Learning Machines Lab

Wouldn’t it be nice if your textbook learned about you as you learned from it?

The Learning Machines Laboratory (LML) is creating just such an electronic textbook.

While too many of today’s e-textbooks are just as static and uninviting as their paper counterparts, the LML is creating an engaging e-textbook that integrates text, video, simulations, problems, feedback hints, and tutoring and customizes the learning experience based on each user’s background, context, and learning goals. Our personalized learning system (PLS) couples the latest advances in cognitive science, machine learning, and open educational resources (OER).

• Cognitive science: The PLS embodies robust and highly replicable principles from the science of learning that produce superior retention and transfer relative to more conventional ways of studying.
• Machine learning: The PLS is flexible, generalizable, and scalable thanks to powerful machine learning algorithms (think Google, Amazon, and Netflix) that optimize the learning experience by analyzing and modeling both the educational content and data from a large number of learner interactions.
• Community content development: The PLS leverages the large and growing universe of freely available and easily remixable OER content. Our sister project, Connexions, is one of the world’s first and largest open-access educational repositories. Over 2 million unique users per month from 190 countries access over 17,000 reusable learning modules combined into over 1000 e-textbooks, courses, and articles.

Learn more at the LML web site.

Other Research at Rice