LinkedIn to offer ‘verified skill badges’ through new standardized testing feature

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Microsoft-owned LinkedIn is adding new standardized tests to let users prove how skilled they are in a variety of areas.

The company today unveiled LinkedIn Skill Assessments, a series of short assessments that use Adaptive Testing to measure skills and proficiency in various programs. Users who score in the 70th percentile or higher on tests can brag about their grades with new “verified skill badges” in everything from coding languages like C++ to programs like Adobe Photoshop.

In a blog post, LinkedIn says the program isn’t just about verifying skills. It also feeds into the company’s hiring ecosystem. Recruiters will better be able to zero in on candidates with a proven skill that matches a job, and jobseekers should get funneled to more open positions that match their capabilities.

It wouldn’t be a test without the potential for cheating. LinkedIn laid out in the blog post the various measures it is putting in place to prevent people from gaming the system.

First of all, we apply all the basic steps to make copying questions hard: a Skill Assessment can only be retaken a finite number of times within a certain timespan, any text content is disabled for copying on the web/mobile clients, and a time limit is enforced for answering each question.

A second and more foolproof component to prevent cheating is the nature of Adaptive Testing itself. That is, if a member tries to quickly click through an assessment to learn the questions beforehand (likely on a different LinkedIn account), they will only be surfaced easy, low-point questions. Guessing the wrong answers to these mean they will continue to be surfaced easy, low-point questions. They will then get a low score, and are never able to see the more intermediate and advanced questions.

Finally, due to the dynamic nature of our content creation pipeline, questions will continuously be rotated and retired, so keeping a static cheatsheet of all the questions available is simply not feasible.

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