We all know that one size does not fit all. Everyone has a unique perspective and outlook on a subject matter. Learning abilities differ across learners, and training courses should respect that. These are the main principles behind adaptive learning and the cause of its subsequent popularity among learners and instructional designers.

Adaptive learning uses technologies and methods to customize educational content for individual learners. Thus, it creates the effect of one-on-one tutoring. The main advantage is effective education and a greater number of learners benefiting from a course.

But, what do instructional designers really mean when they talk about adaptive learning? How does it achieve results, and what are your options if you want to implement it? Let’s look at these answers in detail.

What is adaptive learning?

An adaptive learning system provides educational content that adapts to the needs and preferences of each learner in a unit. This adaptation occurs based on the collected data about each learner’s performance, skills, and unique situations.

Adaptive learning vs. traditional learning

The traditional way of learning or conveying information doesn’t take learners’ individual needs into consideration. Typically, instructional designers provide one generic piece of content and rely on the learner’s capability of extracting the knowledge needed from it. Adaptive learning does the exact opposite.

Instead of solely depending on the learner’s capabilities, it engages each learner. This includes providing relevant and timely feedback suited to the individual learner’s performance. Adaptive learning also breaks down the course material into easier concepts that that a specific learner can grasp.

Additionally, it can offer relevant resources or review prior course material if the learner is having difficulty with any of the content.

Therefore, the course material in adaptive learning is more personalized and hands-on compared to the non-interactive content of the traditional approach.

Means of adaptive learning: data and AI

Adaptive learning identifies the weaknesses and strengths of individual learners by analyzing past and present performance data. An adaptive-learning approach generates this data from the learner’s interaction with the course material and can also acquire information about the individual from a general database.

Nowadays, artificial intelligence-based, smart courseware and web-based platforms form the basis of adaptive learning.

How does adaptive learning work?

Now that you know what adaptive learning is, you are probably wondering how it works.

The ultimate goal of an adaptive learning approach is to become a one-on-one tutor for each learner in a large educational unit. All adaptive learning strategies and technologies are designed around this concept. Through their concerted effort, adaptive learning works by creating a personalized learning experience for individuals.

One-on-one training

Most of the time, learners consume training in three ways. First, there is the traditional method. The instructor delivers a lecture to the class and then assesses the learners based on the knowledge they got from the class. In the eLearning version of that approach, learners consume content through online modules and then complete an assessment or an assignment based on the material.

The other two methods are mastery and one-on-one tutoring. In the former method, the learner learns through continuous testing and feedback until they have mastered the material. Tutoring is similar, but the learner-to-teacher ratio is smaller. Therefore, learners can obtain more personalized feedback and instructions.

Unsurprisingly, research found that the last method yields the highest success rate among learners. Adaptive learning works by implementing this one-on-one strategy. When it comes to eLearning, smart technologies play a huge role in providing actionable, personalized feedback that learners can implement right away.

Challenging gaps in knowledge 

Suppose a group of learners is participating in a four-month course. At the end of this period, they will be taking a test to assess how much they learned from it.

Naturally, not all learners in this class have the same strengths and weaknesses, and not all learners will struggle with the same topics or concepts. Traditional eLearning automatically assumes certain background knowledge that learners possess and certain gaps that need to be covered. 

Adaptive learning, on the other hand, eliminates any broad assumptions and focuses on the learner. So, they first take a pre-test and then, based on the results, the system identifies the gaps in knowledge of each learner.

In addition to the pre-test performance, adaptive learning systems can also compare the learners’ past records. Based on this analysis, adaptive learning can adjust the course material to challenge the specific learner to improve in the area where improvement is needed. As a result, learners get to the goal much faster, and the overall outcome of the course becomes more successful.

Achieving mastery through repetition

Adaptive learning achieves its goal by repeatedly requiring learners to practice their weak points. While practice doesn’t necessarily make “perfect,” practice does ensure long-term knowledge recall.

At first, the system identifies what the learner needs more practice with. Then, it takes the content and re-shapes it into different activities. Not only does this approach add variety to the learning experience, but it also allows learners to consume the information through different modalities. Furthermore, the learners receive the benefits of practicing the material repeatedly. Once the system determines that the learner has overcome the weakness or mastered the skill, it stops the process.

