Implementing Adaptive, Data-Driven Course Design to Improve Student Learning
Implementing Adaptive, Data-Driven Course Design to Improve Student Learning
Wednesday, March 29, 2017 | 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
Presenters
Jeremy Anderson
Vice President of Institutional Research, Collin County Community College District
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