Adaptive learning is the future of employee training as it gauges the ability of employees and adjusts to challenge them based on their unique learning needs. As each learner’s needs are different and so are their expectations from a learning program.
Adaptive learning uses technology to create personalized learning by tailoring the path and pace of learning for each employee based on data that is gathered throughout the learning process and deliver better learning outcomes. The adaptive learning platforms use data mining via skill mapping, learning object mapping, and content mapping to put together learning content for learners that’s optimized for their learning needs. The platform uses the data that it continually gathers when a learner interacts with any learning content and helps deliver components that are relevant to the learner.
Adaptive Learning Platforms
An e-learning platform should focus on the effective sequencing of modules so that a user’s learning experience proceeds in a step-by-step manner. An effective adaptive learning platform successfully creates a perfect learning ladder. Further the pace at which employees learn vary from one another. Hence, an organization’s learning strategy must therefore be adaptive enough to adjust to the pace of each employee’s learning. The learning experience will be meaningful only if the learning platform ensures that every employee’s progress through the learning system happens only after they master what they are currently learning.
An adaptive learning platform must also take into consideration every employee’s prior knowledge base before letting the learners embark on their learning journey. If the learning platform fails to take this into account, it will end up providing either a frustrating experience to the beginners or a boring experience to the intermediate learners. The employee’s desired learning goals will depend on his/ her current knowledge base and a good adaptive learning experience can only be created if the learning program is tailored to enable every employee to assess the effectiveness of their training modules by putting the learned skills into practice Hence, enabling them to master the skills needed on the job.
An e-learning platform will fall short of its main purpose if it cannot keep the employee engaged. Learning process takes a lot of dedication and commitment from the side of the learners to be effective. A learning experience needs to be motivating and enjoyable to keep learners engaged. The e-learning strategy must not confine itself to directing and instructing employees so that they can proceed but should also promote interactive learning by which learners are made to think by themselves especially with regard to problem solving.
Finally, an adaptive learning platform should retrieve data based on learner responses and feedback and get insights from them. These analytics should be used to modify the elements of the adaptive learning platform so that the learning strategy is a dynamic one, always striving to provide a good learning experience.
Conclusion
Adaptive learning is here to stay and will be increasingly adopted in corporate training environments to manage training challenges. By custom-tailoring the learning paths continuously, adaptive learning fosters better learning outcomes and enhances the efficacy and performance of employees.
As organizations from various industries are challenged to provide continuous development that is effective and customized. With its data-centric approach, the scope of adaptive learning is exponentially growing to enable companies to keep pace with the evolving learning dynamics.
