Making the workforce future proof is currently high on the agenda of all of us in training and education. In this session you will get an idea of how InnoEnergy uses artificial intelligence (AI) to bridge the skills and competency gap of engineers working in the sustainable energy field. You will learn the three steps that make the full cycle of the project: 1) Extracting emerging skills and competencies from industry reports and road maps, 2) Analyzing resumes of engineers who want to enter the energy sector or want to upskill or reskill their capabilities, and 3) Using the skills gap that emerges from the first two steps to come to an adaptive learning path in the third step of the process.  

You will learn what can be done to automate learning in order to achieve more personalized assessments, the challenges we face in reusing learning elements, and the journey we have gone through to be where we are now. In the end, you will understand how we build a full cycle—starting with an examination of industry needs, pinpointing the skills gap of engineers, and then providing personalized learning paths to the engineers.

In this session, you will learn:

• What AI in education can provide for the workforce
• From real examples of automatically-generated assessments (using AI)
• About the challenges that come with reusing learning elements
• The opportunities and possible risks of this approach

Audience:

Developers, managers, senior leaders (directors, VP, CLO, executive, etc.)  

Technology discussed:

AI from TechWolf, AI from Wildfire Learning, X5gen reuse of OER