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    Intersectional identity: factors impacting student odds of first semester STEM major declaration
    (Montana State University - Bozeman, College of Education, Health & Human Development, 2023) Jacobs, Jonathan Daniel; Chairperson, Graduate Committee: Lauren Davis
    Though there is a large amount of literature on those who graduate from college with STEM degrees, there is a dearth of literature involving intersectional identity of college freshman who are considering entering STEM majors. This study seeks to begin the process of meeting the gaps in research. Data from the High School Longitudinal Study of 2009 (HSLS:2009) were analyzed using logistic regression; using listwise deletion, intersectional identities which impact odds of student declaring a STEM major were identified. Student race and ethnicity, student sex, student socio-economic status, teacher race and ethnicity, teacher sex, science utility, science interest, science self-efficacy, and science identity were the components of intersectional identity for this study. Student race, student socio-economic status, science self-efficacy, and science identity were statistically significant factors that increased student odds of entering college with as STEM degree (p<0.001). Students who were Asian had a statistically significant increase in odds over White students to enter college with a STEM degree. All other aspects of identity were not statistically significant. More research is needed in this field to gain a deeper understanding of how intersectional identity impacts a students' odds of declaring a STEM majors their first semester in college.
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    Self-efficacy, student engagement, and student learning in introductory statistics
    (Montana State University - Bozeman, College of Education, Health & Human Development, 2017) Lindsey, Heidi L.; Chairperson, Graduate Committee: Arthur W. Bangert
    Close to half of undergraduate students in the United States are served by community colleges. Minority, low income, and first-generation postsecondary education students utilize community colleges as a gateway to postsecondary education. Additionally, these institutions provide access to higher education for many nontraditional students, such as adults who work full time while enrolled. This study used partial least squares structural equation modeling (PLS SEM) to investigate and explore the relationship between community college student self-efficacy, engagement, and statistics conceptual understanding in the non-mathematical introductory statistics course and is based on Linninbrink & Pintrich's (2003) model for conceptual understanding. There is much research regarding statistics anxiety, statistics attitude, learning behavior, and statistics achievement where students at four year institutions or graduate students were studied, but few if any studies exist that investigate these same factors with community college students. Data for this study was collected from n=161 student volunteers at three different time points during the semester using all or a subset of the following instruments: Current Statistics Self Efficacy (CSSE) (Finney & Schraw, 2003), Survey of Attitudes Toward Statistics (SATS) (Schau, Steven, Sauphinee, & Del Vecchio, 2995), Motivated Strategies for Learning Questionnaire (MSLQ) (Pintrich, Smith, Garcia, & McKeachie, 1993), and Comprehensive Assessment of Outcomes in Statistics (CAOS) (delMas, Garfield, Ooms, & Chance, 2007). Problems with missing data were resolved with multiple imputation methods to preserve power and sample size and prevent introducing bias into the analysis. Overall, the relationships of self-efficacy and engagement explained R2=7.6% of the variance in conceptual understanding of statistics. This study found positive relationships between student conceptual understanding of statistics, selfefficacy to learn statistics and student engagement. Behavioral and cognitive engagement did not appear to mediate the influence of self-efficacy but motivational engagement was found to mediate this effect. Additionally, it was found that self-efficacy to learn statistics had a medium effect on statistical understanding at course end. Suggestions for future research are given.
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    Understanding of statistical data analysis among elementary education majors
    (Montana State University - Bozeman, College of Education, Health & Human Development, 2000) Thomas, Cynthia Skillingberg
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