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.