30 Aug

Approach to curriculum

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The amount of freedom in the development of curriculum is strongly dependent on the specific course in question.

Courses like general chemistry have a large enrollment and serve many different majors. As a result, there is a need for a well-defined core of the topics presented in these courses and the expectations for student demonstration of mastery of these topics. There is relatively little freedom in the selection of topics. However, the ordering of topics and their relative emphases are still important issues to consider. In general, Prof. Talaga will often start with a concept map of the topics to determine their relative dependencies. From there, a linear ordering for the purpose of a course schedule can be imposed while properly maintaining any hierarchical requirements of the topics.

In general education courses like Chem 100 there is more flexibility as it is not a prerequisite for further studies. In this case I set about 60% of the core curriculum and then allow the students to select the remaining 40% from an a la carte list of relevant topics.

For 400 level “capstone” courses I select topics that include modern applications of the advanced topic that I judge to be most relevant to contemporary laboratory practices. For example Chem 447, Biophysical Chemistry, included significant material on hydrodynamics of macromolecules which may not always be included in an undergraduate course, but which are now routine measurements in biochemical and pharmaceutical laboratories. 

For 500 level graduate courses, my focus is on creating increased depth of understanding and developing tools and strategies for approaching more complicated problems that may not have well-defined answers. For example in Chem 540 Chemical Thermodynamics we  examine how a statistical approach to thermodynamics' two laws allows us to investigate the molecular basis of chemical properties like solubility, vapor pressure, surface tension, miscibility, equilibrium, phase separation, elasticity, ligand binding curves, cooperativity, polymer properties, protein folding, and more. Often in the laboratory we cannot conveniently measure the property we want to know; thermodynamics can allow us to convert the results of a convenient measurement to the inconvenient property we desire. Students in the course learn to use the software package Mathematica to derive and implement the formulas needed to make such conversions. Using those formulas in Mathematica students analyze analyze experimental data to illustrate and practice Thermodynamic analyses. 

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