• Personal Resonance© is a research forum engaged in transforming findings from proven research studies on learning, training, performance and expertise into practical training solutions and practices to 'accelerate time-to-expertise' of organizations and professionals. Aggressive time-to-market drives organizations to develop complex cognitive skills of their employees at faster pace to beat their competitors. Goal of forum is to find and share the answer to that ‘speed’. The forum is trying to develop a core knowledge-base in four areas by systematically assimilating, analyzing and synthesizing the proven research studies in wide range of disciplines like cognitive sciences, neuroscience, psychology, education, learning and brain science, etc.: 1) Accelerated Workplace Expertise: Proven research-based strategies and methodologies to accelerate expertise of organization as a whole through training and learning. 2) Accelerated Professional Expertise: Science-based resonance techniques to accelerate expertise, peak performance and effectiveness of individuals. 3) Strategic Training Management: Experience-based competitive philosophies and processes to manage large-scale complex learning and knowledge operations to produce proficient workforce. 4) Competitive Instructional Design: Advanced instructional and learning design techniques to deliver higher order complex skills like problem solving, critical thinking, decision making, technical troubleshooting.

What does it take to develop Expertise in Complex Problem Solving Skills?

Building Expertise in Complexity

In this post I would like to address a very different challenge for training experts – domain of building / accelerating expertise from research in the area of complex problem solving skills. Sometimes back I wrote a paper on this and I am re-purposing some of the contents here in organizational context.

In today’s environment, employees are expected to possess proficiency in top order problem solving and troubleshooting skills. General strategies for developing expertise in other context are seen to be not working effectively in such jobs. Developing expertise of individuals and developing it faster is extremely challenging task. Let me break challenges in developing troubleshooting expertise in employees step-by-step.

What makes Jobs Complex?

Global jobs, especially the technical ones are become complex day by day. Complex jobs are the jobs that are characterized by the complexity of the decision making, complexity of problems, complexity of problem solving, complexity and ambiguity of the tasks, uncertainty in the environment and complexity of interactions it entails. Task complexity is another key factor to determine the job complexity. TaskManagementGuide website defines task complexity as “a collection of properties inherited by a task. These properties (like priority, due date, duration, and urgency) define the difficulty of this tasks and its significance to a performer (a person who should do the task)”.

Several jobs require employees to handle critical and complex technical issues almost on daily basis. The job ranges from problem solving responsibility being a part of the jobs to the main job itself. Examples of such jobs are: Equipment repair service, internal organ medical surgery, Network and  database administration, Cyber security, Aircraft maintenance, Airplane piloting, Oil and gas exploration, Air Traffic Control, Civil engineering, Biomedical engineering, Strategic military operations, Satellite and rocket control, Space and astronautically missions to name a few (Onetoonline, n.d). These kinds of jobs require its employees with ability to resolve problems of any complexity and order quickly and efficiently.

Complex Problems a Common Denominator of Complex Jobs

All the complex jobs have one thing in common – complex problems. What makes a problem complex? Complexity of a problem is a function of the number of issues, functions, or variables involved in the problem; the number of interactions among those issues, functions, or variables; and the predictability of the behavior of those issues, functions, or variables (Xu et.al, 2007). Jonassen (2000) maintains that dynamicity is another dimension of complexity. In dynamic problems, the relationships among variables or factors change over time. Changes in one factor may cause variable changes in other factors. The more intricate these interactions, the more difficult it is any solution.

Solving Complex Problems – Complex Problem Solving (CPS)

Technical problems are typically very complex in nature due to nature of the domain and far more reaching effects than the business problems. This goes beyond the general problem solving we talk in day-to-day life. There is a well-developed body of knowledge called Complex Problem Solving (CPS). This moment was originally started in Europe. For those who find CPS as a new term, let me define it briefly:

Quesada et.al (2005) presented a compact characteristic of complex problem solving based on Frensch and Funke (1995b):“Complex problem solving tasks are situations that are: (1) dynamic, because early actions determine the environment in which subsequent decision must be made, and features of the task environment may change independently of the solver’s actions; (2) time dependent, because decisions must be made at the correct moment in relation to environmental demands; and (3) complex, in the sense that most variables are not related to each other in a one-to-one manner. In these situations, the problem requires not one decision, but a long series, in which early decisions condition later ones. For a task that is changing continuously, the same action can be definitive at moment t1 and useless at moment t2.

