Chunking to Increase Executive Function Utility in Virtual Learning

The neurological process of learning is complex and relies extensively on an individual’s ability to access the executive functions of the brain. Executive function involves the modulation of various cognitive skills, enabling an individual to process information through working memory while simultaneously preventing hyperemotional responses to stimulation, and sustaining attentional focus as required [1, 2]. Neuro-executive abilities permit an individual to focus and sustain attention, effectively systematizing thoughts when encountering stimuli that are potentially disruptive and elicit increased levels of stress. When executive brain functions are compromised in virtual learning environments, due to either various external stimuli, an identified specific learning disability, or a combination of both, the individual’s access to a meaningful learning experience is impeded [2–4]. Therefore, educators and instructional designers need to understand the complexity of learning and the impact executive function has on learning in order to develop effective didactics and pedagogy.

The aforementioned complexities of learning were amplified by the forced presence of online learning that evolved from restrictions enforced during the COVID-19 pandemic. Instructors were, and continue to be, faced with providing content through virtual platforms while attempting to maintain student focus and ensure meaningful learning through effective virtual classroom management skills. Although the use of technology in the learning environment was not foreign to students or instructors during this time, the process of effective didactics and pedagogy in the virtual education environment was often unfamiliar to instructors [5, 6]. In the virtual education world, instructors found that the challenge of supporting students in the learning process with proficient retention and sustained attention was heightened [3, 5].

In a newer era of instruction heavily focused on virtual learning, instructors now frequently provide content through asynchronous, synchronous, or a combination of both modalities. Regardless of the delivery method, lectures are commonly sequenced in a manner that requires student attention for approximately 50–60 minutes [3, 5]. Whether instruction is delivered face-to-face or virtually, research suggests student engagement during lectures gradually declines after 10–15 minutes [3, 7]. The decline in engagement is related to the incongruency between attention and the amount of new information presented at one time [3]. It is safe to say that during a typical lecture sequence, many students experience an obstructed ability to regulate attention and insufficient memory retention, resulting in a reduction of intrinsic motivation and increased stress from the cognitive demand. 

Through the use of brain imaging, research has substantiated that when cognitive demand increases, blood flow to the area of the brain responsible for executive functions and emotions increases [2, 8]. This directional flow of blood during extensive cognitive demands in both face-to-face and virtual learning environments leads to the release of higher levels of cortisol, the chemical responsible for an individual’s fight-or-flight response to stress [9, 10]. This chemical increase can result in an inability to sustain attention to a given task, reducing motivation to continue with the cognitive process, and consequently resulting in decreased retention of the material being taught. At this point in the learning process, an individual has reached what is referred to as high cognitive overload and eventually experiences cognitive fatigue [8].

To lessen these negative effects, it is essential for educators and instructional designers to incorporate supports that reduce the cognitive load students experience in virtual learning environments. Cognitive load is the amount of mental effort required to process information. Theory distinguishes between three types: intrinsic, germane, and extraneous load. Intrinsic load is related to the complexity of the material itself and is influenced by the learner’s prior knowledge. It reflects the inherent difficulty of the task. Germane load is the mental effort dedicated to processing, constructing, and systematizing mental schemas, which assist in organizing information. This type of load is beneficial for learning as it helps in a deeper understanding. Extraneous load is the unnecessary cognitive effort imposed by inadequately designed instructional materials or what is perceived as an irrelevant task, which may hinder learning by distracting the learner. Reducing extraneous load allows learners to focus more on intrinsic and germane load, thereby enhancing learning efficiency [1, 3, 8, 10].

High cognitive load occurs when intrinsic complexity and extraneous distractions overwhelm working memory, whereas low cognitive load allows for easier processing and schema-building through reduced extraneous load and manageable intrinsic and germane demands [3, 11]. Instructors can minimize extraneous load through effective pedagogy, supporting learners with strategies that reduce the germane load of virtual didactics and pedagogy. 

Chunking is one example of an evidence-based strategy for preventing the effects of high extraneous load by grouping related pieces of information into small sections. When used in instructional design and content delivery, chunking enhances an individual’s motivation and ability to maintain focused attention, which can lead to deeper understanding and better retention of information [3, 7, 12]. 

Chunking

The concept of chunking was first conceptualized by the research of George Miller [13]. Miller’s research suggested individuals can recall seven (+/- 2) pieces of new information at one time. Beyond the number seven, memory becomes fragmented and ineffective. Miller reported that when large blocks of material are chunked, it requires less mental command for attention, freeing up the load capacity of the working memory. Consequently, this increases the quantity of information an individual can mentally encode for comprehension and accurate retrieval later [5, 12, 13].

An effective pedagogical approach that provides instructional chunking in education is known as scaffolding [14]. Scaffolding provides instructors a systematic way to break complex tasks or concepts down into smaller, more manageable parts to support student learning. In virtual instruction, this strategy provides temporary guidance and structure, helping students focus on one “chunk” at a time, building their understanding incrementally. This approach organizes information into bite-sized, digestible pieces that are interrelated, making learning more accessible and reducing cognitive overload. Overall, scaffolding serves as a structured, supportive way to help students build their understanding progressively in both face-to-face and virtual learning environments, which can enhance both comprehension and retention of complex material [14, 15].

