1. Gaining attention (reception)
2. Informing learners of the objective (expectancy)
3. Stimulating recall of prior learning (retrieval)
4. Presenting the stimulus (selective perception)
5. Providing learning guidance (semantic encoding)
6. Eliciting performance (responding)
7. Providing feedback (reinforcement)
8. Assessing performance (retrieval)
9. Enhancing retention and transfer (generalization)

• Introduction to Instructional Design
• Foundations of Instructional Design

• Instructional Analysis: Analyzing the Learning Context
• Instructional Analysis: Analyzing the Learner
• Instructional Analysis: Analyzing the Learning Task
• Assessing Learning from Instruction

• A Framework for Instructional Strategy Design
• Strategies for Declarative Knowledge Instruction
• Strategies for Instruction Leading to Concept Learning
• Strategies for Instruction Leading to Learning Procedures
• Strategies for Instruction Leading to Principle Learning
• Strategies for Problem-Solving Instruction
• Strategies for Cognitive Strategy Instruction
• Strategies for Attitude Change, Motivation, and Interest
• Strategies for Psychomotor Skill Learning
• Marco Strategies: Integration of Types of Learning

• Implementation
• Management of Instruction
• Formative and Summative Evaluation

• Instructional objectives are most useful when stated as intended outcomes and defined in terms of student performance. Stated as such, they provide direction for instruction, guidelines for student learning, and targets for formative and summative evaluation.
• Objectives at the training level are typically stated as specific, limited, and well-defined tasks to be performed.

• Begin each general objective with a verb that encompasses a domain of student performance (see Bloom’s Taxonomy), includes only one general learning outcome, and contains an action verb that specifies observable performances.
• Don’t neglect complex objectives (e.g., thinking skills) simply because they are difficult to define in terms of specific learning outcomes.

• Instructional objectives should be prepared before selecting the methods and materials of instruction and assessment.
• Use a three column planning chart to ensure the (1) objectives, (2) content, and (3) assessment are all in sync. The chart states what the instruction is to achieve, how you plan to achieve it, and how you will determine the success of your training.
• Sharing instructional objectives with students can provide clear targets for learning and contribute to self-assessment skills and independent learning.

• Content standards are general goals that indicate what students are expected to learn. Content standards provide a framework for developing the curriculum, but specifically stated instructional objectives are needed for teaching and assessment.

• A frame of reference that classifies the various types of learning outcomes can aid in identifying, stating, and organizing objectives into an appropriate list.
• Check your final list of instructional objectives for appropriateness, representativeness, attainability, relevance to the instructional program, and relevance to the basic principles of learning.

• Most areas of instruction include knowledge outcomes (remembering material), comprehension outcomes (grasping the meaning of material), and application outcomes (using the information in some way).

• Higher-level thinking skills are commonly discussed as critical thinking, creative thinking, and problem solving. They are in the domains of analysis, synthesis, and evaluation (see Bloom’s Taxonomy).
• Instructional objectives at the thinking level require that the problems or situations be new to the students and affective components of thinking should not be overlooked.

• Objectives in the affective domain are more difficult to write than cognitive and skill outcomes. They should be written in terms of observable behavior whenever possible, but feelings, opinions, and preferences should not be neglected.

• When performance objectives are clearly defined, the list of specific outcomes can be easily converted to checklists or rating scales for use in the assessment. They should include all specific outcomes that are crucial to successful performance.

• Problem-solving projects are useful for integrating learning and skills from many different areas, developing higher-level thinking skills, and providing opportunities for student self-assessment and independent learning.
• Restricted problem-solving projects are limited in scope, highly structured, and typically assigned by the facilitator. Extended problem-solving projects are broad in scope, concerned with ill structured problems that have many possible solutions, and the learners are typically free to select and study a problem of their choice. It is critical in both cases to provide clear criteria for judging the performance.

• Instructional objectives play a key role in the testing of student achievement by describing the types of performance to be measured.
• A table of specifications is a two-dimensional table that indicates the nature and number of test items needed to obtain a balanced measure of the intended learning outcomes.
• Instructional objectives can be used to interpret assessment results to students. This may be done in terms of the specific learning outcomes or the general objectives.

