The Modern Learning Ecosystem summary

Let’s start this section with a reminder of L&D’s key responsibilities: providing job knowledge and skills, sharing accessible, reliable information, offering on-demand performance support, enabling ongoing practice and reinforcement, giving personalized coaching and feedback, and creating new skill development opportunities. These are crucial for both current job performance and future skill growth.

For effective management of these tasks, a framework is essential, which is where MLE comes in. MLE redefines learning structure and accessibility in organizations, aligning solutions with learner needs and availability. It addresses a broad range of learning elements, offering a flexible approach to modern L&D challenges.

Imagine joining a new team and suddenly having to take over a key role with little guidance, a situation Dillon faced when he joined a contact center training team. The e-learning developer quit, and Dillon had to upskill quickly but struggled to find the necessary information. After two years of inaction from his boss and a failed attempt with a gigantic PDF, a solution emerged: a wiki-based knowledge reservoir. This became the cornerstone of the organization’s learning strategy, embodying the essence of shared knowledge in their MLE framework.

Learning is fundamentally social, yet many attempts at social learning fall short because they don't create a sustainable reservoir of knowledge. Tools like Microsoft Teams and Slack offer instant communication but don't accumulate shared knowledge. This gap often leads to employees wasting time searching for information, which is why shared knowledge is the foundational layer of the MLE.

In this second section on the MLE, we’ll cover the four elements that come above shared knowledge and performance support in the framework, beginning with reinforcement.

Let’s start with a little question: Can you recall what you had for lunch exactly one week ago? It's a challenging question for most people. Why is that? Well, your memory tends to prioritize more significant information. This illustrates the need for reinforcement, especially when dealing with complex matters. But in many workplaces reinforcement is often not given enough attention. Just like the details of a mundane lunch might be hard to recall, work-related information can be overwhelming, leading to quick post-training forgetfulness. To effectively embed training information, it's crucial to incorporate practice directly into the workflow. This might involve activities like role-playing, simulations, reflective exercises, and spaced repetition.

Measurement is crucial in every department, including L&D. L&D often operates reactively, addressing issues as they arise rather than proactively analyzing performance trends. Access to comprehensive data, beyond just learning metrics, is essential for a proactive approach. It’s also not good enough simply to ask a trainee if they’ll use the information they’ve learned in their work, L&D must validate its impact by linking learning solutions to actual performance outcomes, justifying investments in skill development.

Data plays a pivotal role in shaping the future of L&D. It can enable personalized employee support and even align their growing skills with suitable projects and roles. Regular measurement of employee skills and performance capabilities is necessary, as skills can deteriorate if not utilized.