AN EXPECTANCY VALUE THEORY PREDICTS ACHIEVEMENT IN UNDERGRADUATE STATISTICS THROUGH ACADEMIC DELAY OF GRATIFICATION

Q3 Social Sciences

Statistics Education Research Journal Pub Date : 2021-07-11 DOI:10.52041/SERJ.V19I2.109

Robert F Corwyn, Phillip P. McGarry

引用次数: 2

Abstract

We tested a model that integrates academic delay of gratification with Expectancy Value Theory to predict achievement in an undergraduate psychology and nursing statistics class at a metropolitan university in the southeastern United States. We analyzed measurements (n = 163: 80.4% female) of past performance, academic delay of gratification, effort, value, affect, and cognitive competence with students’ final exam score. The path model analyzed explained 14.9% of the variance in scores. Past performance inmathematics and student effort had direct effects on grades and all expectancy value theory constructs, as well as academic delay of gratification, were indirectly related to grades. We present details of our analysis and discuss theoretical and pedagogical implications of this study. First published June 2020 at Statistics Education Research Journal Archives

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期望值理论通过学业延迟满足预测本科生统计学成绩

我们测试了一个将学业延迟满足与期望值理论相结合的模型，以预测美国东南部一所大都市大学心理学和护理统计学本科生的成绩。我们分析了过去表现、学业延迟满足感、努力、价值观、情感和认知能力的测量结果（n=163:80.4%为女性）与学生期末考试成绩的关系。所分析的路径模型解释了14.9%的分数差异。过去的数学表现和学生的努力对成绩有直接影响，所有期望值理论结构以及学业延迟满足都与成绩间接相关。我们介绍了我们的分析细节，并讨论了这项研究的理论和教学意义。2020年6月首次发表在《统计教育研究期刊档案》

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来源期刊

Statistics Education Research Journal Social Sciences-Education

CiteScore

1.30

自引率

0.00%

发文量

期刊介绍： SERJ is a peer-reviewed electronic journal of the International Association for Statistical Education (IASE) and the International Statistical Institute (ISI). SERJ is published twice a year and is free. SERJ aims to advance research-based knowledge that can help to improve the teaching, learning, and understanding of statistics or probability at all educational levels and in both formal (classroom-based) and informal (out-of-classroom) contexts. Such research may examine, for example, cognitive, motivational, attitudinal, curricular, teaching-related, technology-related, organizational, or societal factors and processes that are related to the development and understanding of stochastic knowledge. In addition, research may focus on how people use or apply statistical and probabilistic information and ideas, broadly viewed. The Journal encourages the submission of quality papers related to the above goals, such as reports of original research (both quantitative and qualitative), integrative and critical reviews of research literature, analyses of research-based theoretical and methodological models, and other types of papers described in full in the Guidelines for Authors. All papers are reviewed internally by an Associate Editor or Editor, and are blind-reviewed by at least two external referees. Contributions in English are recommended. Contributions in French and Spanish will also be considered. A submitted paper must not have been published before or be under consideration for publication elsewhere.