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Elsevier acquires Authess, creator of advanced performance-based competency assessments

Using machine-learning technology and data analytics, Authess measures learners’ job readiness, not just test readiness

St. Louis – WEBWIRE

Elsevier, a global leader in information analytics specializing in science and health, and part of RELX, has acquired Authess, the Boston-based developer of an advanced performance-based competency assessment platform that evaluates how students solve complex, open-ended problems they would encounter on the job.

Founded in 2015, Authess built a scalable platform for authoring, delivering and scoring performance-based competency assessments. The company’s machine-learning models and data analytics observe students as they work through a task, capturing not just their answers but their behaviour, process and problem-solving approach.

“When we founded Authess, our goal was to help ensure that learners are job ready and not just test ready,” said Paul Crockett, CEO and Co-founder of Authess. “That’s why we developed an authentic assessment platform that leverages real-world scenarios, advanced technology and machine learning to measure competency. Now, with Elsevier, we are looking forward to a new and exciting future to help develop more competent, job-ready nurses.”

A longtime leader in nursing and health education, Elsevier has built a robust portfolio of well-known brands. These include HESI, the comprehensive review and testing solution that prepares nursing and health students for high-stakes exams and career success, and Sherpath, the personalized, fully integrated teaching and learning technology built specifically for health care education.

“We are excited to work with Authess’ breakthrough technology to advance our assessment solutions, enable improved customer outcomes and help prepare future health professionals,” said Brent Gordon, Managing Director of Nursing & Health Education, Elsevier.


About Authess
Authess, a Boston-based startup with MIT roots, uniquely leverages technology to measure an individual’s ability to solve complex, real-world problems. The Authess platform supports authoring, delivery, analysis, and reporting of authentic, performance-based assessment. Authess engages proprietary machine learning models and data analytics to capture not only answers to assessments, but also observe behavior, process and problem-solving approach. Authess performance reports offer insight into the knowledge, skills and abilities proven more credible predictors of an individual’s competence and future performance than conventional assessments and training methods.

About RELX
RELX is a global provider of information-based analytics and decision tools for professional and business customers. The group serves customers in more than 180 countries and has offices in about 40 countries. It employs over 33,000 people of whom almost half are in North America. The shares of RELX PLC, the parent company, are traded on the London, Amsterdam and New York Stock Exchanges using the following ticker symbols: London: REL; Amsterdam: REN; New York: RELX. The market capitalisation is approximately £33.2bn, €37.9bn, $42.9bn.

About Elsevier
Elsevier is a global information analytics business that helps scientists and clinicians to find new answers, reshape human knowledge, and tackle the most urgent human crises. For 140 years, we have partnered with the research world to curate and verify scientific knowledge. Today, we’re committed to bringing that rigor to a new generation of platforms. Elsevier provides digital solutions and tools in the areas of strategic research management, R&D performance, clinical decision support, and professional education; including ScienceDirectScopusSciValClinicalKey and Sherpath. Elsevier publishes over 2,500 digitized journals, including The Lancet and Cell, 39,000 e-book titles and many iconic reference works, including Gray’s Anatomy. Elsevier is part of RELX, a global provider of information-based analytics and decision tools for professional and business customers.

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