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Tag : learning analytics

NAMEC Recognizes ACHL, ArcheMedX and Partners With 2017 ‘Best Practice in Collaboration Among CME Stakeholders’ Award

ACHL, Pro-ficiency, Simumetrix and ArcheMedX were recognized ​​for collaboration on The Evolution of Therapies for NSCLC: Navigating New Therapies & Counseling Patients in Clinical Decisions CHARLOTTESVILLE, Va., May 2, 2018 (Newswire.com) - The Academy of Continued Healthcare Learning (ACHL), Pro-ficiency, Simumetrix and ArcheMedX have been recognized by The National Association of Medical Education Companies (NAMEC) for their innovative collaboration on The Evolution
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ArcheMedX Growth Trajectory Accelerates, Attracting More Capital and Expanding Leadership Team

$2.5 million equity financing to support product development and scale up marketing for award-winning healthcare digital training and analytics platform Charlottesville, VA, October 26, 2017 (Newswire.com) - ​​ArcheMedX, a healthcare informatics and e-learning technology company, has experienced explosive growth and attracted $2.5 million in equity financing to accelerate the company’s transformation of
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ArcheMedX Selected as Finalist for 2015 Best of eLearning! Awards

The ArcheViewer, a data-driven elearning and analytics platform, has been named a finalist in the 2015 Best of eLearning Awards for the best Learning Analytics Solution. Since launching in 2013, the ArcheViewer has empowered the nation’s leading healthcare organizations to more effectively deliver and analyze hundreds of online training programs.
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Leading Change: Optimizing Student Success Through Analytics | Learning Environments

Analytics in higher education is a major focus at many of today’s institutions. Many campuses are claiming the power of analytics to improve student success. Analytics provides the tools to assess, analyze, and change what institutions do in relation to students, faculty members, and the learning environment. President Michael Crow
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Learning analytics for better learning content | Ed Tech Now

We thought you needed: large quantities of data (volume); varied sources of data (variety); semantically meaningful data (which is a similar to validity), the latter being  about accuracy and the former being about having a meaningful standard in the first place, against which that accuracy can be measured. This is a complex topic
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