Some researchers believe that complex problem solving competency may not an extension of general problem-solving process to complex situation; rather it is a separate competency (OECD, 2003).

Troubleshooting – A special Case of Complex Problem Solving

With technological advances, more and more complex problems surfaced which are technical in nature. Troubleshooting is a “special case” of larger field of complex problem solving, mostly in technical domain, which refers to searching the most likely cause of a fault in a larger set of possible causes (Schaafstal et al., 2000). Wikipedia state it as “a logical, systematic search for the source of a problem so that it can be solved, and so the product or process can be made operational again.” Troubleshooters then search for actions that will efficiently eliminate the discrepancy.

Within complex problem space, troubleshooting is also considered a separate construct in itself but highly integrated with CPS. In several instances of complex problems mainly in technical domain, the complex problem solving and troubleshooting works hand to hand. Though troubleshooting is seen to require highly specific strategies over and above general and complex problem solving.

Performance and Expertise in Complex Problem Solving and Troubleshooting

Complexity is one of the several factors which may result into several levels of performance for the same task and thus can affect how a person is deemed competent, proficient and expert. During learning, novice completes simple version of tasks and as skill increases he can move to more and more complex tasks. Acquiring more skills, the learner gains skill and he becomes skillful in more complex tasks and can process several factors at same time. Merrill, (2006) state that “adequate measurement of performance in complex real-world tasks requires that we can detect increments in performance demonstrating gradually increased skill in completing a whole complex task or solving a problem.”

Complex Problem solving and troubleshooting is a complex process which requires a range of cognitive and metacognitive skills to be used by the problem solver to identify and resolve a problem. Research has shown that there are several competencies and strategies which are used by the proficient problem solvers and those are generally acquired by them while working on the issues. Lyn (2011) lists the abilities learners need to deal with complex systems for success beyond the school:  “Such abilities include: constructing, describing, explaining, manipulating, and predicting complex systems; working on multi-phase and multi-component component projects in which planning, monitoring, and communicating are critical for success; and adapting rapidly toever-evolving conceptual tools (or complex artifacts) and resources (Gainsburg,2006; Lesh & Doerr, 2003; Lesh & Zawojewski, 2007)”.

Complex technical problem solving and troubleshooting remains complex, even for highly experienced individuals. However, experts have the advantage of experience. For example, expert troubleshooters have well-developed cognitive schemas and strategic knowledge than novices’ schemas do (Chi, Glaser, & Rees, 1982; Larkin, McDermott, Simon, & Simon, 1980).  When troubleshooting familiar systems, experts can use their prior knowledge they gained from experience. They form a schema of their mental representation during their experience. When faced with unfamiliar systems troubleshooting, their prior schema and mental representation help them to quickly develop a mental representation of that system faster than less experienced troubleshooters can (Egan & Schwartz, 1979). These sophisticated mental representations are used by proficient troubleshooters to reason why a system may not be working. There are several competencies and strategies which are used by the experienced problem solvers and those are generally acquired by them while working on the issues.

Also proficient troubleshooters have well developed metacognitive knowledge and tested strategies like structured approach to troubleshooting (Schaafstal et al., 2000). On the other hand the novices rely on weaker strategies which use domain-general heuristics (Sweller, 1988; Sweller et al., 1998).

Nevertheless, differences in novice vs. expert apart, the real organization challenge is how training experts in large organizations can develop expertise of their employees through training as proficient problem solvers to solve complex problems.

Tips for Teaching Complex Problem Solving and Troubleshooting

There is surmounting challenge when it comes to building proficiency in complex jobs involving complex tasks, Complex decisions and complex problem solving through training courses. Not only it requires trainers to deliver knowledge, skills and competencies required to solve real-world problems, but also at the same time needs to develop learners with strategies appropriate for that domain. Historically, most of the traditional training models assumed solving all problems in same way. The recent theories have established that different context and different domains requires different approach to solve the problem. Thus solving same problem in two different situations or disciplines may altogether be different (Mayer, 1992; Sternberg & Frensch, 1991).

Hung (2009) quoted on how current training strategies are not working, “Traditional pedagogies, such as lecturing and demonstrating solutions to problems, very often result in students being capable of solving “textbook problems,” but unable to apply the knowledge to solve real life problems” (Brown, Collins, & Duguid, 1989; Mayer, 1996; Perkins & Salomon, 1989).

Let me address a core tip in teaching problem solving and troubleshooting in next post.

