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Cognitive Design Principles

Understanding the learning process, and the impact of various instructional strategies and methods on learning is primary. It is the foundational knowledge required to plan, design, develop and deliver E-Learning products and activities.
What are the key cognitive-behavioral learning principles
to guide instructional design and development?

Cognitive Information Processing

The following Cognitive Information Processing model (CIP) of learning presents a well-established paradigm of cognitive-behavioral psychology. The model articulates the limited capacity of "working memory." Working memory is tasked with the burden of processing incoming information, transferring information to long-term memory and retrieval of information from long-term memory. The concept of "cognitive load" — the amount of work imposed on working memory by a learning task — is based on observations of the functions of working memory.

The CIP model addresses the following learning issues: rehearsal, auditory & visual channels, attention, elaboration, mental models, schema and metacognitive skills (including motivation).

Cognitive Information Processing (CIP)

 

Nine Events of Instruction

Dr. Robert Gagne's famous Nine Events of Instruction, first presented in The Conditions of Learning (1985), are derived from a cognitive information processing model of learning. We can think of these components as describing the "tactics of instruction" that can be applied to most instructional methods or learning activities.

Gagne's Nine Events of Instruction
Events of Cognitive/
Learning Process
1. Gaining attention Reception / Motivation
2. Informing learners of objective Establishment of expectancies
3. Stimulating recall of prior learning Retrieval (from long-term memory)
4. Presenting stimulus material Selective perception
5. Providing learning guidance Semantic encoding
6. Eliciting performance (practice) Response generation
7. Providing feedback Reinforcement
8. Assessing performance Metacognition
9. Enhancing retention and transfer Generalization
Gagne, R., Briggs, L. & Wager, W. Principles of Instructional Design (4th Ed., 1992)

This table illustrates the power of the CIP model to provide a coherent description of what the instructor and learner are each doing – external behavior, internal information processing, and the interaction between teacher and student. It therefore becomes a powerful problem-solving tool for discovering and correcting gaps in the instructional process — providing a deeper understanding the art as well as the science of teaching.
 

The Science of Instruction

Among the many researchers in the field of instructional design and educational technology, there are three important researchers we can turn to for an understanding of the science of instruction: Dr. David M. Merrill, Dr. Richard Mayer, and Dr. Ruth Clark.

Each of these researchers seeks to advance the scientific validation of instructional principles by identifying the cognitive processes associated with each principle — as well as their practical application in E-Learning.

Dr. David M. Merrill has contributed a body of research and literature to the field of instructional design. Particularly important is his article, "The New Component Design Theory: Instructional design for courseware authoring." Instructional Science, (1987)16, 19-34. His latest contributions related to this discussion are:

  • First Principles of Instruction (2002) — summarizes principles of instructional design and delivery that apply to all instructional environments
  • Designing Five Star Instruction (2003) — provides an approach to evaluating instruction to verify its fundamental design integrity, especially for E-Learning products
  • Knowledge Objects and Mental Models (2000), In D. A. Wiley (Ed.). The Instructional Use of Learning Objects (in press) — presents an explanation of mental models; as a preface he defines cardinal principles of instruction
  • Merrill defines a principle as: "a relationship that is always true under appropriate conditions regardless of program or practice."
  • He has helped make popular the saying: “If an instructional product does not teach, then it has no value.”

Dr. Ruth Clark and Dr. Richard Mayer have recently collaborated on the book, E-Learning and the Science of Instruction (2003). This text summarizes empirical research that supports specific E-Learning instructional strategies and is based on an information-processing model of learning.

Both of these approaches are aligned in a Cognitive Information Processing (CIP) model of learning — originally popularized by Gagne and then elaborated by numerous theorists. Clark and Mayer summarized Cognitive Learning Theory this way:

Four Learning Architectures

In relationship to theories of learning, Dr. Clark has suggested that there are four distinct Learning Architectures:

