Abstract
On the one hand, the numerical nature of quantitative PER resembles that of those in natural sciences, and therefore the practice of quantification is often idolized as “the scientific method” in education research. On the other hand, quantitative PER can be mistakenly equated to pure statistics and hence demonized as a process of finessing numbers to create “lies”.
In this seminar, I draw on paradigmatic inquires to refute such misconceptions by elucidating the tacit theoretical foundations of quantitative methods in PER (or in any quantitative education research). Specifically, I compare and contrast quantitative PER with quantitative studies in physics, as well as compare quantitative and qualitative PER. In addition, I introduce a new categorization model to delineate three traditions of quantitative practices. An important emphasis of the discussion is on the unique features of each tradition regarding their ontological assumptions, epistemological commitments and methodological implications.
While the discussion uses PER a referent, the paradigmatic ideas are fundamental and in fact can be generalized to quantitative studies in any discipline-based education research.
Biography
Lin Ding, Ph.D. is an Associate Professor of STEM Education in the Department of Teaching and Learning at The Ohio State University. Dr. Ding’s scholarly interests lie in discipline-based science education research. His work includes theoretical and empirical investigations of learners' content learning, problem solving, reasoning skills, and epistemological development. Dr. Ding has been leading or co-leading several federal and state projects sponsored by the National Science Foundation and the Ohio Department of Education. Also, he has served as Associate Editor for the PER-Central resource center and Editor for the Physics Education Research Conference Proceedings (2015-2017).