Saturday, December 22, 2012

Training Evaluation Misses the Critical Thinking Dimension

For typical training courses the following four or five evaluation steps are the norm:

Level 1: Reaction and Perceived Values
Measures reaction to, and satisfaction with, the medium, content, and value of the project or program.

Level 2: Learning and Confidence
Measures what participants understand or learned from the project or program (information, knowledge, skills, and contacts).

Level 3: Application and Implementation
Measures what participants understand or learned from the project or program (information, knowledge, skills, and contacts).

Level 4: Impact and Consequences
Measures progress after the program implemented (the use of information, knowledge, skills, and contacts).

Level 5: ROI
Monetary Benefits.
(Phillips, & Phillips, 2007)

Evaluation is further divided into formative and summative evaluation, with formative evaluation relating to evaluating the training program and summative evaluation relating to the long-term effects of the training program (see Evaluation). Level 2, Learning and Confidence, is more of a formative evaluation measure and identifies whether trainees learned the material presented in the training. Level 3, application and consequences, is categorized as summative evaluation in which it looks at whether the trainees on-the-job behavior represents their learning from the training program.  

For these two specific levels of evaluation Phillips and Phillips (2007) highlighted information, knowledge, skills, and contacts. Providing employees (trainees) with the information that they need to conduct their job functions is critical. Additionally, providing employees with the knowledge to utilize this information in a productive manner is key to success. Having the skills to perform one's job is self-explanatory, but, as experience has shown us, people often lack the proper skills required to perform their main job function. Having the right contacts as well as knowing who has the information when needed is equally important. 

Using the following variables to evaluate training programs (information, knowledge, skills, and contacts) have proven to be effective for years. However, expanding on these variables to improve the evaluation process follows the continuous improvement process. As an effort to expand on the accuracy of training I would pose adding critical thinking to the mix.

Training employees to think critically helps to eliminate issues such as functional fixedness and mental sets. Ollinger, Jones, and Knoblich (2008) termed mental set as: " the repeated application of a successful method makes blind any alternative approach, because of the mechanization of the particular solution method" (p. 270). Alternatively, Duncker (1945) identified functional fixedness as: "the tendency to fixate on the typical use of an object or one of its parts" (as cited in McCaffrey, 2012, p. 216).

Adding the dimension of critical thinking to training endeavors will help transform learners (trainees, employees) to effective learners. Brindley, Walti, and Blaschke (2009) identified effective learners as those who are capable of coping with "complexity, contradictions, and large quantities of information, who seek out various sources of knowledge" (p. 3). By seeking out new sources of knowledge employees will better avoid the aforementioned traps of mental sets and functional fixedness. 

Including critical thinking skills as part of the training program, as well as incorporating evaluation of employees critical thinking skills on-the-job, could prove to produce better training results and on-the-job performance results. Additionally, including critical thinking in both the instructional and evaluation phases of the training program could improve both the formative and summative evaluations of the overall program. 

Brindley, Walti, & Blaschke (2009). Creating effective collaborative learning groups in an online environment. International Review of Research in Open and Distance Learning, 10(3), 1-18. 

McCaffrey, T. (2012). Innovation relies on the obscure: A key to overcoming the classic problem of functional fixedness. Psychological Science, 23(3), 215-218. dpi: 10.1177/0956797611429580

Ollinger, Jones, & Knoblich (2008). Investigating the effect of mental set in insight problem solving. Experimental Psychology, 55(4), 269-282. dpi: 10.1027/1618-3169.55.4.269

Phillips, & Phillips (2007). Show me the money: The use of ROI in performance improvement, part 1. Performance Improvement 46(9), 8-22. dpi: 10.1002/pfi.160

Tuesday, December 18, 2012

Representativeness (Intuition) versus Probability (Statistical accuracy)

"Experts are led astray not by what they believe, but by how they think" 
(Kahneman, 2011, pp. 219-220).

Every day decisions are made that affect the organization as well as the workplace and the workers. For example, decisions are made during an interview process to determine who the best candidate for the job will be. Additionally, decisions are made to identify who should be promoted from within the organization. Numerous other similar types of decisions are made weekly, sometimes daily, within organizations. These decisions are made using the information at hand (resume, work related performance records, referrals, manager's evaluation, etc…) as a predictor of future performance.

Basing a decision on intuition alone has been shown to be ineffective. Utilizing the information at hand can prove to produce slightly better predictions, depending on the validity of the information. The best that one can do when faced with having to make such a decision in a short time frame is to separate your subjectivity and base your decision on the data. Kahneman (2011) supported this position: "prediction  by representativeness is not statistically optimal" (pp. 150-151).  Here Kahneman refers to 'representativeness' as the decision-makers subjectivity, the decision-makers intuitive judgements about a particular candidate. Decisions based on representativeness have been shown to be no more accurate than in random assignment. Accuracy in decision making comes when statistical evidence (empirical data) guides the decision process. Kahneman made the following recommendations when making decisions:

  • Anchor your judgement of the probability of an outcome on a plausible base rate.
  • Question the diagnosticity of your evidence (p. 154).

Additional guide-lines, or rules, for making predictions are provided by  Kahneman (2011):

  • Errors of prediction are inevitable because the world is unpredictable.
  • High subjective confidence is not to be trusted as an indicator of accuracy (p. 220).

Basing decisions on 'plausible base rates' can lead to more accurate predictions in the long-term. The flexibility here is the term plausible, utilizing the best information made available in conjunction with your current knowledge of the field will assist in making more accuracy predictions. Avoiding subjective, or representative decisions, will improve the accuracy of predictions for the short-term as well as the long-term.