REFERENCES

  1. Brown, J. S., Collins, A., & Duguid, P. (1989). Situated cognition and the culture of learning. Educational Researcher, 18, 32–42.
  2. Chi, M. T. H., Glaser, R., & Rees, E. (1982). Expertise in problem solving. In R. J. Sternberg (Ed.), Advances in the psychology of human intelligence, Vol. 1 (pp. 7-76). Hillsdale, NJ: Erlbaum.
  3. Egan, D. E., & Schwartz, B. J. (1979). Chunking in recall of symbolic drawings. Memory and Cognition, 7, 149-158.
  4. Frensch, P. A., & Funke, J. (Eds.). (1995b). Complex problem solving: The European Perspective. Hillsdale, NJ: Lawrence Erlbaum Associates.
  5. Hung, W., Jonassen, D. H., & Liu, R. (2008). Problem-based learning. In J. M. Spector, M. D. MerrillJ. van Merriënboer, & M. P. Driscoll (Eds.), Handbook of research on educational communications and technology (pp. 441–456). New York: Routledge.
  6. Jonassen, D. (2000), Nature of Problem Solving, Centre for the study of Problem Solving, available at http://csps.missouri.edu/proposal.php
  7. Larkin, J., McDermott, J., Simon, D. P., & Simon, H. A. (1980). Expert and novice performance in solving physics problems. Science, 208, 1335- 1342.
  8. Mayer, R. E. (1992). Thinking, problem solving, cognition (2nd ed). New York: Freeman
  9. Mayer, R. E. (1996). Learning strategies for making sense out of expository text: the SOI model for guiding three cognitive processes in knowledge construction. Educational Psychology Review, 8, 357–371.
  10. OECD. (2003b). The definition and selection of competencies (DeSeCo): Executive Summary of the final report. Paris: OECD. cd.org/dataoecd/47/61/35070367.pdf
  11. Onetoonline available at http://www.onetonline.org/find/descriptor/result/2.B.2.i
  12. Perkins D N, Salomon G 1989 Are cognitive skills context bound? Educational Researcher 18 (1): 16-25.
  13. Quesada, J., W. Kintsch, and E. Gómez Milán (2005) “Complex problem solving: A field in search of a definition?,” Theoretical issues in Ergonomics Sciences (6) 1, pp. 5-33
  14. Schaafstal, A., Schraagen, J. M., & Van Berlo, M. (2000). Cognitive task analysis and innovation of training: The case of structured troubleshooting. Human Factors, 42,75-86.
  15. Sternberg, R. J., & Frensch, P. A. (Eds.). (1991). Complex problem solving: Principles and mechanisms. Hillsdale, NJ: Lawrence Erlbaum Associates.
  16. Sweller, J. (1988). Cognitive load during problem solving: Effects on learning. Cognitive Science, 12, 257-285.
  17. Sweller, J., Van Merrie¨nboer, J. J. G., & Paas, F. (1998). Cognitive architecture and instructional design. Educational Psychology Review, 10, 251-295.
  18. Xu, J., G. Alan Wang, G.A., Li, J., Michael Chau, M., (2007), Complex Problem Solving: Identity Matching Based on Social Contextual Information, Journal of the Association of Information System, Volume 8, Issue 10, Article 2, pp. 525-545

 Image Credit: Stuart Miles @ freeDigitalPhotos.net

 

About Raman K. Attri

Raman K. Attri is a complex learning strategist, a transformational training consultant and a researcher with over 20 years of experience in engineering, management and technical training. His primary area of focus is to provide strategic directions to organizations in implementing next-generation competitive training strategies. His research interests include complex learning, accelerated expertise and advanced instructional design. He is also the founder of Personal Resonance©, a research forum with a charter to transform proven research studies on accelerated expertise into organizational training practices. His training and learning solutions are strongly founded in system engineering techniques applied to large-scale training programs. Equipped with scientific training methods, he innovated two research-backed complex learning frameworks namely SEAT© (Systems Engineering Approach to Training) and ProBT© (Proficiency Based Training) methodology primarily meant for organizations to accelerate development of complex cognitive skills of their employees systematically at faster rate. He is highly passionate about learning. He holds Professional Doctorate in Corporate Training, MBA in Operations Management and Executive MBA in Customer Relationship Management. Currently he is pursuing another Doctorate degree from Southern Cross University. His personal interests involve writing and painting.
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