(untitled) (ENTRENOVA - ENTerprise REsearch InNOVAtion Journal, 2019)
In this paper, we present a software to support educators by collecting and processing data in each step of the experimental learning cycle for cognitive apprenticeship. We do so by developing a system that allows educators to (1) define a set of competences, (2) link keywords to each competences, (3) analyse reflexive papers written by students as evidences of their acquired competences after practical projects and (4) analyse multiple documents to assign students to different clusters to better coach them. The theoretical ground for our artefact lays in the intersection between the body of knowledge concerning experiential learning and statistical learning theory. We support our claims by illustrating results coming from 15 students of a Team Academy course and 100 students of a university course. This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.