Crawley, Alisha M.

Shapiro, Faculty Advisor, Lionel R.

Digital Commons @ Illinois Wesleyan University

Illinois Wesleyan UniversityDigital Commons @ IWUJohn Wesley Powell Student ResearchConference 1995, 6th Annual JWP ConferenceApr 22nd, 10:00 AM - 4:00 PMError Recognition in Calculus Problems: WhatCharacterizes Expertise?Alisha M. CrawleyIllinois Wesleyan UniversityLionel R. Shapiro, Faculty AdvisorIllinois Wesleyan UniversityFollow this and additional works at: http://digitalcommons.iwu.edu/jwprcThis Event is brought to you for free and open access by The Ames Library, the Andrew W. Mellon Center for Curricular and FacultyDevelopment, the Office of the Provost and the Office of the President. It has been accepted for inclusion in Digital Commons @ IWU bythe faculty at Illinois Wesleyan University. For more information, please contact digitalcommons@iwu.edu.©Copyright is owned by the author of this document.Alisha M. Crawley and Lionel R. Shapiro, Faculty Advisor, "Error Recognition in Calculus Problems: What CharacterizesExpertise?" (April 22, 1995). John Wesley Powell Student Research Conference. Paper 30.http://digitalcommons.iwu.edu/jwprc/1995/posters/30ERROR RECOGNITION IN CALCULUS PROBLEMS: WHAT CHARACTERIZES EXPERTISE? Alisha M. Crawley and Lionel R. Shapiro*, Department of Psychology, IWU Previous research in the area of expert-novice comparisons of mathematical problem solving has focused on the differences in categorization of and performance on math problems. These studies have led to the conclusion that while solving or categorizing problems, experts focus on deep processing and novices focus on surface structure. Other research dealing with true/false multiplication equations has shown that adults (considered experts in multiplication) can reject false answers before processing the equation. This study attempts to extend these findings by looking at the differences between experts and novices in the recognition of errors in true/false calculus verification expressions. The participants were professors (experts) and two groups of math students (novices). The experiment consisted of participants answering 76 true/false calculus expressions (equations or conditionals) at three levels of difficulty. Reaction time, accuracy, and level of confidence were recorded. Data was analyzed using a 3 x 3 x 2 x 2 (experience level by problem difficulty by problem type by truth value) ANOV A. Based on the previous studies, experts are expected to be able to process errors at a faster rate. This will provide further support for the hypothesis that experts are not only quantitatively better at task performance, but qualitatively different from novices in the type of processing they employ. Results and implications will be discussed. 

Error Recognition in Calculus Problems: What Characterizes Expertise?

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Error Recognition in Calculus Problems: What Characterizes Expertise?

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