Engaging Faculty in the Adoption of Learning Analytics in a Large Introductory Chemistry Course

In this session, researchers will present the outcomes of a project to integrate learning analytics in a large undergraduate chemistry course. We will discuss the process of using predictive modeling on multiple sources of data to develop a model of student learning outcomes that was then used to design a data visualization system in the campus learning management system. The purpose of our presentation is to provide the audience with concrete strategies for engaging faculty members and administrators on how to incorporate digital tools and students' academic records into a learning analytics program that can boost student achievement.

OUTCOMES: Learn communication strategies for engaging faculty on learning analytics * Learn principles regarding the use of data to inform instructional decisions * Learn how to solicit student feedback on learning analytics