Another benefit of repetition is to help the learners remember the content through interaction and reflection. For instance, holding a Q&A session immediately after a course module or following up a module with a live class can increase knowledge retention.

The system presents the same instructional content in different formats, but the active interaction keeps the learning process fun and engaging. At the same time, by reflecting on what they just learned, the learners can retain the information better. Such interactive forms of education are also implemented in blended learning.

Implementing intelligent technology

Advanced and interactive web platforms, courseware, and automation work together to make adaptive learning possible. Simply put, the behind-the-scenes process is very similar to how social media platforms show targeted ads. The platform tracks the learner’s activity, preferences, and personal data to present them with the most suitable educational material.

The implementers of adaptive learning can take two kinds of technological approaches. First, there is “designed adaptivity.” This approach follows an if-this-then-that model. In other words, an expert instructional designer will define the conditions under which the adaptive training system will work.

Such conditions include individuals’ profiles, performances, and behaviors. The design is set up so that if one specific condition occurs, Event A will happen to the learning content. If the conditions are not present, then Event B takes place.

The second approach is less manual and more automatic. Here, smart algorithms decide and provide a learning element. They do so based on how the learner performed in the previous session. The feedback and relevant resources they provide all happen automatically based on the algorithm’s evaluation of the learner.

Types of customizations for adaptive learning

If you ask eLearning experts to define adaptive learning, they will most likely give you similar responses. However, their opinions on the implementation of the method often vary. Here are some of the most common types:

Content-based adaptive learning

Content-based adaptive learning is the method that adapts the instructional content according to the learner’s needs. When a learner responds to a question, the system provides hints, feedback, materials to review, etc., suited to that specific learner. However, the basic structure and curriculum of the course remain unaltered.

You can think of this as providing one-on-one explanations to learners as to why their answers are correct or incorrect. This helps the learners to actually understand the concept instead of blindly memorizing it. Content-based adaptive learning can also be helpful for organizations trying to cultivate a continuous learning culture.

Adaptive sequences

In contrast to adaptive content, adaptive sequences or pathways alter the course’s structure. Based on the algorithm’s evaluation and the learner’s response, the system will determine what content the learner sees next.

So, the system might introduce something entirely outside the course curriculum if it determines that the learner needs to increase their skill in that area. It will also increase the duration of the course to make time for additional practice to cover deficits in a subject.

Adaptive assessment

In adaptive assessment, the question pattern changes according to the learner’s performance. So, depending on how well the learner answered Question A, the system will design a specific Question B.

When a learner answers correctly, the difficulty level of the following questions increases. Meanwhile, if the learner provides incorrect answers, the questions that follow will become easier until the learner masters the concept.

Such an assessment accurately determines a learner’s progress and ensures everyone who completes the course receives the same level of education. Here, the contrast to traditional assessment is quite notable, where assessments are mostly a means of imposing hierarchy among learners.

The benefits of adaptive learning

Adaptive learning has proven beneficial in educational entities, corporate organizations, and government entities. It saves the learner’s precious time, addresses their weak points, and helps to make improvements. As a result, it keeps learners motivated, engages them, and increases their confidence and the overall effectiveness of the eLearning course.

  • During adaptive training sessions, learners receive personalized feedback and instructions on their performance. The system identifies the weak points and works until the learner overcomes that deficit, which allows mastery of the subject. As a result, a greater percentage of participants benefit from the course. Meanwhile, in an unadaptive training program, only a few people appear at the top. Besides benefiting the learners, adaptive learning strategies lead to more success for the instructional designers.

The Adaptive Learning Advantage

Adaptive learning is undoubtedly the future of eLearning. Instructional designers have recognized the benefit of one-on-one tutoring for a long time. However, the necessary technologies weren’t available back then. Therefore, this kind of learning was only reserved for the privileged few.

Thankfully, times have changed. And with the implementation of adaptive learning, you can ensure everyone gets quality training and achieves measurable results. So, do you want your organization to enjoy the benefits of adaptive learning? Then, contact us today.