Designing Adaptive eLearning Experiences
For decades, eLearning has consisted of online, self-paced courses. Learners access the course material, read the content, watch videos and complete self-assessment activities that reinforce the learning points. After each activity, there is feedback for correct or incorrect answers and usually a final exam at the end of the course. It's the same course for all learners, regardless of prior knowledge or experience.
Adaptive learning lets you change that. In an adaptive learning course, learners may complete a pre-test to check their understanding and find any knowledge gaps or they might take an introduction to the course and be tested on that knowledge. Based on their answers, the LMS builds individualized learning paths for each learner to suit their needs. You no longer need to settle for a one size fits all learning solution!
In this article, I'll explain what adaptive learning is and discuss some of the benefits of using this type of learning, as well as some of the ways that you can create adaptive learning experiences for your learners.
What is adaptive learning?
In simple terms, adaptive learning is learning that adapts to the learner's needs. But it's not that simple.
eLearning has changed the face of training from traditional, facilitated sessions to online, web-based, mobile learning that meets the needs of the modern learner. Training magazine's State of the Industry states that while classroom instruction is still widely used, the use of online learning continues to grow and the use of technology is on the rise.
Adaptive learning customizes what each learner will be assigned, based on that learner's needs and performance as determined by the LMS. It features:
- Adaptive content: Additional content specific to the learner's needs, informed by quantified student progress based on tracked learning experience (self-assessments, knowledge checks, feedback, final quizzes, etc.).
- Adaptive assessment: Assessments built by the LMS for individual learners based on learning history, on a per topic basis.
- Adaptive content and course structure: Course content and structuring developed for each learner, based on predictive analytics and learning algorithms.
Benefits of adaptive learning
Why should you consider adaptive learning? Here are some reasons:
- Many users prefer personalized learning experiences: Modern learners are used to online experiences that they can tailor to fit their personal preferences (think social media platforms, Google, Netflix). So why shouldn't their learning experiences reflect their specific needs?
- Greater ROI for learners and for the organization: Learners value their time and so should the organization. After all, learners are being paid while they learn. By creating individualized adaptive learning, organizations maximize the learning while keeping the time spent learning to a minimum, and learners spend less time on irrelevant content and learn only what they need.
- Adaptive learning is more effective in aligning learning with corporate targets: The objective of training has always been related to meeting an organization's goals (higher productivity, reduced safety incidents, etc.). Focusing on individual learning needs allows the organization to ensure that each learner has what they need to better contribute to reaching those goals.
- It saves time: Adaptive learning happens when best suits the learner and as the training is needed. Learners can learn the skill, use it, then update their knowledge by taking quizzes or content updates as they become available.
- Adaptable learning is mobile: Correctly implemented adaptable learning is not confined to the desktop. It should be accessible by any mobile device, allowing learners to learn anytime, anywhere they need it.
- Adaptable learning is flexible: Adaptable learning content can be delivered in text format, in videos, infographics, photos, quizzes, puzzles and games. It depends on the audience and what will best suit their learning needs. Training time is also flexible as learners can access the content anytime and go through as much of it as they want or need.
Designing adaptive learning experiences
Getting the data you need
Adaptive learning design depends on gathering data about individual learners and then using that data to create learning designed to meet their specific needs. So, how do you get that data?
Have learners identify their knowledge gaps; pre-tests and assessment results will give you a good idea of what the learner needs, but is that all the data you need to tailor the learning to the learner? Why not ask the learners what they need?
Try producing a few mini-courses that include videos, games, knowledge check activities and other challenges that will indicate where the learner needs improvement. Ensure that questions and feedback given to learners are not intimidating. What you want is performance data, so use your design skills to create content that will challenge the learner and give you the data you need.
Another effective way to get learner data is to personalize the learning. Design the learning so that the learner is addressed by first name. People respond better when they are treated personally. You may want to ask the learner questions about how they feel about their performance or their opinions on what they may need. Try asking open-ended questions to ask learners what they would like to learn more about. You may want to use a Likert-type scale to rate their responses to your questions and use those ratings to deliver the content they need.
