Developing and Assessing a Conceptual Approach to an Algebra-based Second Course in Statistics

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Demands for a statistically literate society are increasing, and the algebra-based introductory statistics course remains the primary venue for learning statistics for the majority of high school and undergraduate students. However, the typical introductory statistics course does not give students experience with multivariable statistical methods, which are the primary methods used in the workforce today. The primary barrier to students' progressing beyond their first statistics course is that they have not yet taken (or do not intend to take) prerequisite courses in probability, calculus, and/or linear algebra. Toward increasing the number of students who take a statistics course that focuses on multivariable methods, this project will develop, pilot-test, and study the use of materials for an algebra-based second course. These materials will (1) emphasize the overarching statistical process in the context of multivariable hypotheses, (2) start with straightforward multivariable study design and exploratory data analysis concepts to build on student intuition and understanding, (3) utilize a writing style and pedagogical approach designed for the typical undergraduate student, (4) develop and integrate technology tools for facilitating student exploration and discovery, and (5) be informed by assessment results. The proposed project will provide college faculty with a fully integrated set of curriculum materials to teach a substantially different curriculum for a second course in statistics, aimed at important multivariable statistical concepts. Such concepts include minimizing unexplained variability, planning and controlling for confounding variables, and exploring and modelling interactions between variables. These materials will leverage prior support that produced materials for introductory statistics centered on simulation-based inference. The project's accompanying assessment activities, development of a new assessment tool (a Multivariable Statistics Concept Inventory), and examination of student assessment results, will address research questions such as (1) In which areas of multivariable statistical thinking are there significant gains in conceptual understanding using this new curriculum? and (2) What are the characteristics of students' learning trajectories for key inferential and descriptive statistics concepts?