A Primer on Educational Psychology

Educational psychology is the branch of psychology focused on the development of effective teaching techniques and the assessment of learners' aptitudes and progress. A look at adult education wouldn't be complete without a view of the theories shaping the way we learn and the way we teach.

While we may be aware that various theories exist, few technology professionals, and even fewer consumers, are aware of the differences between the theories and how they affect the way we learn.

This glimpse into the different theories introduces the principle names, theories, and implications of each approach. Full explanations follow the summaries. With this knowledge, we can identify which theory is appropriate for our needs and which we should look to when evaluating instructional programs.

Behavioral psychology states that behavior can change as a result of extrinsic motivators such as incentives, rewards, and punishments. Behaviorists advocate influencing behavior through the systematic adjustments of stimulus-response reinforcements.

Most research in the field is based on B. F. Skinner's work in the early 1930s. He concluded that by controlling the environment of mice in a lab he could 'train' them to behave consistently. From this research came theories designed to train humans.

Behavioral instruction hinges on the use of observable, measurable, and controllable objectives. A teacher (or organization) determines what objectives the learner should achieve. These objectives are met when the learner responds in a certain way, based on controlled stimuli.

Cognitive psychology holds that information is more likely to be acquired, retained, and retrieved for future use if it is learner-constructed, relevant, and built upon prior knowledge.

Cognitivists are concerned with the study of individuals' perceptual processes, problem-solving abilities, and reasoning abilities. Cognitive programs are often organized in chunks, and have built-in or learner-generated memory devices to help learners retain and use the information in the future.

Cognitive models give learners control by introducing conceptual frameworks, and by relying on both experiential and discovery learning.

Constructivist psychology tells us that learners do not simply absorb and store information. We make tentative interpretations of experiences and go on to elaborate and test what we determine. Our mental structures are formed, elaborated on, and tested until we establish a satisfactory structure.

Constructivists report that people are active and don't only respond to stimuli as behaviorists suggest. We engage, grapple, and seek to make sense.

Humanist psychology focuses on individual growth and development. It stems from the theory that learning occurs primarily through reflection on personal experience, and as a result of intrinsic motivation. Humanists uphold the andragogic belief that significant learning leads to insights and understanding of ourselves and others.

Humanist instruction involves learners in all stages, including planning to ensure that we understand the relevance of topics. These programs rely on self-analysis, team building, learner evaluation, and peer learning using various tools and approaches.

For instructional design to work, methods must match and support goals. Each approach offers advantages and disadvantages. Some programs successfully integrate aspects of different models. Instruction needs to make use of research and be grounded in sound educational theory. If programs are created without an instructional model or ignore what is known about educational theory, we leave learning to chance.

Educational psychology is steeped in controversy. Though each theory has elaborate research behind it, most organized instruction has been based on one model: Behaviorism.

To take advantage of the other very useful approaches, we must overcome strong biases and beliefs. If we accept that the old ways of working are no longer complete answers in the information age, we should amplify the number of approaches we use to learn. We must evolve.

The following continuum charts how behavioral, neo-behavioral, cognitive, constructivist, and humanist theories view learners.

In short, behaviorists view learners as mechanical responders; cognitivists understand us as cerebral thinkers; and humanists work with us as changing individuals. While instruction nears the right end of the continuum, we benefit from the andragogical principles that rose out of humanism.

The chart lists the prominent researchers in each area and some defining terms associated with each theory.

