All in the head: online cheats exposed by face tilts

US researchers claim 76 per cent success rate in using video analysis to identify likely misconduct

April 18, 2017
cheating online
Source: iStock
Cheating can be harder to detect in online assessment than invigilated exams due to the lack of an invigilator

Asking an invigilator to prowl the university exam hall has long been a simple and effective way to stop students from cheating.

But how do you prevent candidates from sneaking a look at notes or even googling answers if they are taking an online exam in the privacy of their own home? The solution, according to US researchers, is to monitor the rotation of students’ heads.

Researchers at Arizona State University claim they are able to predict, with an accuracy of 75.6 per cent, whether online candidates are cheating based on whether they turn their heads or not and whether there is a pause in answering a question, according to a study published in the journal Higher Education Research and Development.

In the paper, titled “Detecting probable cheating during online assessments based on time delay and head pose”, authors Chia Yuan Chuang, Scotty D. Craig and John Femiani explain how they filmed the head movements of 42 first-year students as they took a short online exam.

When students were allowed to have written notes on the exam subjects with them, the position of their head changed noticeably – indicating they were looking off-screen at the materials, the authors state.

While this was not enough to conclude definitively that students were cheating, it showed that a student was “behaving in a manner that is consistent with cheating”, the paper says.

This may “provide the possibility of building a proctoring system that could flag suspicious students in remotely administered exams automatically” and “reliably rule out a large portion of exam recordings as inconsistent with cheating using an automated method”. 

The research comes amid growing interest in creating reliable systems of online assessment that are not open to flagrant cheating.

In April 2016, the European Union announced that it was funding a €7 million (£5.9 million) project into online assessment using facial, voice and keystroke identification technology.

The Adaptive Trust-based E-assessment System for Learning (Tesla) initiative, which aims to encourage more universities to launch online courses, will be piloted in 2018 with a cohort of 14,000 students before being developed into a product available for purchase by institutions.

However, the latest study highlights that such approaches must be assessed carefully. Although its success rate in identifying those cheating was 75.6 per cent, a further 10 per cent of cases were falsely flagged as showing misconduct.

Use of time delay and head position analysis should therefore be viewed only as “as one potential resource which can help in the detection of cheating behaviors”, the paper says.

jack.grove@timeshighereducation.com

You've reached your article limit.

Register to continue

Registration is free and only takes a moment. Once registered you can read a total of 3 articles each month, plus:

  • Sign up for the editor's highlights
  • Receive World University Rankings news first
  • Get job alerts, shortlist jobs and save job searches
  • Participate in reader discussions and post comments
Register

Have your say

Log in or register to post comments

Featured Jobs

Most Commented

men in office with feet on desk. Vintage

Three-quarters of respondents are dissatisfied with the people running their institutions

A face made of numbers looks over a university campus

From personalising tuition to performance management, the use of data is increasingly driving how institutions operate

students use laptops

Researchers say students who use computers score half a grade lower than those who write notes

Canal houses, Amsterdam, Netherlands

All three of England’s for-profit universities owned in Netherlands

As the country succeeds in attracting even more students from overseas, a mixture of demographics, ‘soft power’ concerns and local politics help explain its policy