Challenges and Ideas for Teaching Experts: Dual Process Reasoning Theory

Posted by Reni Gorman on Feb 4, 2011 4:54:00 AM

by Reni Gorman

I have been doing training for 20+ years now and the audience that gives me the most pain in terms of designing instruction is an audience of experts. Why? Well because experts “know everything”--even if they don’t. That means they are often trying to align new knowledge into categories they already understand. The response to the content you’re teaching is often “Oh, yeah, that is just like…” and they bring up things that they can relate to in their own expert fields. Instructional designers are often encouraged to teach people with examples that learners can relate to—but is this true with experts as well? If experts try to relate everything (or most things) to other things they know, what happens if they get it wrong? Then their brains have just encoded information in an incorrect way—which is not easy to change. It also makes me wonder, maybe this is true for all of us, not just experts. It is just that experts are vocal about it. We know as learning designers that misperceptions have to be uncovered and dealt with upfront before learning can happen in the “right way.” So what can we do?

Well, dual process reasoning theory indicates that two systems collide when it comes to reasoning of any kind. (Holyoak & Morrison, 2005) System 1 is our evolutionary system reflecting a collection of innate modules. Think of this as our instincts; they are so fast and automatic that they do not even register in our consciousness until after the reaction. Kind of like when people jump to very quick conclusions about what they know.

System 2 is our intellect, our cognition; it is slow as we think things over and reason about the problem at hand. When we get brand new information that we can’t relate to anything we already know, we actually have to think it through as we learn it; that when we use System 2. After we think it through we may well find something we can relate the new information to—but the point is, we have thought it through instead of jumping to conclusions.

Can we create conditions to which System 1 cannot react? Can we set learners up to have to reason and think things through? Maybe we should try. How? Perhaps by giving learners a problem with which they are not familiar with at all. Try it and let me know how you make out!


Holyoak, K.J. & Morrison, R.G. (2005). The Cambridge Handbook of Thinking and Reasoning. New York: Cambridge University Press.

Topics: Performance Improvement, Learning Theory, Cognition

The Science Behind Learning: Cognitive Tips and How Tos for Corporate Training (Part 6)

Posted by Reni Gorman on Jul 22, 2010 9:56:00 AM

by Reni Gorman

Tip #6: Provide many examples and practice exercises in which the same underlying concept is at work.

Cognitive Psychology: Provide examples to facilitate transfer and meaningful deliberate practice to promote understanding and increase memory performance.

Why (Justification):

Bransford et al. (2000) recommend that teachers provide “many examples in which the same concept is at work”. (p. 20) In a study by Gick and Holyoak (1980), they presented subjects with a story of a general who breaks up his army into several smaller groups to take different roads to avoid setting off mines. They still all arrived at the same time and were able to take over the capital. Then subjects were ask to solve a problem where the doctor had to radiate a tumor with enough force to destroy it but without harming the tissue around it. Subjects were told to use the story as the model to solve the problem and most subjects realized that the strategy is to break up the radiation source into smaller rays and focuses them only on the tumor so that the strongest radiation is only there.

“Hands-on experiments can be a powerful way to ground emergent knowledge...” (Bransford et al., 2000, p. 22) However there are different ways to practice. Consider doing math homework with the use of formulas and theorems. If you just followed the rules of the formula, you may have completed your homework in less time than if you truly went through the formula to fully and deeply understand all the ins and outs of the formula. Students who understand the reasons behind a formula can usually remember it much better and apply it much better in the long run. They may even be able to more easily learn or transfer to related mathematical (or other) information that shares the same abstract underlying core concepts, or knowledge elements. (Anderson, 2000) “In mathematics, experts are more likely than novices to first try to understand the problems, rather than simply attempt to plug numbers into formulas.” (Bransford et al., 2000, p. 41) Paige and Simon (1966) conducted a study where they presented subjects with an algebra problem. The expert group quickly realized that the problem was logically impossible.

In addition, practice will help your learners remember and recall faster. According to the power law of learning, your memory performance improves as a power function of practice. (Anderson, 2000) In a study by Pirolli and Anderson (1985) subjects practiced sentences and their speed to recall the sentence improved the more they practiced, before leveling off.

“Students’ abilities to acquire organized sets of facts and skills are actually enhanced when they are connected to meaningful problem-solving activities, and when students are helped to understand why, when and how those facts and skills are relevant.” (Bransford et al., 2000, p. 23)

Therefore, just as we draw a line between memorizing facts and learning with understanding, we must differentiate practice from deliberate practice. Practicing the mathematical formula by applying it to problem after problem is not the same as “deliberate practice” where you may apply the formula, and as you do, continuously check and recheck your own understanding. This means you use metacognitive strategies to insure a deep level of understanding. (Bransford et al., 2000) This is also consistent with the depth of processing theory that states that information processed at a deeper level of analysis improves memory for that information.

