The need to demonstrate the business impact of learning is paramount in today’s data-driven, increasingly transparent world. Today’s fast-paced and often disruptive business climate makes it harder than ever to engage diverse skills, abilities and backgrounds and ensure organizational readiness to perform, let alone quantify it. Geographic dispersion often compounds the challenge.
To solve these problems, CLOs are turning to adaptive learning, or systems of artificial intelligence that optimize each learner’s experience in real time, enabling him or her to learn as efficiently and effectively as possible. The technology creates a more human-centered vision of learning that is also more scientific and can be directly tied to business outcomes.
At their best, adaptive learning platforms provide CLOs with technology so fine-tuned and intelligent, it’s like having a one-on-one instructor for every learner. Essentially, adaptive drives learning mastery in a personalized way at scale.
Mastery, Personalization, Scale
Mastery-based learning, the idea that learners’ progression through a course is dependent on mastery as opposed to seat time, lies at the core of adaptive learning. The concept is actually intrinsic to corporate life. Our progress up the corporate ladder is based on factors generally unrelated to seat time: achievement, initiative and networking. Progress isn’t about the passage of time, it’s about focus and intensity. Adaptive learning applies this principle to learning: If mastery is what’s important in learning, then why not optimize for it?
Adaptive technology takes this concept of mastery one step further by personalizing it, so that each learner progresses not only according to his or her accuracy level but other factors like confidence and engagement as well.
To achieve this, adaptive learning incorporates algorithms. Different theories work together to give adaptive learning its reflexes, the way an instructor might pivot strategies from learner to learner.
For example, metacognitive theory holds that people learn best when they know what they know and don’t know. Another principle often used in adaptive learning is the theory of deliberate practice, which suggests that understanding weaknesses helps refine and focus practice. To address this principle, an adaptive learning platform continually tailors content based on the individual learner’s weaknesses, saving time and focusing energy for maximum efficiency. At the same time, this theory can be tempered by the theory of fun for game design, which holds that learners are most engaged when they are challenged but not too challenged. Adaptive learning can put this concept to work by continually adjusting the content to challenge but not overwhelm the learner.
Additionally, the concept of spaced repetition, which holds that to truly learn something, learners must commit it to long-term memory, and that the best time to do so is just as learners are about to forget it. Incorporating this theory, an adaptive platform can use data to predict when a learner is likely to lose a concept from short-term memory. It can then automatically reintroduce this content just before it slips away, solidifying it in the learner’s mind as long-term memory.
It’s called adaptive learning not just because it adapts seamlessly to a variety of learners, but also because it’s flexible enough to transform almost any content – technical, qualitative or quantitative – into an adaptive course. Whether it’s technical skills, accounting or public speaking, a successful adaptive learning platform can take any content and transform it into a modularized course that’s responsive to each learner’s specific needs and capabilities.
Outcomes for Individuals vs. Organizations
For individuals, the benefits are clear. Adaptive learning improves outcomes, including proficiency rates, efficiency and engagement. Time and energy are allocated to the areas where a learner most needs to focus in order to make the greatest gains. Learning becomes a more satisfying process and engagement levels improve because learners always have a clear path forward. They’re presented with the content they need to see at the precise moment they need to see it.
For corporate organizations, the benefits are holistic and far-ranging. Adaptive technology drives training ROI and unlocks organizational performance. I would loosely break down the benefits into five categories.
- Measurement: According to a CEB industry report, 36.7 percent of L&D teams say that “measuring learning impact” is their top priority. Learning teams need to articulate a next-generation vision of learning that is both human-centric in design and delivery and directly tied to business outcomes. Because adaptive learning requires a fine-grained approach, it achieves this naturally. Whatever the ontology or the authoring mechanisms, adaptive requires some granular mapping or breakdown of concepts that lays the foundation for true measurement.Because it collects data on an atomic level, adaptive yields insight into learning down to the granular level of the learning objective and each learner’s interaction with it. This is data we can use to measure the process of learning and find patterns, tie learning to business outcomes, and most importantly, optimize each learner’s progress toward mastery. This happens in different ways depending on the platform, but is typically surfaced through reporting dashboards and helpful visualizations natively built into the adaptive program.
- Mastery: As described above, adaptive is inherently mastery-based, not seat-time based. The technology, in other words, is optimized for mastery. Accordingly, each learner in an adaptive program achieves 100 percent mastery of the specified objectives. In a situation where compliance is at stake, 70 percent mastery is different from 100 percent mastery. The gap can translate into misallocated funds or a major security breach.In traditional education, we’ve been accustomed to accepting the standard outcomes distribution curve, where some perform well, and others don’t. Exemplary performance is usually reserved for those who are gifted in a subject or who possess great discipline. (The very concept of grades and an all-consuming final assessment condition is to accept less from ourselves. A vs. B students, for example.) But what if real mastery, rather than relative performance, were the goal for each individual? Adaptive learning puts each learner on the path to actually achieving total mastery. On an individual basis, this is a nice-to-have. On an organizational basis, when compliance and security are at stake, it’s a must-have.
- Efficiency: Personalized learning paths that show each learner only what they need to see at the moment they need to see it results in time saved. For example, the time-to-completion for a one-size-fits-all course was originally five hours. With an adaptive course, in which each learner achieves mastery in their own way, the average time-to-completion became 3.4 hours, resulting in an immediate ROI of 32 percent in full-time hours of work recovered, the saved time redistributed toward other activities. Not only is the course more effective, it’s more efficient.
- Engagement: There’s a lot of talk in the corporate space about engagement. The perks (free dinner and yoga, massages in the office), the culture (whether it’s “radical honesty,” “ownership,” or “humility”) and the social recognition (likes, upvoting, badges) that produce engagement, the X-factor that is supposed to make an organization blossom and achieve relentless innovation and competitive advantage.This is all beneficial, but I want to argue for something more straightforward. Can we motivate learners simply by showing them a clear path to attaining their goals and by providing immediate feedback and targeted remediation along the way? By focusing on the organization of content and optimizing each learner’s interaction with every piece of it, adaptive motivates learners by keeping them in a state of flow. It removes distraction and boredom and drives focus, like a cognitive “work-out machine.”
- Agility: Real-time intelligence for every stakeholder (learners, trainers, content authors and managers) results in more real-time action and responsiveness for each stakeholder.Learners, for instance, can access reports on their performance at any given point and are able to adjust their practice accordingly. Trainers/managers grasp cohort dynamics through real-time analytics and know exactly what their learners are struggling with, so they can quickly adapt training. Authors understand what content works and doesn’t work, so they can continually refine content and keep it evergreen.
At its core, the fine-grained data-driven approach of adaptive delivers benefits to every stakeholder, holistically powering the organization and making it more agile.