Collaborative learning in interpreting: A collaborative cognitive load theory approach

Examining different types of collaborative learning in a complex computer-based environment: A cognitive load approach

Safe anesthesia is indispensable to achieve global safe surgery and equitable health care access. The disease burden and lack of specialists in South Africa (SA) require junior, nonspecialist doctors to be fit-for-purpose from day 1 when they provide anesthetic services in peripheral hospitals with limited supervision. Graduating students report low self-perceived preparedness for administering anesthesia, but it is not known how their curricular experiences influence their learning. Cognitive load theory defines intrinsic, extraneous, and germane cognitive loads (subtypes). Intrinsic load relates to learning tasks, extraneous load to distractions, and germane load to students' learning processes. This study used a cognitive load theory lens to explore SA students' experiences of their undergraduate anesthesia training. In a constructivist cross-sectional descriptive study, we explored the qualitative factors that influenced students' curricular experience of undergraduate anesthesia training in SA. Two investigators analyzed the data independently in an initial coding round. An emerging theme of lack of time to achieve the expected outcomes, prompted the use of cognitive load theory as a conceptual framework for further analysis by the 3 authors. The subsequent analysis informed the development and refinement of a final cognitive load theory framework for anesthesia training, the COLOAD (COgnitive LOad in Anesthesia eDucation) framework. Data were collected between November 2017 and February 2019. The 1336 respondents (79% participation) reported a variety of determinants of learning pertaining to all 3 cognitive load subtypes. Participants were novices in an inherently complex environment and experienced a high cognitive load during anesthesia training. The number-, complexity-, and interactivity of tasks influenced intrinsic load, while extraneous load was affected by ineffective instructional methods, external- and internal distractors. Program design, metacognition, and learner motivation impacted germane load. Cognitive load theory provided a useful theoretical basis for understanding students' curricular experiences. The COLOAD framework suggests a microlevel interrelatedness of the constituting elements of the 3 cognitive load subtypes. This has implications for curriculum design, pedagogy, and student support. Learning outcomes development and curriculum mapping are important to ensure a lean curriculum, but measures to enhance germane cognitive load might be equally important to achieve competence. Attention to the hidden curriculum and active promotion of reflective practice might reduce cognitive load in complex learning environments such as anesthesia training.

Although there have been previous publications on curriculum innovations in teaching O&G to medical students, especially utilizing simulation-based education, there have been none, as far as we know, incorporating and evaluating the outcomes using cognitive load theory. The aim of this article was to describe the introduction, implementation, and evaluation of an innovative teaching program in O&G, incorporating simulation-based education, underpinned by cognitive load theory. Cognitive load is defined as the amount of information a working memory can hold at any one time and incorporates three types of cognitive load-intrinsic, extraneous, and germane. To optimize learning, educators are encouraged to manage intrinsic cognitive load, minimize extraneous cognitive load, and promote germane cognitive load. In these sessions, students were encouraged to prepare in advance of each session with recommended reading materials; to limit intrinsic cognitive load and promote germane cognitive load, faculty were advised ahead of each session to manage intrinsic cognitive load, an open-book MCQ practice session aimed to reduce anxiety, promote psychological safety, and minimize extraneous cognitive load. For the simulation sessions, the faculty initially demonstrated the role-play situation or clinical skill first, to manage intrinsic cognitive load and reduce extraneous cognitive load. The results of the evaluation showed that the students perceived that they invested relatively low mental effort in understanding the topics, theories, concepts, and definitions discussed during the sessions. There was a low extraneous cognitive load. Measures of germane cognitive load or self-perceived learning were high. The primary message is that we believe this teaching program is a model that other medical schools globally might want to consider adopting, to evaluate and justify innovations in the teaching of O&G to medical students. The secondary message is that evaluation of innovations to teaching and facilitation of learning using cognitive load theory is one way to contribute to the high-quality training of competent future healthcare workers required to provide the highest standard of care to women who are crucial to the overall health and wellbeing of a nation.

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.

