Cognitive Load Theory-Informed Curriculum Design in Health Sciences Education

Definition

Cognitive load theory-informed curriculum design in health sciences education refers to the purposeful organisation of teaching strategies and learning materials based on the principles of Cognitive Load Theory (CLT), a framework developed by John Sweller in the late 1980s. CLT is grounded in cognitive psychology and recognises that the working memory has a limited capacity for processing new information. It identifies three types of cognitive load: intrinsic load, which refers to the inherent complexity of the material being learned; extraneous load, which results from ineffective instructional design or irrelevant information; and germane load, which reflects the mental effort directed toward understanding, integrating, and organising information into long-term memory. In health sciences education, students frequently engage with tasks that require the simultaneous processing of multiple interacting elements, placing high demands on working memory at specific points in time. This includes foundational biomedical sciences such as anatomy, physiology, and pathophysiology extending to applied clinical skills, diagnostic reasoning under uncertainty, health service management within complex systems, and ethically grounded decision-making. Without thoughtful instructional design, learners may be overwhelmed by excessive information and cognitive demands, which can hinder understanding, retention, and performance. Applying CLT-informed strategies, educators can reduce unnecessary cognitive burden, sequence learning activities to align with learners’ cognitive capacity, and promote deeper learning. This approach supports more effective knowledge acquisition and transfer and is particularly valuable in content dense academic environments such as medicine, nursing, allied health education, public health and health service management education. Therefore, integrating CLT-informed principles into curriculum design can help optimise learning experiences and support the development of competent health professionals.

1. Introduction and History

Cognitive Load Theory (CLT) emerged in the late 1980s from the work of Australian educational psychologist John Sweller, who sought to understand why some instructional approaches were more effective than others in facilitating meaningful learning [1]. CLT was grounded in earlier developments in cognitive science, particularly theories of memory and information processing that gained prominence during the mid-twentieth century. The conceptual roots of CLT can be traced to George Miller’s influential 1956 paper, which suggested that the capacity of working memory is limited to approximately seven units of information [2]. This was later developed by Nelson Cowan, who argued that working memory could manage about four interacting elements rather than discrete items at any given time, depending on the individual and the context [3].

Throughout the 1960s and 1970s, educational theorists increasingly shifted their attention from behaviourist models of learning to cognitive frameworks that emphasised the mental processes underpinning understanding and skill development. In this context, CLT represented a significant theoretical advancement by articulating how instructional design interacts with the cognitive architecture of learners. Sweller and his colleagues demonstrated that learners often struggle not because the material is inherently difficult, but because the way in which information is presented can exceed the processing limits of working memory [4,5,6]. In a series of experimental studies, the authors showed that students who were provided with worked examples, which provided step-by-step guidance for solving problems, performed better on problem-solving tasks than those who were left to discover solutions independently [7].

CLT distinguishes among three types of cognitive load [8]. Intrinsic load refers to the inherent complexity of the content and is shaped by the degree of interaction among elements that must be understood simultaneously. Extraneous load results from suboptimal instructional design that distracts from learning objectives, such as disorganised layouts or irrelevant information. Germane load, on the other hand, refers to the cognitive resources allocated to schema construction and automation in long-term memory. Schemas are mental structures stored in long-term memory that organise knowledge and allow efficient retrieval and automation of complex information during problem-solving. There is some debate to the distinctiveness of germane load within both intrinsic/extraneous load with some authors suggesting it should not be treated as fully separable from intrinsic/extraneous load rather considered as the allocation of remaining working-memory resources to learning [8]. At the level of individual learning tasks, CLT is concerned with how information is processed in working memory during instruction. Cognitive overload occurs when the number of interacting elements within a specific task exceeds working memory capacity, even when this involves only a small number of elements (e.g., more than four interacting components).

Importantly, cognitive load is influenced not only by content complexity and instructional design but also by the mode and structure of learning. Online or hybrid learning environments can impose additional extraneous load if technological platforms, virtual interfaces, or poorly integrated multimedia disrupt attention. Conversely, they can reduce load when designed to scaffold understanding through interactive modules, simulations, or just-in-time resources [9]. At a program level, structural features such as curriculum sequencing and pacing may influence the distribution of cognitive demands across learning experiences. However, CLT is primarily a theory of moment-to-moment cognitive processing, and therefore such macro-level considerations should be interpreted as indirect influences on task-level cognitive load rather than cumulative “load over time”. Without well-designed support structures that respect cognitive limitations, students may experience reduced comprehension, inefficient knowledge retention, and impaired clinical performance. Aligning educational strategies with CLT, instructors and curriculum designers can better manage cognitive load and foster deeper learning [10]. Techniques informed by CLT include segmenting content into manageable units, integrating visual and verbal information, eliminating redundant materials, and providing scaffolding that gradually shifts cognitive responsibility to the learner [11]. Through these strategies, educators can support the development of expertise and improve long-term educational outcomes.

