AI remote proctoring has seen an incredible increase of usage during the COVID pandemic. ASC works with a very wide range of clients, with a wide range of remote proctoring needs, and therefore we partner with a range of remote proctoring vendors that match to our clients’ needs, and in some cases bring on a new vendor at the request of a client.
At a broad level, we recommend live online proctoring for high-stakes exams such as medical certifications, and AI remote proctoring for medium-stakes exams such as pre-employment assessment. Suppose you have decided that you want to find a vendor for AI remote proctoring. How can you start evaluating solutions?
Well, it might be surprising, but even within the category of “AI remote proctoring” there can be substantial differences in the functionality provided, and you should therefore closely evaluate your needs and select the vendor that makes the most sense – which is the approach we at ASC have always taken.
How does AI remote proctoring work?
Because this approach is fully automated, we need to train machine learning models to look for things that we would generally consider to be a potential flag. These have to be very specific! Here are some examples:
- Two faces in the screen
- No faces in the screen
- Voices detected
- Black or white rectangle approximately 2-3 inches by 5 inches (phone is present)
- Face looking away or down
- White rectangle approximately 8 inches by 11 inches (notebook or extra paper is present)
These are continually monitored at each slice of time, perhaps twice per second. The video frames or still images are evaluated with machine learning models such as support vector machines to determine the probability that each flag is happening, and then an overall cheating score or probability is calculated. You can see this happening in real time at this very helpful video.
If you are a fan of the show Silicon Valley you might recall how a character built an app for recognizing food dishes with AI… and the first iteration was merely “hot dog” vs. “not hot dog.” This was a nod towards how many applications of AI break problems down into simple chunks.
Some examples of differences in AI remote proctoring
1. Video vs. Stills: Some vendors record full HD video of the student’s face with the webcam, while others are designed for lower-stakes exams, and only take a still shot every 10 seconds. In some cases, the still-image approach is better, especially if you are delivering exams in low-bandwidth areas.
2. Audio: Some vendors record audio, and flag it with AI. Some do not record audio.
4. Peripheral detection: Some vendors can detect certain hardware situations that might be an issue, such as a second monitor. Others do not.
5. Second camera: Some vendors have the option to record a second camera; typically this is from the examinee’s phone, which is placed somewhere to see the room, since the computer webcam can usually only see their face.
6. Screen recording: Some vendors record full video of the examinee’s screen as they take the exam. It can be argued that this increases security, but is often not required if there is lockdown browser. It can also be argued that this decreases security, because now images of all your items reside in someplace other than your assessment platform.
7. Additional options: For example, Examus has a very powerful feature for Bring Your Own Proctors, where staff would be able to provide live online proctoring, enhanced with AI in real time. This would allow you to scale up the security for certain classifications that have high stakes but low volume, where live proctoring would be more appropriate.
Want some help in finding a solution?
We can help you find the right solution and implement it quickly for a sound, secure digital transformation of your assessments. Contact email@example.com to request a meeting with one of our assessment consultants. Or, sign up for a free account in our assessment platforms, FastTest and Assess.ai and see how our Rapid Assessment Development (RAD) can get you up and running in only a few days. Remember that the assessment platform itself also plays a large role in security: leveraging modern methods like computerized adaptive testing or linear on-the-fly testing will help a ton.
What are current topics and issues regarding AI remote proctoring?
ASC hosted a webinar in August 2022, specifically devoted to this topic. You can view the video below.
Nathan Thompson, PhD, is CEO and Co-Founder of Assessment Systems Corporation (ASC). He is a psychometrician, software developer, author, and researcher, and evangelist for AI and automation. His mission is to elevate the profession of psychometrics by using software to automate psychometric work like item review, job analysis, and Angoff studies, so we can focus on more innovative work. His core goal is to improve assessment throughout the world.
Nate was originally trained as a psychometrician, with an honors degree at Luther College with a triple major of Math/Psych/Latin, and then a PhD in Psychometrics at the University of Minnesota. He then worked multiple roles in the testing industry, including item writer, test development manager, essay test marker, consulting psychometrician, software developer, project manager, and business leader. He is also cofounder and Membership Director at the International Association for Computerized Adaptive Testing (iacat.org). He’s published 100+ papers and presentations, but his favorite remains https://scholarworks.umass.edu/pare/vol16/iss1/1/.