Taking Personalisation to a New Level with Adaptive eLearning
The last few years have seen eLearning software transform significantly. Newer systems of technology have paved the way for different, more efficient approaches to learning, such as adaptive learning. With fixed paths and standardised learning, comes an experience that can become rather overwhelming for a learner; especially for the sake of navigation when tracking where one stands or where one last left off. It is no wonder that the way for adaptive systems has been chiselled perfectly in the corporate world. Using a wide range of simple and complex algorithms, adaptive systems make for irrefutable new platforms for learning. Simple algorithms customise content on the basis of pre-testing, and complex algorithms take a more holistic approach that involves multiple data points, so as to be able to customise learning paths, analytics, HR data, performance feedback, and so on. Allowing individuals to learn at their own pace, as per their ability to answer questions accurately and confidently, adaptive learning has the potential to push businesses towards achieving their goals by enhancing the efficiency of corporate training. So what exactly can adaptive systems do for you?
Adaptive learning is algorithmic and accustoms itself to the needs of the learner based on tasks and responses. In standardised eLearning software, personalized feedback does not exist. Adaptive learning understands that one size does not fit all. When learning is carried out one-to-one, the smallest of the learner’s problems are focused on and understood.
Focus on Learner Engagement
Building simple algorithms that can be rolled out to employees helps to use the feedback thus gathered to improve learner engagement. The personalized approach that understands every individual’s learning pace, allows for a more time-efficient approach to training employees. Based on the ability of individuals to grasp basic concepts, the learners do not need to go through content that they already understand, thus increasing and maintaining engagement.
Reduction in the Learning Time
Redundant content is out, smaller capsules of content are in! Microlearning can be considered as a complementary approach to the existing adaptive learning frameworks, so as to reduce the time each individual learner takes to go through and understand the learning modules.
Focus on Feedback and Remediation
Adaptive learning looks into modelling what the user already knows and strongly focuses on strengthening concepts that employees struggle with, rather than purely on the results obtained. Systems can collect and return the learner’s feedback, so as to aid the corporate in viewing trends and modifying content and its flow to ensure that learner experiences are constantly improving. The application, scaled up to the enterprise level, needs to be flexible to enable continuous improvement.
Ability to provide real-time insights
Adaptive systems are useful for employers to gauge the level of the employee’s skills. They track performance and enable the organization to decide if the employee is ready to take on more intensive assignments. Real-time analytics help in ensuring that content is flexible and well-aligned for the needs of the business and those of the employees.
Certainly, along with the indisputable benefits of adaptive learning, there come challenges that need to be carefully considered. The solutions to these challenges vary but can be steered through with a clear roadmap, starting small and using feedback to augment a larger workflow. Executed correctly, adaptive learning can be both, time and cost effective. For a presentation on adaptive learning, how it works, and how it can be implemented for your business, get in touch with us on firstname.lastname@example.org.