Boost Training Transfer Using Predictive Learning Analytics™ (PLA)

Friday, August 18, 2017 11:00am - 12:00pm EDT  
Host: Association for Talent Development
By: Ken Phillips, Founder and CEO, Phillips Associates

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What is arguably the number one issue facing L&D professionals today? The answer: scrap learning. Scrap learning refers to the gap between training that is delivered and what is actually applied back on the job. It’s a critical business issue because learning that is delivered but not applied is a waste of an organization’s resources.

In this webcast, you will learn how to use predictive learning analytics to reduce the amount of scrap learning associated with a learning program. You will:

  • Discover the meaning of the term scrap learning and its impact on wasted organizational resources and lost credibility with business executive stakeholders.
  • Analyze how to build an algorithm that predicts which learners are most and least likely to apply what they learned in a training program back on the job.
  • Examine the three-phase, nine-step predictive learning analytics methodology using data from an actual implementation.


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Ken Phillips
Ken Phillips

Founder and CEO, Phillips Associates

Ken is founder and CEO of Phillips Associates, a consulting and publishing company with expertise in measurement and evaluation of learning and predictive learning analytics. He has more than 30 years of experience designing learning instruments and assessments and has authored more than a dozen published learning instruments. He regularly speaks to Association for Talent Development (ATD) groups, university classes, and corporate L&D groups. Since 2008, he has spoken at the annual ATD International Conference on topics related to the measurement and evaluation of learning.

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