Catching Cheaters in Online Education

A look at the risks involved in accusing students of online cheating.

As I have previously mentioned, cheating is one of the biggest issues facing online education today. It is essential that new technologies and methods be introduced to limit cheating; however, a false positive runs the risk of hampering the academic career of a student forever.

I recently read an interesting article on the topic that led me to dive deeper myself. In it, the article states that schools and MOOC providers are spending large sums of money into cheat detection technology. This technology would attempt to verify that the student is who they say they are, and that the student isn’t checking Google for all their answers.

The article first suggests the concept of remote proctoring. In this set up, a TA or professor watches a handful of students via web camera or within a prearranged physical meeting place. Both of these options could prove impossible with the size of some classes, though, and the distances of some students. The scheduling of exam writing also defies the “work as you please” nature of online learning.

Webcams have many other issues associated with them, assuming the student even owns one in the first place. I know that besides age and eye colour, I am the spitting image of my brother. With the graininess of webcam images it is quite easy for a look alike, perhaps even an unrelated one, to pull a Parent Trap-esque trick on the proctor.

Furthermore, webcams will not take a look at what the student is doing on their computer. Programs like gotomeeting can be used to monitor the screens of students during examinations, but again the sheer number of students involved is a logistical nightmare. Also, a student could always use more than one computer.

This has led to various other solutions, including IP/network, biometrics and keyboard habit analysis. These methods can be quite expensive, though, and the aforementioned false positive can be damaging to a student’s future.

One such program is BioSig-ID, which verifies the habitual height, angle, speed and length of every keystroke to assess identity. The system is audited and compares to the IP and history of the user. This method of identification can get dicey, however, when digital or physical interpreters are involved.

WCET has already found that schools online are lacking in accessibility to the disabled community. Imagine the backlash involved when a student receives a new interpreter the day before the test and school software labels them a cheater.

Relying on IP address, network location and computers can also pose a risk. I have seen firsthand students accused of cheating at alarming rates, simply because they have shared a network or IP address in a residence. In fact, the number of students accused of cheating in one particular course was simply hard to believe.

“Perhaps the best method to limit cheating is to design your tests and assessments to be student specific, where applicable and appropriate. If students are assigned, or choose a specific topic, say based on their workplace, the students can be assessed on their application of course principles to their own situation.  However, this does put the burden on the instructor in the grading process and can hinder the solution with respect to class size” says Sandy Lieske, Assistant Professor and Program Coordinator at the University of Idaho.

This article is not necessarily a call to limit cheating detection software in the online education community. But as a famous starship Captain once said “there can be no justice so long as laws are absolute.” Accusing students of cheating is no light task. The situation, circumstances and supporting evidence must be taken into account before the student’s future is put into jeopardy. After all, mistakes do happen.

Source: Beforeitsnews

Written by

Shawn Wasserman

For over 10 years, Shawn Wasserman has informed, inspired and engaged the engineering community through online content. As a senior writer at WTWH media, he produces branded content to help engineers streamline their operations via new tools, technologies and software. While a senior editor at, Shawn wrote stories about CAE, simulation, PLM, CAD, IoT, AI and more. During his time as the blog manager at Ansys, Shawn produced content featuring stories, tips, tricks and interesting use cases for CAE technologies. Shawn holds a master’s degree in Bioengineering from the University of Guelph and an undergraduate degree in Chemical Engineering from the University of Waterloo.