How (Application):

    1. Try to weave in an example to every section, definitely for the main points that communicate the core concepts, and, if possible, for the sub-concepts as well.
    2. Also follow-up at the end of each section with a practice exercise to let learners practice and apply what they have learned themselves. Design practice exercises where the same underlying concepts are at work. They shouldn’t be too simple, as that will not engage the learner, but they shouldn’t be too difficult as that would discourage the learner. For example, if you are teaching addition and show examples of adding two numbers, give students a practice exercise of adding three numbers. It is more challenging than the examples you used to teach but still manageable for the student to solve.


 Anderson, J. R. (2000). Cognitive Psychology and Its Implications: Fifth Edition. New York, N.Y.: Worth Publishers.

Bransford, J. D., Brown, A. L., & Cocking, R. R. (2000).
How People Learn: Brain, Mind, Experience, and School. Washington, D.C.: National Academy Press.

Gick, M. L., & Holyoak, K. J. (1980).
Analogical problem solving. Cognitive Psychology, 12, 306-355.

Paige, J. M., & Simon, H. A. (1966).
Discipline-specific Science Education and Educational Research: The Case of Physics. Paper prepared for the Committee on Developments in the Science of Learning for the Sciences of Science Learning: An Interdisciplinary Discussion.

Pirolli, P. L., & Anderson, J. R. (1985).
The role of practice in fact retrieval. Journal of Experimental Psychology; Learning, Memory and Cognition, 11, 136-153.

Topics: Series, Performance Improvement, Learning Theory, Cognition, Metacognition

The Science Behind Learning: Cognitive Tips and How Tos for Corporate Training (Part 4)

Posted by Reni Gorman on May 16, 2010 11:48:00 PM

by Reni Gorman
Tip #4: Find out what your learners know, or think they know.

Cognitive Psychology: Draw out pre-existing conceptions and, more importantly pre-existing misconceptions.

Why (Justification):

“Students come to the classroom with preconceptions about how the world works. If their initial understanding is not engaged, they may fail to grasp the new concepts and information that are taught, or they may learn them for purposes of a test but revert to their preconceptions outside the classroom.” (Bransford et al., 2000, p. 14-15) An excellent example comes from Vosniadou and Brewer (1989). Children think the earth is flat because of their pre-existing experiences with it such as walking on it and looking at it. When told the earth is round children picture a pancake instead of a sphere. They must be told it is spherical along with explanations as to why they have experienced it as flat in order for them to really learn and accept this new information.

New information learned can have an effect on how well you remember older information learned especially if the new information causes a conflict with the old and creates interference. (Anderson, 2000) The good news is that if we learn something new that contradicts what we thought in the past (retroactive interference), we will eventually forget the old information and remember the new information.

If learners have misconceptions that are not brought to light and corrected, they will never be able to effectively build on that knowledge in the future. Knowing what your learners know will also help you set the base-line and pace for the course. Many times instructors assume that their learners have a certain baseline knowledge, when in fact they do not… or they may think they know but their base line understanding is incorrect.

How (Application):

When designing your course, you must learn as much as you can about your learners. Are they beginners, intermediate, or advanced? What do they know, what do they need to know and what may they think they know or know incorrectly? If you can’t reach out to your learners before class then anticipate as much as you can… For example, you can think about the most common misconceptions about each of your main points. Try to come up with a question for each main point, the answer to which will clarify the misconception. For example: Do you think that pre-existing knowledge makes a difference in how people learn?


Anderson, J. R. (2000). Cognitive Psychology and Its Implications: Fifth Edition. New York, N.Y.: Worth Publishers.

Bransford, J. D., Brown, A. L., & Cocking, R. R. (2000).
How People Learn: Brain, Mind, Experience, and School. Washington, D.C.: National Academy Press.

Vosnaidou, S., & Brower, W. F. (1989).
The Concept of the Earth’s Shape: A study of Conceptual Change in Childhood. Unpublished paper. Center for the Study of Reading, University of Illinois, Champaign, Illinois.

