Question-Score Identity Detection (Q-SID)
Version 2.0 (Sept. 2021)
Q-SID identifies groups of students whose scores for many exam questions are more similar to each other than is usual. Using this information, the course instructor can then compare the written answers of students within each identified group to determine if this similarity is due to collusion.
Educational instructors upload an excel file that contains the scores to each question for each student who took the exam. Q-SID
- gives each student a Collusion Score that defines the similarity of their exam to that of the partner in the class with the largest number of question scores identical to the student's,
- clusters any student/partner pairs that share unusually high Collusion Scores into small Collusion Groups of typically two to five students.
- estimates the false positive rate for each Collusion Group based on the frequency that Collusion Groups are found by Q-SID in strictly proctored examinations taken in person.
To use Q-SID, read the Q-SID Guide, view Example Results, and go to the Analyze Data page. Students should read the explanation on the For Students page.
Q-SID was developed to counter the increase in cheating that has occurred since the COVID-19 pandemic prevented strict proctoring of exams. Q-SID was established and optimized using data from in-person proctored, pre-pandemic exams and unproctored, online, pandemic era exams taken at UC Berkeley. Q-SID assigns each Collusion Group one of three false positive rates (FPRs): 0.5% FPR, 0.2% FPR, or 0.05% FPR. Approximately half of the students known to have colluded based on analysis of their written answers as well as on student confessions are found at FPR 0.05%, as shown here. Q-SID identifies 40% to 90% of the students who have colluded on a given exam, depending on the number of question scores available.
Q-SID was developed by researchers in the Department of Statistics at UCLA for the wider academic community. Its goals are fourfold: One, to identify those students most likely to have colluded; Two, to protect the majority of students who obey their school‘s honor code by ensuring that they receive the grade that they deserve, not a lower one; Three, to deter cheating by informing students in advance that their exams will be screed by Q-SID; Four, to allow departments and institutions to measure collusion system-wide and thereby establish more informed policies. Read this Article for evidence that Q-SID deters cheating.
Q-SID works well for all class sizes of 25 or more. It requires at least 20 question scores recorded per exam and performs best if an exam has at least 40 scores and ideally >60. Q-SID can combine data from two or more exams from the same class to facilitate optimum analysis. Please read the Q-SID Guide for full details.
Q-SID does not store users' data or require registration. The Q-SID team would, however, welcome feedback on its performance. Feel free to email us about your experience with Q-SID at qsid@stat.ucla.edu.
We do not record IP address, location or other user information. For users whose browser allows tracking, the site will record (anonymously) each occasion that a Q-SID analysis is run. Users who do not wish their use of Q-SID to be so counted can prevent this by using Firefox with Privacy set to 'Strict' and Do Not Track set to 'Always'.
Academic or nonprofit researchers, as well as teachers employed by nonprofit institutions, are permitted to use the Q-SID Program posted on this site subject to the Academic License.