Automated Partial Credit Grading Software System
Department
Computer Science
Major
Computer Science
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 moved to Missouri in 1999 and attended Blue Springs South High School in Blue Springs, Missouri. He joined Missouri S&T in 2007 pursuing a bachelor's degree in Computer Science. He is currently a senior in Computer Science with a minor in Business on track to graduate in May 2011.
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 Wisely