Adaptive learning course design
Here are some examples of adaptive learning course design.
- Branched content: Branched content allows the learner to move through the course depending on how they respond to the course content. Correct answers to a series of questions may indicate that the learner's knowledge of a concept is up to standard and he or she will be directed to a different section of the course. Incorrect answers would lead to additional content on that topic. Branched content helps ensure that learners do not have to plow through what they know to get to what they need to learn.
- Speech-enabled content: This type of content uses speech recognition software and is especially useful for learners who are visually impaired, or for those learning a language (e.g. English as a second language). Learners can actually communicate with the program, which then analyzes their responses in order to direct their learning. This differs from voice recognition in that the program recognizes what was said rather than recognizing the learner's voice. Language learners may also be allowed to choose their own learning paths in such programs depending on their strengths, weaknesses or interests.
- Microlearning: This is a great tool for adaptive learning. Microlearning delivers bite-sized chunks of learning, typically no more than 5 minutes in length, to learners' mobile devices, laptops and desktop computers. Content can be specifically designed for microlearning or it can consist of existing materials that are broken down into short segments. It fits into adaptive learning because the learning can be delivered in modules, which can then be chosen to fit the learner's needs. Slower learners would receive the basic modules to start and repeat them as necessary until the content is understood. More advanced learners would receive higher level content with a greater emphasis on knowledge retention. Because microlearning is portable, it can be delivered anytime it is needed.
- Gamification: Gamification can be used as an adaptive learning tool because it lets learners demonstrate their knowledge and expertise. Use Open Badges, or points and leaderboards to recognize learner achievements and create a little friendly competition. When used with feedback and assessment tools, these devices can be used to provide data that will allow learning customization for each learner. Adaptive learning and gamification is offered as a course on LinkedIn Learning. Use this link to watch an introductory video.
JD Dillon, a prolific author and renowned workplace strategist, offers a hypothetical example of how adaptive learning can be used in the workplace in his article 4 Dimensions of Adaptive Learning:
Bill works in a warehouse where safety is a HUGE concern. Bill receives continuous online reinforcement training on key safety principles, such as lifting procedures, to ensure his knowledge on the topic remains current. He is pushed videos and questions on topics that he struggles with more often than topics he has mastered. He is also provided with links to best practices and job aids.
Bill is regularly observed on the job by his manager and auditors, who record data on proper and improper lifting executions. Lately, Bill has been slacking on his lifting behaviors and has fallen below the required threshold. Bill's manager receives a notification about Bill's behavior gap. At the same time, Bill receives a refresher online training session during an upcoming shift. Between the additional training and coaching, Bill is able to close his behavior gap and prove his knowledge on the topic. However, the online reinforcement training and behavior observations continue to ensure sustained retention and execution.
While Bill is receiving his individual support, the organization is reviewing knowledge and behavior data for the entire warehouse team and comparing it with safety results, including OSHA-recordable injuries. The L&D team uses this data to continuously adjust their training resources and behavior observation process to focus on areas that are seeing real-world challenges rather than covering every possible safety behavior at the same time.
As eLearning continues to evolve, we will see greater use of data in tailoring learning to individual learners and helping them grow where they need it and when. Adaptive learning is one more way that eLearning providers can make learning experiences more meaningful and relevant for all learners.
In this article, we've talked about what adaptive learning is and its benefits. We've also talked a bit about how it can be used in eLearning design. As technology improves, so will eLearning, making it more adaptive and applicable to more learners everywhere.
Shauna graduated from the University of Toronto in 2002 with a Master of Arts in English before moving home to Calgary to work in the fast-paced, detail-oriented oil and gas industry. Now certified as a technical writer, Shauna is comfortable writing in a variety of styles, and for a variety of audiences.