Exploring progressive mental model representation of core physiology concepts in physician assistant students through word frequency and association analyses

Abstract

This study applies text mining, an artificial intelligence form of natural language processing, to evaluate a series of physiology student-written prompt completions. Text mining of student writing in physiology has not yet been reported in the literature. Through the application of this technique, longitudinal trends in student development of mental models of core concepts were identified and visualized through word frequency distributions and cluster dendrograms.