The education sector continuously sees new solutions arriving on the scene that merge technology and education with the end goal of transforming the learning process for efficiency sake. Many trends have emerged in recent years including several linked to eLearning. One in particular has sparked its share of debate and which should come to a head in the years to come is adaptive learning. Leaning on neuroscience, artificial intelligence, big data as well as education, this issue is an important one in terms of learning.

Adaptive learning is an educational concept aimed at adapting education to the abilities and needs of each learner. This concept is strongly linked to learning profiles (gains, aptitudes, etc..) and was founded in the 1970s by Antoine de la Garanderie. The idea was born from the sheer variety of student profiles given the way everyone learns in their own way according to their memory, their preferences and their pace. This training mode is inspired by big data and algorithms.

Adapting a pedagogical decision to the student is what is expected of trainers and teachers on a daily basis. Nevertheless, here it is about digitization of adaptive learning since it is a matter of automating the adaptation of pedagogical decisions using science (algorithms, big data, neuroscience and neuro-pedagogy).

Essentially, these are online courses, exercises or assessments adapted to the learner in real time, according to their pace, difficulties, strengths and preferences. As such, in following any course, two students will not have an identical path. The goal is for everyone to progress and avoid abandonment or frustration.

We can also observe different models:

  • Either we create a set of educational resources and we run the algorithm on it,
  • Either from a set of pre-existing educational resources, which must be mapped before being able to run the algorithm on it.

But beware, the key idea is not only to work on the content that is made available, but also on the user experience that we want to offer to the learner.

There are positive results that can be explained by undeniable advantages: responding to the individual needs of each learner during the training process by offering personalized learning that will motivate them to learn and not give up along the way.

Ultimately, training more students by optimizing costs and making them succeed through a personalized learning process are the issues that adaptive learning tries to address. If it questions and sometimes probes the learner, he or she will be able to succeed and there is no doubt that it will soon be at the heart of all training modules.

Caroline Irrmann, web editor