  • Receptive Learning (information acquisition) : reflects an absorptive metaphor of learning; the primary goal is information acquisition — characterized by an emphasis on providing information with little opportunity for interaction, practice or feedback. Examples are traditional classroom lectures, reading assignments, and watching educational television.
  • Directive Learning (response strengthening) : reflects a behavioral model of learning; the primary goal is response strengthening — characterized by a high degree of instructional support, feedback and reinforcement — with limited learner control. Emphasizes the acquisition of pre-determined knowledge and skill hierarchies. Examples include traditional coaching, skill based mentoring, programmed instruction, CBT and WBT courses.
  • Guided Discovery Learning (knowledge construction) : reflects a cognitive model of learning; the primary goal is knowledge construction — typically characterized by problem-solving and scaffolded guidance that supports learning from an inductive, case-based and example approach. Learners may work alone or in conjunction with others to internally generate unique knowledge structures. Examples include game and scenario learning, and "Cognitive Apprenticeship".
  • Exploratory Learning (linking to real world tasks & resources) : reflects a cognitive model of learning with a constructivist emphasis; the primary goal is linking to real world tasks and resources — characterized by the highest degree of learner control, initiative, and self-direction. Learners must search out and access the information that is required. The Internet and intranet provide a robust exploratory environment unlike the limitations imposed by traditional classroom learning. Examples include lab assignments, fieldwork and clinical study, library and Internet research assignments.

See Ruth Clark: Building Expertise (2nd ed, 2003) pp. 4-12; "The New ISD: Applying Cognitive Strategies to instructional Design," www.ispi.org, August 2002; "Four Architectures of Instruction," Performance Improvement, v.39 #10, pages 31-37, 2000.
 

A Framework of Cognitive Design Principles

In listing the following principles, brief descriptions have been used. See the full elaboration of the principles in the texts by the original authors. Seventeen principles were drawn from Clark & Mayer, and nine from Merrill — with a certain amount of overlap. There is a mix of principles of cognitive learning and principles of instruction. As the science of instruction advances, additional items will be added and the wording of these items will no doubt be modified. So this is a transitional compilation.

The Cognitive Design Process organizes the cognitive learning principles into four sets (or clusters) to make them easier to work with.

  1. Principles of Multimedia Learning
  2. Principles of Cognitive Load Management
  3. Principles of Interactive Engagement
  4. Principles of Problem-based Instruction

 

Principles of Multimedia Learning

Principles of Multimedia Learning describe the optimum ways to use text & graphics for engaging learner attention and information processing.

Dr. Mayer developed the following six cognitive principles from his research. Observing problems of cognitive load and misdirected attention, he noted that, "In the case of multimedia lessons, students tend to learn more when less is presented."

  • Multimedia Principle — adding graphics to words can improve learning
  • Contiguity Principle — placing text near graphics improves learning
  • Coherence Principle — using gratuitous visuals, text and sounds can hurt learning
  • Modality Principle — explaining graphics with audio improves learning
  • Redundancy Principle — explaining graphics with audio and redundant text can hurt learning
  • Personalization Principle — use conversational tone and pedagogical agents to increase learning

Effective E-Learning design will take into account all six of these principles applied to the learning structures of Information, Instruction, Media and Delivery System.

See Richard Mayer, Multimedia Learning (2001), and Clark & Mayer,
E-Learning and the Science of Instruction
(2003)
 

Principles of Cognitive Load Management

The issue of cognitive load — the amount of mental resource in short-term memory required by a learning task — is an integral factor in the six Principles of Multimedia Learning. However, Clark and Mayer also introduce its broader application: Intrinsic load — cognitive load that is inherent, due to the complexity of the learning task content itself; and Extraneous load — cognitive load that is introduced by the use of an instructional strategy and method.

  • Extraneous Load Principle — reducing or eliminating extraneous cognitive load will improve learning.
  • Intrinsic Load Principle — reducing intrinsic cognitive load will improve learning.

Management of extraneous cognitive load is accomplished by looking at the composite effect of all information presentation, instructional strategies, media use and delivery system implementation, as well as the effect of individual elements.

Management of intrinsic cognitive load is achieved through: task analysis to identify and validate specific learning tasks; ensuring that pre-requisite knowledge and skills are available before presenting a new learning task; and "chunking" content into smaller, easier to handle, learning steps. The chunking method applies to presentation, interactivity, guidance and feedback.

It is important to note that task analysis is also optimally conducted in relation to job analysis and competencies — validating specific learning tasks in terms of performance expectations and learning goals.

See Ruth Clark, Building Expertise, (2nd Ed., 2003), p. 46 ; Clark & Mayer, E-Learning and the Science of Instruction, (2003).
 

Principles of Interactive Engagement

Principles of Interactive Engagement describe the ways in which an active learning environment can be created — which optimizes information processing (encoding and retrieval) and as well as motivation (metacognition).

Interactive Engagement requires that the learner be in a mode of active responding; be required to practice with guidance & feedback, and be offered independent practice with naturalistic cues.

