Attendance and identity verification done right: untapping the potential of eLearning

In recent years, the demand for eLearning solutions has been booming, and there can be little doubt that growth of the sector will continue in the coming years. Indeed, through the last decade, the ecosystem around eLearning has dealt with many of the technical issues that plagued early developments. No bulletproof solution has been found for copyright protection and digital rights management, but this is ultimately of relatively little consequence given the abundance of free eLearning resources online. Indeed, monetization of eLearning will likely come first and foremost from certification, and from this point of view the position of educational institutions and certification authorities is still rock solid: if someone needs a certification, nothing else will do, and getting access to pirated contents of a course is effectively of no practical purpose.

But here comes the main outstanding problems for eLearning providers: how can they confirm attendance and identity verification in a robust, convincing, cost-effective, privacy-respecting, and scalable way?

If attendance and identity verification is strong enough, then many businesses will simply decide that certification coming from a given eLearning platform is not trustworthy: they will not use it for training their own staff, and they will not consider it when hiring new recruits. In order to increase the trustworthiness of their certification, platforms must therefore introduce additional verification methods.

And this is where the nightmare for both users and platforms themselves starts. Constant prompts to check that somebody is actually following a training clog the user experience and ultimately distract from the learning process. Established identity verification mechanisms involve storing and, often, repeatedly requesting sensible biometric data, which immediately raises privacy issues. And in spite of the pain this approach causes on both sides, the results are still largely unconvincing.

This became most evident when in 2013 the eLearning platform Coursera tried to introduce new techniques to deal with online cheating, including by introducing stylometrics analysis. Their approach, however, did not fundamentally solve the problem they were meant to address, as effectively summarised by Bruce Baer Arnold, a professor at the University of Canberra:

“Coursera’s authentication regime is readily subverted. We can be sure that someone is online. But we can’t be sure that the person online is the person being awarded the certificate, that the same person has been online throughout the unit or isn’t being cued by an associate.”

Indeed, such solutions are both ineffective, and problematic from the point of view of privacy, as they force the platform to store a substantial amount of private data.

So here we are, with huge potential market revenues still untapped, because no convincing solution to attendance and identity verification has yet entered the mainstream market of eLearning platforms.

Attendance and identity verification done right

At MorphCast, we believe technology can finally allow for trustworthy attendance and identity verification to be integrated with eLearning platforms, without hampering the user experience or causing privacy-related administrative and security headaches to platform providers.

MorphCast’s patented technology enables face and sentiment recognition directly from within the browser. This is a key point: not only does MorphCast work directly from the browser without the need for installing any external plug-in, but, fundamentally, it processes the data and the information inside the browser. No picture or other private data is ever sent to an external server or to the cloud.

MorphCast’s identity module can verify that a given person is sitting in front of the computer throughout the whole course. Legacy approaches asked to take a picture at the moment of the final test, but this did not really say much about attendance, which is a fundamental part of many certifications. Besides, while it is rather easy to fool an automatic face recognition system that has access to a static picture, this cannot possibly work for live video, where blinking eyes and other micro-movements can be detected(so… no, just putting a picture in front of the webcam would not fool the system).

MorphCast’s attention module can verify that a person is sitting attentively in front of the computer. This is certainly important for certification, but can also provide important information to tutors about which parts of the course lead most students to get distracted, thus providing important feedback that can be used to improve the quality of the course itself.

Again, all of the above can be done reliably throughout the course, without biometric information ever leaving the user’s browser, and without requiring to install any additional software, both on desktop and mobile (yes, by using standard technologies we can be completely platform independent: Windows, Mac, Linux, Android, iOS… as long as there is a reasonably modern browser, MorphCast will work out of the box).

Knowing that a given person (not just someone, but that given person) has been sitting in front of a computer, looking attentively at the screen throughout a course and the ensuing testing, then it is possible to claim that both attendance and identity have reliably been ascertained. Without biometric data ever leaving the browser, and without disrupting the user experience with annoying requests.

By fixing the biggest outstanding issues limiting the growth of eLearning in the business and certification sectors, MorphCast is ready to untap new potential in this promising market sector.

To find out more about what MorphCast can offer to your eLearning platform, get in touch with our support team or click here to see how our technology has already been adopted in marketing and other sectors.