Personalized Learning: Technologies that have the capability to allow learners to follow Multiple Trajectories through their learning experience, depending on abilities and preferences. See MathSpring.
Affect and Motivation: We study how to assess students’ affective states as they learn, and how to bring students back to optimal affective and motivational states for learning through a variety of Interventions. See MathSpring.
Metacognition: : We investigate how to promote good study habits as students learn, by helping them set goals, be strategic while performing an activity, seek for help, and reflect about their performance by self-monitoring and self-evaluating their progress. See MathSpring.
Active Physical Learning : We investigate how children can learn mathematics while exploring the physical space, getting a different understanding of math learning by gesturing, and using technology to guide them through 3D spaces.
Educational Games : We investigate how Games and Game-Like Elements can promote learning and motivation, and afford a better relationship to STEM.
Open-Tutor Platforms: We are making Tutoring Systems and Learning Environments connect with each other through Application Protocol Interfaces (APIs). MathBuds is the result of making the ASSISTments and MathSpring tutoring systems use each other, in order to make a better final product to teach middle school mathematics, capitalizing on the strengths of each other.
Learning Technologies for the Developing World : We are interested in Socio-Cultural Differences and how to create low-cost devices that could be immersed in developing countries and bring learning technologies to those in most need
Personalized Learning Working in close collaboration with the Center For Knowledge Communication at UMASS Amherst, and the ASSISTments group at WPI. : This research is supported by the National Science Foundation (NSF) #1324385 IIS/Cyberlearning DIP: Collaborative Research: Impact of Adaptive Interventions on Student Affect, Performance, and Learning and by the Office of Naval Research, # N0001413C0127; STEM Grand Challenges: Building an Effective and Efficient OPEN Tutor Platform. Any opinions, findings, and conclusions, or recommendations expressed in this paper are those of the authors and do not necessarily reflect the views of NSF or ONR.