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March 14, 2011

eCoaching Tip 86 Four Strategies for Supporting Learners on Their Expertise Journey

Practice, Practice, Practice

You have probably all heard the classic tale about the tourist who asked a New Yorker, ”How do I get to Carnegie Hall?”  And the response — in some versions of the story —by Arthur Rubenstein was, “Practice, practice, practice.” 
In our collective journeys from novices to experts, practice is also the answer.  But just how do we provide for the practice of complex cognitive experiences in our courses? This is a demanding question, but one that I think is worth exploring. Learners are   searching not just for knowledge learning outcomes, but hoping and expecting to develop competencies and skills.  

Four “Practice” Strategies

Here are four “practice” strategies that will aid learners on their journey from novice to expert from Peter Fadde and Gary Klein, two researchers on expertise and decision-making.  They describe these strategies in a 2010 article on “deliberate performance.”  The strategies are:

  • Estimation
  • Experimentation
  • Extrapolation
  • Explanation

This eCoaching tip first defines each of these strategies and then gives some examples of each of them. The expertise framework developed by K. Anders Ericsson over the last 20 years usually focuses on the need for deliberate practice for developing world-class expertise. Fadde and Klein use the term “deliberate performance” as a way of contextualizing practice into the world of management, leadership and other complex cognitive professions. 


What is the skill of estimation? Estimating requires making judgments of probable time, resources or likelihood of success based on incomplete information, sometimes using rules of thumb that have developed over time.  Estimation is a skill that is fundamental to project planning, resource planning and budget planning and task planning. Professionals in all fields including business, health, military, engineering and creative endeavors all depend on knowledge and experience in making estimates.

Fadde and Klein note that, “Beyond any job-specific value, estimation exercises develop an awareness of interrelated elements in a task or work environment” (p.4). This statement affirms two very important ideas: that estimating is a valuable generic skill and that good estimating requires an awareness of the many variables that have an impact on a task.  We also know that expertise develops over time after many experiences with diverse and complex scenarios.  Being a good “estimator” often relies on much tacit or hidden knowledge that an expert has acquired over time and that is difficult to quantify or state explicitly.
What learning experiences might incorporate this type of skill? Here are a few possible practice scenarios.

  • Estimating projected business revenues.
  • Estimating times for discussing meeting topics in a business meeting.
  • Estimating the amount of time required for interacting with patients, employees, and clients.
  • Estimating time and resources for software projects
  • Estimating resources and times and strategies for solving problems, such as those in technology, health, engineering, business, etc.)

Estimating time for learning can also be part of your course.  Estimating and then recording time for doing various elements of learning projects can be incorporated into a course. This builds knowledge about the time for complex cognitive tasks that are usually part of professional responsibilities, such as writing reports, memos, project plans and doing research.


Experimenting is the process of defining and implementing various means of achieving the same goal.  Practitioners often try out a new process, procedure or strategy; then they observe the outcomes and may keep, adapt, or reject the process.  
What type of learning experience might incorporate experimentation? Here are some starting points.

  • Research some of the ways that companies use experimentation in their business practices of new products, management strategies and communications.  This might include research of focus groups and strategies for the launching of new products, such as building “buzz”.
  • Research how health care organizations experiment with strategies for reducing costs and errors and build a wiki or other useful outreach tool with the data.
  • Develop and test strategies for innovating within organizations.
  • Summarize ways of experimentation that test different hypotheses.

The learners in most online courses are already at some point in their journey from novice to expert.  Sharing experiment strategies from within their organizations and previous experiences can provide a whole set of experiences that learners can incorporate into their own knowledge.  In this way, shared experiences provide risk-free environments for vicariously experiencing experiments of all types.


Extrapolation is the process by which we deduce, derive, or generalize from vicarious or experienced cases to add to the knowledge base of our particular domain of expertise.  The process of extrapolation, according to Fadde and Klein, uses surprises, failures and potential or near failures to reflect on and add to our understanding of potential causal relationships. Some of the examples cited by these authors include learning from the many near misses recorded by controllers and pilots. Other examples include learning from errors in resource, time or budget planning.  
What type of learning experience might incorporate extrapolation? Here are some ideas.

  • Case studies of all types are useful for extrapolation exercises and learning through analysis of surprise results, failures, or sometimes potentially catastrophic results.
  • Simulations of all types are opportunities for studying and learning from causal relationships and connections between the elements of scenarios. This includes simulations of leadership, management, client interactions and negotiations.
  • Course projects that serve an external client or organization also provide opportunities for extrapolation to see where the projects went well and where they did not.

Extrapolation is another area in which there are rich opportunities for learners to learn from each other’s experiences both within the course and from learners’ current and previous experiences. Expertise grows out of a series of many years of experience.  These types of exercises serve to compress years of experience to develop the knowledge database of expertise more quickly.