• Instructional objectives play a key role in assessing performance skills and affective outcomes by describing the relevant aspects to be judged. They provide the criteria for assessment.
• Performance skills may be assessed during analytical scoring (a separate judgment on each criterion) or holistic scoring (a general impression of the performance).
• Analytical scoring is typically done by using a rating scale for recording the degree to which an element is present, or by using a checklist that simply requires a judgment of presence or absence.
• Holistic scoring typically uses a scoring guide or rubric that classifies the performance into one of several categories, such as advanced, proficient, average, below average.
• A portfolio is especially useful in evaluating complex performance skills and affective behavior because the changes are subtle and take a long time to develop. The periodic collection of evidence makes the changes more apparent and thus more useful in judging student performance.

• Instructional Design: What is It and Why is It?
• A Metatheory of Instruction: a Framework for Analyzing and Evaluating Instructional Theories and Models
• Descriptive and Prescriptive Theories of Learning and Instruction: an Analysis of Their Relationships and Interactions

• Contributions of Gagné and Briggs to a Prescriptive Model of Instruction
• A Behavioral Approach to Instructional Prescription
• The Algo-Heuristic Theory of Instruction
• Instructional Strategies Based on the Structural Learning Theory
• A Cognitive Theory of Inquiry Teaching
• Component Display Theory
• The Elaboration Theory of Instruction
• Motivational Design of Instruction

• Is Instructional Theory Alive and Well?

Clark, Ruth; Nguyen, Frank; and Sweller, John (2006). Efficiency in Learning: Evidence-Based Guidelines to Manage Cognitive Load. Pfeiffer.

This book provides an outstanding set of guidelines, each painstakingly backed by research, to achieve efficient instruction. The guidelines are based on application of cognitive load theory, and focus on minimizing unproductive contributions to cognitive load while maximizing productive sources of cognitive load. This, in turn, leads to creating an efficient learning intervention and/or environment.

Cognitive Load Theory:

According to the findings of George Miller, our cognitive system can only process 7 plus or minus 2 "chunks" of content at one time. When this limit is exceeded, our thinking and learning processes are negatively impacted. The size of these 7 plus or minus 2 chunks is directly related to the existing knowledge and expertise of the individual: an expert in the content field processes much larger chunks than a novice.

• Chapter 1. Expertise, Learning, and Instruction
• Chapter 2. The Psychology of Building Expertise
• Chapter 3. How Working Memory Works
• Chapter 4. Managing Cognitive Load in Instruction
• Chapter 5. Managing Attention
• Chapter 6. Leveraging Prior Knowledge
• Chapter 7. Helping Learners Build Mental Models: Implicit Methods
• Chapter 8. Helping Learners Build Mental Models: Explicit Methods
• Chapter 9. Learning versus Performance: The Psychology of Transfer
• Chapter 10. Teaching for Transfer
• Chapter 11. Problem-Centered Instruction
• Chapter 12. Metacognition and Self-Regulated Performance
• Chapter 13. Cognitive Perspectives on Motivation
• Chapter 14. Building Expertise through Training: A Summary

• Use Signals and Cues to draw attention to important content. (Attention)
• Use graphics in place of text when the content can be communicated more efficiently visually. (Memory Load)
• Plan graphics that are consistent in style and low in complexity. (Memory Load)
• Use organizational visuals such as graphic organizers to show qualitative relationships among lesson content. (Building Mental Models)
• For online practice of computer procedures, support transformational visuals with on-screen contiguous text to provide directions, feedback, and memory support. (Procedures)
• Use interpretive visuals such as schematics and visual analogies to represent abstract processes such as how computer program code works. (Processes)
• Create project specific standards and guidelines through samples, prototypes, templates, and appropriate documentation. (Communicate Your Graphic Plans)

• Rule #1: Exercise boosts brain power.
• Rule #2: The human brain evolved, too.
• Rule #3: Every brain is wired differently.
• Rule #4: We don't pay attention to boring things.
• Rule #5: Repeat to remember.
• Rule #6: Remember to repeat.
• Rule #7: Sleep well, think well.
• Rule #8: Stressed brains don't learn the same way.
• Rule #9: Stimulate more of the senses.
• Rule #10: Vision trumps all other senses.
• Rule #11: Male and female brains are different.
• Rule #12: We are powerful and natural explorers.

