Adaptive Learning (or adaptive learning) provides a set of possibilities for achieving better pedagogical effectiveness and better engagement of learners and better business agility.
What is adaptive learning?
Adaptive learning, or adaptive learning, is a method that adapts the learning path, both in terms of resources and pace, to the activity of each user.
Its origins lie in the cognitive psychology of the 1950s. Subsequently, American universities boosted its use in response to the health crisis and the obligation to transfer teaching from face-to-face to distance learning.
To set up effective programs, data is collected at the beginning of the training based on an initial test, which makes it possible to assess the level of the learner in the targeted skill. The data is then exploited in real time, as the user interacts with the platform. LXP. In return, the system “reacts” and updates its educational proposals.
Adaptive learning takes into account each learner and how he or she remembers the knowledge he or she gains. The program is thus adapted to his profile to support him in the acquisition of new knowledge and skills. In concrete terms, a group of learners enrolled in an LXP including an adaptive learning program will thus have the same theoretical base but a different implementation adapted to each profile, both in terms of pace and in terms of the content made available. Adaptive learning thus makes it possible to rreduce the dropout rate and to promoteLearner engagement.
How to get uses adopted through adaptive learning?
Adaptive learning - or adaptive learning - continuously defines the profile of the learner by taking into account the time spent storing information and his progress, but also thanks to The AI that will analyze its intentions and actions.
To get users to adopt uses and building a learning culture thanks to adaptive learning, the Digital Learning Manager must be based on four criteria:
- Adapt to the learner's learning pace : the memorization and integration of knowledge are more effective when learners choose their pace of work. Learners will therefore only be able to move forward in their career once each concept has been mastered.
- Take into account the level of knowledge : an adaptive learning program analyzes the needs of learners and their goals beforehand and then sets up the learning path necessary to achieve them. This makes it possible to adapt the program according to the level of users.
- Suggest resources to involve the learner : vary resources is essential to keep learners motivated, especially at a time when the web offers many formats for training or information: video, text, podcast, etc. It is also possible to integrate concepts of Gamification in learning to involve users more.
- Analyzing learners' responses : the adaptive learning system interacts continuously with learners as they progress through their training program. AI analyzes their ability to solve problems or the speed with which they respond to questions asked during evaluations. In this way, the system analyzes all the data. in real time to adapt to the pedagogical approach of each user.
Adaptive learning offers the right content, at the right time and at a level of difficulty adapted to everyone.
