Empirical Approach to Interpreting Card-Sorting Data
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| Title: | Empirical Approach to Interpreting Card-Sorting Data |
|---|---|
| Language: | English |
| Authors: | Wolf, Steven F., Dougherty, Daniel P., Kortemeyer, Gerd |
| Source: | Physical Review Special Topics - Physics Education Research. Jan-Jun 2012 8(1):010124. |
| Availability: | American Physical Society. One Physics Ellipse 4th Floor, College Park, MD 20740-3844. Tel: 301-209-3200; Fax: 301-209-0865; e-mail: assocpub@aps.org; Web site: http://prst-per.aps.org |
| Peer Reviewed: | Y |
| Page Count: | 15 |
| Publication Date: | 2012 |
| Document Type: | Journal Articles Reports - Evaluative |
| Education Level: | Higher Education |
| Descriptors: | Expertise, Mechanics (Physics), Classification, Science Education, Statistics, Problem Solving, Science Instruction, Experiments, College Students, College Faculty, Introductory Courses, Data Analysis |
| Geographic Terms: | Michigan |
| DOI: | 10.1103/PhysRevSTPER.8.010124 |
| ISSN: | 1554-9178 |
| Abstract: | 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 [Cogn. Sci. 5 121 (1981)]. 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. (Contains 12 figures and 2 tables.) |
| Abstractor: | As Provided |
| Number of References: | 26 |
| Entry Date: | 2012 |
| Accession Number: | EJ975385 |
| Database: | ERIC |
| Abstract: | 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 [Cogn. Sci. 5 121 (1981)]. 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. (Contains 12 figures and 2 tables.) |
|---|---|
| ISSN: | 1554-9178 |
| DOI: | 10.1103/PhysRevSTPER.8.010124 |