Kahneman, D. (2010). Thinking, Fast and Slow. New York, NY: Farrar, Straus, and Giroux.

Monday, December 10, 2012

Book Review

I have recently had my book-review for Edmondson's teaming (2012) published in the Learning and Performance Quarterly online journal. LPQ is a student-led, blind peer-review journal. LPQ is an open-access publication designed to make research available to the public and to support a greater exchange of global knowledge with articles supporting innovative learning and performance across disciplines (LPQ). As a reviewer for LPQ we are looking for additional reviewers and potential editors. If anyone is interested or needs the experience of being a reviewer for their resume go the the web page and submit your name. By being an open-source publication there is no membership required,  all articles are available for reading at any time. I hope you enjoy LPQ. You can also follow LPQ on Facebook.

The book-review is listed below:

Learning and Performance Quarterly, 1(3), 2012 31 
 Book Review 
Teaming: How Organizations Learn, Innovate, and Compete in the Knowledge Economy 
Jossey-Bass; 2012; 334 Pages; ISBN: 978-0-7879-7093-2 
New emerging constructs found in today's literature include those referring to collaboration, complexity, and globalization. One concept that builds on each of these aforementioned constructs is teaming. Edmondson has been involved with noteworthy research in the areas of small group and team research, including that of team psychological safety. Team psychological safety represents a climate in which group and/or team members feel comfortable questioning other's ideas, feel comfortable being challenged to defend one's own point of view, and are more open to constructive criticism. In her research, Edmondson identified psychological safety as a team construct in which a psychological safety measurement was developed showing that psychological safety affects learning behavior and also team performance. In her recent book, teaming, team psychological safety is but one construct identifying the learning construct teaming. 
Edmondson stated that “teaming is teamwork on the fly” (p. 13). Teams are traditionally portrayed in the literature as being a noun, consisting of fixed groups in pursuit of a common goal. Edmondson changes the discussion by placing teams as a verb, representing a dynamic activity, determined by the mindset and practices of teamwork. In Edmondson’s foundation for learning model, teaming is the first foundation, representing the structural support required for all other activities to take place. Edmondson identified four behaviors to accompany the foundation of teaming: speaking up, experimentation, collaboration, and reflection, 
Organizing to Learn 
Teaming is further differentiated from recent literature in that teaming is an organizational learning model. Edmondson’s model puts teaming as the driver for successful organizational learning functions. While teaming provides an environment for learning, Organizing to Learn, the second foundation for Edmondson’s learning model, promotes collective learning. Collective learning includes the following individual learning behaviors: a) asking questions, b) sharing information, c) seeking help, d) experimenting with unproven actions, e) talking about mistakes, and f) seeking feedback (p. 27). Edmondson identified the following four steps for the foundation organizing to learn: framing for learning (mental maps), creating psychological safety, learning from failure, and reaching across boundaries. 
The third and final foundation in Edmondson’s foundation for learning model was Execution-as-Learning, paralleling the same idea as that of action learning. Action learning follows four general principles, a) learning is acquired by doing, b) participants address organizational problems as well as personal development, c) participants work in Learning and Performance Quarterly, 1(3), 2012 32 
teams with peers, and d) participants follow an attitude of learning-to-learn. Execution-as-Learning was best described by Edmondson as the place in which "action and reflection go hand in hand” (p. 222). Four steps were included in Edmondson’s foundation for learning model to represent the foundation Execution-as-Learning: diagnose, design, act, and reflect. 
Together, these three foundations structure a learning environment (teaming) functioning on collective learning principles (Organizing to Learn) in which problems are addressed through systematic action learning steps (Execution-as-Learning). In Edmondson’s model a heavy emphasis was placed on leadership, which is required to get the process rolling. This heavy emphasis on leadership could be viewed as a weakness if an organization does not have a supportive leader. Edmondson indicated that leadership is what makes the process work, tying the foundations together. Successful teaming and learning thrive when leadership is able to focus on the foundations for learning, thus creating the by-product of a learning culture. Teaming is about more than just teams and their internal interactions. Teaming becomes the building block for a learning organization, which is the strength of Edmondson’s book. 
John R. Turner is currently a doctoral student in the Applied Technology & Performance Improvement (ATPI) program at the University of North Texas. His background is in engineering, with a second bachelor’s degree in Psychology from the University of Arkansas at Little Rock and a Master’s degree in Human Resource Development (HRD) from the University of Texas at Tyler. His research interests include performance improvement, team performance, team cognition, cognition/metacognition, outcomes-based evaluation, and meta-analysis techniques, and he has published in Performance Improvement and Journal of Knowledge Management. 

9th International Technology, Knowledge, & Society Conference

Coming up at the beginning of 2013 I will be presenting my paper Multiagent Systems as a Team Member at the 9th International Technology, Knowledge and Society conference on January 13-14, 2013, in Vancouver, Canada. This conference is being presented by Common Ground Publishing, USA. There is a great line-up of speakers from all disciplines in which you are sure to find something interesting. The website for the conference is:

My paper is being considered for publication by The International Journal of Technology, Knowledge and Society journal. Listed below is the abstract for the paper that I will be presenting. Once the presentation slides are put together, edited, and finalized I will have them posted on slideshare. I will post the link to the presentation slides once I have them completed. I am currently scheduled to present on on Jan. 14 under the Business Management and Organizational Technologies section around 1:30 pm.


