The landscape for learning is changing rapidly. New technologies and an increased understanding of human performance have us rethinking learning and development (L&D). How do we harness these new opportunities to develop talent and enable learning—particularly learning at scale?
The ADL Initiative, through a multiyear study on the future of learning, has launched the future learning ecosystem, a concept explained in Modernizing Learning: Building the Future Learning Ecosystem. This complex idea is characterized by interconnected lifelong learning systems, a blending of formal and informal learning, and an integration of emerging technologies with contemporary learning science principles. Here are three steps organizations can take toward build a learning ecosystem.
1. Develop a continuum of learning.
The future learning ecosystem promises to change the way we learn, moving away from models of disconnected, disjointed experiences to a continuum of lifelong learning. We tend to build “learning islands”—individual L&D experiences cut off from one another—such as training videos, e-learning courses, on-the-job mentorship, or professional workshops. In each case, learners are generally treated as blank slates who exist for just that moment; their prior learning and job performance, competencies, goals, and other characteristics rarely have a meaningful impact on an activity’s design or delivery. Similarly, material from one event is rarely referenced in or reinforced by another.
Rather than creating thousands of standalone learning activities, what if we explicitly connected them—building bridges from island to island? We could pass data about individuals, their performance, and the topics they learned from one activity to the next. We could look across the entire system to pinpoint specific opportunities and reinforce learning activities in combination. Contemporary technologies make interoperability possible, and organizations are already beginning to capitalize on its benefits.
2. Invest in an outcomes-focused common currency: competencies and credentials.
While building bridges between islands unlocks their data, that data typically use different terms, criteria, and standards, as if each learning island has its own unique currency.
While we do have a metaphorical “currency exchange” across the islands, it is flawed because today’s common currency relies on time factors. Degrees are conferred based on Carnegie Units; workshops are measured in contact hours. Individuals usually need a minimum passing score, but mastery is rarely enforced, which erodes the quality of those learning experiences. Additionally, since most learning activities are defined by their input characteristics, like contact time and curricular designs (rather than based on the capabilities graduates gain from them), each tends to develop its own methods of defining and conferring value. The portability of meaningful data across experiences, then, is limited.
The next step toward the future learning ecosystem is to develop a new common currency—a shared touchstone that’s focused on outcomes rather than inputs. That currency is likely to be found in competency frameworks and associated credentials.
The credentials concept has gained attention and is being touted in the forms of micro-credentials, nano-degrees, and digital badges. These emerging formats are similar to their more traditional siblings, formal degrees, and certificates. In whatever form, credentials represent an assurance by some trusted body, like a university or assessment center, that someone possesses certain competencies. Competencies are those patterns of knowledge, skills, abilities, behaviors, and other characteristics individuals need to successfully perform work roles or tasks. They’re usually defined as observable behaviors at different levels of mastery (e.g., novice, intermediate, advanced).
Shifting to a competency-based system means moving toward quality-focused, outcomes-based performance standards whose achievement can be validated with credentials. Because competencies describe general performance, they’re not tied to one task; they provide a common way to describe L&D activities, personnel capabilities, and job requirements. They help to decouple learning outcomes from their idiosyncratic island-specific currencies.
3. Professionalize L&D systems by valuing their impacts and upskilling their workforces.
Organizations need to recognize the importance of quality of L&D design and delivery. Not all learning experiences are created equal. Quality matters and it is both art and science to creating high-quality L&D systems. Many organizations already recognize the value of such investments, yet others still treat L&D as an afterthought—or worse, as if exposure to training and education were enough to achieve the desired outcomes.
To evolve, organizations need to invest in their L&D systems, recognizing the impact that skilled talent development professionals can have when they’re given the time, resources, and authorities needed to do their jobs. In the future learning ecosystem, such investments are the baseline and by themselves aren’t enough. We need to do more.
Specifically, we next need to focus on upskilling the L&D workforce toward holistic approaches such as learning experience design and learning engineering. These disciplines account for a wider range of individual and organizational factors that affect learning, such as user experience, emotion, motivation, data-driven analytics, and environment. Considering longitudinal and large-scale outcomes from a more strategic perspective and borrowing from related disciplines like behavioral economics is also beneficial.
Don’t build islands; instead, weave together the various L&D experiences, particularly by using the latest interoperable technology and data standards. Use a common currency. Specifically, use competency frameworks to shift the focus from inputs to outcomes and make those outcomes interpretable across technical and organizational silos; use credentials to help validate the competencies and aid their portability. Finally, level-up your L&D enterprise by investing in high-quality talent development professionals as well as upskilling their capabilities with new methods that address holistic outcomes, data-driven learning, and learning at scale.
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