In the expertise framework, explanation of any performance or learning event is similar to our familiar process of reflection. Learners take time to process, reflect, examine, analyze why any particular performance happened in the way it did.  Explanation as a process is well established in most professional practices. Doctors reflect on cases; pilots reflect on flights; managers reflect on their businesses, researchers reflect on their studies; businesses reflect on strategies for communicating with consumers, and teachers reflect on the success, or not, of their courses.  
What type of learning experience might incorporate explanation or reflection processes to aid learners in developing expertise in their particular domain?  Here are some starting points; many of which you are probably already using.   

  • Learners keep a blog or journal about their learning experiences and how they are integrating what they are learning as well as the processes that help them to learn.
  • You guide learners and support their reflection of a discussion by discussion wraps, and occasionally have the learners lead or prepare the discussion wraps.
  • Learners reflect on the processes and outcome of their course project, whether it is an individual or team project, developing rules of thumb for future experiences.
  • Learners reflect on their research habits and skills in their particular domain of desired expertise and how they might be improved.

One of the challenges of searching for explanations for deliberate performance exercises is that explanations are not available or accurate and most explanations are a combination of related elements. It is this complexity that drives the need for the multiple experiences over time. 
A rule of thumb about developing expertise is that it takes ten years of deliberate practice to develop expertise.  The complexity of all the interrelated elements in a domain is why it takes this time and deliberate performance in a domain.

Background on the Journey from Novice to Expert

Many of these eCoaching tips have referred to the building of expertise as a desired learning outcome.  We know that few of our students will become experts while in a program due to the ten-year rule of thumb.  But again, many of our learners are not exactly novices, either.  Here are the major phases of building expertise to help you estimate where your students are and the next step that you want to help them to achieve.  This phase description (2006) is from Michelene. T. H. Chi, now at Arizona State University. 

  • Novice - Person with minimal exposure to field
  • Apprentice - Person working in a domain under supervision who has completed an introductory period of study which can vary from 1 to 12 years
  • Journeyman (Assistant) - Person who can perform routine work unsupervised
  • Expert - Person whose judgments are uncommonly accurate and reliable; is highly regarded by peers; performance shows skill, economy of effort; can handle difficult and unusual cases  
  • Master - Can teach others; member of an elite group of experts whose judgments set regulations, standards or ideals

For more detail on these strategies and background on the expertise framework, be sure to download and read a copy of the 2010 Fadde and Klein article. Gary Klein is also the author of a couple of other interesting books on decision-making that many of you may find useful, if you are not already familiar with them.
Call or write regarding this tip, past or future ones.  It helps to know the topics and ideas that are helpful or not!  And your suggestions for future tips or webinars.


Chi, M. T. H. (2006). Two approaches to the study of experts' characteristics. In K.A. Ericsson, N. Charness, P.J. Feltovich, & R.R. Hoffman (Eds.), The Cambridge handbook of expertise and expert performance (pp. 21-30). Cambridge: Cambridge University Press.

E-Coaching Tip 25 (2006) Discussion Wraps -- A Useful "Cognitive Pattern" or "Collection of Discrete Thought Threads?" Retrieved January 19, 2011 from http://www.designingforlearning.info/services/writing/ecoach/tips/tip25.html

Ericsson, K. A. (2006). The influence of experience and deliberate practice on the development of superior expert performance. In K. A. Ericsson, N. Charness, P. Feltovich, and R. R. Hoffman, R. R. (Eds.). Cambridge handbook of expertise and expert performance (pp. 685-706). Cambridge, UK: Cambridge University Pres
Ericsson, K. A. (2000). Expert Performance and Deliberate Practice: An updated excerpt from Ericsson. Retrieved March 9 2011 from http://www.psy.fsu.edu/faculty/ericsson/ericsson.exp.perf.html Note: This is a really good starting point with a list of references if you are interested in pursuing ideas about expertise.
Fadde, P. J. and Klein, G. A. (2010), Deliberate performance: Accelerating expertise in natural settings. Performance Improvement, 49: 5–14. doi: 10.1002/pfi.20175. Retrieved March 8 2011 from http://web.coehs.siu.edu/units/ci/faculty/pfadde/Research/DelPer-UncorrectedProof.pdf.

Klein, G. (2009). Streetlights and shadows: Searching for the keys to adaptive decision making. Cambridge, MA: MIT Press.

Klein, G. (1998). Sources of Power. Cambridge, MA: MIT Press.

Note: These eCoaching tips were initially developed for the professional development of online faculty in the School of Leadership & Professional Advancement at Duquesne University. This library of tips has been organized and updated through 2010 in a book The Online Teaching Survival Guide: Simple and Practical Pedagogical Tips coauthored with Rita Marie Conrad. Judith can be reached judith followed by designingforlearning.org.



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Revised May 20 2013
Copyright Judith V. Boettcher, 1997-2013