Automated Partial Credit Grading Software System
Department
Computer Science
Major
Computer Science and Computer Engineering
Research Advisor
Tauritz, Daniel R.
Insall, Matt
Advisor's Department
Computer Science
Second Advisor's Department
Mathematics and Statistics
Funding Source
Missouri S&T Opportunities for Undergraduate Research Experiences (OURE) Program
Abstract
Education in the 21st century is quickly moving away from the traditional classroom lecture structure. A new generation of computer savvy students is accustomed to working at their own pace and receiving continuous feedback. The current financial situation is actually reducing the number of grader hours, overwhelming instructors and leading to less feedback. Educational companies have responded by offering automated training and test tools. However, these tools are very rudimentary, providing full credit for exact matches to model answers and no credit for any other answer. There is a clear and urgent need for a far more sophisticated system which can analyze student error, assign partial credit, and provide detailed feedback to the student.
Biography
Michael is a native of Saint Louis, Missouri and is a junior at Missouri S&T studying computer science and computer engineering. He is actively involved in ACM SIGSecurity, a computer security special interest group, and ACM SIG-Game, a software development special interest group. Michael is also a Peer Learning Assistant for Missouri S&T's Learning Enhancements Across Disciplines program.
Research Category
Research Proposals
Presentation Type
Poster Presentation
Document Type
Poster
Location
Upper Atrium/Hallway
Presentation Date
06 Apr 2011, 1:00 pm - 3:00 pm
Automated Partial Credit Grading Software System
Upper Atrium/Hallway
Education in the 21st century is quickly moving away from the traditional classroom lecture structure. A new generation of computer savvy students is accustomed to working at their own pace and receiving continuous feedback. The current financial situation is actually reducing the number of grader hours, overwhelming instructors and leading to less feedback. Educational companies have responded by offering automated training and test tools. However, these tools are very rudimentary, providing full credit for exact matches to model answers and no credit for any other answer. There is a clear and urgent need for a far more sophisticated system which can analyze student error, assign partial credit, and provide detailed feedback to the student.
Comments
Joint project with Michael Virag