PITTSBURGH—A first-of-its-kind program offered at Carnegie Mellon University will help create the learning engineers of the future by using “big data.”
The new Learning Science and Engineering Professional Master's Degree Program at CMU will teach students how to use and analyze “big data” to develop and evaluate educational programs in a variety of settings, including schools, workplaces, museums and other locations. Through the use of data, the program’s students can better understand human learning and create educational technologies that increase student achievement.
The program combines the disciplines of computer science, cognitive psychology, education, information technology and design, and builds on CMU’s decades-long expertise in creating educational technology solutions. Students will be able to develop and implement advanced tools that use state-of-the-art technologies and methods, such as artificial intelligence and machine learning.
“Technology has really transformed how we teach,” said Ken Koedinger, professor at CMU’s Human-Computer Interaction Institute and director of the Pittsburgh Science of Learning Center. “The availability of data on how people learn provides us with the opportunity to create more engaging and effective instruction. We want to create learning engineers — people who not only understand their subject area, but the science behind learning.”
One problem with relying only on subject matter experts for course development is that experts can only articulate about 30 percent of their knowledge, Koedinger said. Using data, learning engineers can identify trouble areas for students and address issues that a subject expert may miss.
Graduates of the program will be ready to assume key positions in schools, universities and corporations, he said. These positions include designers, developers and evaluators of educational technologies and learning environments, as well as domain experts, learning technology policymakers and chief learning officers.
Through case studies and real-world applications, students will learn to engineer and implement innovative educational solutions employing “in vivo” experiments and educational data mining techniques. They will learn how to develop continual improvement programs that identify best practices as well as opportunities for change. Students will gain depth in psychometric and educational data mining methods, interaction design, cognitive and social psychology principles, design, implementation and evaluation of educational interventions.
The program builds on CMU’s work with LearnLab, the Pittsburgh Science of Learning Center (PSLC), which researches instructional methods that lead to robust learning. Sponsored by the National Science Foundation, PSLC partners include CMU, the University of Pittsburgh and CMU spinoff Carnegie Learning, a leading publisher of innovative, research-based math curricula for middle school, high school and post-secondary students.
The deadline to apply for the program is Jan. 31. To learn more about the program or to apply for admission, visit: http://www.hcii.cmu.edu/learning-science-and-engineering-professional-masters-program-admissions.
View CMU press release here.
