Learning theory drives learner personalization

This post is provided by guest blogger, Katie Sachs, graduate student at the University of St. Francis in Joliet, IL, MS in Training and Development program.

Artificial intelligence (AI) technology is making today’s corporate learning management systems (LMS) into adaptive learning platforms that can help training and development professionals better serve their diverse learner populations – which include geographically dispersed employees from different generations and with vastly different skills and learning needs. But what makes this personalization work? In a recent article by Zach Posner and Christina Yu for the Association for Talent Development (ATD), the answer is rooted in four learning theories: metacognitive theory, the theory of deliberate practice, the theory of fun for game design, and the Ebbinghaus forgetting curve.

Because of their large learner populations, it makes sense that medium-to-large companies should utilize technology (AI-driven LMS) to achieve learner personalization. But getting your leadership to make the investment in an AI-driven LMS could be a tough sell, so it’s helpful to back up your ROI indicators with proven learning theories. And utilizing the four theories suggested in this article can help all size corporations challenge and engage their learners, and commit lessons learned to long-term memory, thereby saving “organizations valuable time, energy, and resources, making time spent on education as efficient as possible.” That kind of value will be music to your executives’ ears.



Posner, Z. and Yu, C. (2018, January). Personalizing adaptive learning. TD Magazine. Retrieved from: https://www.td.org/magazines/td-magazine/personalizing-adaptive-learning

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