Theory

Behaviorism

Neo-behaviorism

Cognitivism

Constructivism

Humanism

Theorists

Skinner
Thorndike
Watson

Hebb
Hull
Bandura

Piaget
Gagné
Bruner
Ausubel

Piaget
Papert

Rogers
Maslow
Knowles
Vella

Role of instructor

Behavior modifier

Source, model, and prompter

Prompter, disseminato r of information

Dialogue facilitator, prompter, challenger

Facilitator, coach, listener, partner

Level of structure

High level

High level

Moderate level

Low level

Varying level depending on learner needs

Processing required

Low conceptual levels

Low conceptual levels

Moderate conceptual levels

High conceptual levels

High conceptual levels

Behaviorism

A fable.
A scientist put a laboratory mouse in a box with six rooms. The mouse soon learned the cheese was in room three. Therefore, it always ran directly to room three upon being put in the box. One day the scientist put the cheese in room five. Upon entering the box, the mouse ran directly to room three. "Hmmm...no cheese." The mouse looked around. Tried room four. No cheese. Tried room five. "Ah-ha! Cheese!"

What would a human being have done? He or she would have continued to return to room three again and again and again -- expecting and then demanding cheese. "Where is my cheese!? This is where it has always been. It's supposed to be here! I want it NOW -- GIVE ME MY CHEESE!!! I have rights you know. Blah, blah, blah." And so the complaining was heard through the night in the now-dark laboratory. Meanwhile, the cheese remained in room five.

So what is the difference between mice and people? Mice get their cheese.

- Author unknown

The fable reflects a society dependent upon rewards and external praise as viable methods to alter behavior. Even though our organizations require more advanced information processing skills, behaviorism is so pervasive that most of us don't question its validity or use in our lives. Because of this bond, it would be naive to assert we should stop using behavioral instruction altogether.

Behaviorism suggests that (1) teachers ensure learners attain defined learning objectives, usually specified as observable, behavioral outcomes. (2) Learning activities are sequenced so that learners move through a series of carefully designed, progressively complex operations. (3) Educational activities are evaluated as successful when the defined learning objectives are achieved.

Many educators don't realize B. F. Skinner said shortly before his death in 1990, "The worst mistake my generation has made is to treat people as if they were rats."

The fact that Skinner, himself, recanted his basic premise has had little effect on those who persist in thinking of minds as vessels to be filled with disconnected facts. Behaviorism still dominates formal education despite mounting evidence that it leads to long-term problems and few short-term gains.

When has behaviorism not dominated our lives? Most of us were raised in families offering tokens for completing tasks. We grew accustomed to external rewards and altered our behavior to acquire more.

Schools carried this approach forward by offering grades, stars, and attention based on the way we behaved. Shrewd students noticed that well-behaved children were treated better than those who misbehaved. As adults, companies pay and provide bonuses to those who follow the rules.

Entrenched in behaviorism, you may even be wondering, "What's the problem?" Many of us only change our behavior, challenge what we know or think, and try something new when a 'carrot' dangles before our eyes.

If we didn't compete in the market, would businesses be re-engineering their tried-and-true work practices? Would we be wanting to learn about learning if we didn't know it would bring us some financial gain?

Most of us don't ask ourselves why we do things and what we want to do differently in the future. We lock into routine tasks and low-level processing.

This cycle continues because we learned to rely on drill and practice, the most common behavioral method for teaching new facts and responses. Do something enough and it stays with you for a lifetime. Control what we practice and teachers control what we learn.

Behavioral instruction offers little opportunity or context to develop independent thought. Behaviorists haven't proven that condition and response techniques transfer to other situations or materials.

Adult education often capitalizes on these despite the facts. Authors, such as Robert Mager, advocate behavioral objectives that break tasks into small, measurable pieces. His books profoundly influence the instructional technology field despite the fact they can instruct educators to measure things too narrowly. They teach novice instructional designers a limiting approach to development.

It's not that Mager encourages anyone to do anything wrong. Without the requisite expertise in instructional design, however, readers may not know when these approaches shouldn't be used. They may not have a thorough enough understanding of their changing business needs to know when this approach will end up inhibiting learning. As a result they may use this methodology in all of their courses.

