<p class="Standard" style="text-align:justify; margin-bottom:13px"><span style="font-size:11pt"><span style="line-height:115%"><span style="font-family:Calibri, sans-serif"><b><span style="font-size:12.0pt"><span style="line-height:200%"><span new="" roman="" style="font-family:" times="">RESUME&nbsp;</span></span></span></b></span></span></span></p> <p class="Standard" style="text-align:justify; margin-bottom:13px"><span style="font-size:11pt"><span style="line-height:115%"><span style="font-family:Calibri, sans-serif"><span style="font-size:12.0pt"><span style="line-height:150%"><span new="" roman="" style="font-family:" times="">Partant d&rsquo;un mod&egrave;le de description du dispositif d&rsquo;apprentissage en ligne fond&eacute; sur la notion d&rsquo;appropriation, l&rsquo;exploration de la plateforme permet de d&eacute;gager des profils en fonction de la dynamique des interactions communicationnelles g&eacute;n&eacute;r&eacute;es tout au long du parcours des apprenants. Chaque profil est discrimin&eacute; &agrave; partir des circuits emprunt&eacute;s durant la r&eacute;alisation des activit&eacute;s collaboratives (forums de discussion) et individuelles (glossaire et wiki) programm&eacute;es dans la plateforme, moyennant les ressources int&eacute;gr&eacute;es (supports en pdf et liste bibliographique). La mobilisation des outils d&rsquo;analyse des </span></span></span><i><span style="font-size:12.0pt"><span style="line-height:150%"><span new="" roman="" style="font-family:" times="">data learning</span></span></span></i><span style="font-size:12.0pt"><span style="line-height:150%"><span new="" roman="" style="font-family:" times=""> (langage Python&hellip;) permet de traquer les &laquo;&nbsp;traces&nbsp;&raquo; des participants au point de rendre potentiellement identifiable leur degr&eacute; d&rsquo;implication en termes d&rsquo;acquisition, de restitution et de capitalisation des connaissances mutualis&eacute;es<i>.</i></span></span></span><span style="font-size:12.0pt"><span style="line-height:150%"><span new="" roman="" style="font-family:" times=""> La diff&eacute;renciation ainsi d&eacute;gag&eacute;e laisse voir des profils h&eacute;t&eacute;rog&egrave;nes susceptibles de mesurer le niveau d&rsquo;engagement (et/ou de d&eacute;sengagement) des apprenants et de rep&eacute;rer, un tant soit peu, leurs strat&eacute;gies d&rsquo;apprentissage en ligne. </span></span></span></span></span></span></p> <p style="text-align:justify; margin-top:19px; margin-bottom:19px"><span style="font-size:12pt"><span style="line-height:150%"><span new="" roman="" style="font-family:" times=""><b>Mots cl&eacute;s&nbsp;:</b> <i>Tracking flow</i>, Interaction, Trace num&eacute;rique, M&eacute;diatisation, Apprentissage</span></span></span></p> <p style="text-align:justify; margin-top:19px; margin-bottom:19px"><span style="font-size:12pt"><span style="line-height:115%"><span new="" roman="" style="font-family:" times=""><b><span lang="EN-US" style="font-size:12.0pt"><span style="line-height:115%"><span new="" roman="" style="font-family:" times="">ABSTRACT </span></span></span></b></span></span></span></p> <p style="text-align:justify; margin-top:19px; margin-bottom:19px"><span style="font-size:12pt"><span style="line-height:115%"><span new="" roman="" style="font-family:" times=""><span lang="EN-US" style="font-size:12.0pt"><span style="line-height:150%"><span new="" roman="" style="font-family:" times="">Starting from a model of description of the online learning system based on the concept of ownership, the exploration of the platform allows profiles to be identified according to the dynamics of the communication interactions generated throughout the learner&rsquo;s course. Each profile is discriminated against from the circuits borrowed during the conduct of collaborative activities (discussion forums) and individual activities (glossary and wiki) scheduled in the platform. The mobilization of data learning analysis tools (Python software...) enables the tracing of participants to be traced to the point of potentially making their level of involvement in the acquisition, restitution and capitalization of mutual knowledge identifiable. The differentiation thus revealed heterogeneous profiles that can measure the level of commitment (and/or disengagement) of learners and identify, at some point, their online learning strategies.</span></span></span></span></span></span></p> <p style="text-align:justify; margin-top:19px; margin-bottom:19px"><span style="font-size:12pt"><span style="line-height:115%"><span new="" roman="" style="font-family:" times=""><b><span lang="EN-US" style="font-size:12.0pt"><span style="line-height:115%"><span new="" roman="" style="font-family:" times="">Keywords</span></span></span></b><span lang="EN-US" style="font-size:12.0pt"><span style="line-height:115%"><span new="" roman="" style="font-family:" times=""> : Tracking flow, Interaction, Digital Trace, Media, Learning</span></span></span></span></span></span></p>