Investigators from Rice University and Duke University will build a Personalized Cyberlearning System, designed around three principles from cognitive science (retrieval practice, spacing, and enhanced feedback), that leverages advances in machine learning and makes use of an existing instructional content material and problem set database aimed at undergraduate engineering students. The system will use artificial intelligence methods to optimize practice and feedback for students. Research will seek to advance knowledge, in a real-world setting, about a range of issues concerning how feedback facilitates learning, how individual differences come in to play, as well as those more specifically aimed at the development of the learning technology system itself.

The project is important as part of the effort to harness the vast quantities of information on the web to personalize instruction for a wide range of learners. Moreover, the development of such cyberlearning technologies holds promise for opening up STEM education for motivated self-learners while also allowing access to a large volume of material for a range of students who might not otherwise have it.

Agency
National Science Foundation (NSF)
Institute
Division of Information and Intelligent Systems (IIS)
Type
Standard Grant (Standard)
Application #
1124535
Program Officer
Janet L. Kolodner
Project Start
Project End
Budget Start
2011-09-01
Budget End
2015-08-31
Support Year
Fiscal Year
2011
Total Cost
$594,150
Indirect Cost
Name
Rice University
Department
Type
DUNS #
City
Houston
State
TX
Country
United States
Zip Code
77005