Topics: Series, Performance Improvement, Learning Theory, Cognition, Metacognition, Retroactive Interference, Interference

The Science of Simulation: Mirror Neurons

Posted by Rich Mesch on May 11, 2010 3:58:00 AM

by Rich Mesch

I was first exposed to the concept of mirror neurons when I attended the NASAGA (North American Simulation and Gaming Association) Conference in Vancouver in 2007.  I was privileged to hear a talk by Dave Chalk. Chalk is an interesting guy on a number of levels, but most notably because he has had a highly successful career, including being a pilot, an entrepreneur, and a broadcasting personality, despite having been diagnosed at an early age of having a profound learning disorder.

One of the concepts Chalk discussed was the idea of mirror neurons. Research has demonstrated that in primates, our nervous systems react in certain ways when we engage in certain behaviors. The research further demonstrates that they react the same way when we observe the behavior or when we engage in a simulated version of the behavior. As noted by Rizzolatti & Craighero in Annual Review of Neuroscience, 27:

Each time an individual sees an action done by another individual, neurons that represent that action are activated in the motor cortex. This automatically induced, motor representation of the observed action corresponds to what is spontaneously generated during active action and whose outcome is known to the acting individual. Thus, the mirror system transforms visual information into knowledge 1

This is incredibly intriguing, because it seems to demonstrate a biological basis for the benefits of simulation. As simulation designers, we always make the argument that engaging in behaviors in simulation prepares us to engage in behaviors in the real world. But the argument has always been from a cognitive perspective—it helps us form the way we think. The mirror neuron research would suggest that it’s deeper than cognition. And for that matter, that simulation may not just be the next best thing to real world experience—it may be nearly equivalent.

Here are a few links to more info on mirror neurons: mirror

1 Reference: Rizzolatti, G. & Craighero, L. (2004). The mirror-neuron system. Annual Review of Neuroscience, 27, 169-192.

Topics: Performance Improvement, Cognition, Simulation

The Science Behind Learning: Cognitive Tips and How Tos for Corporate Training (Part 3)

Posted by Reni Gorman on Apr 11, 2010 12:36:00 PM

by Reni Gorman

Tip #3: Present main points first (the ones you wrote in Tip #2), followed by details, wrapped up by summaries of main points.

Cognitive Psychology: Presenting main points first primes learners and activates associated knowledge pathways. Take the Serial Position Curve into consideration by presenting main points up front, and as part of summaries at the end. Present material using the PQ4R study method (this is a great method, see below for details).

Why (Justification):

When I say: “It is very important to design your course material to facilitate learning with understanding.” Hopefully you deeply processed and understood the sentence and every associated concept you know has just been activated in your brain, this is referred to as associative priming. In addition, activation should spread to the surrounding concepts as well. This is called spreading activation. (Anderson, 2000) Now that you are primed, and have activated your relevant knowledge, you will be much faster at retrieving related knowledge to map new knowledge onto, bring up possible misconceptions, and prepare your mind to learn.

In a study by Meyer and Schvaneveldt (1971) subjects judged associated word pairs such as bread and butter, a lot faster than nurse and butter. These results indicate that when they saw the word bread, it associatively primed the word butter increasing recognition and judgment speed.

The PQ4R study method (Thomas & Robinson, 1972) was designed to help students learn and remember text from a chapter in a textbook. It encourages students to: Preview, Question, Read, Reflect, Recite, Review. To conduct the preview, Anderson (2000) recommends the following: “Read the section headings and summary statements to get a general sense of where the chapter is going and how much material will be devoted to each topic. Try to understand each summary statement and ask yourself whether this is something you knew or believed before reading the text.” (p. 5) It seems that by doing this we are priming ourselves not just for what is to come, but the organization of what is to come, called advanced organizers.

In a study by Frase (1975), subjects who received advanced organizers scored better on tests, then the group who did not receive advanced organizers.

Hierarchical encoding of serial-order information means that “subjects store long sequences hierarchically, with sub-sequences as units in larger sequences.” (Anderson, 2000, p. 132) Therefore, learners create groups and subgroups and organize them hierarchically as they learn to store and later to recall information from memory.

Consider the study conducted by Klahr, Chase and Lovelace (1983) based on subjects speed at recalling certain letters of the alphabet. In the alphabet song, pauses indicate the end of a group and the start of another. [(ABCD, EFG) (HIJK, LMNOP)] [(QRS, TUV) (WX, YZ)] A subject may be given the letter “K” and asked to generate the next letter. Generation times were faster at the beginning of a group and progressively slower toward the end of a group. This represents the front anchoring effect that subjects access the beginning of each group first, then search for the target from there.

