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Learner
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Manager
Author
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Learner
  • Diagnostic of the learner’s target skills with an adaptive assessment
  • Learning recommendations adapted to the learner’s profile and needs
  • Gamified dashboard to follow the learner’s upskilling process
Learner
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Manager
Author
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Manager
  • Interface to monitor the learners both individually and collectively
  • Reporting on the learners’ proficiency on the required skills
  • Dashboard to measure the efficiency of the learning actions
Learner
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Manager
Author
Group 23 Created with Sketch.
Author
  • Design of themes in autonomy via Domoscio Hub authoring tool
  • Functionality to export in SCORM format and distribute on the LMS
  • Dashboard with feedback on the relevance of the learning materials

Our clients improve the impacts of learning

Illustration Temps gagné pour acquérir les compétences cibles
37 %

Time saved to acquire the target skills

illustration Échecs en moins dans le parcours de formation
49 %

Fewer learners failing the learning path

The results presented above have been achieved as part of experimental protocols carried out with several clients of Domoscio.


Adaptive learning to individualize the learning plans

An illustration of a learner in the process of carrying out a learning program adapted to his profile and pedagogical objectives.

Hub is an adaptive learning solution which individualizes the learning plans according to each learner’s skills proficiency and job requirements. 

  • The learner’s objective is defined by job requirements or strategic workforce planning 
  • The learner’s level of proficiency is assessed with an adaptive positioning test: the quizzes evolve in real time according to the collected results
  • The learner’s path is built with recommendations of learning materials adapted to their individual profile: classroom training, e-learning, micro-learning, immersive learning, etc.

Once the recommendations have been followed, the algorithm reassesses the learners to measure their progress and, if necessary, recommend them new learning materials to follow. The machine learning models make use of this new data to identify the most efficient learning materials according to the different typologies of learners.

Hub adapts to the context of each company and each business unit by using existing content, no matter the format (face-to-face, virtual classroom, video, quiz, etc.) and the source (LMS, digital material library, video streaming platform, etc.). To do this, it interfaces with existing learning platforms (LMS, TMS, LEP, etc.) using the interoperability standards of the learning market: SCORM, LTI, xAPI, etc. Therefore, the user experience is seamless and transparent for the learners, which improves their engagement. 

Thanks to the generated data, Hub provides the different stakeholders with analytics adapted to their needs. The manager can monitor the skills development of his or her employees, individually and collectively, to identify potential training actions to be implemented. The learning team has access to data on the use, difficulty and relevance of materials, to better adjust their learning design strategy. Finally, the HR manager can monitor aggregate analytics related to the use of the tool and skills management.


They trust us


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