This Guest paper series was originally published by the Cutter Consortium Agile Product & Project Management Advisory Service in 2009. It is reproduced here, with permission from the publishers (

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Part 2 published here October 2014.

PART 1 | Introduction | "Higher" Higher-Order Thinking Skills
Aligning the Organization's Educational Infrastructure | Conclusions | PART 3

"Higher" Higher-Order Thinking Skills

Teaching someone the finer points of programming practice represents a significantly easier task than teaching some of the other skills used in delivering a technology project. While programming practices can be clearly captured and discussed based on physical examples of code, skills such as project management involve subjective issues that are less visible and less easily measured.

That difficulty is reflected in much of the current training for project managers. A significant portion of the commonly available project management training focuses on the relatively easy to train tools, techniques, and methodologies of project management (the so-called science of project management) rather than the more advanced topics and soft skills (the "art" of project management).

Even advanced training often does little to bridge the gap, and I've seen a number of so-called advanced project management courses that do little more than delve into tools, techniques, and methodologies in a deeper way than introductory training is able to do. In many cases, that advanced training is of little value because the focus on processes and tools again centers on the lower levels of Bloom's Taxonomy and does little to help participants develop the higher-order thinking skills that are the essential core of becoming an expert in project management.

In part, this focus on the lower levels of Bloom's Taxonomy is because of the difficulty of codifying more advanced layers of project management knowledge. How do we express such information in a way that it can be shared in a format suitable for training? While sports teams can set up realistic drills that emulate real play and can videotape complete games for detailed analysis, such methods are less viable in the context of something like project management.

The good news is that new tools are beginning to take hold that can help organizations address that problem. One particularly useful tool that is being adopted in a number of fields is the use of pattern languages. Christopher Alexander, professor emeritus at Berkeley University in California, first proposed the concept of a pattern language.[8] His work in architectural design led him to the idea that successful designs often used repeated patterns.

By understanding and documenting those patterns, they can be used as a training vehicle to help others develop skills more quickly than if they had to experience the trial and error of discovering the patterns themselves. It is interesting to note that the identification of patterns and subsequent recognition of similar events is a key component of Klein's definition of expertise. Thus it is easy to see how the use of patterns as a learning tool can help bridge the gap to higher-order thinking skills.

Pattern theory and the documentation of patterns have become mainstream ideas in a number of fields. The most well known is the design of IT architectures. The growth of the field and the value it brings has seen the concept applied not just to design, but to other areas as well (e.g., patterns of behavior, patterns of collaboration, and decision-making patterns).

To complement patterns of behaviors or events that lead to success, some groups are now also exploring so-called anti-patterns. Anti-patterns represent the patterns of destructive behavior or common problems that lead to project failure. The DAFT model itself could be considered an anti-pattern in the management domain, and common online repositories such as Wikipedia have more extensive lists.

The field of identifying patterns that apply to project management is relatively new, although a body of knowledge is beginning to develop. Through the study of both successful and failed projects, clear patterns can be distilled. The use of these patterns provides a platform from which individuals can be trained. It also provides a vehicle to allow participants to reflect on their own experiences and isolate out the sequences of decisions and events that lead to certain outcomes (be they positive or negative).

A second field of study that holds great value is the field of systems dynamics. Systems dynamics is the study of the cause-and-effect relationships and feedback loops that exist within complex systems. Thanks to the interaction among people, time, budget, and other factors, a project can be considered a complex system.

By modeling the factors that affect project outcomes, a dynamic picture of the mechanics that drive events in a project can be built. Again, such models directly support Klein's definition of expertise. By allowing us to understand the inner workings of a project and the chains of events that lead to certain outcomes, dynamic models can play a significant role in helping develop the insights needed to improve levels of expertise.

Patterns and dynamic models can be used in combination to help build simulations of a project. Such simulations allow hands-on participation and experimentation that again helps reinforce messages. The combined use of simulations, patterns, and dynamic models directly supports the natural processes by which people develop expertise. It also offers a realistic option for organizations in their efforts to deepen the levels of project management expertise within their ranks.

Introduction  Introduction

8. Alexander, Christopher, Notes on the Synthesis of Form, Harvard University Press, 1964.
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