Clark and Mayer present the principles of Practice, Learner Control and Problem-solving — with research data to substantiate their conclusions.

  • Initial Learner Motivation Principle — establishing lesson relevance and building learner confidence engages motivation to stay on task
  • Activating Prior Knowledge Principle — encoding of new learning must integrate with existing knowledge; activating long-term memory relevant to new information can improve learning
  • Selective Attention Principle — selectively attending to what is most relevant in the learning task by adding cues can improve learning; eliminating distractions which divide attention can improve learning
  • Elaborative Rehearsal Principle — elaborative rehearsals can improve learning (supports the construction of schema to encode and retrieve long-term memory)
  • Demonstrations & Practice Principle — observation strengthens learning; structured opportunities to engage with the content by responding to a question or taking an action to solve a problem can improve learning
  • Mental Models Principle — the use of mental models can improve learning (supports the construction of schema to encode and retrieve long-term memory)
  • Learner Control Principle — learner control works best to improve learning when the learner has prior knowledge of the subject and when he has good metacognitive skills; adaptive control can improve learning
  • Problem-solving Principle — problem-solving skills depend on very specific job knowledge and metacognitive skills; engaging in problem-solving can improve learning
  • Metacognitive Skill Principle — the "executive function" of working memory can be trained to monitor various facets of information processing, and then adjust strategies to improve learning; metacognition can particularly engage motivation for learning

See Clark & Mayer, E-Learning and the Science of Instruction (2003), and Ruth Clark, Building Expertise, (2nd Ed., 2003), p. 29-31.
 

Principles of Problem-based Instruction

Dr. David M. Merrill has offered the following four cardinal principles of instruction:

  • The Cognitive Structure Principle — The purpose of instruction is to promote the development of that cognitive structure that is most consistent with the desired learned performance.
  • The Elaboration Principle — The purpose of instruction is to promote incremental elaboration of the most appropriate cognitive structure to enable the learner to achieve increased generality and complexity in the desired learned performance.
  • The Learner Guidance Principle — The purpose of instruction is to promote that active cognitive processing that best enables the learner to use the most appropriate cognitive structure in a way consistent with the desired learned performance.
  • The Practice Principle — The purpose of instruction is to provide the dynamic, ongoing opportunity for monitored practice that requires the learner to demonstrate the desired learned performance, or a close approximation of it, while the instructor monitors the activity and intervenes with feedback both as to result and process.

See David M. Merrill, "The New Component Design Theory: Instructional design for courseware authoring." Instructional Science, (1987) 16, 19-34; and Knowledge objects and mental models (2000), in D. A. Wiley (Ed.). The Instructional Use of Learning Objects (in press)

Most recently, Dr. Merrill presented the "Five Star Instruction" model for effective design. It is a problem-based instruction model, and a comprehensive, yet simple, device for the evaluation process. Dr. Merrill suggests that the most effective learning environments are those that are problem-based and involve the learner in four distinct phases of instruction.

  Merrill (2002)

  • Problem Principle — Learning is facilitated when learners are engaged in solving real-world problems
  • Activation Principle — Learning is facilitated when existing knowledge is activated as a foundation for new knowledge
  • Demonstration Principle — Learning is facilitated when new knowledge is demonstrated to the learner
  • Application Principle — Learning is facilitated when new knowledge is applied by the learner (e.g., guided and unguided practice)
  • Integration Principle — Learning is facilitated when new knowledge is integrated into the learner's world

See David M. Merrill, Five Star Instruction (2003); and First Principles of Instruction (2002.)

Principles of Problem-based Instruction aim at making the instructional context relevant, focused on meaningful skills and therefore effective for transfer-of-learning.

Problem solving also creates an explicit opportunity for metacognitive skills to be practiced and taught (i.e., awareness and control of one's own cognitive processing, including setting goals, monitoring progress and adjusting strategies as needed).

Organizing instruction around learner problem-solving mobilizes associations with previous learning. It creates encoding and retrieval hooks upon which successful transfer-of-learning depend. It establishes a motivational context essential for the adult learner.
 

Conclusion

The Cognitive Design Process includes a checklist of review questions based on the Cognitive Design Principles just enumerated. The checklist is designed for use in both planning and evaluation of E-Learning products and activities.

The Cognitive Design Process applies these evaluation criteria to the production processes of Information, Instruction, Media and Delivery System — and throughout the process of planning, design, development and delivery. An E-Learning Impact Scale (2003) is currently in development.

Cognitive Design Principles

  2003 Cognitive Design Solutions, Inc.