Ever wonder how Amazon, Netflix, and Google always seem to recommend the right content at the right moment? They use analytics and predictive modeling based on data from millions of user interactions and searches, providing the optimal recommendation, personalized to each user. What if higher education faculty and instructional designers had the same capability to comb through the vast array of digital academic resources available to them today? This panel session will explore how instructional designers, faculty, and student support professionals can use content metrics to understand and drive student engagement while optimizing course content and design to best meet students’ needs.

With thousands of online students accessing their academic resources through OER, library, commercial, and other digital content, the very materials that students are using provide a critical window into the factors influencing student experience, satisfaction, and learning. Drawing on innovations in adtech and digital marketing and tapping into analytics to measure student engagement through content utilization, instructional designers can now use new technologies to quickly discover content and track its use to accelerate and improve course development and enhance the overall learner experience.