EVALUATING MODELING TECHNIQUES BASED ON MODELS OF LEARNING.

While there are many techniques for systems analysis, there are a few methods or tools for comparative evaluations of the techniques. The article addresses the principles of systems analysis, suggesting combined theoretical and empirical approaches to assess technique performance. Users of model techniques, like systems analysts and software engineers construct understanding from models using prior experience, so the information represented is not necessarily information understood. The paper also presents a framework for empirical comparisons of modeling techniques in systems analysis based on a model of the learning process. Following this approach, the knowledge acquired by a user of the systems analysis model can be evaluated using a problem-solving task, where the solutions are not directly represented in the model. There are three steps to evaluate modeling techniques. First is to establish whether are differences in grammars among the techniques. Second is to suggest why these differences might lead to differences in grammar performance, and lastly is to perform observations to assess grammar performance. The first two can be based on theoretical considerations. The third requires cognitive approaches to explain performance differences and establish empirical procedures to measure whether or not the differences exist.