Mathematics, Statistics, and Computer Science
student ability, conceptual understanding, learning, performance
The recent simulation-based inference movement in algebra-based introductory statistics courses has provided preliminary evidence of improved student conceptual understanding and retention of key statistical concepts. However, little is known about whether these positive effects in courses using simulation-based inference are preferentially distributed across different types of students. Recent studies investigating predictors of student performance in traditional, algebra-based introductory statistics courses (Stat 101) have focused primarily on mathematical achievement or competencies in high school and early college. Little consideration has been given to how prior experience and competency with statistical thinking may be associated with student performance in college-level courses. In this talk I will present recent assessment results exploring students' growth in conceptual understanding as a function of their prior statistical thinking ability, as well as self-reported college GPA or ACT score, with a particular emphasis on differences between students using a simulation-based curriculum vs. a traditional introductory statistics curriculum.
Tintle, N. L. (2016). Assessing the Association Between Quantitative Maturity and Student Performance in Simulation-Based and Non-Simulation Based Introductory Statistics. Retrieved from https://digitalcollections.dordt.edu/faculty_work/677