Health and behavior change programs play a crucial role in improving health behaviors at individual and family levels. However, these programs face challenges with engagement and retention and typically show modest efficacy. Cognitive load theory is an established and highly used educational theory that proposes individuals have a finite capacity to process new information ("working memory"). Learning, engagement, and performance are negatively impacted when working memory is exceeded. Cognitive load theory is grounded in an understanding of human cognition and conceptualizes different types of cognitive loads imposed on individuals by a learning experience. Cognitive load theory aims to guide the design of learning experiences, considering how the human mind works, leading to more meaningful and effective learning. Cognitive load theory is increasingly applied to domains outside the classroom, such as designing patient and clinical education. Applying cognitive load theory to the design of health programs, their materials, and interfaces can provide insights. By considering the cognitive demands placed on individuals when interacting with health programs, design can be optimized to reduce cognitive load and better facilitate learning and behavior adoption. This may enhance engagement, retention, and effectiveness of programs. Cognitive load theory may be particularly valuable for individuals with diminished working memory due to high levels of mental load and stress. Design principles are presented to consolidate knowledge from cognitive load theory and existing approaches to guide researchers, policymakers, and health programmers. Further research and interdisciplinary collaboration are needed to realize the potential of cognitive load theory in health.

For more than three decades, cognitive load theory has been addressing learning from a cognitive perspective. Based on this instructional theory, design recommendations and principles have been derived to manage the load on working memory while learning. The increasing attention paid to cognitive load theory in educational science quickly culminated in the need to measure its types of cognitive load — intrinsic, extraneous, and germane cognitive load which additively contribute to the overall load. In this meta-analysis, four frequently used cognitive load questionnaires were examined concerning their reliability (internal consistency) and validity (construct validity and criterion validity). Results revealed that the internal consistency of the subjective cognitive load questionnaires can be considered satisfactory across all four questionnaires. Moreover, moderator analyses showed that reliability estimates of the cognitive load questionnaires did not differ between educational settings, domains of the instructional materials, presentation modes, or number of scale points. Correlations among the cognitive load types partially contradict theory-based assumptions, whereas correlations with learning-related variables support assumptions derived from cognitive load theory. In particular, results seem to support the three-factor model consisting of intrinsic cognitive load, extraneous cognitive load, and germane cognitive load. Results are discussed in relation to current trends in cognitive load theory and recommendations for the future use of cognitive load questionnaires in experimental research are suggested.

It has been said that “[W]ithout an understanding of human cognitive architecture, instruction is blind”. In this respect, collaborative learning as an instructional approach is at best sight-impaired and at worst stone-blind. While collaborative learning is increasingly used in school and lifelong learning for acquiring work-life skills, there is little evidence-informed theory based on human cognitive architecture to guide its implementation. Cognitive load theory has traditionally been associated with individual learning. Based on evolutionary educational psychology and our knowledge of human cognition, in this chapter we indicate that the theory can be used directly to explain collaborative learning. Additions are needed to account for the particulars of collaboration, but those additions also require the basic concepts used by the theory. The major additions are the concept of a collective working memory and generalised domain group knowledge. We suggest that cognitive load theory, with these additions, can clarify collaborative learning and generate novel hypotheses.

The integration of embodied cognition and cognitive load theory offers a promising framework for advancing educational practices. Cognitive load theory emphasizes the constraints of working memory and the importance of managing cognitive load through effective instructional design. Embodied cognition highlights the role of physical actions, such as gestures, object manipulation and whole-body activities, in enhancing cognitive processes. This Review highlights the importance of bridging these frameworks by exploring their theoretical foundations and synthesizing empirical evidence on the benefits of physical actions in learning. Here we present the introduction of the relevance-integration taxonomy as a transformative advancement in embodied cognition research, offering new perspectives for educational interventions. Additionally, we identify current gaps in cognitive load theory applications and propose future research directions to unify these approaches, aiming to optimize learning outcomes across diverse educational settings. This work has broad implications for advancing evidence-based instructional design.

The rapid integration of digital tools in education has transformed classroom environments, creating new opportunities and challenges for instructional design. One key area of focus is the management of cognitive load, which refers to the mental effort required to process information during learning. Cognitive Load Theory (CLT) offers insights into how instructional materials can be optimized to improve learning outcomes. In digital classrooms, the effective design of instructional content becomes even more critical due to the increased multimedia elements and potential for cognitive overload. This study aims to explore the implications of Cognitive Load Theory (CLT) for instructional design in digital classrooms. It examines how digital tools, such as multimedia content and interactive activities, impact learners’ cognitive load and suggests strategies for reducing extraneous cognitive load to enhance learning efficiency and effectiveness. A mixed-methods approach was used, combining quantitative surveys to assess students’ cognitive load during digital learning activities and qualitative interviews with instructors to understand their perspectives on instructional design challenges. The study was conducted across several digital learning environments in higher education. The findings indicate that digital learning environments often lead to high cognitive load, particularly when multimedia content is poorly integrated. However, using principles from CLT, such as segmenting information and reducing unnecessary complexity, can significantly lower cognitive load and improve student learning outcomes. Both students and instructors reported that well-designed digital content led to better engagement and more efficient learning. The study concludes that applying Cognitive Load Theory to instructional design in digital classrooms can enhance learning by minimizing cognitive overload. Educators should be mindful of cognitive load when creating digital learning experiences to improve student performance and engagement.

