解释卡片分类数据的经验方法
An empirical approach to interpreting card-sorting data
摘要：
自30年前首次发表以来，Chi et al.的开创性的论文专家和新手分类的介绍性问题，导致了过多的后续研究领域内外的物理[池等认知科学5，121 - 152（1981）]。这些研究通常包括“卡片分类”练习，参与者将问题分组。虽然这种技术确实可以洞察解决问题的方法，但简单的描述性统计往往无法找到专家和新手之间的显着差异。在超越描述性统计，我们描述了一种新的微观方法，考虑到卡的个人身份，并使用图论和模型来可视化，分析和解释问题分类实验。我们将这些方法应用到一个介绍性的物理（力学）问题分类实验中，发现分类结果的大部分变化不是由于分类器是专家还是新手，而是由于一个独立的特征，我们称之为“堆叠器”与“散布器”。“专家-新手的区别只占较小的变化量，这一事实可以解释在进行这些实验时频繁出现的零结果。
英文摘要：
Since it was first published 30 years ago, Chi et al.'s seminal paper on expert and novice categorization of introductory problems led to a plethora of follow-up studies within and outside of the area of physics [Chi et al. Cognitive Science 5, 121 - 152 (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 interpreting 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.
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