In health sciences education, these principles are particularly relevant, as learners frequently engage with tasks that require the simultaneous processing of multiple interacting elements. When these demands exceed working memory capacity, cognitive overload may occur, leading to suboptimal learning outcomes. Under such conditions, students are more likely to adopt surface learning strategies, such as rote memorisation, rather than developing deeper conceptual understanding required for clinical reasoning and application [12,13]. Cognitive overload has also been associated with increased psychological strain, including burnout and reduced motivation, which can negatively impact academic performance and retention [14,15]. Instructional strategies designed to manage cognitive load, such as spaced learning and retrieval practice, can improve knowledge acquisition and retention in health sciences education [16,17]. These findings underscore the importance of aligning teaching approaches with cognitive principles to optimise learning and support student wellbeing.

CLT continues to inform instructional practice across a wide range of disciplines. In the context of health sciences education, its application holds particular promise for addressing the challenges of information overload, enhancing knowledge transfer, and improving student performance in all academic, management and clinical settings [18]. This paper aims to explore how CLT has evolved and been applied in health sciences education, with a focus on identifying instructional strategies that manage cognitive load effectively. This study seeks to synthesise empirical and theoretical insights on the consequences of cognitive overload, highlight evidence-informed teaching practices, and outline future directions for integrating CLT principles into curriculum design to enhance learning efficiency and clinical competence in medical and allied health training.

2. Cognitive Load Types and Their Impact on Health Sciences Learning

Cognitive Load Theory identifies three primary types of cognitive load: intrinsic, extraneous, and germane [19]. Each type plays a distinct role in the process by which learners acquire, retain, and apply knowledge, particularly in intellectually demanding disciplines such as health sciences education as described in

Table 1. Cognitive load types, sources, and instructional strategies in health sciences education.

Cognitive Load Type	Definition	Sources in Health Sciences Education	Examples	Educational Strategies
Intrinsic Load	Load determined by the inherent complexity of the content and moderated by the learner’s prior knowledge	Complex topics (e.g., pharmacokinetics, pathophysiology) Integration of anatomy, physiology, and biochemistry Rapid updates in medical technology	Understanding drug interactions across multiple systems Applying multiple disciplines to health management	Build foundational knowledge gradually Organise content by difficulty level
Extraneous Load	Load imposed by poor instructional design unrelated to learning goals	Overloaded slides with dense text Split attention between unintegrated materials Redundant information across formats	Explaining electrocardiogram while rapidly showing dense visuals Textbooks with disorganised structure or poorly integrated sections Materials containing unnecessary detail or irrelevant information	Streamline slides and visuals Integrate materials effectively Avoid unnecessary repetition
Germane Load	Productive cognitive effort used for schema construction and automation	Deep engagement with content Structured problem-solving activities	Using step-by-step worked examples Applying scaffolded clinical cases	Provide worked examples Use scaffolding techniques Apply dual coding (text and visuals)

. The educational strategies outlined in Table 1 are grounded in core principles of CLT, including element interactivity and the goal-free effect. For example, chunking reduces the number of interacting elements processed simultaneously, while goal-free tasks minimise extraneous cognitive load and allow learners to focus on the underlying problem structure.

2.1. Intrinsic Cognitive Load

Intrinsic cognitive load arises from the inherent complexity of the subject matter and is influenced by the learner’s prior knowledge [19]. In the context of health sciences, core subjects such as pathophysiology and pharmacology are intrinsically demanding due to their abstract, multidimensional, and interconnected nature [20]. For instance, understanding how a drug modulates multiple biochemical pathways requires substantial cognitive effort, particularly for novice learners who may lack established mental frameworks.

