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January 29, 2014

Skillsoft Signs Multi-phase Joint Development Agreement with IBM Research

Skillsoft signed a multi-phase joint development agreement with IBM (News - Alert) in order to harness the power of big data in enterprise learning which would lead to enhanced user engagement and learning outcomes.

Anshul Sheopuri, manager and IBM master inventor at IBM Research, stated, “Big data has the opportunity to transform corporate learning outcomes. We are pleased to work with Skillsoft to create new enterprise learning-based big data techniques that will drive personalized user interaction resulting in improved engagement. Our initial findings show insights that can make the learning experience customized to users’ preferences and drive next generation adaptive learning and integrated development.”

The Big Data analytics from IBM Research utilizes advanced methodical techniques against very large and diverse data sets. Big data supposedly holds the insights into who one’s customers are and what motivates them and using IBM big data analytics users can discover ways to improve customer interactions, add value and build relationships that last.

Skillsoft offers learning assets that are termed as a resource within a learning management system (LMS) used for training purposes. By leveraging the comprehensive learning solutions from Skillsoft, businesses can help their employees to be more productive and prepare staff for critical IT and business certifications and also meet the special requirements set by government training environments.

The new partnership will merge the features of the IBM Research big data analytics and Skillsoft learning assets in order to realize new means of creating and assessing optimal learning experiences.

John Ambrose, senior vice president of strategy and corporate development and emerging business at Skillsoft, asserted, “We are thrilled to explore new ways of leveraging data to boost learning outcomes. With IBM’s research scientists and technology, we now have the ability to holistically look at content interaction data and understand trends in user interactions and drivers of engagement. Together, we look forward to further harnessing the power of big data to define a more personalized, adaptive enterprise learning experience.”




Edited by Ryan Sartor
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