With the increasing complex business environment that organizations have to operate in today, teams are being utilized to complete complex tasks.  Teams are capable of completing complex tasks that no one individual can achieve.  Effective team decision-making requires team members to discuss new information (unshared knowledge) and to consider this new information along with existing information (shared knowledge).  Research has shown that shared knowledge is favored over unshared knowledge during team discussions.  One method of transferring unshared knowledge to shared knowledge is to take advantage of new multiagent systems that are designed to support teams.  Multiagent systems are capable of filtering information without the bias toward shared information over unshared information.  This conceptual manuscript presents a model that incorporates individual intelligent agents and multiagent systems that monitor and actively interact with team members as an effort to address the unshared knowledge barrier, resulting in better team decision-making and problem solving outcomes. 

If you are planning on attending the conference drop a line and we can try to meet up at the conference.

Saturday, August 25, 2012

Teams & Knowledge Management: New Publication

My most recent published article is now available from the Journal of Knowledge Management.  I was fortunate to work with my professor, Dr. Jeff Allen, and my colleague, TK.  The electronic version is now available from Emerald publishing with their EarlyCite version. Once the finalized version is available for their print version the EarlyCite version will be transferred to a permanent, fully coded, electronic version.  The content will remain the same, only some publication alterations will be made and the author's biographies will be new. The reference for the new article is listed below:

Turner, J. R., Zimmerman, T., & Allen, J. (2012). Teams as a process for knowledge management. Journal of Knowledge Management, 16(6).  Retrieved from

The Abstract / Purpose is provided below:

Within the expansive body of literature on knowledge management, very little research is found that examines the use of teams as a sub-process for knowledge management. This article addresses this limitation by providing a theoretical framework that examines the similarities between the benefits of incorporating teams into the workplace and incorporating knowledge management principles. Recognizing that knowledge management has several critical dimensions, the framework that ties workplace teams to each of these knowledge management dimensions is built. Knowledge management and teams in the workplace are viewed at the individual, team and organizational level of analysis.

The full article will have to be read via JKM due to copyright rules.  However, once the print version is out, if you have trouble obtaining the article, I can probably help with forwarding a pdf version of the article. Just let me know. 

Tuesday, August 7, 2012

Multitasking Illustration

Multitasking can cause cognitive overload, thus reducing the actual amount of material learned and the quality of your output.  People who practice multitasking have "greater difficulty filtering out irrelevant stimuli from their environment... are less likely to ignore irrelevant representations in memory... and they are less effective in suppressing the activation of irrelevant task sets" (Ophir, Nass, & Wagner, 2009, p. 3 or 5). More information can be found in my previous blog post titled Media Multitasking and Memory Processes.

Attached below is an illustration that captures the downfalls to multitasking. This illustration was presented by

Please Include Attribution to With This Graphic Multitasking Infographic


Multitasking. Retrieved from

Ophir, E., Nass, C., & Wagner, A. D. (2009). Cognitive control in media multitasks. Proceedings of the National Academy of Sciences of the United States of America (PNAS), 106(37), 15583-15587. dpi: 10.1073/pnas.0903620106

Incorporate a Mindfulness Culture

Weick and Sutcliffe (2007), in their book Managing the Unexpected,  identified that it is one's expectations that can get a team, group, or department into trouble. Expectations work well for predicting planned change and for setting future goals. However, these are only perceived states. Expectations never go as planned. The difference between one's expectation and what actually occurs is what Weick and Sutcliffe (2007) identified as the blind spot. To counter these unexpected events from occurring, the blind spot, organizations need to develop a more mindful culture, termed mindfulness (Weick & Sutcliffe, 2007): "This enriched awareness, which we call mindfulness, uncovers early signs that expectations are inadequate, that unexpected events are unfolding, and that recovery needs to be implemented" (p. 23).

Being mindful includes a culture where employees are able to notice the unexpected, to update plausible interpretations continuously, and to identify potential problems and remedies (Weick & Sutcliffe, 2007). Five common keys to incorporating a mindful infrastructure were outlined by Weick and Sutcliffe (2007):
  • Principle 1: Preoccupation with Failure.
  • Principle 2: Reluctance to Simplify.
  • Principle 3: Sensitivity to Operations.
  • Principle 4: Commitment to Resilience.
  • Principle 5: Deference to Expertise (pp. 9 - 15).

Incorporating your team, unit, department, or organization into a mindful infrastructure takes time. One way to begin this phase is to start with small wins. Small wins that move people from a mindless culture to a mindful culture start with the following steps outlined by Weick and Sutcliffe (2007):
  • Remember that mindfulness takes effort.
  • Offer support to people who are making an effort to become more mindful.
  • Frame mindfulness in novel ways.
  • Mitigate complacency.
  • Remember that reliability is not bankable.
  • Carry your expectations lightly.
  • Balance centralization with decentralization.
  • Let culture do the controlling (pp. 148 - 150).

Having the capability to recognize problems when they occur and the ability to react to these problems will help reduce the amount of down time due to unexpected events.  As stated by Weick and Sutcliffe (2007): "We find failures of expectations everywhere, which is why managing the unexpected is so crucial" (p. 21).

Weick, K. E., & Sutcliffe, K. M. (2007). Managing the Uunexpected: Resilient Performance in an Age of Uncertainty (2nd ed.). San Francisco, CA: Jossey-Bass.