As learners gain experience and form cognitive schemas, their ability to process complex information improves, effectively reducing the perceived difficulty of the content. Nevertheless, several challenges exacerbate intrinsic cognitive load in health sciences curricula. When students are required to process several interacting elements at once, the demands of the task may exceed working memory capacity and result in cognitive overload. Learners are often expected to synthesise knowledge from multiple disciplines within a single clinical scenario. This interdisciplinary integration intensifies cognitive demands. Moreover, the dynamic and rapidly evolving nature of medical knowledge necessitates frequent curricular updates, which can result in fragmented learning and increased cognitive strain.

2.2. Extraneous Cognitive Load

Extraneous cognitive load refers to the unnecessary mental effort imposed by suboptimal instructional design rather than by the content itself [19]. Inefficient presentation methods can obstruct learning by placing additional demands on limited cognitive resources. In health sciences education, common sources of extraneous load include cluttered lecture slides filled with verbose text, poorly sequenced materials, and disjointed learning resources. These elements force students to expend cognitive effort on processing irrelevant or redundant information rather than focusing on essential concepts.

Notable effects contributing to extraneous load include the split-attention effect, where learners must divide their attention across disparate sources such as lectures, handouts, and digital content [21]. The redundancy effect occurs when identical information is presented in multiple formats without enhancing understanding, thereby burdening working memory [22]. As an example, a medical instructor who reads aloud a densely worded slide while simultaneously presenting a complex electrocardiogram diagram may inadvertently hinder comprehension. Similarly, textbooks that rely heavily on long passages of text with minimal visual support can increase the cognitive burden, especially for visual learners.

2.3. Germane Cognitive Load

Germane cognitive load represents the mental effort invested in processing information, forming schemas, and automating knowledge structures [19]. Unlike extraneous load, germane load is beneficial and should be actively promoted through deliberate instructional strategies. In health sciences education, enhancing germane load involves techniques that support meaningful learning and transfer.

Worked examples that demonstrate step-by-step clinical reasoning processes can reduce cognitive demand during initial learning phases and help build foundational understanding. Scaffolding strategies, such as progressing from basic cases to complex real-world simulations, enable learners to incrementally develop their competence while managing overall cognitive load. Dual coding, which combines visual representations with verbal explanations such as using labelled anatomical illustrations alongside concise descriptions, facilitates schema formation by engaging multiple channels of cognitive processing. These pedagogical approaches align with CLT principles by reducing unnecessary load while enhancing productive mental effort.

3. Strategies for Managing Cognitive Load in Health Sciences Curricula

Given the high cognitive demands of health sciences education, effective curriculum design must incorporate strategies that align with the principles of Cognitive Load Theory. It is important to deliberately manage intrinsic, extraneous, and germane cognitive load to allow educators to enhance learning efficiency and support the development of clinical competence. This section and Figure 1 outline evidence-informed strategies for reducing cognitive overload and promoting deep learning.

3.1. Reducing Intrinsic Load Through Structured Content Delivery

Managing intrinsic cognitive load requires thoughtful sequencing and segmentation of complex material to align with students’ prior knowledge and cognitive capacity. One effective method is chunking, where large topics are broken into smaller, meaningful units [23,24]. For example, an anatomy lecture can be chunked into micro-episodes with segments of specific content and related sub-content, such as the brachial plexus (roots, trunks, and divisions). Additionally, pre-training with introducing foundational concepts before progressing to advanced material can help reduce initial cognitive strain [24]. For example, while teaching ethics, a one-page overview of autonomy, beneficence, non-maleficence, and justice can be provided before a consent scenario.

3.2. Minimising Extraneous Load Through Effective Instructional Design

Extraneous cognitive load can be reduced by refining how information is presented and eliminating non-essential cognitive demands. Instructional materials should adhere to multimedia learning principles, such as combining clear visuals with concise audio narration, to reduce the need for learners to split attention between sources [25]. Replacing text-heavy slide decks with short, focused videos or annotated diagrams improves clarity and retention. Interactive learning modalities, such as case-based learning (CBL) and problem-based learning (PBL), engage students in active processing of knowledge and promote deeper understanding. Furthermore, avoiding redundancy, for example, by not reading text verbatim during lectures, prevents unnecessary repetition that can overwhelm the working memory. Collectively, these instructional refinements can free up cognitive resources and enable learners to focus on meaningful content.

