Do you keep hearing about adaptive learning?
Unpacking the underlying concepts behind the concept – How does it work? Where can it be applied? What are the potential benefits? can help you make an educated decision whether investing in adaptive learning solutions could be relevant for your organization.
We’ve all heard about personalized learning and how individuals absorb information in different ways. Often, we can grasp one concept quicker than another, whilst others may need to learn it on repeat before it sinks in. Learning at our pace and strengthening our weaknesses without wasting time on things we already understand, makes for more effective and enjoyable learning.
Take for example sitting in a class with many students. If the teacher doesn’t have tools to analyze learners, he will simply move from one topic to the next regardless of who understood what and who didn’t. This is the reason a student takes on a private tutor; so that the learning can be adapted to their needs and pace, instead of ‘one size fits all’. Organizations can implement adaptive learning- to provide the ‘private’ feel to the learning by taking data and tracking the learner’s pace, so it can adapt to each learner’s level.
Adaptive learning uses segmentation in order to engage learners at their appropriate level. If there are many students, it will be hard to personalize learning for each one. By segmenting audiences, the obstacle can be overcome. Segmentation can be done based on external characteristics (e.g. tenure, function, etc.), account performance so far and stance on training (e.g. proficiency, engagement level, etc.). For example, if you are a novice in the company, you will be at the novice segment and the level of learning will be at a beginner level, covering basic concepts. Someone with more tenure, on the other hand, will be in a different segment and learning will be focused on new skills and knowledge retention.
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Content Filtering and Adaptation
Another concept used in adaptive learning is classifying and tagging learning content. For example, imagine a bank of 300 training items tagged by level of difficulty. Based on user segmentation, the system can initially send the learner easier training materials about concepts he’s not yet developed a proficiency in, and harder materials on concepts he is already acquainted with. The automation triggers activities to the learners, without the reliance on a supervisor to manually transition the learner from A to B, or to ensure they repeat learning A for that matter, before they can move on.
Microlearning is currently a hot topic in the digital learning world, and it is a great tool for adaptive learning. Microlearning delivers bite-sized learning, either breaking down existing learning materials or creating training snippets and engagements to drive knowledge retention or assist in performance support. This facilitates adaptive learning by allowing modularity in the learning process – fitting relevant microlearning activities to the learner’s pace. The advanced learner might receive more advanced content, focused more on retaining information, whereas the slower learner might receive more basic materials and be required to repeat them more than once, until the concept is understood enough to be applied on the job. Microlearning also allows learning to be delivered at the right time, according to the individual’s needs, such as showing employees short training materials as a refresher just before they are about to do a relevant task.
Adaptive Instructor Led Training
Another benefit of adaptive learning is its ability to optimize and support instructor led training. One of the core issues with instructor led sessions is that it is costly to take employees away from their desks and off work for many hours. Often, this limits the frequency of training and limits it to imparting knowledge, without giving employees the time to practice the skills or absorb the knowledge. With adaptive learning systems, instructors have live access to learner data (both in and outside the class). This enables the instructor to understand which learners need more practice and offer them a follow up self-paced microlearning whilst on-the-job or provide them with more training assignments to bring them up to speed before the next session. The adaptive learning system will also track when the learner has absorbed the knowledge and is ready to move onto the next topic.
Custom Tailored Learning Paths
Employees hate wasting their time. Often, when learning is treated as a one size fits all process, they must learn topics that are irrelevant to their job function or end up revisiting a concept that they have already grasped. Since every person has different skill levels and experience, and some learn quicker than others; adaptive
learning creates a completely customized learning path and adjusts to the learner’s capabilities, using the power of analytics.
Feedback is also a core part of learning. Here too, data can be used to create and automate feedback based on performance and knowledge gaps. Adaptive learning systems can apply more learning or send specific feedback in a notification with a ‘call to action’, that engages the learner based on their performance. Feedback is an essential way to help learners progress, set and reach goals. It helps the learner understand where their weaknesses are and lead them towards strengthening them.
Gameffective provides an adapting learning solution with built in segmentation, microlearning and engagement automation tools. It includes a wide variety of options for segmenting learning audiences and triggering learning activities based on data. Choosing to implement Gameffective or any other adaptive learning platform could be a great investment for your corporation, helping you make learning a daily practice for employees and driving learning to impact performance. To learn more, click here.