By Mikaela Meyer, Josue Orellana, & Alex Reinhart (Carnegie Mellon University)
Abstract
When taking an introductory undergraduate statistical inference course, students struggle to approach problems in the ways experts do. However, articulating how experts solve problems is difficult, and instructors might not be able to detect the misconceptions students harbor when solving these problems. To enable research into student learning, we propose combining cognitive task analysis, a research method from cognitive science, and think-aloud interviews with graduate and undergraduate students to better understand the steps students and experts take to solve statistical inference questions. After using cognitive task analysis to break down the discrete cognitive skills needed to solve simple mathematical statistics problems, we used think-aloud interviews to determine how students and experts applied these skills and to identify skills students lack. In this presentation, we will discuss our analysis of coded think-aloud interview transcripts and our cognitive task analysis of problems where students must identify the relevant variable to operate on, then apply mathematical rules to obtain their answer.