ATD Blog
Wed Dec 12 2018
If you are in the learning and development space, you’ve probably heard the buzz around the term “adaptive learning”. Perhaps you may have even stumbled across a few adaptive learning use cases and learning management platforms.
Several education tech vendors are doing phenomenal and groundbreaking work in adaptive learning. When the right combination of brain science, learning theory, artificial intelligence, and sound instructional design practices are applied to the mix, it is a formula for success.
However, all that glitters is not gold. While some companies are doing excellent work, others aren’t so awesome—they know how to deliver the sizzle, but the steak is not so tasty. But with a working definition of adaptive learning and its transformational power, you can better judge for yourself.
Adaptive learning is a personalized, learner-centric approach to computerized learning. It harnesses the power of artificial intelligence, brain sciences, predictive analytics, gamification, and microlearning to offer real-time adaptation based on learner activity and performance. Adaptive learning is mastery-based and technology-driven, which maximizes learner engagement, efficiency, retention, and effectiveness.
From the perspective of the stakeholders—trainers, facilitators, managers, and C-suite leaders—adaptive learning uses real-time analytics that provides KPIs (key performance indicators) that precisely pinpoint where learners have the most difficulty. When course developers and instructional designers can identify learner challenges in real time, they can rapidly course correct.
The three key aspects that make adaptive learning so powerful are neuroscience, performance impact, and learner personalization.
Fueled by brain science, adaptive learning enhances performance, increases retention, supports rapid upskilling, and holistically engages learners by providing them with a customized experience that accommodates their learning preferences.
Although the exact neuroscience methodologies, learning theories, performance matrices, and fancy terminologies differ from platform to platform, adaptive learning is primarily focused on metacognition, spaced repetition, aspects of game design, and deliberate practice.
In short, these brain sciences are leveraged to combat the forgetting curve and increase retention. They also create fun yet challenging learning experiences that build and measure confidence and competence. Likewise, metacognitive brain science helps learners better understand where their knowledge is strongest and weakest, which develops and increases awareness helping them identify where and when to concentrate their efforts.
A one-size-fits-all approach to training is not only a colossal waste of money, it is also a bad business decision. Savvy companies understand that training is costly—and more importantly, that training should translate into increased performance and business impact.
Imagine if your company could reduce an annual three-hour compliance training down to an hour and a half. Think of the time savings. What if your training event affected 1,000 customer service reps who field service calls? If you could get 75 percent of the reps back on the phone an hour and a half earlier, you would regain 1,125 work hours.
To achieve such time savings, you must consider that not all your employees will possess the same level of knowledge or skill; therefore, not all employees are going to need to see all of the content.
In annual compliance training, seasoned employees are more likely familiar with course content since they have probably seen it before. On the other hand, newer employees are more likely unfamiliar with the content and may require longer consumption times.
Speed to mastery is one of the transformative powers of adaptive learning, and when correctly harnessed can lead to performance impact at both the individual and organizational levels.
No two snowflakes are the same, and neither are any two learners, especially because every person’s brain is uniquely wired. Learners come from different backgrounds, think and act differently, and consume and process information at their own pace. As adults, we have grown to expect a certain degree of personalization similar to our existing self-curated experiences, such as shopping on Amazon, building a Spotify playlist, or setting up a watch list on Netflix.
When training or learning experiences focus on personalization, they become more impactful and definitely stickier, especially when an adult learner has a strong motivation for learning or an immediate need. Adaptive learning ensures a pathway to personalization by providing learners with customization that maximizes engagement. As an efficient and effective data-driven approach, adaptive learning leverages multifaceted artificial intelligence algorithms that predict learning outcomes and prescribe learning solutions in real-time.
At scale, adaptive learning can transform organizational performance because it adjusts the path and pace of individual learning so learners can achieve mastery at their own rate of completion, often eliminating or minimizing access to content that learners have already grasped.
The purpose of implementing personalized learning is to help companies leverage their existing talent pools. Leveraging talent is achievable through understanding employees’ strengths and weaknesses, performance goals, education and work experience (formal and informal), and career aspirations. Under the right circumstances, personalized learning not only gets the proper training to the right people, it also helps companies ensure they have the right person in the right role at the right moment.
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