Behavioral objectives, sometimes referred to as performance objectives, learning objectives, or terminal objectives, inform learners know what will be measured. This type of objective reflects the belief that at a pre-determined, externally controlled time, a learner will know or be able to do something new. The time and place are vital because the test of a behavioral objective lies in its ability to be measured. Often you need to, "Define two of this" or "Name twelve of that."

Measuring is not the problem. After all, who hasn't heard the phrase, "What is measured gets done"? Limiting the working knowledge of a subject to a finite number of tasks or facts, however, seems misguided in many cases.

To give the illusion of testing something useful, objectives may state something such as, "The learner will be able to identify the correct actions to take when such and such happens." This approach is only useful when learners continue to do those specific actions.

Using behavioral objectives allows training departments to report they've succeeded in educating. "We did it!" they may declare. "Your employee learned. We're useful." Instead, the department has only demonstrated that when they provided a stimulus, the employee responded in a programmed way.

The behavioral approach to instructional design is teacher-centered. An instructor who makes unilateral decisions, regardless of their merits, is in effect saying that the class doesn't belong to the learners. People don't usually cheer when things are done to them.

Authentic learning and lasting behavioral change comes as a result of adapting to our environment and experiencing new things. To evolve, we must be flexible and adaptable when needed.

Testing from behavioral objectives proves just as problematic. Drill and practice programs are only moderately effective at increasing test scores and reinforce educational practices with little bearing on the modern workplace.

Employers don't need performers who can pass tests. They need people who get the job done. It would be more profitable to measure employee's ability to adapt and evolve as things change.

We need learners who have acquired a very different skill set than those required to solve multiple choice problems under the pressure of a stopwatch. Education programs should expose us to new models, help us see things in new ways, and build links so we know where to find additional information when we needed it.

Does this imply there is no place in the field of adult education for behaviorism? Not quite. There are some tasks that lend themselves to drill and practice, as well as condition and response.

Stephen Brookfield, a leading adult education theorist, wrote in Facilitating Adult Learning:

[Behaviorism] is seen most prominently in contexts where the objectives to be attained are unambiguous, where their attainment can be judged according to commonly agreed upon criteria of successful performance, and where a clear imbalance exists between teachers' and learners' areas of expertise. Examples might be learning to give an injection, learning a computer program, learning accountancy procedures, learning to swim, or learning to operate a sophisticated machine. Although no learning is without elements of reflection or emotive dimensions, these examples are all located primarily in the domain of task-oriented, instrumental learning, and it is this domain that fits most easily with the behaviorist approach.

There are few examples in business today, however, where objectives are unambiguous and success can be commonly agreed upon by the learner, the teacher, the organization, and the content. In the information age, rules change daily. If we face variation, we may need a different approach.

Cognitivism

Teaching methods based on research in cognitive science are the educational equivalents of the polio vaccine and penicillin. Yet, few outside the educational research community are aware of these breakthroughs or understand the research that makes them possible.

- John T. Bruer, The Mind's Journey from Novice to Expert

Cognitive psychology is the study of how our minds work, how we think, how we remember, and ultimately, how we learn. There is more to education than cognition, but studying what goes on in the brain can drive progress, help us make decisions, and improve educational programs.

Our innate cognitive architecture remains the same no matter what subject we try to master. Learning about that structure can improve the way we learn. The implications are staggering for learning technologies based on how the brain deals with ideas.

The study began in 1965 when psychologists, linguists, and computer scientists met at the Massachusetts Institute of Technology for a symposium on information science. The three-day meeting started the cognitive revolution in psychology, a revolution replacing behaviorist psychology with a 'science of the mind.' The revolutionaries maintained that human minds and computers are similar enough that a single theory -- the theory of computation -- could guide research in both psychology and computer science.

"The basic point of view inhabiting our work," wrote two of the participants, "has been that the programmed computer and human problem-solver are both species belonging to the same genus IP." Both are species of the genus information-processors. Both are devices that process symbols.