3.3. Promoting Germane Load Through Schema-Building Activities

Enhancing germane cognitive load involves stimulating mental effort directed toward organising and integrating new information into long-term memory. Spaced repetition can enable repeated engagement with content over time, improving consolidation and recall. This can be facilitated by tools such as Anki, an open-source flashcard application designed to support long-term memory retention through the use of active recall and spaced repetition [26]. Moreover, deliberate practice, originally described in expertise development research, refers to structured, purposeful, and repetitive engagement in task performance with immediate feedback and progressive refinement of skills. In health sciences education, this is often operationalised through repeated clinical simulations, supervised skill rehearsal, and formative assessments that allow learners to progressively improve accuracy and efficiency. Such structured repetition supports the development of automaticity and clinical fluency by strengthening schema construction and reducing cognitive effort required for task execution over time [27,28]. In addition, concept mapping allows learners to visualise connections between ideas and fosters systems-level thinking, which is especially important in interdisciplinary areas such as pathophysiology, pharmacology, or health management. These strategies can collectively nurture schema construction, facilitate critical thinking, and help learners manage complex clinical tasks with greater cognitive efficiency.

4. Advancing the Application of Cognitive Load Theory in Health Sciences Education: Gaps and Future Directions

Cognitive Load Theory has become an increasingly influential framework in educational psychology and instructional design, providing valuable insights into how teaching can be aligned with the human cognitive architecture. While the application of CLT in general education has produced a robust body of evidence supporting its utility, its translation into health sciences education remains underdeveloped and fragmented.

4.1. Integration with Adaptive Learning Technologies

One of the most promising frontiers for applying CLT principles lies in the development of adaptive learning technologies. These platforms, often powered by artificial intelligence (AI), can assess learners’ performance in real time and dynamically adjust the difficulty, complexity, or presentation style of instructional content [29,30]. When grounded in CLT, adaptive systems can be engineered to monitor indicators of cognitive load, such as response latency, error rates, or even physiological measures such as pupillometry, and modulate content delivery accordingly. This approach has the potential to reduce extraneous load while scaffolding intrinsic complexity, thereby maximising germane cognitive load for optimal learning [29,31]. As an example, a digital anatomy platform could begin with low-fidelity models and gradually introduce more detailed structures as the learner demonstrates mastery. This strategy applies the expertise reversal effect, in which instructional techniques that benefit novice learners (e.g., worked examples or simplified models) may become less effective as learners gain expertise [32]. The personalised scaffolding aligns with the principle of reducing unnecessary cognitive burden while encouraging active schema construction. The increasing use of Generative AI in education may assist learners to demonstrate their innovation abilities, but the associated cognitive load from information technology use may negatively impact their learning, supporting the importance of managing cognitive load [33]. However, further empirical research is required to evaluate the effectiveness of CLT-informed adaptive systems, particularly their impact on long-term retention, transfer of learning, and student satisfaction in clinical and health sciences education settings.

4.2. Longitudinal Cognitive Load Monitoring

Most empirical studies applying CLT in health sciences have relied on cross-sectional data or single-session interventions. However, the demands of medical and allied health education unfold over extended periods, often spanning multiple years. Consequently, longitudinal research that tracks cognitive load across time is essential to gain a comprehensive understanding of when and where overload is most likely to occur. Cognitive load is not constant but fluctuates across curricular phases, with heightened overload reported during transitions such as pre-clinical to clinical training [12]. A longitudinal approach could identify “cognitive bottlenecks” in the curriculum, which represents periods or courses that consistently induce overload, thereby guiding targeted instructional redesign. Additionally, repeated measures of both subjective and objective cognitive load indicators could help elucidate the relationship between perceived effort, academic performance, and learner wellbeing.

4.3. Cross-Cultural and Contextual Variability

Health sciences education is not monolithic, and it varies significantly across countries, institutions, and pedagogical traditions. Some programs emphasise problem-based learning, while others rely heavily on didactic lectures. These contextual differences may influence the types and levels of cognitive load experienced by learners. Further research is needed to determine how instructional approaches interact with cultural expectations, learner preferences, and prior educational backgrounds to affect cognitive processing [34]. Cross-cultural comparative studies could explore how CLT-informed strategies are received and implemented in diverse contexts, including low- and middle-income countries (LMICs) where resource constraints may affect the feasibility of certain instructional innovations. Additionally, equity-focused research could examine how CLT intersects with learner diversity, particularly among students with neurodivergent profiles or those who speak English as an additional language, to ensure that CLT-informed curricula are inclusive and accessible to all learners.

