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Sex Differences in Problem-Solving Strategies Used by High-Scoring Examinees on the SAT-M

Author(s):
Gallagher, Ann M.
Publication Year:
1992
Report Number:
CBR-92-02, RR-92-33
Source:
ETS Research Report
Document Type:
Report
Page Count:
35
Subject/Key Words:
650 Scores College Board Gifted Item Analysis Mathematics Achievement Problem Solving Scholastic Aptitude Test (SAT) Sex Differences

Abstract

An item classification scheme developed by Gallagher (1990) was refined, resulting in a more accurate prediction of sex differences in performance on the mathematical sections of the College Board's Scholastic Aptitude Test (SAT). When Differential Item Functioning (DIF) procedures were performed on item data for examinees scoring above 650, the majority of items that were flagged as favoring males required the use of mathematical insight, whereas all the items flagged as favoring females required standard algorithmic solutions. Structured interviews were conducted with students (25 males and 22 females) in this score range to determine the nature of differences in strategy use. A classification scheme was developed for strategies that paralleled the item classification categories. There was substantial overlap in strategies used by males and females; however, analyses of strategy types used across all items indicated that females were more likely than males to use algorithmic strategies and males were more likely than females to use insightful strategies. It should be noted that these findings constitute a generalization across a group of subjects and items, and that there were several individual instances of males using more algorithmic strategies than females and females using more insightful strategies than males. Questionnaire data gathered from students who participated in interviews indicated a positive relationship for both males and females between SAT-mathematical performance and positive attitudes toward mathematics (e.g., liking mathematics as a subject and recognizing its usefulness to their adult lives). The use of algorithmic strategies, however, was correlated with negative attitudes toward mathematics (e.g., mathematics being difficult and not being relevant to their lives). Implications of these and other findings are discussed. (35pp.)

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