1. Create a teaching points document, which will address the specific training need.
2. Analyze: understand what makes up successful performance. You also have to “find the gaps”---places where performers tend to be held back by mistakes.
3. Choose a design theme.
4. Review prior courseware.
5. Create a design timeline.
6. Create a task skeleton and some sample content.
7. Do a text walkthrough.
8. Create a slide show.
9. Implementation Review.
10. Functional Specification.

• Waking in the Night an Thinking About E-Learning, Allison Rossett
• The Forum Report:  E-Learning Adoption Rates and Barriers, David E. Simmons
• Performance Support - Driving Change, Gloria Gery
• Learnativity:  Into the Future, Wayne Hodgins
• Blended Learning:  The Magic is in the Mix, Elliott Masie
• E-Learning in the Old World:  A Reflection on the European E-Learning Situation, Christian Volkl and Folkert Castelein
• Covering Your Assets:  10 Things Trainers Should Know About Copyright Law, Sarah Fister Gale

Part Two – Developing Great E-Learning

• From Binders to Browsers:  Converting Classroom Training to the Web, Shonn R. Colbrunn and Darlene M. Van Tiem
• Ten Things to Look for When You're Buying WBT, Le'a Kent
• Putting Learning Standards into Practice:  A Primer, Richard Clark
• Learning Objects Need Instructional Design Theory, David Wiley
• A Framework for Designing Interactivity into Web-Based Instruction,  Pam Northrup
• Games That Teach:  Simple Computer Games for Adults Who Want To Learn, William Horton
• Virtual Games for Real Learning:  Learning Online with Serious Fun, Marie Jasinski and Sivasailam Thiagarajan
• Don't Forget the High-Touch with the High-Tech in Distance Learning, Dean R. Spitzer
• The Handheld Web:  How Mobile Wireless Technologies will Change Web-Based Instruction and Training, Paul G. Shotsberger and Ronald Vetter
• Designing Discussion Questions for Online, Adult Learning, Zane L. Berge and Lin Muilenburg

Part Three – Managing E-Learning Success:  Strategies That Turn Promises into Performance

• The Four C's of Success:  Culture, Champions, Communication, and Change, Marc. J. Rosenberg
• How to Keep E-Learners from E-scaping, Jim Moshinskie
• Six Steps to Developing a Successful E-Learning Initiative:  Excerpts from the E-Learning Guidebook, Brandon Hall
• How to Facilitate E-Collaboration and E-Learning in Organizations, Nory B. Jones and James Laffey
• Technology Adoption:  Bringing Along the Latecomers, Rebecca Vaughan Frazee
• How Can We Use Knowledge Management? Allison Rossett and Kendra Sheldon
• Distributed Cognition:  A Foundation for Performance Support, Jan D. Greenberg and Gary J. Dickelman
• Getting IT Support for E-Learning, Tom Barron
• Emerging Instructional Technologies:  The Near Future, John W. Jacobs and John V. Dempsey
• Building Performance-Centered Web-Based Systems, Information Systems, and Knowledge Management Systems in the 21st Century, Barry Raybould

Part Four – Is E-Learning Too Good To Be True?

• The State of Online Learning - What the Online World Needs Now:  Quality, Kevin Dobbs
• Web-Based Education:  A Reality Check, Rob Foshay and Corrie Bergeron
• Digital Backlash, Karl Albrecht and Ronald Gunn
• Top Ten E-Learning Myths, John V. Moran and Haidee E. Allerton
• Challenging E-Community Myths, David Mager and Warren Karlenzig
• Evaluating the Return on Investment of E-Learning, Jack J. Phillips, Patricia P. Phillips, Lizette Z. Duresky, and Cyndi Gaudet
• Benefits, Costs and the Value of E-Learning Programs, David C. Forman

Part Five – E-Learning for the E-Learning Professional:  Developing the People Who Will Lead the Field

• Professional Development to Go? George Lorenzo
• Not Too Cool for School, Patti Shank
• Preparing E-Learning Professionals, Bob Hoffman
• The Four Levels of Web Site Development Expertise, Albert L. Ingram

