Adaptive Learning: Moving from learning styles to learning preferences
Before going in-depth about what Adaptive Learning means, it is important to highlight that Adaptive Learning uses the concept of Learning Preferences to create personalized and tailor-fit experiences for learners. Learning preferences are all about how people learn, not only in terms of how information is conveyed but also how they approach learning, in other words, “Learning preferences refer to how much a learner prefers certain educational modalities over others.”
Learning preferences refer to how much a learner prefers certain educational modalities over others.
Even if this seems natural and logical to you, the idea of Learning Preference represents a pedagogical change from the previous reigning approach: Learning Styles. Learning Styles refers to the method by which new information is introduced. There are four globally used learning styles:
- Visual,
- Auditory,
- Reading, and
- Kinesthetic
The Learning Style approach was based on the premise that when learners were accommodated within a specific learning style understanding and knowledge retention increased. However, Learning Preferences represents a more holistic approach to learning, a move towards providing the learner more choice and agency/authority over their learning environment, including multiple Learning Styles. A holistic approach to learning to understand the learner and giving them the option to build their own learning path that accommodates to what they want, require and prefer is what Adaptive Learning is all about.
Learning Preferences represents a more holistic approach to learning, a move towards providing the learner more choice and agency/authority over their learning environment, including multiple Learning Styles.
What is adaptive learning and what are its benefits?
In a few words, Adaptive learning is a technique for delivering personalized learning experiences that address the unique learning preferences of individuals through a data-driven approach that self adjusts the path and pace of learning, delivering tailored fit learning experiences at scale. Adaptive Learning aims to debunk a one-size-fits-all learning experience through the use of technology and automation of tedious tasks.
The benefits of adaptive learning, among many others are the following:
- One to one instruction: Rather than a one-size-fits-all approach, adaptive learning allows you to have the closest experience to a one on one instruction as no one else would receive the same experience.
- Better use of learner’s time: Not only avoiding the tedious repetition of training on what they have already mastered, but also spending time effectively with exercises that are best suited the learner
- Confidence-based approach: Exercise and questions ranked based on difficulty that instead of discouraging learners, empowers them.
- Individual Learning Paths: Create a learning path exclusive for each learner’s needs and skills
- Flexible learning: Not only through personalized content and exercise, but allow learners to choose their own pace.
- Increase of knowledge retentions and learner engagement
- Better use of teacher/instructor’s time: Automation of tedious tasks, and automatic creation of tailored content and exercises for each learner.
How has traditional learning tried to approach adaptive learning?
The ability to curate learning experiences isn’t new in the analog world. Most universities have Liberal Arts degrees where students can pick and choose subjects from different fields and work towards a personalized degree. In K-12 systems, students at young ages are able to choose electives and concentrations in an attempt to create a more personalized path that fits their interests and likes. Other efforts are made by teachers in class, trying to understand the knowledge level of learners and trying to create personalized materials and tests. However, this has shown to be extremely tedious and time-consuming. Traditional learning offers limited options to make the learning process more adaptive; however, these are insufficient and sometimes impossible to carry on because of time constraints.
Digital Learning and Adaptive Learning:
Based on what was mentioned above: Does this mean that teachers, course creators, and trainers around the world now need to create individualized experiences, from a to z, for each of their learners? No, that’s where technology comes in. Digital learning has opened a wide range of possibilities through technologies such as AI, NLP, and Machine Learning. Digital learning has been taken to the point that it can automate, compile and, digest previously time-consuming or tedious elements into actionable insights that deliver to the learner experiences that are exactly what they need and want to learn effectively.
How to incorporate Adaptive Learning?
As mentioned above, technology and digital learning have equipped us with plenty of tools to ensure that we can leverage these to create personalized and adaptive learning experiences for learners. Current digital learning solutions use Algorithms, AI, Quizzes and Assessments, Linear and non-linear learning, Natural Language Processing (NLP), and finally, personalized learning. Adaptive Learning within digital learning solutions remains to be scarce; however, there are companies like Duolingo that have been recognized for their use of Adaptive Learning. “Users start with Duolingo’s AI-driven adaptive placement test which probes them with real exercises they would take during the course—so if you’ve had four years of high-school French, you don’t have to start at the beginning of the most basic course. Each question or challenge in the test is adaptively chosen based on the previous question, and whether you got it right or wrong.” More than that, CanopyLAB’s adaptive, social and intelligent learning space includes uses Artificial Intelligence (AI) to understand the learners’ needs, skills, wants, and uses this information for its AI-driven content authoring tool that assures that each course is modelled to create adaptive courses, making sure that every learner has a personalized and adaptive learning experience.
CanopyLAB’s adaptive, social and intelligent learning space includes uses Artificial Intelligence (AI) to understand the learners’ needs, skills, wants, and uses this information for its AI-driven content authoring tool that assures that each course is modelled to create adaptive courses, making sure that every learner has a personalized and adaptive learning experience.
