CSC News

November 21, 2016

NC State Undergrads PRIME for Learning with Intelligent Tutoring Systems

Computing is a fundamental aspect of all STEM disciplines and a required component of most STEM undergraduate curricula. For many degrees in science and engineering, computing is the backbone of the program. Because so many students must take computing courses and use these skills for future careers, it is crucial that students have a firm grasp of the material.
 
A new project lead by Dr. James Lester (Distinguished Professor and Director of the NC State Center for Educational Informatics (pictured at right)) will focus on the creation of the Personalized Real-time Intelligent Mentoring Environment (PRIME) intelligent tutoring system. Co-Principal Investigators include Drs. Bradford Mott (Senior Research Scientist in the NC State Center for Educational Informatics), Eric Wiebe (Professor of STEM in the NC State College of Education), and Kristy Boyer (Associate Professor of Computer Science at the University of Florida). Prime is a joint $2 million project between NC State and the University of Florida. This new program builds on research developed in a series of NSF-supported projects to create technologies that will provide adaptive problem-solving support and adaptive motivational support to help students learn to solve complex computing problems.
 
Serving more 11,000 students over the course of the project, the PRIME intelligent tutoring system will be evaluated in large introductory computing courses. The system will transform introductory computer science education with intelligent tutoring system technologies that not only looks to improve students’ computational abilities but also improves their attitudes toward computing.
 
PRIME will track students’ progress and provide feedback as well as advice. Support from PRIME will motivate students to not only solve problems, but deeply understand foundational concepts of computer science. Prime will provide students with a personalized learning environment that helps them learn and understand the material at their own place. This new technology holds enormous potential for shaping the way students develop computational abilities that will serve them throughout their careers.
 
~scanlon~
 
Note to Editors: The grant abstract follows.
 
“Collaborative Research: PRIME: Engaging STEM Undergraduate Students in Computer Science with Intelligent Tutoring Systems”
 
Investigator(s):James Lester, Eric Wiebe, Bradford Mott
 
Sponsor: North Carolina State University
09/1/2016-08/31/2020
 
Abstract:
The "Engaging STEM Undergraduate Students in Computer Science with Intelligent Tutoring Systems" project will see the design, development, and evaluation of the Personalized Real-time Intelligent Mentoring Environment (PRIME) system, which will provide adaptive problem-solving support and adaptive motivational support to help students learn to solve computing problems. PRIME will track each student's progress while providing real-time feedback, multiple levels of hints, and customized problem-solving advice throughout students' learning interactions. The project will use the block programming language "Snap!" as it eliminates most syntax errors, freeing students to focus on concepts and logic.
 
Introductory computing is a required component of many STEM undergraduate curricula, and because of the fundamental importance of computing for all STEM disciplines, courses that introduce computing to STEM undergraduates hold enormous potential for shaping the way students develop computational fluency that will serve them throughout their careers. The PRIME intelligent tutoring system will be evaluated in a large introductory computing course at North Carolina State University, which serves more than 2,000 students each year. The PRIME environment will also be evaluated at the University of Florida and at Florida A&M University, a Historically Black University. Experimental studies with PRIME will have a dual focus: investigating its impacts on helping students learn about computing (analyzing problems, creating models and abstractions, and building and refining programs) and improving students' attitudes towards computing (self-efficacy for computing and interest in computing).

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