Using Big Data analytics to deliver relevant content to learners

BANGALORE, INDIA: Skillsoft and IBM Research is set to unveil new applications for Big Data in learning and talent development. Skillsoft has been developing next-generation adaptive capabilities with IBM Research over the past 18 months.

IBM Research's big data analytics and natural language processing (NLP) technologies are applied across Skillsoft’s user content interactions, job roles, talent profiles and content assets, including rich text and video, and open knowledge bases like Wikipedia, to generate hyper-personalized learning paths. These goal-based learning recommendations are constructed and dynamically sequenced, based on historical content consumption and the semantics of a large number of courses and learning goals, to optimize employee engagement, knowledge retention, and performance.

“Combining IBM’s data science digital capabilities with Skillsoft’s content intelligence allows us to computationally model and personalize user journeys using self-learning systems,” said Dr. Anshul Sheopuri, principal research staff member and senior manager of digital, IBM Research.

“The system is able to infer relevant learning paths to the individual user and reason how goals are related to content and paths without manual curation or content assignment. This creates a highly engaging experience for users, accelerating talent development that is aligned to personal and organizational goals.”

John Ambrose, senior vice president of corporate strategy at Skillsoft said, “In this big data initiative, Skillsoft and IBM Research have developed a new patent-pending model and system for delivering precisely relevant content to learners at the moment of need. In addition, this content is in a sequence that makes most sense for each individual to accomplish personal and organizational goals, thus fast-tracking their career development.”

These new Big Data applications leverage findings from phase one of the project around how learning experiences can be customized to users' preferences to drive next- generation adaptive learning and integrated development. In the next phase of the initiative, this interactive prototype will be piloted with select customers and users.