Scaling Up for Learning
Community, Collaboration, and Analytics

What can we accomplish together that we cannot accomplish as easily alone?  The age of “big data” offers new possibilities for working together at intersections of disciplinary knowledge, institutional capabilities, faculty teaching, and student learning. The digital trail students leave as they move through higher education can yield important insights into trends and patterns of learning and teaching. As teachers we can explore this potential individually and also, compellingly, in cooperation. We can learn more about the people, roles, goals, knowledge domains, and situational contexts by looking at the complexities distilled by learning analytics. In this talk, I explore the transformative possibilities of faculty, staff, and administrators working together to understand and improve student learning through data analytics. I share research results from a team of six faculty members from the physical sciences, information sciences, social sciences, and humanities--teaching 5 courses and 7000 students each year at Indiana University Bloomington.  Our first-year, general education courses set the stage for students’ success in college, and learning analytics helps us identify major opportunities to improve student learning, individually and collaboratively. Beyond any particular courses or institution, our work shows how Scholarship of Teaching and Learning, big data, and course-level student learning can complement each other in unprecedented ways.

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