Cognitivists describe learning as the building of an internal schema (knowledge structure) or the modification and extension of existing schemata. Our schemes consistently evolve with use. In time, certain actions require little or no thought. The actions become automatic.

Education doesn't always distinguish between what we should memorize and what we need to comprehend. Programs don't address the need for different learning strategies.

Cognitivists view learning as a developmental process. We test our notions about the world against new information before we make it our own. Our prior experience, knowledge, and expectations are key to learning.

We build bridges between new information and what we already know. Educational programs help us do this by offering meaningful organization and contexts to store and retrieve new information. As a result, we effectively build on what we know.

Children follow this model intuitively when they learn to walk. First they roll over. Then they sit up; next pull up. They try to balance, using their arms, feet, and trunk. Once they master balance, they let go, then take one step, and fall. Not liking the feeling of falling, they try to step again and put the other foot out to balance. After two steps, they try three. Soon they can run.

In the cognitive model, learning is the process for novices to become experts. They differ in understanding, storing, recalling, and manipulating knowledge as they solve problems. Novices and experts differ in their problem-solving behavior, not just in the knowledge they possess.

Novices hold naive theories about how things work. For example, computer novices may fear they will break the machine. Children often think teachers don't go to the bathroom! Highly educated adults used to think the moon was made of cheese. These theories don't reflect the novices' intelligence, but rather their lack of necessary information and experience.

These theories so influence how we interpret instruction that even directions can be ineffective when we're new to a subject. For instance, programs are often designed with input from subject matter experts (SME) who offer how they currently perform tasks or solve problems.

Wanting to share their wisdom, experts can leave out the vital chunks and situations that led them to that expert level. They identify the behaviors that learners should possess and envision reinforcing activities for the novices. A better way to develop curricula based on cognitive research would be to build from, address, and then correct these naive theories so that learners can overcome their naive beliefs.

Novices see individual parts. Experts, in contrast, see chunks of relevant information. The experts' more effective, more information-rich chunks allow them to see a larger scope and choose more appropriate areas to turn their attention. Because of this chunking, experts process more and better information in the same amount of time.

Novices and experts learn by altering long-term memory structures. Cognitive psychology suggests that if education helps novices structure their new information, they will be able to use the structures throughout the life of that knowledge. Unlike behavioral 'condition and response' techniques, these mental structures can even adapt and grow.

We modify these structures when we come across problems that our current rules (or scripts) can't solve. We recognize the information we need and process it to build more accurate or up-to-date rules.

Some learners modify their structures automatically while others need some help. Learners who can't modify on their own need direct instruction about the relevant facts and about the strategies to use. With the right approach, we can progress from relative naiveté, through a series of partial understandings, to eventual subject mastery by understanding facts, strategies, and when to use each.

In the early 1980s, researchers noticed that some people learn new subjects and solved new problems more expertly than most regardless of how much knowledge they possess on the topic. Called intelligent novices, these people seem to control and monitor their thought processes. This suggests that there is more to expert performance than topic-specific knowledge and skills.

Cognitive psychologists called this new element of expert performance metacognition. Metacognition defines the ability to think about thinking, to be consciously aware of ourselves as problem solvers, and to monitor and control our mental processing. When we think about how we think, we can reflect on our learning styles, what methods and techniques work best for us, and how we've successfully learned in the past.

There are several keys to metacognition. They include (1) our awareness of the difference between understanding and memorizing material and which mental strategies to use at different times; (2) our ability to recognize difficult subjects, where to start, and how much time to spend on them; and (3) our aptness to take problems and examples from the materials, order them, and then try to solve them. Others are (4) knowing when we don't understand so we can seek help from an expert; and (5) knowing when the expert's explanation solves our immediate learning obstacle.

Metacognitive skills all involve problem solving awareness and control. We can learn metacognitive skills by working through one topic, but can then apply them when trying to learn a second topic.

