Architectures of instruction: Selecting effective teaching methods
Designers of instruction are akin to learning architects. They aim to construct instructional experiences that engender durable, useful, and meaningful understanding in learners. Using the various teaching methods at their disposal, they facilitate each student’s personal efforts to build his or her unique house of knowledge. A successful learning architect knows, as the cognitive psychologist Richard Mayer writes, “which instructional methods work for teaching which kinds of knowledge to which kinds of learners under which kinds of circumstances” (54).
So how do you decide the ideal teaching methods for a particular learning situation?
While there is no single or definitive answer, Clark and Mayer suggest that online teaching typically involves one of three distinct instructional architectures: receptive, directive, or guided discovery, each reflecting a different metaphor for learning (20-22). While necessarily simplified, these approaches provide a useful framework for exploring the strengths and weakness of these popular instructional methods. Although students can learn successfully from all three approaches, it’s knowing when and how to use each method effectively that will make you a skilled learning architect.
According to the information acquisition metaphor of learning, the purpose of instruction is to disseminate information to learners who then store received ideas in memory. The instructional architecture associated with this metaphor is referred to as receptive because it views learners primarily as recipients of information. Common instructional delivery methods associated with this architecture include lecturing, textbook reading, and instructor modeling. In each case a learner is exposed to ideas with minimal interactivity.
Learning benefits and challenges
The benefits of receptive delivery methods are particularly notable for learners with low prior content knowledge. Receptive methods can be effective in assisting learners link their prior knowledge with incoming information, making abstract ideas concrete through use of analogies and metaphors, and drawing attention to important relationships or contrasts (see, deWinstanley and Bjork). Additionally, by modeling tasks and procedures, receptive instructional methods can free learner cognitive resources to focus on encoding relevant information without the burden of performance (Hattie & Yates 78-79).
The limited capacity of our working memory systems, however, means that excessive information presentation using receptive methods can quickly produce cognitive overload (Sweller et al. 259). Successful encoding of information also requires that learners take frequent breaks from receptive approaches in order to engage in more active learning strategies (e.g., retrieval practice, elaboration, and reflection). And given the absence of feedback in most receptive learning environments, students are highly susceptible to ‘illusions of knowing,’ believing they understand material better than they actually do (Bjork, Dunlosky & Kornell 432).
Directive instructional architecture is based on a response strengthening metaphor whereby learning is the result of appropriately supplied feedback in response to learner performance. Directive instruction emphasizes the importance of learners progressing through highly structured, and often carefully predefined, interactions eliciting frequent learner responses in conjunction with prompt feedback. Common directive instructional approaches include computer adaptive instruction, check-your-understanding type activities, and procedural training programs. Directive architectures are characterized by moderate levels of interactivity as learners are frequently expected to provide answers or select next steps.
Learning benefits and challenges
By eliciting frequent learner input, directive instructional methods support the retrieval and rehearsal activities necessary to support long-term learning as well as provide valuable feedback on the status of learner understanding (Rohrer & Pashler 406). Directive instructional methods also facilitate the extensive practice required to achieve mastery and automaticity in the foundational skills underlying higher learning outcomes. Finally, correcting learner misconceptions and teaching procedural skills are aided by the use of more directive teaching techniques (Clark 34; Wittwer & Renkl 59).
Yet directive methods, because of their highly structured and predetermined nature, often produce poorer results when the desired learning outcome is strategic or principle-based. Excessive reliance on directive methods can also result in a lack of cognitive flexibility with learners simply mastering rule application while failing to understand the broader conceptual or contextual implications of what they are learning.
Guided discovery architecture
Guided discovery methods emerged from research supporting the view that learning is a constructive process. The role of instruction, according to the guided discovery approach, is to provide opportunities for learners to construct knowledge by placing them in authentic situations requiring active and personal sensemaking. Instructional delivery methods associated with the guided discovery approach include the use of case studies, project or problem-based work, and simulations. Guided discovery methods are often characterized by high levels of learner interaction with minimal direct instruction.