4.4. Curriculum-Wide Implementation and Faculty Development

Most applications of CLT in health sciences have been at the micro-level, with individual lessons, modules, or learning resources. While useful, such localised interventions often fail to produce sustained or systemic change. A key area for future work is the curriculum-wide implementation of CLT principles. This entails aligning instructional sequencing, assessment strategies, and content delivery modes across entire programs to ensure a consistent and coherent approach to cognitive load management. However, successful implementation requires more than redesigning course materials, as it also demands faculty awareness and expertise in CLT. Faculty development programs should include training on identifying different types of cognitive load, recognising signs of student overload, and designing instructional materials that optimise cognitive processing. Embedding CLT into educator professional development could create a culture of pedagogical intentionality and evidence-informed practice.

4.5. Assessment and Feedback Aligned with Cognitive Load

Assessment practices is a critical area where CLT can be better integrated. CLT-informed programmatic assessment design and feedback may reduce cognitive load in learners who will be working in complex clinical workplaces [35]. Traditional assessment formats, such as multiple-choice questions or high-stakes exams, often do not account for cognitive load dynamics. While such assessments may place greater demands on learners with lower prior knowledge, differences in performance may also appropriately reflect variation in learners’ knowledge and expertise. However, poorly designed assessment tasks may impose unnecessary cognitive burden. For example, negatively marked elimination-format multiple-choice questions have been shown to impose higher cognitive load and be perceived as more difficult than traditional single-best-answer items, which can negatively affect student performance and experience [36]. From a CLT perspective, such effects can be understood in terms of element interactivity, where tasks requiring the simultaneous processing of multiple interacting elements place greater demands on working memory and increase the risk of cognitive overload. Similarly, higher cognitive load has been linked to poorer simulator performance in clinical skills training, suggesting that cognitive load can directly impact assessment outcomes [37]. Future research should explore how formative assessment methods, including retrieval practice, low-stakes quizzes, and diagnostic feedback, can be designed to optimise germane load and reduce anxiety-related extraneous load. Moreover, advances in learning analytics could support real-time monitoring of cognitive load during assessment, providing learners and instructors with actionable insights [38]. As an example, digital exam platforms could incorporate prompts for students to reflect on perceived difficulty or mental effort after each section, allowing instructors to fine-tune future assessments or provide targeted support. While such innovations require empirical validation, they hold promise for making assessment both more equitable and more educationally effective.

4.6. Measuring Cognitive Load in Authentic Settings

A persistent methodological challenge in CLT research is the accurate and valid measurement of cognitive load, particularly in authentic learning environments such as clinical rotations or simulation labs. Traditional self-report measures, while useful, are prone to subjectivity and may not capture moment-to-moment fluctuations in mental effort. Physiological measures, such as eye-tracking, galvanic skin response, or electroencephalography provide more objective alternatives but are often costly and intrusive [39,40]. Future studies should aim to develop and validate multimodal cognitive load measurement frameworks that combine self-report, performance data, and unobtrusive physiological indicators. Such tools would allow researchers and educators to assess cognitive load in real-world instructional contexts, yielding richer data to inform curriculum design. Furthermore, attention should be paid to the dynamic interaction among the three types of loads (i.e., intrinsic, extraneous, and germane) during different phases of learning, which represents an area that remains under-theorised in current CLT literature.

4.7. Emerging Opportunities in Generative AI and Programmatic Feedback

Emerging areas such as generative AI and programmatic feedback design are increasingly relevant to the application of CLT. Generative AI platforms have the potential to personalise learning experiences by dynamically adjusting content complexity and providing interactive scaffolds, aligning with CLT principles to manage intrinsic and extraneous load while maximising germane load [33]. Similarly, programmatic feedback approaches, including structured low-stakes assessments and iterative formative feedback, provide opportunities to optimise cognitive load during complex skill acquisition in clinical education [41]. Further research is required to evaluate how these strategies can be effectively integrated into health sciences curricula to enhance learning outcomes and support equitable, evidence-informed practice.

5. Conclusions

In health sciences education, the complexity and density of curricular content often risk overwhelming learners’ cognitive capacity, hindering both understanding and long-term retention. Cognitive Load Theory provides a robust, evidence-based framework to guide the design of instructional materials and curricula that align with human cognitive architecture. By purposefully managing intrinsic, extraneous, and germane cognitive loads, educators can create learning environments that support deeper knowledge construction, promote clinical reasoning, and reduce learner burnout. A CLT-informed curriculum represents a step toward a more equitable, efficient, and learner-centred model of health sciences education, creating a framework that fosters sustainable learning and professional competence.