Applying Cognitive Theory to Statistics Instruction

Abstract

This article presents five principles of learning, derived from cognitive theory and supported by empirical results in cognitive psychology. To bridge the gap between theory and practice, each of these principles is transformed into a practical guideline and exemplified in a real teaching context. It is argued that this approach of putting cognitive theory into practice can offer several benefits to statistics education: a means for explaining and understanding why reform efforts work; a set of guidelines that can help instructors make well-informed design decisions when implementing these reforms; and a framework for generating new and effective instructional innovations.

Enhancing Statistics Education by Including Qualitative Research

“…The third challenge involves increasing the chance that students will be able to apply what they have learned outside the statistics class; that is, that this knowledge will have influence on how they function in their workplace or in their career; will be applied when they participate in civic activities; and will help them shape their opinions when they listen to or read media reports. This is an issue of skill transfer , which to date has been only scarcely accounted for in the literature on statistics education (Lovett & Greenhouse, ; Hoyles et al , ).…”

Effectiveness of Computer-Assisted Instruction in Statistics

“…These factors have been shown to be important in many learning contexts (Chi, 2009;Halpern & Hakel, 2003;Lovett & Greenhouse, 2000). To assess the extent to which the computer-based instruction provided these features, three authors independently rated specific attributes on a 0-4 scale for each of the 45 studies in our meta-analysis.…”

“…The literature cited earlier indicates that such features are critical to facilitating the learning process and promoting the development of critical thinking skills (Lovett & Greenhouse, 2000;Mills, 2002;Svinicki, 1999). Little empirical work has examined the direct impact that such features of computerassisted instruction have on the learning of statistical concepts.…”

Flipping Statistics Courses in Graduate Education: Integration of Cognitive Psychology and Technology

“…This article has four aims related to graduate-level statistics teaching and learning. First, I review existing frameworks of statistics course design, based on principles of learning (e.g., Lovett and Greenhouse 2000) and the use of memoryenhancement strategies (e.g., spacing) to improve student learning and retention of information. Second, I examine flipped classrooms as a strategic pedagogical approach to statistics education.…”