Abstract

The ability to categorize problems based upon underlying principles, rather than surface features or contexts, is considered one of several proxy predictors of expertise in problem solving. With inspiration from the classic study by Chi, Feltovich, and Glaser, we assess the distribution of expertise among introductory physics students by asking three introductory physics classes, each with more than a hundred students, to categorize mechanics problems based upon similarity of solution. We compare their categorization with those of physics graduate students and faculty members. To evaluate the effect of problem context on students' ability to categorize, two sets of problems were developed for categorization. Some problems in one set included those available from the prior study by Chi et al. We find a large overlap between calculus-based introductory students and graduate students with regard to their categorizations that were assessed as "good." Our findings, which contrast with those of Chi et al., suggest that there is a wide distribution of expertise in mechanics among introductory and graduate students. Although the categorization task is conceptual, introductory students in the calculus-based course performed better than those in the algebra-based course. Qualitative trends in categorization of problems are similar between the non-Chi problems and problems available from the Chi study used in our study although the Chi problems used are more difficult on average.

Highlights

  • The nature of expertise and the transition from novice to expert is of interest to many researchers and practitioners

  • If a faculty member rated a category created by an introductory student as good, we asked that they cross out the questions that did not belong to that category

  • Two versions of the problem sets were used in the study to investigate the impact of specific contexts of questions on categorization, with one version including the seven problems that were available from the Chi study

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Summary

Introduction

The nature of expertise and the transition from novice to expert is of interest to many researchers and practitioners. While many cognitive scientists and education researchers have focused on unraveling the nature of expertise, the community is still struggling with various facets of expertise [1,2,3,4,5,6,7,8,9,10]. These facets include identification of characteristics that are predictors of expertise, how expertise develops, and whether this development is a gradual process or whether there are major boosts along the way in development as a result of certain types of exposure or scaffolding supports [11,12,13,14,15,16,17,18,19,20].

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