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Statistics Related Self-Efficacy A Confirmatory Factor Analysis Demonstrating a Significant Link to Prior Mathematics Experiences for Graduate Level Students

机译:与统计相关的自我效能-验证性因子分析表明与研究生水平的过往数学经验有着重要的联系

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The present study examined students' statistics-related self-efficacy, as measured with the current statistics self-efficacy (CSSE) inventory developed by Finney and Schraw (2003). Structural equation modeling was used to check the confirmatory factor analysis of the one-dimensional factor of CSSE. Once confirmed, this factor was used to test whether a significant link to prior mathematics experiences exists. Additionally a new post-structural equation modeling (SEM) application was employed to compute error-free latent variable score for CSSE in an effort to examine the ancillary effects of gender, age, ethnicity, department, degree level, hours completed, expected course grade, number of college-level math classes, current GPA on students' CSSE scores. Results support the one-dimensional construct and as expected, the model demonstrated a significant link between CSSE scores and prior mathematics experiences to CSSE. Additionally the students' department, expected grade, and number of prior math classes were found to have a significant effect on student's CSSE scores.
机译:本研究考察了学生的与统计相关的自我效能感,并根据Finney和Schraw(2003)编制的当前统计自我效能感(CSSE)清单进行了测量。利用结构方程模型对CSSE的一维因子进行了验证性因子分析。一旦确定,将使用该因子来测试是否存在与先前数学经验的重要联系。此外,还采用了新的后结构方程模型(SEM)应用程序来计算CSSE的无错误潜在变量评分,以检查性别,年龄,种族,部门,学位程度,完成时间,预期课程成绩的辅助影响,大学数学课程的数量,当前学生CSSE得分的GPA。结果支持一维结构,并且正如预期的那样,该模型证明CSSE分数与CSSE的先验数学经验之间存在显着联系。此外,还发现学生的系,期望的成绩和先前的数学课程数量对学生的CSSE分数有重大影响。

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