MIT Omnichannel Education Lab
Pioneering innovation and practice in the new era of education
Why the MIT Omnichannel Education Lab?
Online learning is revolutionizing education on campus, in the workplace, and in the home, offering a multitude of learning options. The MIT Omnichannel Education Lab’s mission is to pioneer innovation and practice for the leaders of this new era of education and learning. We envision a world where educators deliver high-quality, high-impact omnichannel learning programs both online asynchronous and synchronous, and in-person to any individual in any location who wants to learn.
In today’s ever-changing commercial environment, individuals must continuously update their knowledge and skills to keep pace with advances in technology and workplace management. Online and “blended” or “hybrid” learning programs provide more accessible and flexible ways to learn and acquire the new abilities required in this changing landscape.
In response, we are dedicated to helping educators design and deliver online (synchronous and asynchronous), in-person, and hybrid learning engagements for working professionals. Our goal is to enable these educators to offer programs that maximize professionals’ learning objectives, optimize their engagements, and advance their life-long career plans.
Our Research Areas
Omnnichannel education and hybrid formats
Engagement and Dropout
Manage & Track
Learning & Assessment
Dr. Eva Ponce
Dr. Chris Caplice
Senior Research Scientist
Dr. David Correll
Dr. Inma Borrella
Dr. Alexis Bateman
Dr. Sergio Caballero
Updates from the Lab
The project aims at increasing learners’ engagement in massive, open, and online education in Supply Chain Management by applying learning analytics.
In this project we investigate the fundamental trade-off involved with providing an educational platform for both learning and assessment, and propose strategies to ensure academic integrity in a MOOC-based program
This research aims to develop a data-driven framework to evaluate design changes in MOOCs. We explore a change from multiple angles-process, proficiency, and perception- and apply various analytical methods-temporal, causal and predictive to map out the outcome of instruction along multiple dimensions of learning.