“Propositions information can be represented in networks that display the relations among concepts.” (Anderson, 2000, p. 151) Propositional networks are also referred to as a semantic network: of or related to meaning. Presenting all the main points upfront will allow the main points to be the front anchors for the details to come. This will lay the foundation for the conceptual framework (you created in step #1) to be the main organizational network for the information.

How (Application):

1. Create a good clear title for each section of your course that will help get your learners thinking about the information you are about to present. That means using titles that clearly communicate the topic you are about the cover.

A bad example is: Interesting New Findings.

A much better title would be: Interesting and New Findings in How People Learn.

2.  Begin creating an advanced organizer by listing your outline with your nice clear titles and the corresponding main points. Remember that each section or chunk has a main point. There are main points for concepts as well as sub-concepts. Tip: if you notice you have too many main points for a section… try to find a logical break and break it up! (Remember +or-7 from tip #2) The main points are very important. If the student never gets past your advanced organizer and only studies the main points what is the most important information that you want them to walk away knowing?

3.  Since learners tend to remember information presented in the beginning and, even more so, at the end, it is a good idea to present main points in the beginning and at the end. What you have just created can also be used as your summary. (Later we will add questions to the advanced organizer... making it slightly different from your summary.)


Anderson, J. R. (2000). Cognitive Psychology and Its Implications: Fifth Edition. New York, N.Y.: Worth Publishers.

Frase, L. T., (1975). Prose processing. In G. H. Bower (Ed.), The psychology of learning and motivation (Vol. 9.) New York: Academic Press.

Klahr, D., Chase, W. Go, & Lovelace, E. A. (1983). Structure and process in alphabetic retrieval. Journal of Experimental Psychology: Learning, Memory, and Cognition, 9, 462-477.

Meyer, D. E., & Schvaneveldt, R. W. (1971). Facilitation in recognizing pairs of words: Evidence of a dependence between retrieval operations. Journal of Experimental Psychology, 90, 227-234.

Thomas, E. L., & Robinson, H. A., (1972). Improving reading in every class: A sourcebook for teachers. Boston: Allyn & Bacon.

Topics: Series, Performance Improvement, Learning Theory, Cognition

The Science Behind Learning: Cognitive Tips and How Tos for Corporate Training (Part 2)

Posted by Reni Gorman on Mar 21, 2010 8:38:00 AM

by Reni Gorman

Tip #2: Use the conceptual framework (you created in tip #1) to organize course material into hierarchical groups, subgroups and chunks of 7 (plus or minus 2).

Cognitive Psychology: Prepare information for encoding into the propositional network by attempting to organize and chunk material into meaningful patterns of information based on a conceptual framework and limited to groups or units of 7 (plus or minus 2) to account for the standard capacity of verbal working memory.

Why (Justification):

“The fact that ‘expert’ knowledge is organized around important ideas or concepts suggests that curricula should also be organized in ways that lead to conceptual understanding.” (Bransford et al., 2000, p. 42)

Even though experts have vast knowledge basis in their domain, their knowledge is organized around a set of core concepts that guide them. These core concepts “emerge” as a higher level pattern among all the data for their domain referred to as meaningful patterns of information that arose over years of practice. (Bransford et al., 2000) “A key finding in the learning and transfer literature is that organizing information into a conceptual framework allows for greater “transfer”; that is, it allows the student to apply what was learned in new situations and to learn related information more quickly.” (Bransford et al., 2000, p. 18)

In a study by DeGroot (1965) expert chess players were compared to novice players by asking them to verbalize their thinking as they played. The experts were more likely to recognize meaningful chess configurations and strategies that allowed them to consider sets of moves that were superior to novices. “Chess masters are able to chunk together several chess pieces in a configuration that is governed by some strategic component of the game. Lacking a hierarchical, highly organized structure for the domain, novices cannot use this chunking strategy.” (p. 33)

“The superior recall ability of experts… has been explained in terms of how they ‘chunk’ various elements of a configuration that are related by an underlying function or strategy. (Bransford et al., 2000, p. 32) According to Anderson (2000) our minds seem to break information down into the smallest unit of knowledge that can stand as a separate assertion for storage, into a proposition.

Understandably, studies have shown that propositional retention is also better in and of itself when meaning is applied. In an experiment, Anderson (2000) himself participated in; subjects were asked to remember pairs of meaningless acronyms such as DAX-GIB. Meaningless memorization resulted in Anderson scoring the worst in his class. Anderson now suggests tying meaning to the acronyms would have improved his ability to recall them.

“Propositions information can be represented in networks that display the relations among concepts.” (Anderson, 2000, p. 151) Propositional networks are also referred to as a semantic network: of or related to meaning.