This research tells us that metacognition is probably the most important lifelong learning skill. Incorporating these skills into educational programs (and our day-to-day work habits) is vital to our growth. While topic-specific knowledge and skills are essential to expertise, programs must also be metacognitively aware, informed, and explicit.

We need to create and maintain educational environments where learners smoothly journey from novice to expert and learn to become intelligent novices. To do that, we must rethink (or at least re-evaluate) education policy, classroom practices, standards, and teacher training.

Admittedly, we don't know everything about how the mind works, how people best learn, or how to design the best training programs. On the other hand, cognitive science shows us strategies we can apply to improve our programs and our futures.

Constructivism

Leading technologies are often ill-defined and under constant construction. Because the techniques needed to stay ahead in the information age will, most likely, not change as quickly as the technologies that sustain us, the way we learn technology must change.

Tom Peters writes that, "We must abandon our old beliefs about learning to just keep up with change." We must (1) collaborate with one another, (2) draw wisdom from data to be able to (3) articulate what we believe, why we believe it, and (4) be willing to gather new information when it is time to change what we believe.

Constructivist approaches work well when we operate with constantly changing information. If education is to become the soul of the new information systems industry, we must learn better ways to deal with the unstructured, the undefined, and the unknown.

Be warned, however. Constructivist approaches don't lend themselves to computer-based training or evaluation where structure is a requisite part of design.

Constructivism is presented here to offer ideas about what to do when facing uncertainty and how to use different approaches in different times. Constructivism works best when technology is new, very complex, and there isn't time or structures set up to build media solutions. It's arduous to test what no one knows.

The constructivist model comes from several contemporary cognitive theorists who began questioning the benefit of cognitive instruction for unknown information and knowledge. They adopted a different way to look at learning and understanding knowledge. Constructivists assert that knowledge is what we make of it. Without minds there would be no knowledge -- it's a function of how we create meaning from our experiences.

Because of the 'Thriving on Chaos' mentality of the late 1980s and early 1990s, constructivism received increasing attention in the field of training and instructional design. Constructivists emphasize the flexible use of pre-existing knowledge rather than the recall of prepackaged schemes.

As the definitions of words change meaning based on how we understand the context, so too will ideas continually evolve with new use. For this reason, it is critical that constructivist learning (much like cognitive learning) occurs in realistic settings and that the selected learning tasks be relevant to the learner's life experiences. To be successful, meaningful, and lasting, learning must involve actions, understanding concepts, and working knowledge of culture.

For example, a typical constructivist goal wouldn't be to teach novice Local Area Network (LAN) Administrators unique facts about LAN topologies, but to offer them an opportunity to use these facts as they would on the job. By recreating their reality, they learn.

Cognitive learning environments can effectively transfer basic skills and help learners attain advanced knowledge if the information is well defined and available. Much of what needs to be learned today involves advanced knowledge in ill-structured domains. LANs, for instance, vary wildly. Needs change daily.

Constructivists encourage learners to construct their own understanding, based on their reality, and then validate their new perspectives though social negotiations. We must talk with others about what we've learned to find out if we're missing something.

Dialogue helps us clarify the subtleties of our thoughts. As we uncover naive theories, we begin to see our activities in a new light, guiding us toward conceptual re-framing and learning.

Content can't be pre-specified. Computer-based training, for instance, wouldn't work as we know it today. Instead, technology indexes information and cases, and is accessed when needed from the learning team.

For example, constructivism has been widely used in the education of doctors, architects, lawyers, and artisans. Strategies can involve (1) cognitive apprenticeships where experts model and coach a learner toward expert performance; (2) presenting multiple perspectives and using collaborative learning to develop and share alternative views; (3) social negotiation so debate and discussion can take place; (4) using examples as realistic illustrations; and (5) reflective awareness.

This theory proves challenging, if not impossible, when done individually. This is a model to consider as more people within organizations need to overcome the unknown and consortiums assemble individuals from different organizations facing similar challenges.