Friday, July 13, 2012

Activity Theory, Expansive Learning Cycle

Activity theory addresses learning activities that take place in a complex environment (non-linear, dynamic, heterogeneous) as opposed to a linear learning environment (homogenous, static, instructional). In the following diagram the subject interacts with the object mediated by various influences from the environment; instruments, division of labor, community, and rules (Engerstom, 2001).


Retrieved from:

When viewing theories Engerstom (2001) poised that any theory must answer the following four questions:
  1. Who are the subjects of learning, how are they defined and located?;
  2. When do they learn, what makes them make the effort?;
  3. What do they learn, what are the contents and outcomes of learning?;
  4. How do they learn, what are the key actions or processes of learning? (P. 133).

It is from activity theory that Engersom (2001) derived the Cycle of Expansive Learning. This cycle could be viewed as an extension of 
Shewart's Plan-Do-Check-Act cycle (McLean 2006, p. 19) and Lewin's planned approach to change. Both of these change theories are identified under the action research literature. 

Engerstom's cycle of expansive learning is shown in the following figure:

Figure Retrieved from:

In this expansive learning cycle the following steps are followed:
  1. Charting the Situation
    • Something must be done.
    • Commitment to change.
  2. Analyzing the Situation
    • How did we work in the past (history)?
    • What are our present troubles and contradictions?
  3. Creating a new Model/Vision
    • How do we want to work in the future?
  4. Concretizing and Testing the new Model
    • What changes do we want to try next month?
  5. Implementing the new Model
    • Putting into practice the first steps.
    • Pushing for the next steps.
  6. Spreading and Consolidating
    • Teaching others what we learned (knowledge distribution)
    • Codifying the new rules, etc.
    • Permanent reflection (Weber, 2008, p. 53).

Activity theory focuses more on cultural theory while action research focus more on conducting research in natural settings. In either case, there are similarities in the various change models from both schools of theory. Diversifying one's knowledge base can only be productive in allowing one to view change models from different perspectives, resulting in more productive results.


Engestrom, Y. (2001). Expansive learning at work: toward an activity theoretical reconceptualization. Journal of Education and Work, 14, 133-156. doi: 10.1080/13639080020028747

McLean, G. N. (2006). Organization Development: Principles, Processes, Performance. San Francisco, CA: Berrtt-Koehler.

Weber, S. (2008). Intercultural learning in business and human resource education. In Nijhof, W. J., & Nieuwenhuis, L. F. M. (ads.), The Learning Potential of the Workplace, 47-69. Rotterdam, Netherlands: Senge.

Sunday, July 8, 2012

Action Research, Action Learning: Research in Organizations

Action research is a research method that was designed to conduct research in the field as opposed to conducting research in the lab. Action research was coined and practiced successfully by Kurt Lewin and has been used extensively in various disciplines and differing field (live) situations since.  

Compared to traditional research, action research is considered more as a quasi-experimental design. Bryman (2008) identified quasi-experiments as: "studies that have certain characteristics of experimental designs but that do not fulfill all of the internal validity requirements" (pp. 40-41). In natural settings, such as those found in educational settings and in organizations, it is nearly impossible to conduct a pure 'traditional' experiment: resulting in action research being one of the primary experimental designs utilized in natural environments (in one form or another).

Bargal (2008) identified action research as being composed of both quantitative and qualitative research methods: "the scientific and systematic accumulation of data as well as the development of the interventions that represent practical solutions to problems experienced by people and their communities" (p. 18). Bargal (2006) highlighted Lewin's 'action research' systematic steps:
  1. Action research combines a systematic study, sometimes experimental, of a social problem as well as the endeavors to solve it.
  2. Action research includes a spiral process of data collection to determine goals, action to implement goals and assessment of the result of the intervention.
  3. Action research demands feedback of the results of intervention to all parties involved in the research.
  4. Action research implies continuous cooperation between researchers and practitioners.
  5. Action research relies on the principles of group dynamics and is anchored in tis change phases. The phases are: unfreezing, moving, and refreezing. Decision-making is mutual and is carried out in a public way.
  6. Action research takes into account issues of values, objectives and power needs of parties involved.
  7. Action research serves to create knowledge, to formulate principles of intervention and also to develop instruments for selection, intervention and training.
  8. Within the framework of action research there is much emphasis on recruitment, training and support of the change agents (p. 4, Figure 1).

A more condensed version of action research can be found in Gall, Gall, and Borgs' (2010) steps:
  1. Selection of a focus for the study.
  2. Data Collection.
  3. Analysis and interpretation of the data.
  4. Taking Action.
  5. Reflection (pp. 491-493).

As a version of action research, action learning has developed to become a unique problem solving activity used in the classrooms, training rooms, and within organizational teams. Action learning is similar to a training exercise; however, the main difference is that a real problem is being considered opposed to some hypothetical simulated scenario. This process is beneficial to the organization by resolving real issues as well as providing a means for training groups to learn together and to solve real-time problems. Gorrell (2012) identified the benefits of action learning as: "Action learning provides an opportunity to combine the real work objectives of an important offsite event with the beneficial outcomes of a reflective team-building experience" (p. 26). Recommended action learning steps provided by Gorrell (2012) were:
  1. Restate the problem statement.
  2. Determine assumptions behind the issue.
  3. Set goals that would solve the issue at hand.
  4. Set specific tasks to realize the goals.
  5. Create an accountability matrix.
  6. Offer post-action learning feedback (p. 29).

Various other versions of action research and action learning can be found. Regardless of the steps or design, it is recommended to take care to: a) identify the problem carefully, b) place the problem in the environment, c) carefully collect any appropriate data, d) properly analyze the data, e) make a decision, and f) reflect on the processes practiced to make the next problem solving exercise that much easier. And above all, and probably most important, g) assure you have management buy-in.


