Implicit knowledge in complex system control

What does it take to be a successful manager or politician? In Psychology, tasks that these groups face on an everyday basis are called complex problems. Complex problems are characterized by their dynamics (the system that is being altered during problem solving is constantly changing on its own), by the fact that multiple goals have to be achieved at the same time and by their network structure: changes to one variable usually lead to changes of other variables as well.
Experimental Psychology simulates complex problems with computer-simulated dynamic scenarios, also referred to as microworlds; computer games that place the subject into the role of a manager of a factory or a mayor of a small city. Over a simulated period of time, the subject has to improve some target value (e.g. factory profit or item sales) and has a variety of variables that he can change for influencing the system (e.g. number of machines, number of employees, wages, welfare, advertising budget etc).
The current state of research argues that it does not require a special skill for complex problem solving, but that complex problem solving ability is determined by a person's intelligence, especially his/her ability to process information, and by a person's knowledge of the problem domain, i.e. structure of the system. However, research has also shown that with longer experience of system control, subjects tend to show better problem solving abilities without showing an increase in verbalizable knowledge. The question whether this was a sign for implicit knowledge or just some artifact has been heavily debated.
In my experiment, I devided my subjects in two groups. One group learned how to control a complex scenario from texts, the other group also and learned from texts and was able to try out the scenario during the learning period. Both groups scored equal in a post-learning test for verbalizable system knowledge, but the group that had experience with the szenario performed better during actual scenario control. This dissociation between verbalizable knowledge and increased scenario performance is a clear indication for the development of implicit knowledge.
On top of that, the group with experience learning showed a higher density in knowledge organization in my Association Structure Test (AST). This supports my theory that implicit knowledge correlates with a higher density in knowledge organization (which can be found here).

My PhD thesis

Time to sum up the process. Since updating my page at the institute is so cumbersome, I can as well do it in my blog. My PhD thesis is about knowledge: what it is, how it's represented and how to measure it. It is also about how knowledge influences performance and how knowledge overlap in groups affects group performance. I don't really have a catchy title yet but it will be something like 'structural knowledge assessment and knowledge-related determinants of performance in complex problem solving' or something similar. It basically consists of the following parts:

1. What is knowledge and how is it conceptualized in the field of knowledge management? I've written a paper with Kozo Sugiyama on this, it will appear in the February issue of the Journal of Knowledge Management. One of its core assumptions is that unconscious access to structural knowledge is part of individual implicit memory.

2. Based on that assumption, I developed a computer-based psychometric test, the association structure test, that derives a knowledge graph for a given stimulus based on free term associations and reaction times. Unfortunately, it doesn't work quite as good as I expected as I explain in a paper that I successfully submitted to the WM2007 conference. I am also co-chairing the workshop on new approaches for implicit knowledge in knowledge management (NAIK2007) with Wolfgang Scholl at WM2007.

3. Based on structural assumptions from (1), I have developed a similarity algorithm for the skillMap. The skillMap started as a Knowledge Management System envisioned by Dr. Sarah Spiekermann and I have contributed to its actual design and development. There is an own post on that project, but the algorithm calculates a similarity measure between persons based on their knowledge self-assessment. That seems to work pretty good, but I currently cannot publish anything on this as we're trying to spin off a company and sell the technology.

4. Prof. Scholl, the supervisor of my PhD, formulated some theories on how knowledge overlap inside teams influences their performance. Hy says that there is a second-order polynomial connection between cognitive similarities of team members, knowledge increase and performance. I was able to validate his claim with an experiment I conducted in summer 2006. The paper on this is completed and I am currently waiting on his feedback prior to submitting it.

I hope to turn it in in June...