Humanism

The information age requires a self-educating workforce capable of peak performance. Our challenge is to stimulate new thinking. Humanism, the theory of individual growth and development, offers us techniques to think in new, creative ways. It is the predominant paradigm of practice within the literature of North American adult and continuing education.

Drawn from the work of humanistic psychologists and the study of andragogy, this theory encompasses teaching and learning assumptions that profoundly influence the field. Humanist activities facilitate collaborative learning with strong emphasis on learners and instructors negotiating objectives, methods, and evaluative criteria.

Humanism begins with the theory that learning occurs primarily by reflecting on personal experience. The role of instruction is not to put anything in the mind or repertoire of the learner, but to extract lessons from the learner's insights and experience -- like drawing water from a well.

We can gain new insights into previous experiences if we have the opportunity and tools to do so. The role of the instructor is to help learners supplement experiences with new opportunities.

Instruction should ask stimulating questions that help the learner make new connections and uncover what we already know. Real learning is what we discover for ourselves, not something we're told or led to by someone else. This technique took root in the Socratic methods and in Plato's belief that all knowledge is inherent. Later, it developed under Carl Rogers' work with self-directed therapies.

Additional techniques include (1) inductive discussion, (2) individual or group projects, (3) debriefing sessions, (4) action planning, (5) self-assessment, (6) visualization, and (7) guided reflection.

Humanism stresses that we must feel comfortable with the learning environment and the flow of topics. The way we feel about a program influences our commitment to it. If we feel secure, respected, esteemed, and empowered, we're likely to make a strong effort. If we feel threatened, anxious, hostile, or demeaned, we're likely to resist.

Humanism engages learners in intense and personal ways. Programs begin by helping learners identify individual learner-centered objectives drawn from experience. These objectives don't tell us what we should know as defined by someone else. We're responsible for our learning.

Instruction involves learners in the planning stages to ensure topics are relevant and appropriate. Programs rely on self-analysis, team building, and peer learning using various tools and approaches.

Significant learning leads to insights and understanding of ourselves and others. Becoming a better human being is considered a valid learning goal. Rogers believed that anything that can be taught to another person is relatively inconsequential. Rather, desire to learn must come from intrinsic motivation, created by the need for personal growth and fulfillment.

Humanism has little structure, can be used with high conceptual levels, employs self-evaluation, and respects individual differences.

As we move along the behavioral - cognitive - humanist continuum, the focus shifts from teaching to learning. The strategies move from passive transfer of facts and routines to active application of ideas and problems.

While cognitivists, constructivists, and humanists each view learners as active participants, constructivists and humanists regard learners as more than active processors. They believe that learners must elaborate and interpret information.

As we acquire more experience, we progress along a low-to-high knowledge continuum from (1) being able to recognize and apply standard rules, facts and operations (knowing what), to (2) extrapolating from these general rules where problems may occur (knowing how), to (3) developing and testing new understanding and actions when familiar categories and ways of thinking fail (reflection-in-action).

Behaviorism can effectively condition learners to do things in certain ways and familiarize us with the contents of a profession (recognize/know what). Cognitivism proves useful in teaching problem-solving tactics where defined facts and rules apply to unfamiliar situations (extrapolate/know how). Humanism is especially suited to help us deal with whatever problems come our way (formulate/reflection-in-action).

The appropriate instructional approach should be based on the level of cognitive processing required. Tasks requiring low-level processing (such as associations, discriminations, and rote memorization) are most often accomplished with behaviorism. Cognitive strategies fit with subjects that require more advanced processing, classifications, identifying rules, procedural exceptions, and problem solving. Issues that demand high-levels processing are frequently learned best with humanist strategies.

The critical question is not, "Which is the best theory?" but rather, "Which theory is most effective in fostering mastery of specific tasks by individual learners?" What might be most effective when we're novice learners, meeting complex bodies of information for the first time, may not be effective, efficient, or stimulating for learners who are more familiar with the content.

