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A Multi-Level Analysis of the Effects of Statistics Anxiety/Attitudes on Trajectories of Exam Scores
MacArthur, Kelly Rhea; Santo, Jonathan B. – Journal of Statistics and Data Science Education, 2023
This study explores three understudied facets--quadratic effects, change over time, and gender as a moderator--of the otherwise well-documented relationships between statistics anxiety and academic performance. Using pre- and post- course survey data among a sample of 111 undergraduate students in Social Statistics courses at a U.S. Midwestern…
Descriptors: Hierarchical Linear Modeling, Mathematics Anxiety, Statistics Education, Student Attitudes
William Parker Morgan IV – ProQuest LLC, 2020
Accurate placement into an initial college mathematics course is a key step toward the successful completion of college mathematics and, eventually, a college degree. Conversely, misplacement in mathematics may lead to a reduced likelihood of course completion and degree attainment. This study investigated the ability of two placement models to…
Descriptors: College Mathematics, College Students, Student Placement, Mathematics Achievement
Harwell, Michael; Moreno, Mario; Post, Thomas – Journal of Psychoeducational Assessment, 2016
This study examined the relationship between the American College Testing (ACT) college mathematics readiness standard and college mathematics achievement using a sample of students who met or exceeded the minimum 3 years high school mathematics coursework recommended by ACT. According to ACT, a student who scores 22 or higher on the ACT…
Descriptors: College Entrance Examinations, Mathematics Tests, College Mathematics, College Readiness
Moreno, Mario; Harwell, Michael; Guzey, S. Selcen; Phillips, Alison; Moore, Tamara J. – School Science and Mathematics, 2016
Hierarchical linear models have become a familiar method for accounting for a hierarchical data structure in studies of science and mathematics achievement. This paper illustrates the use of cross-classified random effects models (CCREMs), which are likely less familiar. The defining characteristic of CCREMs is a hierarchical data structure…
Descriptors: Mathematics Achievement, Mathematics Instruction, Hierarchical Linear Modeling, Mathematics Curriculum
Chance, Beth; Wong, Jimmy; Tintle, Nathan – Journal of Statistics Education, 2016
"Simulation-based inference" (e.g., bootstrapping and randomization tests) has been advocated recently with the goal of improving student understanding of statistical inference, as well as the statistical investigative process as a whole. Preliminary assessment data have been largely positive. This article describes the analysis of the…
Descriptors: Statistical Inference, Simulation, College Mathematics, Statistics
Mao, Yi; White, Tyreke; Sadler, Philip M.; Sonnert, Gerhard – Educational Studies in Mathematics, 2017
This study investigates how the use of calculators during high school mathematics courses is associated with student performance in introductory college calculus courses in the USA. Data were drawn from a nationally representative sample of 7087 students enrolled in college calculus at 134 colleges and universities. They included information about…
Descriptors: Calculators, Technology Uses in Education, Mathematics Achievement, Mathematics Education
Crisp, Gloria; Reyes, Nicole Alia Salis; Doran, Erin – Journal of Hispanic Higher Education, 2017
This study examines Latina/o students' remedial math needs and outcomes. Data were drawn from a national sample of Latina/o students. Hierarchical generalized linear modeling techniques were used to predict three successful remediation outcomes. Results highlight the importance of providing financial aid and academic support to Latina/o students,…
Descriptors: Predictor Variables, Mathematics Achievement, Remedial Mathematics, Hispanic American Students
Wade, Carol H.; Sonnert, Gerhard; Sadler, Philip M.; Hazari, Zahra – American Secondary Education, 2017
Using data from the first National study on high school preparation for college calculus success, the Factors Influencing College Success in Mathematics (FICSMath) project, this article connects student high school instructional experiences to college calculus performance. The findings reported here reveal that students were better prepared for…
Descriptors: Transitional Programs, Secondary School Mathematics, College Mathematics, Calculus
Lee, Ahlam – Educational Research and Evaluation, 2015
Among the disciplines of science, technology, engineering, and math (STEM), much attention has been paid to the influences of math- and science-related learning contexts on students' STEM major selection. However, the technology and engineering learning contexts that are linked to STEM major selection have been overlooked. In response, a…
Descriptors: STEM Education, Majors (Students), College Students, Hierarchical Linear Modeling
Barnett, M.D.; Sonnert, G.; Sadler, P.M. – International Journal of Mathematical Education in Science and Technology, 2014
Relativizing the popular belief that student effort is the key to success, this article finds that effort in the most advanced mathematics course in US high schools is not consistently associated with college calculus performance. We distinguish two types of student effort: productive and ineffective efforts. Whereas the former carries the…
Descriptors: Calculus, Mathematics Achievement, Correlation, Advanced Courses
Jones, Curtis J. – Educational Policy, 2015
This study used a mixed-methods approach to explore the heterogeneity of effectiveness between supplemental educational services (SES) providers in the Chicago Public Schools (CPS). Using surveys of schools and SES providers, and statistical modeling, providers using college graduates and teachers as tutors were found to be more effective than…
Descriptors: Supplementary Education, Program Effectiveness, Academic Achievement, Public Schools
Hegedus, Stephen; Tapper, John; Dalton, Sara; Sloane, Finbarr – Research in Mathematics Education, 2013
We describe the application of Hierarchical Linear Modelling (HLM) in a cluster-randomised study to examine learning algebraic concepts and procedures in an innovative, technology-rich environment in the US. HLM is applied to measure the impact of such treatment on learning and on contextual variables. We provide a detailed description of such…
Descriptors: Randomized Controlled Trials, Student Diversity, Hierarchical Linear Modeling, Algebra
Henry, Gary T.; Campbell, Shanyce L.; Thompson, Charles L.; Patriarca, Linda A.; Luterbach, Kenneth J.; Lys, Diana B.; Covington, Vivian Martin – Journal of Teacher Education, 2013
Calls for evidence-based reform of teacher preparation programs (TPPs) suggest the question: Do the current indicators of progress and performance used by TPPs predict effectiveness of their graduates when they become teachers? In this study, the indicators of progress and performance used by one program are examined for their ability to predict…
Descriptors: Teacher Education, Preservice Teachers, Evidence, Predictive Validity
Fike, David S.; Fike, Renea – Community College Journal of Research and Practice, 2013
This study focused on assessing the relationship of class scheduling with student outcomes in Intermediate Algebra, the prerequisite course for College Algebra. Numerous studies of information processing theory and the spacing effect on learning have been conducted; they have produced mixed findings. Relatively few studies have been conducted to…
Descriptors: Community Colleges, Remedial Mathematics, Developmental Studies Programs, Mathematics Achievement
Thomas, Matthew – ProQuest LLC, 2013
This dissertation examines the relationship between an instructional style called Interactive-Engagement (IE) and gains on a measure of conceptual knowledge called the Calculus Concept Inventory (CCI). The data comes from two semesters of introductory calculus courses (Fall 2010 and Spring 2011), consisting of a total of 482 students from the…
Descriptors: Introductory Courses, Calculus, Mathematics Instruction, Teaching Styles
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