Bargal, D. (2008). Action research: A paradigm for achieving social change. Small Group Research, 39(17), 17-27. doi: 10.1177/1046496407313407

Bargal, D. (2006). Personal and intellectual influences leading to Lewin's paradigm of action research. Action Research, 4(4), 367-388. doi: 10.1177/1476750306070101

Bryman, A. (2008). Social Research Methods (3rd ed.). New York, NY: Oxford University Press.

Gall, M. D., Gall, J. P., & Borg, W. R. (2010). Applying Educational Research (6th ed.). Boston, MA: Pearson.
Gorrell, P (2012). Action learning for teams. Chief Learning Officer, July, 26-29.

Thursday, July 5, 2012

Training & Learning Theories: Pedagogy, Angragogy, Heutagogy

Basic theories of learning include Pedagogy (child and adolescent learning theories), Andragogy (adult learning theories including self-directed learning), and now Heutagogy (self-determined learning theories).

Andragogy includes learners who are actively involved in identifying their needs and how to meet those needs in which the educator takes the role of a tutor or a mentor (Blaschke, 2012).  The goals for andragogy include: "helping learners develop the capacity for self-direction, supporting transformation learning" (Blaschke, 2012, Andragogy).

The Andragogical model is based on six general assumptions:
  1. The need to know.
  2. The learner's self-concept.
  3. The role of the learners' experiences.
  4. Rediness to learn.
  5. Orientation to learning.
  6. Motivation (Knowles, Holton III, & Swanson, 2005, pp. 64-68).

Heutagogy is the study of self-determined learning in which the focus is person-centered (Davis, 2001) as opposed to teacher-centered or teacher-student centered. Heutagogy was coined in 2000 by Hase and Kenyon, acknowledging that "learners do immensely valuable work for themselves by filling in the gaps of their formal education through discovery and reflection" (Parslow, 2010, p. 121).  A heutagogical environment would focus on both the development of the learner as well as the development of the learners capability to learn and capacity to learn (Blaschke, 2012).

The educator in a heutagogical environment facilitates the learning process through guidance and by providing appropriate resources, much in the same manner as with andragogy. However, in heutagogy the educator relinquishes control/ownership of the learning path and process (Blaschke, 2012).  Here the learner determines their path and sets their own learning goals.

Heutagogy is influenced by Argyris' theory of double-loop learning. Schein (2010) described it best in his discussion on implicit assumptions: "To learn something new… requires us to resurrect, reexamine, and possibly change some of the more stable portions of our cognitive structure" (p. 28).

Compared to andragogy, self-directed learning requires the acquisition of both competencies and capabilities. Blaschke (2012) identified competencies as one's ability to acquire knowledge and skills, compared to capabilities that are the learner's self-efficacy on their ability to recall and use their new knowledge or skills. 

Heutagogy was termed and utilized to describe today's online learning environment where learning activities have moved away from the traditional classroom setting to a more asynchronous environment for both the instructor and the students. An equal and similar environment, that of training and development in the workplace, heutagogy principles could be found to be beneficial.  For example, focusing attention on both competencies and capabilities for training and development efforts could prove to be most successful. Additionally, Blaschke (2012) provided course design elements to support a hetagogical approach to training:
  • Learner-defined learning contracts
  • Flexible curriculum
  • Learner-directed questions
  • Flexible and negotiated assessment

As part of the reflection process (the 'reexamine' portion identified by Schein) Blaschke (2012) identified the following design elements to support reflective practice:
  • Learning Journals
  • Action Research
  • Formative and Summative Assessment
  • Collaborative Learning Environments

As informal and non-formal learning initiatives increase in the workplace with the aid of mobile technologies, these training functions could benefit from utilizing the general principles provided by heutagogy learning theories. 


Blaschke, L. M. (2012). Heutagogy and lifelong learning: A review of hetagogical practice and self-determined learning. The International Review of Research in Open and Distance Learning, 13(1). Retrieved from

Davis, L., & Stewart, H. (2001). The river of learning in the workplace. In Research to Reality: Putting VET Research to Work. Retrieved from ERIC.

Knowles, M. S., Holton III, E. F., & Swanson, R. A. (2005). The Adult Learner: The Definitive Classic in Adult Education and Human Resource Development. New York, NY: Elsevier.

Parslow, G. R. (2010). Multimedia in biochemistry and molecular biology education. Commentary: Heutagogy, the practice of self-learning. Biochemistry and Molecular Biology Education, 38(2), 121. doi: 10.1002/bmb.20394 

Friday, June 22, 2012

Organizational Culture and Change

Meyerson and Martin (1987) view organizations as cultures in which organizational change incorporates "changes in patterns of behavior, values, and meanings (p. 624). From their research, Meyerson and Martin (1987) identified three paradigms of organizational culture: integration, differentiation, and ambiguity.

Paradigm 1: Integration

Integration views of organizational culture identifies with those views that are shared: "for example, a common language, shared values, or an agreed-upon set of appropriate behaviors" (Meyerson & Martin, 1987, p. 624). Through an exhaustive search of cultural studies and theories, Meyerson and Martin (1987) identified three common characteristics for integration cultural theories: "consistency across cultural manifestations, consensus among cultural members, and -usually- a focus on leaders as culture creators" (p. 625). An integration culture would be found in most organizations that operate in a traditional top-down, controllable, manner.

