Using the expectancy value model of motivation to understand the relationship between student attitudes and achievement in statistics
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Author(s)
Hood, M
Creed, PA
Neumann, DL
Year published
2012
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We tested a model of the relationship between attitudes toward statistics and achievement based on Eccles' Expectancy Value Model (1983). Participants (n = 149; 83% female) were second-year Australian university students in a psychology statistics course (mean age = 23.36 years, SD = 7.94 years). We obtained demographic details, past performance, attitudes, and expectancies in Week 2, and attendance records (effort) and course marks (achievement) at the end of semester. Path analysis was conducted via AMOS 19. The final model fit well and explained 40% of the variance in achievement. Past performance (22%), effort (8%), and ...
View more >We tested a model of the relationship between attitudes toward statistics and achievement based on Eccles' Expectancy Value Model (1983). Participants (n = 149; 83% female) were second-year Australian university students in a psychology statistics course (mean age = 23.36 years, SD = 7.94 years). We obtained demographic details, past performance, attitudes, and expectancies in Week 2, and attendance records (effort) and course marks (achievement) at the end of semester. Path analysis was conducted via AMOS 19. The final model fit well and explained 40% of the variance in achievement. Past performance (22%), effort (8%), and expectancies (2%) made significant direct contributions. There were significant indirect contributions by each attitude component. Cognitive competence made the largest indirect contribution.
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View more >We tested a model of the relationship between attitudes toward statistics and achievement based on Eccles' Expectancy Value Model (1983). Participants (n = 149; 83% female) were second-year Australian university students in a psychology statistics course (mean age = 23.36 years, SD = 7.94 years). We obtained demographic details, past performance, attitudes, and expectancies in Week 2, and attendance records (effort) and course marks (achievement) at the end of semester. Path analysis was conducted via AMOS 19. The final model fit well and explained 40% of the variance in achievement. Past performance (22%), effort (8%), and expectancies (2%) made significant direct contributions. There were significant indirect contributions by each attitude component. Cognitive competence made the largest indirect contribution.
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Journal Title
Statistics Education Research Journal
Volume
11
Issue
2
Publisher URI
Copyright Statement
© 2012 International Association of Statistics Education. This is an electronic version of an article published in Statistics Education Research Journal, Vol.11 (2), pp.72-85, 2012. Statistics Education Research Journal is available online at: http://iase-web.org/Publications.php?p=SERJ with the open URL of your article.
Subject
Mathematical sciences
Education
Educational psychology