A natural concern in the field of computer‐supported collaborative learning is how participants in collaborative learning project attain individual deep understanding through pedagogical or technological support. This study explores such individual outcomes as influenced by designing a collaborative learning project supported with a diagram‐based thinking tool based on cognitive load theory (CLT). A comparative experiment was designed to evaluate the effectiveness of the diagram‐based thinking tool. A total of 49 first‐year graduate students were recruited and assigned to two conditions. In the experiment condition, the group students completed the collaborative learning project through a diagram‐based thinking tool, while the group students in the control condition completed the same project through an alternative text‐based thinking tool. Pre‐and posttesting of the domain knowledge was employed to evaluate each individual's learning outcome. Group discourse was employed to evaluate how group students actively engage during collaboration. Results show that the support of diagram‐based thinking tool integrated in collaborative learning can facilitate individual understanding intensively. Moreover, diagram‐based thinking tool can engage group students into cognitively demanding learning activities actively. Findings demonstrate that the semantic diagram tool provides promising technological support when designing collaborative learning project based on CLT. This study serves as a foundation to the design of technological support for future classroom‐based collaborative learning project. Practitioner NotesWhat is already known about this topic According to cognitive load theory, the construction of shared knowledge and also the benefit of communication and coordination during social interaction should be optimized when design the collaborative learning. To help learners benefit from social interaction during collaborative learning project, technological support should be carefully designed. External representations have been recognized as one kind of suitable technological affordance for learners’ cognitive and social development. What this paper adds The diagram‐based visible thinking tool with conceptual and socio‐cognitive support integrated in collaborative learning can facilitate individual understanding intensively. The diagram‐based thinking tool with conceptual and socio‐cognitive support can actively engage group students into cognitively demanding learning activities. Implications for practice and/or policy The idea of semantic diagram tool with conceptual and socio‐cognitive support is suitable technological support for effective collaborative learning from the perspective of cognitive load theory. The idea of semantic diagram tool with conceptual and socio‐cognitive support provide teachers with more understandable guidance to design and conduct the collaborative learning project in the classroom.

Over the last few years, cognitive load theory has progressed and advanced rapidly. The articles in this special issue, which document those advances, are based on contributions to the 3rd International Cognitive Load Theory Conference (2009), Heerlen, The Netherlands. The articles of this special issue on cognitive load theory discuss new conceptualizations of the different categories of cognitive load, an integrated research perspective of process-oriented and cognitive load approaches to collaborative learning, an integrated research perspective of cognitive and social–cognitive approaches to example-based learning, and a specification of the theory focusing on the acquisition of generalized knowledge structures as a means to facilitate flexible problem-solving skills. This article provides a short introduction to the theory, discusses some of its recent advances, and provides an overview of the contributions to this issue.

Context specificity, or the variation in a participant's performance from one case, or situation, to the next, is a recognized problem in medical education. However, studies have not explored the potential reasons for context specificity in experts using the lens of situated cognition and cognitive load theories (CLT). Using these theories, we explored the influence of selected contextual factors on clinical reasoning performance in internal medicine experts. We constructed and validated a series of videotapes portraying different chief complaints for three common diagnoses seen in internal medicine. Using the situated cognition framework, we modified selected contextual factors--patient, encounter, and/or physician--in each videotape. Following each videotape, participants completed a post-encounter form (PEF) and a think-aloud protocol. A survey estimating recent exposure from their practice to the correct videotape diagnoses was also completed. The time given to complete the PEF was randomly varied with each videotape. Qualitative utterances from the think-aloud procedure were converted to numeric measures of cognitive load. Survey and cognitive load measures were correlated with PEF performance. Pearson correlations were used to assess relations between the independent variables (cognitive load, survey of experience, contextual factors modified) and PEF performance. To further explore context specificity, analysis of covariance (ANCOVA) was used to assess differences in PEF scores, by diagnosis, after controlling for time. Low correlations between PEF sections, both across diagnoses and within each diagnosis, were observed (r values ranged from -.63 to .60). Limiting the time to complete the PEF impacted PEF performance (r = .2 to .4). Context specificity was further substantiated by demonstrating significant differences on most PEF section scores with a diagnosis (ANCOVA). Cognitive load measures were negatively correlated with PEF scores. The presence of selected contextual factors appeared to influence diagnostic more than therapeutic reasoning (r = -.2 to -.38). Contextual factors appear to impact expert physician performance. The impact observed is consistent with situated cognition and CLT's predictions. These findings have potential implications for educational theory and clinical practice.