Paradigm 2: Differentiation

Differentiation theories of organizational culture espouse diversity, where attention is paid to "inconsistencies, lack of consensus, and non-leader-centered sources of cultural content" (Meyerson & Martin, 1987, p. 630). Where an integrated culture is more closed, a differentiation culture is more open, influenced from both inside and outside influences (Meyerson & Martin, 1987). A differentiation culture would be found in organizations that operate with a flat or horizontal hierarchy, allowing more decisions to be made from front-line employees.

Paradigm 3: Ambiguity

Where paradigm 1, integration, resists ambiguity due to its rigidity, paradigm 2, differentiation, is more open to ambiguity so that it can be managed. For paradigm 3, ambiguity is accepted as "the way things are, as the 'truth', not as a temporary state awaiting the discovery of 'truth'" (Meyerson & Martin, 1987, p. 637). An ambiguity culture would be found in organizations that operate on a network theory or a complexity theory model.

Organizations address culture differently, partly based on the type of environment they operate in. Weick and Sutcliffe (2007) recommended to make your organization as complex as the environment - the more complex the environment, the more complex the organizational system will need to be in order to function accordingly. 

No one organization operates completely in one paradigm, there are usually portions of each type of paradigm present in any organization. When addressing change, it is recommended to view the change effort from each of the three paradigms rather than solely from one paradigm. As Meyerson and Martin (1987) pointed out: "An awareness of all three paradigms simultaneously would avoid the usual blind spots associated with any single perspective" (p. 643).


Meyerson, D., & Martin, J. (1987). Cultural change: An integration of three different views. Journal of Management Studies, 24(6), 623-647. Retrieved from

Weick, K. E., & Sutcliffe, K. M. (2007). Managing The Unexpected: Resilient Performance in an Age of Uncertainty. San Francisco, CA: Jossey-Bass.

Wednesday, June 20, 2012

Personal Learning Strategy

In becoming a leader, or a self-directed learner, one must be able to learn effectively.  Learning effectively not only requires learning in a classroom setting, it also entails learning from experience, learning while doing, learning from others, and being able to teach or mentor what you have learned. Thomas (2008) identified a personal learning strategy as: "something to be owned and enacted by an individual, driven by his or her personal vision, tailored to his or her learning style, aimed to extract insight from the broadest possible range of experiences, and dedicated to achieving meaningful results" (p. 86).

Personal Vision
Identify what your own vision is. This requires asking hard questions such as: why you want to do what you are doing (ex: why you want to lead), what type of leader do others perceive you to be, what type of leader do you want others to identify you as, what does a day as a good leader look like, and how do you get from where you are today to where you desire to be?

Thomas (2008) listed McClelland's individual motivation assessment to help one determine how best they are motivated to lead.  McClelland's types of motivation, based on an individual's specific needs, include achievement, affiliation, and power. An achievement motivated leader would be motivated by achieving excellence and doing things well, with an emphasis on performance. An affiliated motivated leader includes one who is concerned with social relationships, wanting to be liked, with preferences to being part of a group. A power motivated leader wants to influence relationships and be in charge. This exercise in determining your own personal motivation is first to identify your own personal type. Next you want be cognizant of the other types of motivating forces so you will be able to recognize them. By determining a person's needs you will be more capable to influence that individual.  Further information on McClelland's, and other motivational theories (Herzberg's Motivators and Hygiene Factors, McGregor's XY Theory, and others) can be found at and

Persoanal Learning Style
Thompson (2008) highlighted the importance of what he called adaptive capacity. Adaptive capacity refers to "an individual's ability to adapt and his or her ability and willingness to learn" (p. 103). Understanding how you learn best, and how you learn best in differing situations, will aid you in developing your personal learning strategy.  There are a number of learning style tests available.  One familiar test is Kolb's Learning Style Inventory consisting of four types of learners: converging, assimilating, diverging, and accommodating. Converging learners prefer practical applications and solving problems, assimilating learners focus on planning and creating models, diverging learners are more imaginative and open to new ideas, while accommodating learners use trial-and-error and are more prone to taking risks.  More information on Kolb's learning styles can be found at Clark's web page; other types of learning styles are also available such as the Visual, Auditory, and Kinesthetic Learning Styles (VAK), and the Learning Style Survey. Each of these learning style theories are designed to be used as a reference point for the individual, one's type of learning style should not direct the way one approaches learning. Rather, concentrate on the different types of learning styles, know your own style, and work on building your abilities in those styles that you are weaker in.  Broaden your learning spectrum.

Extract Insight & Learn from Experience

Developing a personal learning strategy also includes being able to extract meaning and purpose from your experiences. Being honest, having integrity to do whats right, taking the lead, or allowing others to lead, and engaging others through shared meaning provide opportunities to extract insight from experience. Thomas (2008) emphasized not only learning from experience, but also to learn while doing: "when you don't have time to practice and yet you seek to improve your performance, you have to learn how to practice while you perform" (p. 62).

Providing a personal learning strategy helps to provide one with a guidebook for their journey.  A personal learning strategy can be changed, it is not written in ink. Actually, a personal learning strategy should be malleable, allowing one to change it as they grow. One other benefit for having a personal learning strategy is that it helps prevent one from becoming stagnant: "Skills can stagnate from underuse; they can be blunted through misuse; and they can be superseded by advances in the field. They must, therefore, be renewed" (p. 222).


Thomas, R. J. (2008). Crucibles Of Leadership: How To Learn From Experience To Become A Great Leader. Boston, MA: Harvard Business Press.

