Our annual summit it premised on the understanding that faculty adoption of big data, predictive models, and learning analytics (LA) is critical to advancing a data-informed culture in higher education. Faculty care deeply about their students and want to make the most of the limited instructional time they have with them. Classes have been getting ever larger and it is hard for faculty to know how to inclusively engage with the broad range of student backgrounds and abilities. At the same time, post-secondary institutions are rapidly adopting LA to improve teaching, and enhance student learning, retention and graduation rates.
In higher ed., a data-informed culture will only be sustained when faculty assume personal ownership of learning analytics and see its value for their students, courses and programs. But how do we support and encourage faculty to make use of learning analytics in meaningful and thoughtful ways?
In this working session we will share how a number of schools have taken differing approaches to engaging faculty in learning analytics and big data. Summit participants will also have the opportunity to discuss what is occurring on their own campuses and learn from one another about the kinds of programing that is supporting their faculty, and any results achieved thus far.
This rich discussion will be framed around change theories that encourage a top-down, bottom-up and middle-out approach (Corbo et al., 2014), acknowledge the multifaceted nature of sustaining innovation in college settings (Kezar, 2014), and consider new insights about change from complexity science (Siemens, Dawson & Eshelman, 2018).
George Rehrey, founding director of Indiana University’s Center for Learning Analytics and Student Success (CLASS).
Ryan Goodwin, founding director of the Center for Higher Education Innovation at the University of Central Florida
Corbo, J. C., Reinholz, D. L., Dancy, M. H., Deetz, S., & Finkelstein, N. (2016). Framework for transforming departmental culture to support educational innovation. Physical Review Physics Education Research, 12(1), 010113. https://doi.org/10.1103/PhysRevPhysEducRes.12.010113
Kezar, A. J. (2014). How colleges Change: Understanding, leading, and enacting change. New York: Routledge.
Siemens, G., Dawson, S., & Eshleman, K. (November/December, 2018). Complexity: A leader’s framework for understanding and managing change in higher education. Educause Review, 53(6), 27–42.
At last year’s inaugural summit, we began a conversation about the ethical, moral and legal dimensions concerning the use of learning analytics. One outcome of that working session was an acknowledgement by participants that any ethical discourse about learning analytics must begin at the local level and consider the context and situational factors shaping each campus’s current use of big data. It also became apparent that such discourse would be ongoing as the field develops and new challenges arise. Furthermore, the consensus was that schools could benefit from a larger cross-institutional community of transformation dedicated to addressing the multitude of situations that arise once schools use learning analytics to improve student success.
This working session will be framed along a continuum of possibilities for ethical discourse, which can progress from simply starting a conversation on your campus, to creating principles and codes of practice that may ultimately lead to establishing sound policies (Folkestad et al., 2019). Using a Rapid Outcome Mapping Approach (ROMA) (Young et al., 2014), you will have an opportunity to contribute to this conversation, leave with an action plan to further learning analytics ethical discourse at your school, and to join a larger community of scholars interested in supporting the ethical dimensions of each other’s work. Participation in last year’s working session is in no way required.
Linda Shepard, Assistant Vice Provost and Director of Bloomington Assessment and Research
James Folkestad, Director of the Center for Analytics and Leaning, Professor of Education, Colorado State University
Marcia Ham, Distance Education Professional Development Manager, The Ohio State University
Folkestad, J., Rehrey, G., Shepard, L., Groth, D., & Hickey, M. (2019). Developing a learning analytics community for ethical discourse. In Companion Proceedings of the 8th International Conference on Learning Analytics & Knowledge. Tempe, Arizona.
Young, J., Shaxon, L., Jones, H., Hearn, S., Datta, A., & Cassidy, C. (2014). Rapid Outcome Mapping Approach (ROMA): A guide to policy engagement and influence. London Overseas Development Institute.