Examinator: A Plagiarism Detection Tool for Take-Home Exams

Faculty: 
Thad Starner
Students: 
Raghav Apoorv, Akshay Dahiya, Uma Sreeram, Bharat Rahuldhev Patil India Irish, Rocko Graziano

Examinator compares pairs of take-home exams to select which should be manually checked for plagiarism. Examinator also generates a report with evidence for these cases
using its own metrics and those generated as a by-product of the commercial grading tool Gradescope. Examinator supports degree-seeking graduate programs (both on-line and on-campus) at a top computer science graduate institute in the United States. Since Spring 2019, Examinator has compared over 2 million pairs of exams from a popular Artificial Intelligence course, resulting in 56 cases being referred for discipline. Iterative development has reduced the fraction of exams delivered to instructors for manual inspection for plagiarism and correspondingly improved the percentage of referrals of suggested cases for discipline from 15% to 25%.

Lab: 
Director: 
Thad Starner

The Contextual Computing Group (CCG) creates wearable and ubiquitous computing technologies using techniques from artificial intelligence (AI) and human-computer interaction (HCI). We focus on giving users superpowers through augmenting their senses, improving learning, and providing intelligent assistants in everyday life. Members' long-term projects have included creating wearable computers (Google Glass), teaching manual skills without attention (Passive Haptic Learning), improving hand sensation after traumatic injury (Passive Haptic Rehabilitation), educational technology for the Deaf community, and communicating with dogs and dolphins through computer interfaces (Animal Computer Interaction).