Friday, June 15, 2012

Innovation - Organization and Human Resources

Traditionally, organizations designed their training and transfer of knowledge to their employees on an as-needed basis, or what management thought was needed for their employees.  This type of system has become to be known as a 'push' system, directions coming from the top-down.  As organizations are experiencing globalization, more complex working environments with an ever-expanding resource of information, they are being forced to adjust to what is termed a 'pull' system (Hagel III, Brown, & Davison, 2010), representing a flatter organizational hierarchical structure.  

This age of complexity has also been referred to as the knowledge economy (macro), or the knowledge organization (micro) as termed by Drucker (2007). This knowledge organization is designed to focus more on contribution rather than on power, is structured according to the flow of information, and is multidimensional - breaking traditional organizational silos (Drucker, 2007). 

With a flatter organizational hierarchy structure the organization fosters innovation from both top-down and bottom-up communications.  To better foster innovation from the bottom-up communication chain McFadzean (1999) recommended the following to motivate employees to think creatively:
  1. Motivate employees: reward employees for good practice.
  2. Motivate think: give employees time to think about their own pet projects.
  3. Motivate creative: train employees in how to think more creatively.
  4. Employees creative: encourage the use of creative problem-solving techniques during meetings.

When conducting team and/or collaborative activities for innovation, Hunter et al. (as cited in McFadzean, 1999) offered the following guidelines:
  1. Get to know the other people.
  2. Be clear about the group purpose, values, ground rules and practices.
  3. Contribute to discussions, group decision making and task allocation.
  4. Share thoughts, ideas, feelings and concerns.
  5. Listen generously to other people.
  6. Speak concisely and to the point.
  7. Maintain focus and ensure that the process will lead to the fulfillment of the meeting's goals.
  8. Be proactive. Make suggestions, propose alternatives, look at what's missing in the discussion and add it.
  9. Be flexible. Avoid taking a fixed position. 
  10. Ensure that you understand the conversation that you are contributing to.
  11. Do not avoid conflict. Disagreement and conflict are an important part of the development of the group.
  12. Keep to the ground rules and encourage others to keep to them as well.
  13. Fulfill the commitments that have been promised in the appropriate time frame.

Encouraging and fostering ideas from employees will be required more as the organizational hierarchy changes from a top-down structure to a more bottom-up structure.  Drucker (2007) described that innovation needs to come from "the places that control the human resources and the money… from the existing large aggregate of trained people and disposable money" (p. 152).  The guidelines presented above will assist with the human resources portion of innovation.  Innovation is an organization function, consisting of all employees, stakeholders, and shareholders. "The innovative organization manages to innovate as an organization, that is, as a human group organized for continual and productive innovation (Drucker, 2007, p. 154).


Drucker, P. F. (2007). People and Performance: The Best of Peter Drucker on Management. Boston, MA: Harvard Business School Press.

Hagel III, J., Brown, J. S., & Davison, L. (2010). The Power of Pull: How Small Moves, Smartly Made, Can Set Big Things in Motion. New York, NY: Basic Books.

McFadzean, E. (1991). Encouraging creative thinking. Leadership & Organization Development Journal, 20(7), 374-383. Retrieved from Emerald. 

Tuesday, June 5, 2012

Learning and Performance Quarterly

There is a new open access journal now available from the Department of Learning Technologies at the University of North Texas titled; Learning and Performance Quarterly. The student-lead team, faculty supported, that has put this publication together has done some great work. This peer reviewed publication is worth checking out for information relating to learning and performance. Plus, this publication takes an international perspective to learning and performance issues.
The primary goals for this open access journal are stated as follows:
  • Create interdisciplinary partnerships between scholars, scholar practitioners, and practitioners;
  • Provide a platform for emerging and established scholars and scholar practitioner to dissemination research in the area of learning and performance;
  • Serve as an incubator for learning and performance innovation;
  • Nurture future scholars and scholar practitioners;
  • Decrease the gap between theory and practice;
  • Increase exchange of knowledge between education and business;
  • Develop knowledge solutions platforms to increase learning and performance; and
  • Servie as curators of knowledge solutions for organizational systems (Retrieved from

For more information on the journal you can access the following links.  Additionally, if you are interested in submitting an article feel free to follow the link provided.
LP Quarterly, Vol. 1, No. 1 is Published
Stay connected with up to date call for submissions at:

Friday, June 1, 2012

Team Learning - Psychological Safety

One key internal mechanisms that aids teams to operate effectively is the psychological safety that team members gain while operating within the unit of the team.  Edmondson (2012) identified the general premise of psychological safety: no one team member can perform perfectly in every scenario. Team members vary on their knowledge and experience, additionally work places and tasks vary on levels of complexity.  As the level of complexity increases psychological safety becomes an even more critical team construct.

Kostopoulos and Bozionelos (2011) identified psychological safety where team members are safe for interpersonal risk taking, meaning that teams and team members are able to take risks without any repercussions if they fail.  The learning process, rather than the results, is what is important to the team - as long as the team members continue to learn by trying new methods to solve problems they should feel free to explore without being penalized in any manner.  Psychological safety provides a healthy learning environment by facilitating exploratory learning and creating an environment conducive to critical thinking and open discussion (Kostopoulos & Bozionelos, 2011).

