Teaching introductory statistics for evidence-based practice: integration of context

Abstract

The ability to critically evaluate quantitative research outcomes is an essential skill for effective decision-making, particularly in the health and behavioral sciences, where the focus is on evidence-based practice and clinical judgment. Introductory college-level statistics courses can serve as a vehicle for engendering these competencies. In this regard, the first course in statistics has been targeted for reform, aimed at building a meaningful foundation for statistical thinking. There is a consensus among educators that the goal of the introductory statistics course should be to foster statistical literacy by emphasizing concepts and applications rather than mathematical procedures and computations; an instructional method that embodies active- learning. Underpinning this pedagogical approach is the constructivist philosophy which regards context knowledge as central to meaningful and appropriate analysis, interpretation and use of data. This paper presents a model for conceptualizing an introductory statistics course to foster evidence-based practice (EBP). It depicts a unifying and holistic view of statistics, and posits that meaningful evidence results from the interaction of statistical methods with the data context, which refers to the research design, the underlying theory, and the practice domain.