Cognitive load theory has traditionally been associated with individual learning. Based on evolutionary educational psychology and our knowledge of human cognition, particularly the relations between working memory and long-term memory, the theory has been used to generate a variety of instructional effects. Though these instructional effects also influence the efficiency and effectiveness of collaborative learning, be it computer supported or face-to-face, they are often not considered either when designing collaborative learning situations/environments or researching collaborative learning. One reason for this omission is that cognitive load theory has only sporadically concerned itself with certain particulars of collaborative learning such as the concept of a collective working memory when collaborating along with issues associated with transactive activities and their concomitant costs which are inherent to collaboration. We illustrate how and why cognitive load theory, by adding these concepts, can throw light on collaborative learning and generate principles specific to the design and study of collaborative learning.

This article proposes a novel conceptual framework that integrates Artificial Intelligence (AI) with Cognitive Load Theory (CLT) and the Cognitive Theory of Multimedia Learning (CTML) to enhance Open Distance eLearning (ODeL) systems. By bridging the gap between traditional cognitive theories and cutting-edge AI technologies, this framework supports adaptive cognitive load management, AI-mediated schema creation, and human-AI collaborative learning. A refined critique of Twabu's (2023) PhD study, based on conceptual analysis of its theoretical scope and limitations, highlights the absence of AI integration. This article presents a unique contribution by synthesizing established cognitive theories with the dynamic potential of AI, a perspective underrepresented in current literature. Practical examples, policy recommendations, and ethical considerations are consolidated to offer a comprehensive path forward. The study proposes an expanded framework incorporating AI-enhanced cognitive load management, AI-mediated schema creation, and human-AI collaborative learning. The Literature review and theoretical framework emphasises AI's role in simplifying cognitive processes by dynamically adjusting content presentation based on learner needs and performance. This includes AI-mediated adjustments to manage cognitive load and enhance schema development through personalised feedback and tailored content delivery. Such integration promises to create a more effective learning environment by aligning multimedia content with individual learner profiles, thus addressing the challenge of cognitive overload and improving knowledge retention and understanding.

PurposeThe present study aimed to test the relationship between the components of the Cognitive Load Theory (CLT) including memory, intrinsic and extraneous cognitive load in workplace-based learning in a clinical setting, and decision-making skills of nursing students.MethodsThis study was conducted at Shahid Sadoughi University of Medical Sciences in 2021–2023. The participants were 151 nursing students who studied their apprenticeship courses in the teaching hospitals. The three basic components of the cognitive load model, including working memory, cognitive load, and decision-making as the outcome of learning, were investigated in this study. Wechsler’s computerized working memory test was used to evaluate working memory. Cognitive Load Inventory for Handoffs including nine questions in three categories of intrinsic cognitive load, extraneous cognitive load, and germane cognitive load was used. The clinical decision-making skills of the participants were evaluated using a 24-question inventory by Lowry et al. based on a 5-point scale. The path analysis of AMOS 22 software was used to examine the relationships between components and test the model.FindingsIn this study, the goodness of fit of the model based on the cognitive load theory was reported (GIF = 0.99, CFI = 0.99, RMSEA = 0.03). The results of regression analysis showed that the scores of decision-making skills in nursing students were significantly related to extraneous cognitive load scores (p-value = 0.0001). Intrinsic cognitive load was significantly different from the point of view of nursing students in different academic years (p = 0.0001).ConclusionThe present results showed that the CLT in workplace-based learning has a goodness of fit with the components of memory, intrinsic cognitive load, extraneous cognitive load, and clinical decision-making skill as the key learning outcomes in nursing education. The results showed that the relationship between nursing students’ decision-making skills and extraneous cognitive load is stronger than its relationship with intrinsic cognitive load and memory Workplace-based learning programs in nursing that aim to improve students’ decision-making skills are suggested to manage extraneous cognitive load by incorporating cognitive load principles into the instructional design of clinical education.