Author B. Sherin

Open peer commentary on the article “Studying Conceptual Change in Classrooms: Using Association Rule Mining to Detect Changes in Students’ Explanations of the Effects of Urban Planning and Social Policy” by Arthur Hjorth & Uri Wilensky. Abstract: Horth and Wilensky have taken an important first step in introducing a new method for capturing changes in student thinking, one that draws from the field of machine learning. However, I argue that there is much work to be done by educational researchers, as we seek to understand how best to apply methods from machine learning, and to appropriately interpret the results they produce.