Learning benefits and challenges
The guided discovery instructional architecture is typically viewed by researchers as most beneficial for high knowledge learners who do not require strong instructional support. Once learners have gained sufficient expertise in foundational skills, research evidence supports the value of having learners work on complex real-world problems that promote the acquisition of transferable and flexible knowledge (Merrill 44). The use of case studies and problem-solving activities can enhance the transfer of knowledge outside the instructional environment by maximizing the similarity between the teaching and transfer situations. Properly designed guided discovery methods can also be useful for teaching 21st century skills (e.g., critical thinking and collaboration) to supplement domain-specific content knowledge.
Discovery instructional methods should be used with care, however, as research has found that novice learners can find minimally guided discovery activities cognitively overwhelming (Kirschner et al. 77). High fidelity learning environments–those closely approximating real-world environments and/or discipline procedures–introduce many extraneous details that can interfere with successful learning. Similarly, the use of discovery methods like problem-based learning have been found to be most effective when used to help learners apply and expand their understanding rather than as a technique for acquiring new knowledge (Bruyckere et al. 54).
If you are interested in exploring these instructional architectures more, I encourage you to read Ruth Clark’s excellent paper, “Four Architectures of Instruction,” and also downloading the associated white paper.
About the Author
Jay Lynch has worked at Pearson since 2011. He earned his PhD and MA in Philosophy from the University of Colorado at Boulder and his BA at the University of Arizona. Jay has publications in both educational theory and philosophy. His research interests span the field of the learning sciences and he is particularly interested in the topics of desirable difficulties and improving research methodology in education. Jay also has several years of experience applying learning research in the design and development of online courses.
Bjork, Robert A., John Dunlosky, and Nate Kornell. “Self-regulated learning: Beliefs, techniques, and illusions.” Annual review of psychology, vol. 64, 2013, pp. 417-444.
De Bruyckere, Pedro, Paul A. Kirschner, and Casper D. Hulshof. Urban myths about learning and education. Academic Press, 2015.
Clark, Ruth C. “Four Architectures of Instruction.” Performance Improvement, vol. 39, no. 10, 2000, pp. 31–38.
Clark, Ruth C., and Richard E. Mayer. E-Learning and the Science of Instruction: Proven Guidelines for Consumers and Designers of Multimedia Learning. Fourth Ed. John Wiley & Sons, Inc, 2016.
deWinstanley, Patricia Ann, and Robert A. Bjork. “Successful Lecturing: Presenting Information in Ways that Engage Effective Processing.” New Directions for Teaching and Learning, vol. 89, 2002, pp. 19–31.
Hattie, John, and Gregory Yates. Visible learning and the science of how we learn. Routledge, 2014.
Kirschner, Paul A., John Sweller, and Richard E. Clark. “Why Minimal Guidance During Instruction Does Not Work: An Analysis of the Failure of Constructivist, Discovery, Problem-Based, Experiential, and Inquiry-Based Teaching.” Educational Psychologist, vol. 41, no. 2, 2006, pp. 75-86.
Mayer, Richard E. Applying the Science of Learning. Pearson Education, 2011.
Merrill, M. David. “First Principles of Instruction.” Educational Technology Research and Development, vol. 50, no. 3, 2002, pp. 43– 59.
Rohrer, Doug, and Harold Pashler. “Recent research on human learning challenges conventional instructional strategies.” Educational Researcher, vol. 39, no. 5, 2010, pp. 406-412.
Sweller, John, Jeroen J.G. van Merrienboer, and Fred G.W.C. Paas. “Cognitive Architecture and Instructional Design.” Educational Psychology Review, vol. 10, no. 3, 1998, pp. 251–296.
Wittwer, Jorg, and Alexander Renkl. “Why Instructional Explanations Often Do Not Work: A Framework for Understanding the Effectiveness of Instructional Explanations.” Educational Psychologist, vol. 43, no. 1, 2008, pp. 49–64.