University of Memphis Receives $2.58 Million to Begin Data Science Learner Data Institute
October 24, 2019 - A $2.58 million National Science Foundation (NSF)-funded project, led by Dr. Vasile Rus, William Dunavant Professor in Computer Science at the University of Memphis, will lay the foundation for a future Learner Data Institute (LDI).
Its mission will be to harness the data revolution to better understand how people learn, improve adaptive instructional systems (AISs) and make the learning technology ecosystem more effective and cost-efficient. The LDI’s primary focus will be online learning with AISs and blended learning classroom environments in which AISs play a key role alongside classroom teaching and learning, seeking data-driven innovations that make experiences in both contexts more effective and engaging for teachers and learners.
The LDI will build on previous efforts and cyber-learning infrastructure, including
MATHia®, Carnegie Learning’s widely-deployed K-12 artificial intelligence-driven mathematics
software; two NSF-funded projects, the LearnSphere/DataShop project and the SPLICE
(Standards, Protocols and Learning Infrastructure for Computing Education) project;
the Advanced Distributed Learning (ADL) Initiative, a Department of Defense-wide program;
and the U.S. Army Research Laboratory’s Generalized Intelligent Framework for Tutoring
The two-year conceptualization phase focuses on building a strong community of interdisciplinary researchers, defining research priorities and developing prototype solutions that address student learning, cyber learning, and learning engineering challenges. Contributors from academia, industry and government will work toward building a framework that will facilitate science convergence to accomplish the mission, recognizing that solving critical challenges will involve innovations that synthesize work in a number of different fields.
The LDI team will also address a number of specific core educational tasks in the context of online and blended learning environments, using advanced methods such as deep learning and statistical relation learning. The proposed data science methods and models are generally applicable to other instructional contexts as well as other science and engineering areas.
The project’s core team consists of a unique mix of academics, faculty and students from the University of Memphis and researchers and developers from a research-oriented commercial provider of computer-based educational services, Carnegie Learning Inc. The LDI team consists of a group of interdisciplinary faculty and students from computer science, statistics, cognitive science, education, engineering and social work.
Carnegie Learning is a leading developer of adaptive instructional systems, curriculum and professional services, serving more than 400,000 students (primarily in grades 6-12) and thousands of teachers in more than 2,000 school districts across the U.S. every year. A group of external partners includes companies (Aptima, Gooru, SoarTech, Workbay), government research labs (U.S. Army Research Laboratory) and universities (University of Colorado Boulder, University of Wisconsin-Madison, University of Pittsburgh, North Carolina State University and University of Texas at Dallas).
The project, with a budget of $2,584,309, will involve 40 individuals, including six PhD students. It is set to begin Jan. 1, 2020.
For more information, contact Dr. Vasile Rus at firstname.lastname@example.org.