Candidate: Keith A. Schramm
Degree of: Doctor of Philosophy
Date: Friday, July 5, 2002, 11:00 a.m.
- 1:00 p.m.
The literature review is used to situate this research with respect to studies of the teaching of qualitative organic analysis, expertise in problem-solving, chemistry problem-solving, and physics problem-solving. Rationales for the use of a computer simulation, problem selection, methodology, and models for analysis are provided.
Each of the eleven qualitative organic analysis problems was solved in a computer simulated environment to allow for extensive problem-solving from the experts and to evaluate the simulation's ability to model the problem-solving environment. The data provided consisted of the typical instrumentation available to university undergraduate students, including infrared, proton nuclear magnetic resonance, carbon-13 nuclear magnetic resonance, and mass spectral data. Traditional wet chemistry data were also provided in the software, including solubility tests, fusion tests, classification tests, and derivatives. This data was included to evaluate the extent to which experts would solve problems using traditional methodology in contrast to solving problems by spectroscopic means only. Selected problems included a variety of functional groups and structures.
Declarative knowledge used by the subjects is explained. Differences in the approaches utilized by industrial chemists and academic chemists are analyzed. A procedural model of expert performance for qualitative organic analysis is presented. Three fundamental strategies pertaining to the use of the percent composition in problem-solving are described: initial strategy, revert to strategy, and a check strategy. Each strategy is included in the model.
The fundamental strategies related to the model of expert performance are used to provide a model of desired performance. This model provides an outline of how students might approach qualitative organic analysis problem-solving in a systematic fashion.
The ability of a computer environment to simulate the qualitative organic analysis problem-solving environment is discussed. Suggestions for improvements in the software are described.
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