Whether hiring new employees or developing the skills of seasoned professionals, training has become an essential part of business operations. Training is no simple matter, and the costs can be a drain on some businesses. A 2020 report from Training Magazine found that companies spend roughly 1,100 dollars on training for each employee every year. For small businesses, that’s a lot of money to spend on professional development, even when knowing the benefits. Consequently, many organizations want training options that are cost-effective but still get results and help their employees develop their skills. That’s where adaptive learning comes in.
In this article, learn what adaptive learning is, the types of technology it uses, common adaptivity methods and types, and the benefits that come with it.
What is Adaptive Learning?
Adaptive learning uses computer software that creates custom experiences and materials to help people learn and retain information. The adaptive learning method provides feedback and resources that are unique to each individual, creating personalized learning that responds in the most effective way to each student or trainee. In other words, the system adapts to the situation and the person using it. Adaptive learning is sometimes called adaptive teaching or adaptive education, but the principle of shaping education and training materials to each person’s needs remains the same.
A Brief History of Adaptive Learning
Most experts agree that adaptive learning got its start back in the 1950s with B.F. Skinner and his work in psychology and behaviorism. It mainly picked up steam due to advances in artificial intelligence several decades later, thanks to research done among universities. This type of adaptive technology eventually entered the mainstream as major companies started to use it for their operations. Companies like Netflix, Hulu, and Amazon feature adaptive technologies like this, though not necessarily for education purposes. Adaptive education has become more widespread among NASA and the U.S. military in the past few decades. Now companies are starting to see its benefits in the business world for training and development.
Adaptive Learning Technology
The technology used in adaptive learning often involves different types of artificial intelligence and advanced data algorithms to help teachers and trainers with their lessons. Most adaptive learning software is as simple to follow as an online guide, so the use of advanced technology shouldn’t intimidate businesses. At the moment, adaptive learning is most common in grade schools and higher education, but these adaptive learning systems have slowly made their way into the business world. Adaptive learning has two common variations for use, which are discussed in more detail below.
The designed adaptivity method is where an instructor designs the teaching sequence, indicating how adaptive learning systems should respond depending on the situation. It’s the classic “if A happens, then B happens” approach where the designer dictates the system’s reactions. For example, if a student is going through the material at a breakneck pace, a prompt may appear, telling them to slow down and focus more on the lesson. Or, if a student is showing mastery of the material already, the adaptive learning software might provide even more complex material to study. The benefit of this adaptive learning variation includes giving instructors and trainers more control over what students see and how they progress.
As the name describes, the algorithmic adaptivity method uses algorithms to respond to the student’s actions. These algorithms essentially determine what the student knows and what they should experience next. From there, the adaptive learning systems can choose learning materials which the student needs at that moment. Common algorithmic frameworks used in this method include Item Response Theory (IRT) and Bayesian Knowledge Tracing (BKT). While this might sound too complex for a novice to use, instructors and trainers don’t need a deep knowledge of these algorithms to use this adaptive learning method.
Adaptivity Factors and Types
The key component of training workers with adaptive learning is to have a system that changes responses depending on the situation. Much like situational leadership, flexibility is needed to promote the best responses that lead to the best outcomes. With adaptive learning, this comes from taking into account several important factors that create certain adaptivity types.
For this adaptivity factor, the student willingly provides data to the adaptive learning system. Requests from the system will prompt a response from the student, such as how confident they feel with what they’ve learned. If the student indicates that they don’t feel confident with the material, adaptive learning systems might respond by reviewing the material more in-depth. Or, if a student says that they would like to learn more about a specific subject, the system will change to provide more material on that subject.
Adaptive learning monitors the behavior of the learner, which leads to changes in learning experiences. For example, if students take a long time to complete specific tasks, the system may respond by going over material more slowly. These changes happen subtly, but the adaptive nature ensures that everyone who goes through training has the same knowledge and skills.
One of the most common adaptivity factors is performance. The adaptive learning system will change its responses depending on how well the student does. For example, if the student gets a wrong answer, the system will repeat that material. If they get the correct answer, the system will consider that material known and not repeat that information. Adaptive learning systems can measure performance on a micro-scale, such as task by task, or a macro-scale, over an entire lesson or series of lessons.
Moving on to adaptivity types, these are the ways in which lessons and materials can adapt based on the factors listed above. In the case of differentiated pathways, the system provides materials in varying sequences that ensure learners master a particular concept or topic. For example, students who struggle with one concept will need to go through that material until they master it. Only then will adaptive learning mechanics allow them to continue to new topics. Students may also be able to choose what they want to learn with differentiated pathways, giving a sense of freedom during the process.
Some adaptive learning systems will respond with real-time feedback. As a student works through a lesson, the system can provide helpful hints and suggestions to help a person learn the material and develop their skills. These feedback systems can step in when the learner needs it most, giving guidance without it feeling overbearing.
Benefits of Adaptive Learning
Extra Help For Instructors and Trainers
Adaptive learning can provide significant help for instructors and trainers as an added tool for their arsenal. Instructors can ensure students are getting proper feedback and correction, even when they can’t be there at all times. A study from Australia looked at adaptive learning and concluded that these systems help instructors and lead to better outcomes for students.
Many organizations don’t have the time or resources to spend on multiple trainers, but with adaptive learning, one trainer can work with more students. This opens up more opportunities for people to learn and develop their skills. Trainers won’t have to feel overwhelmed as they’re getting help from the adaptive learning software. Adaptive learning also allows for teaching more topics than before, so workers can expand their skill set.
The traditional method of teaching and training requires evaluation at the end of a course, usually through a test or demonstration. This evaluation process usually takes extra time to ensure accuracy. With adaptive learning, evaluation happens much more quickly. Sometimes people receive results almost instantly after completing a final evaluation. Adaptive learning systems also identify areas where students may have struggled, giving them insight on where to focus future efforts.
Imagine having an entire course tailored precisely to your needs with goals that are specific to you. That’s the kind of advantage adaptive learning brings to the table. Thanks to a fully customized approach, every student feels like their lessons relate specifically to them. Indeed, no two lessons will be taught in the same way. People can have confidence that they have the best chance to succeed due to this personalized learning technique. It’s almost like having a mentor helping you every step of the way.
At the same time, adaptive learning also promotes better engagement with the learner. Think of the last time you read a textbook. Was it boring? Now imagine if the book was written personally for you. That would lead to a whole new level of interaction, and it’s what adaptive learning can offer. People who feel more engaged with what they learn will stick with it longer and get more out of it.
Improved Productivity and Mastery
The result of using adaptive learning is an increase in productivity and the true mastery of a topic. If companies use this technique for employees, they end up with workers who excel with their newfound skills. For example, if they have adaptive learning courses teaching leadership skills, organizations will have more leaders at all levels. Workers who have mastered their lessons and gained useful knowledge will perform better and produce more. The business as a whole will be better off for it.
Adaptive Learning for the Future
Adaptive learning tools are still in their infancy in the business world. However, if what educational institutions have seen is any indication, it will soon become more widespread and accepted. Training courses will see noticeable changes as learners have a personalized learning experience. The result will be a more productive and versatile workforce. Companies should begin focusing on the advantages of adaptive learning as it could become the new wave of the future.
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