Using IMMEX as an Alternative to Laboratory Exams Charlie Cox, Presenter Melanie M. Cooper Ron Stevens Rebecca Pease Valerie Smith
What is IMMEX? Internet - Based Software Designed at UCLA Medical School Case - Based Problems
IMMEX Problems Prolog Problem Space HTML Tracking Ability Dialog Boxes
Prolog Screen Shot
Problem Space
Search Path Maps
Assessment Techniques Artificial Neural Networks Hidden Markov Modeling Item Response Theory
Artifical Neural Networks Pattern Recognition Groups similar strategies Represented using Nodes
Node Description Problem Space Item PROBABILITYPROBABILITY Background Flame, Solubility, Conductivity Litmus HCl, NaOH Precipitins
6 x 6 Node Description
Hidden Markov Models Predictive Modeling More simplistic than nodes Described using five states
Hidden Markov Models (HMMs)
Item Response Theory Separates latent abilities from item characteristics. Model:
Laboratory Problems Separation Hazmat TLC Finding Carbons Neighbors Spectra Analysis
Separations
Solved Separation
Finding Carbons Neighbors Chemical Tests Physical Tests Library
Chromatography Challenge Unknown identification based upon TLC analyses.
Spectra Analysis 1 H, 13 C, IR, and MS data is available for students to elucidate an unknown’s structure.
1 H NMR Spectra
Other Features 1.Example Spectra a. Benzaldehyde b. 2-butanone c. Benzene d. Butylamine e. Propionic Acid 2.Correlation Tables 3. Library
Implementation Second semester organic laboratory. Used as part of the laboratory practical (50%) Students are told to answer 4 cases correctly with a guessing penalty.