Part Six – E-Learning at Work:  Case Studies

• E-Learning Evangelism, Kim Kiser
• Using Objects for Online Learning:  E-Learning for Project Managers, Warren Longmire, Dan Hughes, and Karen Jost
• Interdisciplinary Studies and New Technologies:  A Case Study, Alan B. Howard
• Washington's Need to Know, Mary Eisenhart
• Mission E-Possible:  The Cisco E-Learning Story, Patricia A. Galagan
  Ready for Liftoff, Kim Kiser
• Blended Learning Case Study, Jennifer Hofmann

Working memory is limited and has no logical “central executive” available to organize new information.  When building onto existing schema, instruction should relate to the existing schema. When presenting new concepts, instruction should be organized to support the development of a new successful schema.

A fundamental hypothesis underlying research on multimedia learning is that multimedia instructional messages that are designed in light of how the human mind works are more likely to lead to meaningful learning than those that are not.  The cognitive theory of multimedia learning (CTML) is based on three cognitive science principles of learning: the human information processing system includes dual channels for visual/pictorial and auditory/verbal processing (i.e., dual-channel assumption); each channel has limited capacity for processing (i.e., limited capacity assumption); and active learning entails carrying out a coordinated set of cognitive processes during learning (i.e., active processing assumption).

The cognitive theory of multimedia learning specifies five cognitive processes in multimedia learning:

1. Selecting relevant words from the presented text or narration,
2. Selecting relevant images from the presented illustrations,
3. Organizing the selected words into a coherent verbal representation,
4. Organizing selected images into a coherent pictorial representation, and
5. Integrating the pictorial and verbal representations and prior knowledge.

Multimedia instructional messages should be designed to prime these processes.

The Four-Component Instructional Design (4C-ID) model claims that four components are necessary to realize complex learning:

1. Learning tasks
2. Supportive information
3. Procedural information
4. Part-task practice

Students may work on learning tasks in simulated task environments, where relevant multimedia principles primarily facilitate a process of inductive learning.  They may study supportive information in hypermedia systems, where principles facilitate a process of elaboration and mindful abstraction.  They may consult procedural information in Electronic Performance Support Systems (EPSSs), where principles facilitate a process of knowledge compilation.  Finally, they may be involved in part-task practice with drill and practice Computer-Based Training (CBT) programs, where principles facilitate a process of psychological strengthening.

The multimedia principle states that people learn better from words and pictures than from words alone. Effectiveness of combining imagery with text varies with the content to be learned, the conditions under which performance is measured, and individual differences in spatial ability, prior knowledge, and general learning ability.

The split-attention principle states that when designing instruction, including multimedia instruction, it is important to avoid formats that require learners to split their attention between, and mentally integrate, multiple sources of information.  Instead, materials should be formatted so that disparate sources of information are physically and temporally integrated thus obviating the need for learners to engage in mental integration.  By eliminating the need to mentally integrate multiple sources of information, extraneous working memory load is reduced, freeing resources for learning.

The capacity limitations of working memory are a major impediment when students are required to learn new material.  Furthermore, those limitations are relatively inflexible.  However, presenting some information in visual mode and other information in auditory mode can expand effective working memory capacity, reducing the effects of excessive cognitive load.

The redundancy principle suggests that redundant information interferes with rather than facilitates learning. Redundancy occurs when the same information is presented in multiple forms or is unnecessarily elaborated. Instructional designs that eliminate redundant material can be superior to those that include redundancy.

When a concise narrated animation containing complicated material is presented at a fast rate, the result can be a form of cognitive overload called essential overload.  Essential overload occurs when the amount of essential cognitive processing (similar to intrinsic cognitive load) required to understand the multimedia instructional message exceeds the learner’s cognitive capacity.

Three multimedia design methods intended to minimize essential overload are the segmenting, pretraining, and modality principles:

• Segmenting principle: People learn more deeply when a multimedia message is presented in learner-paced segments rather than as a continuous unit.
• Pretraining principle: People learn more deeply from a multimedia message when they know the names and characteristics of the main concepts.
• Modality principle: People learn more deeply from a multimedia message when words are spoken rather than printed.

