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Adaptive learning with Big Data

Adaptive learning – Assimilate

Adaptive learning is an algorithm combining research in cognitive science and Big Data. It enhances knowledge assimilation by defining smart learning paths perfectly adapted to the learner’s profile and needs.

“The rapid digitization of the education industry and the emergence of cognitive systems is already happening in parallel.” 

Source: IBM Research 5 in 5 2013 – The classroom will learn you – Cognitive systems will provide decision support for teachers

Assimilation avec l’apprentissage adaptatif et personalisé


Il existe de nombreuses théories sur la manière dont nous apprenons, des rapports sur les modes d’apprentissage, les préférences des apprenants en matière de pédagogie ou encore sur des expérimentions ou concepts… Il est surtout important de réaliser que ces théories convergent sur un même point : chacun a ses propres préférences et facilités d’apprentissage.

D’autre part, les points de départ et de fin de l’apprentissage peuvent varier pour chacun, conduisant à l’importance d’offrir un apprentissage adaptatif et personnalisé.

Il existe tout de même certaines stratégies pour renforcer les résultats de l’apprentissage :

  • Utiliser des pédagogies différentes en fonction des supports,
  • Challenger les apprenants avec des tests,
  • Proposer un suivi avec des données pertinentes et utiles,
  • Adapter le parcours d’apprentissage au rythme de chacun,
  • Définir des objectifs alignant niveau de connaissance et maîtrise des compétences.

Assimilation with adaptive and personalized learning

or how we learn

There are many theories of how we learn, some introduce the learning styles, others insist on learner’s preference with some pedagogies, some others claim about an experimental approach, others more conceptual…

Agree or disagree? What is important to note is that these theories converge at one point: everyone has a preference and facility for some type of pedagogy or knowledge, and this one can differ from one person to another.

Furthermore, the starting and ending point of learning are or can be different for each one, leading to the need of adaptive and personalized learning.

In any case, some important strategies to enhance learning outcomes are:

  • Use different learning pedagogies for each content,
  • Challenge learners with tests,
  • Provide useful and insightful feedback,
  • Adapt the learning path to the individual pace,
  • Settle objectives and goals matching the knowledge level and skills mastery.

Happy New Year 2016 from Domoscio

Domoscio’s team wishes you a happy and successful new year 2016.

As for us, the new year brought Domoscio a brand new logo. It will be soon followed by the renewal of all our PR materials.

Stay tuned for other surprises!

Domoscio’s team


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