Implementing Adaptive, Data-Driven Course Design to Improve Student Learning

Wednesday, March 29 | 2:15PM–3:05PM | Room 550
Session Type: Breakout Session
Delivery Format: Panel Presentation
In this discussion, we will share our experiences with implementing adaptive, data-driven course design and delivery methods for leveraging analytics in the context of improving student learning. Panelists will delve into the "how to" of an adaptive learning implementation, exploring topics such as defining needs, selecting disciplines or courses to pilot, navigating challenges, designing skill maps that drive learning analytics, and exploring our changing roles as educators in the context of data-driven course design. We will also demonstrate course design and delivery techniques for leveraging analytics and deeper insights into learning performance.

Outcomes: Explore the features of adaptive, data-driven learning systems that distinguish them from traditional LMSs * Acknowledge the possible benefits and challenges for students and instructors * Consider best case uses of adaptive, data-driven systems for your institution


  • Jeremy Anderson

    Vice President Learning Innovation, Analytics, and Technology, Bay Path University
  • Matt Maron

    Assistant Teaching Professor of Accounting, Quinnipiac University
  • Erik Moody

    Professor, Marist College
  • Frances Rowe

    Senior Researcher and Instructional Designer, Quinnipiac University

Resources & Downloads

  • Implementing Adaptive Data Driven Course Design_slides

    801 KB, pdf - Updated on 1/22/2024