If you ask people to listen to a list of 20 unrelated words and then ask them to immediately recall them in any order. Then, graph the results with position of the word in the original list on the X (horizontal) axis and the proportion of people who recall that word on the Y (vertical) axis, and you will get a U-shaped curve. This is called a Serial Position Curve and it reveals that the words in the beginning and end of the list are what most people remember, with, generally more words remember at the end. Usually people will remember 7 plus or minus 2. This is considered a standard measurement of the capacity of verbal working memory. (Anderson, 2000) The interesting twist as it relates to the organization of information is that if you give subject-related words, the U-shaped curve still returns, but people will remember more words because they will remember groups of related words.

How (Application):

    • Flesh out the details of your high level outline that you based on the conceptual framework. The first level categorization should remain equal to your conceptual framework and expand the hierarchy from there into a detailed outline with logical related groupings and sub-groupings as needed by taking each concept and creating subgroups of chunks that explain that concepts (sub-concepts). (Main topics and sub-topics.) Make sure you have enough information for each core concept to explain its meaning.
    • In addition to the main points you wrote for your core concepts, write main points for each sub-concept (sub-topic) as well.
    • Take a look at your hierarchical outline when you are done to see if it is chunked optimally. Try to keep each group limited to about 7 (plus or minus 2) if possible.

Bransford, J. D., Brown, A. L., & Cocking, R. R. (2000). How People Learn: Brain, Mind, Experience, and School. Washington, D.C.: National Academy Press.

Anderson, J. R. (2000). Cognitive Psychology and Its Implications: Fifth Edition. New York, N.Y.: Worth Publishers.

Topics: Series, Performance Improvement, Learning Theory, Cognition

The Science Behind Learning: Cognitive Tips and How Tos for Corporate Training

Posted by Reni Gorman on Feb 28, 2010 11:01:00 AM

by Reni Gorman

(Links to other articles in this series: 1 2 3 4 5 6)

Tip #1: Highlight the underlying core concepts. Explain what each concept is and why it is important (the meaning behind it).

Cognitive learning theory focuses on learning with understanding (as opposed to memorizing fact) by teaching the underlying concepts and meanings--and thereby increasing the depth of processing.

Learning with understanding means we understand the underlying core concepts, the meaning behind the facts. Not just knowing the “what” but also understanding the “why.” Once we have a deep understanding of what we are learning, we can relate it to or transfer it to something else. (Bransford et al., 2000) Learning with understanding is critical because: “…‘usable knowledge’ is not the same as a mere list of disconnected facts. Experts’ knowledge is connected and organized around important concepts; it is ‘conditionalized’ to specify the contexts in which it is applicable; it supports understanding and transfer (to other contexts) rather than only the ability to remember.” (p. 9)

Learning with understanding necessitates paying attention to the meaning. The depth of processing theory states that information processed at a deeper level of analysis improves memory for that information. This contradicts earlier ideas that meaningless memorization and rehearsal improves memory. (Anderson, 2000)

Anderson (2000) explains that we may remember details initially, but although we may quickly forget the details, we will remember the meaning a lot longer. Meaning-based representations are best encoded and, therefore, best remembered. Therefore insuring students understand the core concepts and meanings is the only way to successfully teach them. In a study by Davidson (1994) on how well people remember stories and what parts they remember most, even though short term people remembered irrelevant and interruptive atypical actions, long term, their memories of the basic story was what remained.

How (Application):

  1. Extract and list all core concepts. Review what you plan to teach and extract the core concepts. If you find yourself getting entangled in the details, ask yourself why each detail is important. What is the underlying reason that makes that detail important? Trace back all details you think are important until you find the set of core concept underneath.
  2. Prepare a brief explanation for the “big picture” of how all these core concepts work together in a conceptual framework. This explanation will be your course overview. The conceptual framework will be your high level outline.
  3. Prepare main points for each core concept that explain “what” the core concept is and “why” it is important. Keep main points brief – limit to one paragraph.



Anderson, J. R. (2000). Cognitive Psychology and Its Implications: Fifth Edition. New York, N.Y.: Worth Publishers.

Bransford, J. D., Brown, A. L., & Cocking, R. R. (2000). How People Learn: Brain, Mind, Experience, and School. Washington, D.C.: National Academy Press.

Davidson, D. (1994). Recognition and Recall of Irrelevant and Interruptive Atypical Actions in Script-Based Stories. Journal of Memory and Language, 33, 757-775.

Topics: Series, Performance Improvement, Learning Theory, Organizational Learning, Cognition