Edmondson (2012) identified some benefits provided by psychological safe work environments for teams:

  • Encourages speaking up
  • Enables clarity of thought
  • Supports productive conflict
  • Mitigates failure
  • Promotes innovation
  • Removes obstacles to pursuing goals for achieving performance
  • Increases accountability (p. 126, Exhibit 4.2)

Schein (2010) identified that a change leader "must reduce learning anxiety by increasing the learner's sense of psychological safety" (p. 305).  Schein (2010) identified eight activities that a change leader must empliment to provide a psychological safe team environment:

  • A compelling positive vision
  • Formal training
  • Involvement of the learner
  • Informal training of relevant "family" groups, and teams
  • Practice fields, coaches, and feedback
  • Positive role models
  • Support groups in which learning problems can be aired and discussed
  • Systems and structures that are consistent with the new way of thinking and working (pp. 306-307).

When each of these eight activities are created, simultaneous, a clear psychological safe work environment will be provided for teams to operate in - providing a safe learning environment for team members to function in.


Edmondson, A. C. (2012). Teaming: How Organizations Learn, Innovate, and Compete in the Knowledge Economy. San Francisco, CA: Jossey-Bass.    

Kostopoulos, K. C., & Bozionelos, N. (2011). Team exploratory and exploitative learning: Psychological safety, task conflict, and team performance. Group and Organization Management, 36(3), 385-415. dpi: 10.1177/1059601111405985

Schein, E. H. (2010). Organizational Culture and Leadership (4th ed.). San Francisco, CA: John Wiley & Sons.

Tuesday, May 29, 2012

Learning from Training: Learning Theories

Learning is perceived to be both a cognitive construct and a social construct.  Some may argue that learning is predominantly cognitive while others would argue that learning is primarily social.  In either case, regardless of which epistemology you prescribe to, learning from training works best when both cognitive and social activities are incorporated.

Learning as a cognitive construct:

Merriam, Caffarella, and Baumgartner (2007) identified the cognitive perspective of learning from the camps of Piaget, Kuhn, and Dewey.  This perspective views learning as: "meaning… by the individual and is dependent on the individual's previous and current knowledge structure. Learning is thus an internal cognitive activity" (p. 291). This stream of learning theories view past experiences, existing knowledge, and interactions with the environment as critical to new learning.

Learning as a social construct:

Merriam et al. (2007) identified the social perspective of learning from the campus of Vygotsky and Driver. This perspective views culture and social interaction as being critical to learning.  "This approach involves learning the culturally shared ways of understanding and talking about the world and reality (Merriam et al., 2007, p. 292).  From this perspective culture, artifacts, and social interaction with others is critical to new learning.

The learning spectrum:

Merriam et al. (2007) describe these two learning theories as a type of spectrum, with cognitive theories on one end of the spectrum and social theories on the opposite end of the spectrum.  Realistically, the location one is on this learning spectrum is situational. In some situations the learning could be more cognitive, while in other situations this learning could be mostly social.  

Training and Learning:

Viewing the composite of learning from the middle of the learning spectrum one would view learning as both cognitive and social.  Situationally, this would be the optimal position to maximize learning from training.  Specific learning activities have been identified that would take advantage of both the cognitive and social theories of learning.  Listed below are a few activities / theories that could be used during training to optimize learning.

  • Activity Theory (AT): Activity theory 'conceptualizes learning as involving a subject (the learner), and object (the task or activity) and mediating artifacts…. Activity theory… combines the individual and the social (including culture and history) in understanding an activity such as learning' (Merriam et al., 2007, p. 292).
  • Action-Based Learning: Action-Based Learning is "a dynamic, real-time method of training that brings a group of individuals together to identify the cause of real problems and arrive at possible solutions…. requiring those solutions to be put into action and the results fed back to the group" (Kirkpatrick, & Kirkpatrick, 2010, p. 116).
  • Evaluative Research: Evaluative research can be used in a training environment as a means to combine both a groups knowledge and experience through social interactions.  Evaluative research "involves statements about cause-and-effect relationships" (Gall, Gall, & Borg, 2010, p. 12). One example of an evaluative research model is a needs assessment where "a set of procedures for identifying and prioritizing needs related to societal, organizational, and human performance" (McKillip, as cited in Gall et al., 2010, p. 515) is conducted.  Another type of evaluative research would be responsive evaluation, responsive evaluation "focuses on identifying and describing stakeholders' issues… and concerns" (Gall et al. 2010, p. 516).
  • Action Research: Action Research is research conducted in the workplace, where the problem exists.  Gall et al. (2010) identified seven steps to an action research project:
    • Selection of a Focus for the Study (or training)
    • Data Collection
    • Analysis and Interpretation of the Data
    • Taking Action
    • Reflection
    • Continuation or Modification of Practices
    • Preparing a Report of the Findings (or group presentation)
    • *parenthesis include items added, not in original referenced material*


Effective training could maximize learning by focusing activities along the middle of the learning spectrum. Various activities are available from the education and research literature that could be used in training situations that provide learning opportunities for participants.  The above activities are only a few of those available that could be used in a training exercise.  Those listed are identified to maximize learning as viewed from the middle of the learning spectrum.


Gall, M. D., Gall, J. P., & Borg, W. (2010). Applying Educational Research (6th ed.). Boston, MS: Pearson.

Kirkpatrick, J. D., & Kirkpatrick, W. K. (2010). Training on Trial: How Workplace Learning Must Reinvent Itself to Remain Relevant. New York, NY: American Management Association (AMACOM).

Merriam, S. B., Caffarella, R. S., & Baumgartner, L. M. (2007). Learning in Adulthood: A Comprehensive Guide (3rd ed.). San Francisco, CA: Jossey-Bass.

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