The EDM lab is jointly directed by Dr. Daniel Leeds, Dr. Gary Weiss, and Dr. Yijun Zhao who are faculty in Fordham’s Computer and Information Science department. The EDM Lab’s primary education analytics tool, CGAN (Course Grade Analytics with Networks) is currently available from edmlib.ml. This includes the documentation, source code, and executables. If you would like to join the lab, please contact anyone of the directors.
The EDM Lab’s CGAN, Grade Analysis, and Course Sequence Analysis tools have been used in numerous research studies to uncover insights about student performance and course sequencing. CGAN provides advanced course-grade analysis at the student, instructor, and department level, while the Grade Analysis tool analyzes data at the student, instructor, and department level to help identify grade disparities and high-performing instructors. Our Course Sequence Analysis tool uses the Generalized Sequence Pattern algorithm to identify common course sequences taken by students. To learn more about these tools, visit our software page. To learn more about the research these tools have helped facilitated, explore our research outcomes on our publications page.