written by Steven F. Wolf, Daniel P. Dougherty, and Gerd Kortemeyer

Since it was first published 30 years ago, the seminal paper of Chi et al. on expert and novice categorization of introductory problems led to a plethora of follow-up studies within and outside of the area of physics. These studies frequently encompass "card-sorting" exercises whereby the participants group problems. While this technique certainly allows insights into problem solving approaches, simple descriptive statistics more often than not fail to find significant differences between experts and novices. In moving beyond descriptive statistics, we describe a novel microscopic approach that takes into account the individual identity of the cards and uses graph theory and models to visualize, analyze, and interpret problem categorization experiments. We apply these methods to an introductory physics (mechanics) problem categorization experiment, and find that most of the variation in sorting outcome is not due to the sorter being an expert versus a novice, but rather due to an independent characteristic that we named "stacker" versus "spreader." The fact that the expert-novice distinction only accounts for a smaller amount of the variation may explain the frequent null results when conducting these experiments.

• Download PhysRevSTPER.8.010124.pdf - 956kb Adobe PDF Document

Released under a Published by the American Physical Society under the terms of the Creative Commons Attribution 3.0 License. The appropriate citation is: S. Wolf, D. Dougherty, and G. Kortemeyer, Empirical approach to interpreting card-sorting data, Phys. Rev. ST Phys. Educ. Res. 8 (1), 010124 (2012), 10.1103/PhysRevSTPER.8.010124.

Published May 18, 2012
Last Modified May 20, 2012

This file is included in the full-text index.