Cognition in Context

Cognition—the mental processes involved in acquiring knowledge and understanding—is central in learning. But it’s not the whole story. The learning sciences emerged in part as a response to the limitations of fields like cognitive science, which often focused narrowly on internal mental processes while overlooking the broader learning environment. Early learning scientists recognized that learning is shaped not only by what happens in the brain but also by the tools, people, and contexts that surround the learner. Still, theories of cognition remain foundational in the learning sciences because they help us understand the internal mechanisms that make learning possible. By integrating these theories with insights about context and environment, we can design more effective and equitable learning experiences.

Of course, this series cannot describe every theory of cognition used in the learning sciences. Instead, it will describe a few commonly used theories and then discuss instructional design frameworks and models that help apply these theories to practice.

Theories of Cognition

Constructivism: Learning as Active Construction
Constructivism is a core theory in the learning sciences that posits learners build deeper knowledge when they construct it rather than memorize it. Constructivism emphasizes that learners should explore how new information builds upon or contradicts their experiences and prior knowledge. This theory was quite controversial in the late 2000s and has profound implications for instruction. It suggests that teaching should not be about delivering information, but about creating opportunities for learners to explore, question, and make sense of new ideas in relation to what they already know. As with all debated theories, most learning scientists believe that constructivism is more appropriate for some kinds of knowledge, particularly conceptual knowledge, and less effective than more direct instruction for others, like declarative knowledge. For more, see my article summaries on Schwartz & Bransford (1998) A Time for Telling, Lazonder & Harmsen (2016) Meta-analysis of Inquiry-based Learning, Andre (1997) Microinstructional Methods to Facilitate Knowledge Construction, and Alfieri et al. (2011) Does Discovery-Based Instruction Enhance Learning?.

Cognitive Load Theory: Managing Mental Resources
Cognitive Load Theory (CLT), developed by John Sweller, focuses on the limitations of working memory and how instructional design can either support or hinder learning. CLT distinguishes between intrinsic load—the complexity of the material—and extraneous load—unnecessary cognitive effort built into the learning activity. A third type of cognitive load, germane load, describes the mental effort devoted to learning, but it has fallen out of favor in modern CLT work. Effective instruction, according to CLT, creates an optimal amount of cognitive load. For relatively simple material (i.e., low intrinsic load), activities with higher extraneous load can help maintain learner engagement, such as using a game to memorize multiplication tables. For complex material, instruction should minimize extraneous load to avoid cognitive overload. If necessary, complex material should be broken down into smaller units to reduce intrinsic load. For more, see my article summary on Ashman et al. (2019) Explicit Instruction vs. Problem Solving First when Element Interactivity is High.

Zone of Proximal Development: Pushing the Boundaries
Vygotsky’s concept of the Zone of Proximal Development (ZPD) highlights the iterative nature of learning. The ZPD refers to the range of tasks a learner can perform with guidance but not yet independently. Learning occurs most effectively within this zone, where support from a more knowledgeable other—such as a teacher, peer, or digital tool—can help the learner progress. As learning occurs, the ZPD is constantly shifting, and the learner needs more and more challenging tasks. This theory also underscores the importance of interaction, dialogue, and collaboration in instructional design, and it provides a foundation for practices like scaffolding and peer learning.

Implications for Instructional Design

ICAP Framework: Levels of Cognitive Engagement
The ICAP framework, developed by Michelene Chi, categorizes learning activities based on the level of cognitive engagement they promote: Interactive, Constructive, Active, and Passive. Research shows that deeper learning occurs when students are engaged in constructive (e.g., generating new ideas) or interactive (e.g., dialoguing with others) activities, rather than merely active (e.g., highlighting text) or passive (e.g., listening to a lecture). This framework helps educators design learning experiences that go beyond surface-level engagement and foster meaningful understanding.

4C/ID: Designing for Complex Learning
The Four-Component Instructional Design (4C/ID) model is a comprehensive framework for teaching complex skills. It includes four components: learning tasks, supportive information, procedural information, and part-task practice. 4C/ID helps educators sequence instruction in a way that supports learners as they build expertise. It’s particularly useful in domains like computer science, where learners must integrate conceptual understanding with procedural fluency.

Scaffolding and Fading: Supporting Growth Over Time
Scaffolding is an instructional strategy that provides temporary support to help learners accomplish tasks they cannot yet do independently. As learners gain competence, these supports are gradually removed—a process known as fading. This approach is closely tied to the ZPD and reflects a dynamic view of instruction: one that adapts to the learner’s evolving needs. Scaffolding can take many forms, from worked examples and hints to structured peer collaboration and adaptive technologies. For more, see my article summary on Belland et al. (2017) Influence of Contexts of Scaffolding.

To view more posts about learning sciences, see a list of topics on the Intro to the Learning Sciences: Series Introduction.