Generally speaking, adaptive learning refers to the practice of tailoring learning to fit the unique needs of each individual. More specifically as it relates to learning technology, adaptive learning is the use of algorithms and artificial intelligence to curate learning.
The goal of adaptive learning is to move beyond “one size fits all” learning methods, recognising that everyone has their own styles, paces and preferences.
Imagine there is a tech company, “Tech Company A.”
They prioritise their employees’ continuous professional development, and want to make sure everyone’s learning journey is right for them from the very start of their role. To ensure this, Tech Company A has implemented an adaptive learning system.
When a new starter has their first day at Tech Company A, they’ll take a skills assessment within the company’s Learning Management System to evaluate their proficiency in various areas. Based on the results of this assessment, the LMS creates a personalised learning pathway for each new starter.
For instance, a new developer might be proficient in front-end development but lack experience in cloud computing. The system will tailor the learning pathway to focus more specifically on advanced cloud technologies.
The characteristics of adaptive learning are as follows:
Personalisation is at the core of adaptive learning. Adaptive learning systems are designed to customise content to match the learner’s proficiency level and pace.
Varied learning paths and levels of difficulty:
Adaptive systems offer a diverse range of learning paths based on the learner’s progress, and adjust the difficulty of the learning to suit their individual needs.
Data-driven insights and analytics:
Adaptive learning systems collect data on learners’ progress in real time, enabling managers to track progress and adjust the material accordingly. Analytics provide insights into the strengths and weaknesses of each learner.
Engaging learning material:
Adaptive learning incorporates multiple formats designed to engage the user including games, quizzes, videos and multimedia.
Learning Management Systems that embrace adaptive learning will promote collaboration between users, fostering interaction that leads to problem-solving and interaction.
Responsive and user-friendly technology:
The system adapts instantly to learner responses, making adjustments to the content, pace and difficulty in real time. The technology should be responsive and user-friendly to encourage its use, and accessible from anywhere on any device.
The goal of adaptive learning is to provide a personalised and efficient learning experience for each individual. This fosters engagement, addressing diverse learning styles and optimising the learning process through real-time adjustments and data–driven insights.
Some of the pitfalls of adaptive learning include: Potential challenges in accurately assessing complex skills, and the risk of reinforcing bias present within algorithms.
Implementing adaptive learning involves selecting a suitable learning platform, aligning content with learning objectives, and configuring the system to adjust difficulty levels. Establish clear goals for individualisation, provide robust training, and regularly analyse data for insights into learner progress.
Continuously refine the adaptive model based on your users’ feedback.
Explore what impact Thrive could make for your team and your learners today.