Learners across the world can be very well controlled by machine learning (ML) technology. Employees today demand a higher standard of eLearning resources, which are both flexible and interactive. Leading eLearning providers are effectively personalizing learning, predicting learning requirements, and automatically providing relevant and timely content to its learners using a pattern recognition system. Let’s explore more about how ML technology is shaping the future of eLearning.
ML Can Recognize Learner’s Performance Patterns
ML algorithms can be used to track learners’ performance registered in an LMS based on which future learning sessions and their topics can be developed. This way, the actual needs of learning can be met. Such an approach is instrumental in situations like, for instance, 30 learners with different abilities and experience enrolled for a course. The ML LMS delivers customized content according to these individual learners by proactively adapting the course as per the varied learners’ abilities. Hence, by making certain tweaks to the learning content, more knowledgeable learners can progress faster, and less knowledgeable learners get a better opportunity to work on the learning material and acquire proper knowledge.
ML allows learners to acquire knowledge through a personal approach to teaching. With ML, learners can focus on their knowledge gaps rather than continuously hovering over the same and redundant curriculum.
In most of the cases, when learners start a course, they go through many unnecessary and dull parts of the training program. ML eliminates this demotivating aspect of training as the algorithms that monitor learners’ progress effectively refines the curriculum, removing those unnecessary parts.
This allows learners to spend significantly less time on training and acquiring the desired skills and reaching their training objectives. The incorporation of ML enables the learners to understand the fact that the course is tailor-made for fulfilling their knowledge gaps and that there will not be any wastage of time through irrelevant lectures.
They get the opportunity to participate in the course more actively as they know that the course responds precisely to their needs.
As ML has the potential to reduce the course duration significantly, it enables the employees/learners to focus on their job-related tasks. Moreover, since you can access your employees’/learners’ progress, you can schedule your online courses for them that requires a more refined approach to enable them to work better.
You can quickly spot the topics your students struggle with the most by analyzing the data generated by eLearning courses. Learners can focus on their knowledge gaps as ML algorithm will adjust the course material. Hence, you can save a lot of time and resources in training materials.
With the advent of video conferencing apps and messaging apps like Skype, personalized virtual training methodology also became popular. Music classes, project management, engineering discussion, academic tutoring are all nowadays possible due to online training.
Classrooms can be connected to different classrooms spread across broad geographical boundaries for fulfilling various training needs and for promoting a more effective learning system. Leading eLearning providers are using authoring softwares to develop multimedia applications for manipulating multimedia objects.
In the educational space, ML and other fields of artificial intelligence developments will play an imperative role. Natural language processing and ML algorithms are just the beginning of this technological transformation.
ML, when introduced into eLearning systems, can facilitate the acquisition of learner-centered and valuable knowledge. Developing a custom eLearning platform with ML can significantly increase the performance of your learners/employees. In addition, they will get enough time to get their job-related tasks done in an efficient way.