, and GL. Traditionally, CLT researchers assumed that emotion primarily affected EL. Our results suggest a much broader impact of emotion. Significance: The study models how emotion and cognitive load can be measured during a workplace learning activity. These results suggest that enhancing invigoration and tranquility will reduce cognitive load and improve learning and performance. This highlights the importance of developing instructional strategies that help trainees regulate their emotions.

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

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.

This article discusses a three-step method that was used in a college calculus course. The three-step method was developed to help students understand the course material and transition to be more independent learners. In addition, the method helped students to transfer concepts from short-term to long-term memory while lowering cognitive load. The three-step method is based off of the theory of worked examples, which falls under cognitive science and cognitive load theory. The article describes cognitive load theory, worked examples, and how worked examples are connected to the three-step method. The quantitative results of the research study show that, on average, participants performed significantly better than non-participants in the course and performed better on the final exam. The article ends with a discussion of the results of the study and why the three-step method helped students in the class.