Extraneous overload occurs when essential cognitive processing (required to understand the essential material in a multimedia message) and extraneous cognitive processing (required to process extraneous material or to overcome confusing layout in a multimedia message) exceeds the learner’s cognitive capacity.

Five multimedia design methods intended to minimize extraneous overload are the:

• Coherence principle: People learn more deeply from a multimedia message when extraneous material is excluded.
• Signaling principle: People learn more deeply from a multimedia message when cues are added that highlight the organization of the essential material.
• Redundancy principle: People learn more deeply from graphics and narration than from graphics, narration, and onscreen text.
• Spatial contiguity principle: People learn more deeply from a multimedia message when corresponding words and pictures are presented near rather than far from each other on the screen/page.
• Temporal contiguity principle: People learn more deeply from a multimedia message when corresponding animation and narration are presented simultaneously rather than successively.

Social cues may prime social responses in learners that lead to deeper cognitive processing during learning and hence better test performance.  The personalization principle is that people learn more deeply when the words in a multimedia presentation are in conversational style rather than formal style.  The voice principle is that people learn more deeply when the words in a multimedia message are spoken in a standard-accented human voice rather than in a machine voice or foreign-accented human voice.  The image principle is that people do not necessarily learn more deeply from a multimedia presentation when the speaker’s image is on the screen rather than not on the screen.

Inquiry or scientific discovery learning environments are environments in which a domain is not directly offered to learners but in which learners have to induce the domain from experiences or examples.  Because this is a difficult task he discovery process needs to be combined with guidance (e.g., scaffolding, cognitive tools) for the learner.  The most effective way to provide this guidance is to integrate it in the learning environment.  Guidance may be directed at one or more of the discovery learning processes.  With adequate guidance discovery learning can be an effective learning approach in which mainly “intuitive” or “deep” conceptual knowledge can be acquired.

Based on sociocultural and social cognitive theory, computer support for collaborative learning has emerged as a new research and development subdiscipline of computer-mediated communication.

Learning in multimedia environments is hard because it requires learners to actively comprehend and integrate information across diverse sources and modalities.  Self-explanation is an effective learning strategy that helps learners develop deep understanding of complex phenomena and could be used to support learning from multimedia.

Clark, Ruth; and Mayer, Richard (2007). e-Learning and the Science of Instruction: Proven Guidelines for Consumers and Designers of Multimedia Learning (2nd ed.). Pfieffer: San Francisco.

Great book! It’s easy to read & follow along with. Most chapters in the book contain an outline, a preview of the content, a Design Dilemma & resolution, research based principles, graphic examples, and a short summary of what to look for when developing or selecting an e-Learning course.

Clark & Mayer provide several research based principles (described below) to apply to e-Learning (or to look for when choosing an e-Learning course). Not only does the book teach you the principles and how to apply them to e-Learning, it also provides some of the key research that supports each principle. The principles and research provided can help you make informed decisions about e-Learning courses and explain the decisions to others.

Summary of e-Learning Principles:

Multimedia Principle

Use words and (relevant) graphics rather than words alone.

Relevant graphics help engage the learner – studies show words and pictures increased learners’ scores on transfer tests. Consider this: Would you be able to put together a bike faster if the instructions you used contained text only or text & pictures?

Contiguity Principle

Place corresponding words and graphics near each other.

When possible, actually place words at the appropriate place within the graphic rather than as a text box below it.

Modality Principle

Present words as audio narration rather than onscreen text (if using audio).

When onscreen text can be presented as narration to complement a relevant graphic, the cognitive load is decreased because it is processed by two different modes (audio & visual).

Redundancy Principle

Presenting words in both text and audio narration can hurt learning.

Examples of when to make an exception to this principle:

• When no pictures are available/used
• When the learner would exert more effort to comprehend the spoken text rather than the printed (i.e., non- native speakers)

Coherence Principle

Adding interesting material can hurt learning.

Background sounds/music and extraneous pictures/words (interesting video clips, cute stories, trivia) do not increase learning. They distract the learner from relevant content & disrupt the learner from linking relevant info to prior knowledge.

Personalization Principle

Use conversational style and virtual coaches.

People tend to work hard to understand content when they feel they’re in a conversation with someone (on screen coaches can be an effective tool to do this).