Chunking provides a means for an active and dynamic learning experience for both face-to-face and virtual classrooms. It involves reorganizing or grouping a larger quantity of information into smaller, sequential blocks. Because chunking reorganizes larger segments of instruction into smaller blocks, an individual can manage complex skills using both short-term and long-term memory, improving retention and retrieval of the new skills by creating meaningful connections between main ideas and previously learned elements. Presenting smaller segments of information allows related units to be connected and stored, unlike large segments that are presented in their entirety and may become disjointed [16, 17]. Recent studies show the effectiveness of chunking varies depending on task complexity and learner experience [7, 9]

No matter the method of delivery of instruction (i.e., face-to-face, virtual, or hybrid), chunking is a less intrusive solution to facilitate sustained attention and learning. It requires less redesigning of existing material but involves restructuring of existing material into smaller, interdependent blocks. Similarly, restructuring of the amount of presented content at one time reduces both germane and extraneous loads [2, 3, 7, 12, 16].

Chunking for Virtual Learning

Teaching from a virtual platform presents challenges in keeping students motivated and engaged while accurately measuring learning to determine if adjustments to instruction are necessary [17, 18]. Chunking both instructional lectures and class assignments facilitates a positive learning experience for all parties by increasing intrinsic motivation, active participation, and the evaluation process, while reducing the level of cognitive load. It provides a time-efficient methodology for students to grasp essential concepts faster and for instructors to evaluate learning through productive feedback [3, 5, 18].

It is common for virtual learning environments to follow the traditional framework used in face-to-face classrooms. This framework is often embodied by a series of lengthy related lectures that require students to watch as a single unit, with little opportunity for active participation [17, 18]. This knowledge-transfer model provides a limited opportunity for meaningful internalization of content and results in greater loss of sustained focal attention as well as fragmented learning. Chunking lectures into short, 7–8 minute arrangements with well-organized gaps scaffolds the instruction, permitting students to experience mental breaks between segments, increasing sustained attention and enriching the learning experience [5, 7, 17, 18]. For example, an instructor may take a 60-minute online lecture and break it into five, 8-minute lecture blocks. Each block is followed by 2-3 minutes of structured activity, providing students an opportunity to synthesize the information before moving on to the next section.

Chunking lecture components into more distinct parts facilitates sustained attention due to the intermission generated between blocks. These strategic pauses create a space for authentic student-to-student and teacher-to-student interactions while providing students time to reflect and incorporate new information into mental schemata. Chunking also generates time for instructional feedback at both individual and whole-class levels, reducing cognitive fatigue [12, 18]. Subsequently, the managed interludes result in increased intrinsic motivation for students and enhance memory retention, improving the overall effectiveness of the learning experience [3, 8, 17, 18, 19]. Similarly, chunking assignments into smaller, manageable blocks promotes fluency in working memory [1], allowing learners to experience a greater sense of autonomy over the learning process, which correlates to lower levels of stress [5, 18, 19, 20]. Chunking assignments does not minimize or modify the standard associated with the task, but holds the same expectation for the overall outcome as if the assignment were presented in its entirety.

The benefits of chunking larger assignments are two-fold. First, it benefits the student by reducing the stress associated with the expectations of the entire assignment, providing guided steps that lead to a richer final product with a greater likelihood of meeting the assignment standards. Second, chunking supports the time instructors spend grading. Instructors frequently spend a great deal of time grading larger assignments that often fall at the end of a course, when it is too late to provide meaningful feedback for growth. By chunking assignments, the instructor can check for understanding as each block of the assignment is submitted, allowing for reteaching, correction, or adaptation of subsequent instruction as necessary. This also allows the instructor to grade each chunked component as the course progresses, reducing the overall grading load at the end of the unit while increasing the competency [3, 5, 7].

Key Takeaways

Chunking is a strategy that increases the amount of new content retained and the proficiency of complex skills by breaking larger segments of learning into smaller, more manageable parts for neurological processing. Chunking reduces the potential for high cognitive load, freeing up the working memory capacity. Similarly, chunking reduces distractions and fatigue that often impede the learning experience for individuals. In the post-pandemic education landscape, students are more familiar with the online learning environment and are expected to process information across a variety of modalities. Chunking is a strategy that supports both instructors and students in the virtual world. While chunking is effective in managing cognitive load and improving learning outcomes, its success depends on the complexity of the content, element interactivity, and learner characteristics. When used in conjunction with other evidence-based instructional strategies, chunking contributes to a positive, student-centered learning experience across various platforms.

References

About the Author

Jeremy R. Mills, Ed.D., is an assistant professor and Co-Director of the Special Education Program at the University of Dayton in Dayton, Ohio. His research focuses on developmental dyslexia, the design and implementation of pre-service and in-service educator training programs, strategies for enhancing student engagement, and the integration of technology to support students with high-incidence disabilities. 

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