All of our events are free and open to the public. If you would like to RSVP, you can do so at cunydatamining.eventbrite.com. Alternatively, you can email us with your name, organizational affiliation (if any), and the event name(s) at firstname.lastname@example.org.
In Fall 2014, we will be hosting two seminars and one workshop. We will update this page systematically as we finalize time and place. Make sure to come back and check here for the most up-to-date information!
Fall 2014 Events
SEPTEMBER 18, 2014, 12 Noon @ The Graduate Center, Room 6112
Longitudinal Data Analysis in Education Decision Making
Abstract: Schools are awash in data, from grades, to test scores, discipline reports, and attendance among many others. How can teachers, school leaders, policymakers, students and parents put the data that we already collect in schools to better use? This presentation will provide an overview of the emerging domain of the application of visual data analysis to longitudinal data analytics to examine overall K-12 schooling outcomes (such as high school graduation or dropping out) in an effort to help direct the limited resources of schools to specific student needs. The presentation will focus on determining empirically similar patterns of student longitudinal course grade trajectories, and how to compare so called time-nested “mixture models” with current identification practices in schools.
Bio: Alex J. Bowers is an Associate Professor of Education Leadership at Teachers College, Columbia University, where he works to help school leaders use the data that they already collect in schools in more effective ways to help direct the limited resources of schools and districts to specific student needs. His research focuses on the intersection of effective school and district leadership, data driven decision making, student grades and test scores, student persistence and dropouts. His work also considers the influence of school finance, facilities, and technology on student achievement. Dr. Bowers studies these domains through the application of Intensive Longitudinal Data analysis (ILD), such as data visualization analytics, multi-level and growth mixture modeling, and cluster analysis heatmap data dashboards. He earned his Ph.D. in K12 Educational Administration from Michigan State University, and previous to teaching and education research, spent a decade as a cancer researcher in the biotechnology industry, with an M.S. in Biochemistry, Microbiology and Molecular Biology, and a B.S. in Biochemistry.