Conference Tracks
About SoTL – Analysis, synthesis, reflection, and discussion
Abstract
The age of “big data” offers tantalizing possibilities for working at intersections of disciplinary knowledge, institutional capabilities, faculty teaching, and student learning—what we know as scholarship of teaching and learning. Although a SOTL approach to using big data has been proposed (Baepler and Murdoch 2010), faculty are now exploring its potential to focus digital analysis of student trends and patterns on the roles, goals, and ethics of learning analytics.
This talk explores the transformative possibilities of using learning analytics to inform disciplinary instructors about how students move through their courses. It describes an interdisciplinary, collaborative research project involving seven faculty members from the social, biological, physical, computer, and information sciences, plus mathematics and the humanities–teaching 7 courses and 7000+ students each year.
The project’s big data approach helps uncover drivers of student success in college. However, its real innovation is keeping that data situated within the “small places” of individual courses, where learning is activated and where faculty can intervene. Moreover, the team’s focus on “grade surprise,” the gap between the grade expected and the grade received, brings scholarship of teaching and learning to the scale of the individual student’s embodied experience. Extrapolated beyond any particular institution, course, or individual, this project models how SoTL scholars can scale up their collaborations to transform the college experience in unprecedented ways.
Session Format
Presentation
Location
Harborside Ballroom East
Recommended Citation
Robinson, Jennifer Meta, "Scaling Up the SoTL Commons: Context, Comparison, & Potential with Learning Analytics" (2020). SoTL Commons Conference. 122.
https://digitalcommons.georgiasouthern.edu/sotlcommons/SoTL/2020/122
Scaling Up the SoTL Commons: Context, Comparison, & Potential with Learning Analytics
Harborside Ballroom East
The age of “big data” offers tantalizing possibilities for working at intersections of disciplinary knowledge, institutional capabilities, faculty teaching, and student learning—what we know as scholarship of teaching and learning. Although a SOTL approach to using big data has been proposed (Baepler and Murdoch 2010), faculty are now exploring its potential to focus digital analysis of student trends and patterns on the roles, goals, and ethics of learning analytics.
This talk explores the transformative possibilities of using learning analytics to inform disciplinary instructors about how students move through their courses. It describes an interdisciplinary, collaborative research project involving seven faculty members from the social, biological, physical, computer, and information sciences, plus mathematics and the humanities–teaching 7 courses and 7000+ students each year.
The project’s big data approach helps uncover drivers of student success in college. However, its real innovation is keeping that data situated within the “small places” of individual courses, where learning is activated and where faculty can intervene. Moreover, the team’s focus on “grade surprise,” the gap between the grade expected and the grade received, brings scholarship of teaching and learning to the scale of the individual student’s embodied experience. Extrapolated beyond any particular institution, course, or individual, this project models how SoTL scholars can scale up their collaborations to transform the college experience in unprecedented ways.
