How do we model and improve technical problem solving, such as network subnetting? This paper reports an experimental study that tested several hypotheses derived from Kolb's experiential learning cycle and Huber's problem solving model. As subjects solved a network subnetting problem, they mapped their mental processes according to Huber's problem solving stages by tapping a keypad. Based on Kolb's model, concrete and abstract representations of the subnetting problems were tested to determine whether the form of the problem representation improved performance. For subjects for whom full process data was available, nine of the ten hypotheses were supported. A partial least squares model was developed which explained 27.5 percent of the variance in performance with three predictors. Two of the three predictors for performance were from the Kolb side of the integrated model, whereas the third predictor was from the Huber side. We draw some implications for research and practice, based on the integrated model to explain performance. We conclude that technical problem solving can be modeled as an integration of Kolb's experiential learning cycle and Huber's stages of problem solving. Additional research is needed to extend Kolb's cycle and Huber's stages to other knowledge intensive problem solving domains and to a more diverse set of problem solvers.
Kamis, Arnold and Khan, Beverly K.
"Synthesizing Huber's Problem Solving and Kolb's Learning Cycle: A Balanced Approach to Technical Problem Solving,"
Journal of Information Systems Education: Vol. 20
, Article 10.
Available at: https://aisel.aisnet.org/jise/vol20/iss1/10