While we can mix strategies, a renewed focus on humanist (and andragogic) practices help us function well when optimal conditions don't exist, when situations are unpredictable, and when we need to think on our feet. Our rapidly growing, changing, organic environments demand solutions based on inventiveness, improvisation, dialogue, and social negotiation.


[1] Discussion Paper Series. Instructional principles for adult learning. Bedford, MA: National Education Training Group - Spectrum.

[2] Neo-behaviorism is defined and explained in Appendix B.

[3] Adapted from S. S. Dubin and M. Okun (1973). Implications of learning theories for adult instruction. Adult Education, 24 (1). p. 8.

[4] Stephen D. Brookfield (1989). Facilitating adult learning. In Sharan B. Merriam and P. M. Cunningham (Eds.), Handbook of adult and continuing education. San Francisco: Jossey-Bass.

[5] David Thornburg (1994, September). Killing the fatted calf: Skinner recanted behaviorism. Why can't education? Electronic Learning, p. 24.

[6] Alfie Kohn (1993). Punished by rewards: The trouble with gold stars, incentive plans, A's, praise, and other bribes. Boston: Houghton Mifflin.

[7] Thornburg (1994).

[8] Brookfield (1989).

[9] John T. Bruer (1993, Summer). The mind's journey from novice to expert. American Educator, p. 7.

[10] Howard Gardner (1985). The mind's new science: History of the cognitive revolution. New York: Basic Books.

[11] Allen Newell and Herbert Simon (1972). Human problem solving. Englewood Cliffs, NJ: Prentice-Hall.

[12] Bruer (1993).

[13] Rob Forshay (1991, May). Sharpen up your schemata. Data Training, p. 20.

[14] Bruer (1993).

[15] An expert is defined as someone highly skilled or knowledgeable in a given topic.

[16] Newell and Simon (1972).

[17] A. L. Brown, J. D. Bransford, R. A. Ferrara, and J. C. Camione (1983). Learning, remembering, and understanding. In P. H. Mussen (Ed.), Handbook of child psychology, vol. 3, Cognitive development. New York: Wiley.

[18] Tom Peters (1994). The Tom Peters seminar: Crazy times call for crazy organizations. New York: Vintage Books.

[19] Tom Peters (1987). Thriving on chaos: Handbook for a managment revolution. New York: Harper and Row.

[20] R. J. Spiro, P. J. Feltovich, M. J. Jacobson, and R. I. Coulson (1991). Cognitive flexibility, constructivism, and hypertext: Random access instruction for advanced knowledge acquisition in ill-structured domains. Educational Technology, 31 (9), pp. 24-33.

[21] J. S. Brown, A. Collins, and P. Duguid (1989). Situated cognition and the culture of learning. Educational Research, 18 (1), pp. 32-42.

[22] D. H. Jonassen (1991). Evaluating constructivist learning. Educational Technology, 31 (9), pp. 28-33.

[23] Peggy A. Ertmer and Timothy J. Newby (1993). Behaviorism, cognitivism, constructivism: Comparing critical features from an instructional design perspective. Performance Improvement Quarterly, 6 (4), pp. 50-72.

[24] Brookfield (1989). p. 203.

[25] Tom Kramlinger and Tom Huberty (1990, December). Behaviorism versus humanism. Training and Development Journal, pp. 41-45.

[26] Richard Brostrom (1979). Training styles inventory. In J. E. Jones and J. W. Pfeiffer (Eds.). 1979 Annual handbook for group facilitators. San Diego, CA: Pfeiffer.

[27] T. M. Duffy and D. Jonassen (1993, May). Constructivism: New implications for instructional technology? Educational Technology, 31 (5), pp. 13-17.

[28] Donald A. Schön (1987). Educating the reflective practitioner. San Francisco: Jossey-Bass.

[29] Ertmer and Newby (1993).