Significant technological progress combined with an increased understanding of human performance are changing how we approach learning and talent development. These advancements have helped us realize the promise of “anytime, anywhere” learning as well as learning personalized to individual needs. The ADL Initiative, a U.S. government research program, has recently completed a multiyear study on the future of learning and developed an implementation blueprint for connecting lifelong learning experiences across time, location, purpose, and context. This co-created plan responds to external demands such as the pace of global change and increased need for technical expertise, and it simultaneously considers emerging capabilities, including advancements in AI and neuroscience. The resulting concept, referred to as the “future learning ecosystem,” promises to substantively change the way we learn, moving away from old models of disconnected, disjointed experiences to a connected continuum of lifelong learning, personalized, driven by data, and delivered across diverse locations, media, and periods of time. How do we harness this new power to modernize learning as we know it?
In this presentation, we will discuss the rationale and influences driving this radical shift in learning from external demands, such as the pace of global change and increased need for technical expertise, to the promise offered by emerging capabilities, including advancements in AI and neuroscience. You will learn about the relevant strategic goals and corresponding case studies from business, academia, and government, and we'll discuss specific steps needed in technology, learning science, policy, organizational dynamics, and other supporting structures to realize this vision. Finally, you will take away several practical actions to leverage these advancements to modernize your own learning and development systems—whether in K–12, industry, academia, or government sectors.
You will learn:
- About future trends, learning science and technology trends, and change drivers
- About recommendations for evolving talent development enterprises for the future
- How to take a data-driven approach to learning and development
- How to improve your own learning and development offerings using research-based recommendations