02545nas a2200241   4500008004100000245011500041210006900156260000900225300001400234490000600248520174100254653002501995653002702020653001402047653002402061653002102085100001702106700001902123700001402142700001402156700001602170856011702186       2010                        eng d00aEnabling automatic just-in-time evaluation of in-class discussions in on-line collaborative learning practices0 aEnabling automatic justintime evaluation of inclass discussions   c2010  a322 - 3290 v83 aLearning by discussion when applied to on-line collaborative learning settings can provide significant benefits for students in education in general. Indeed, the discussion process plays an important social task in collaborative learning practices. Participants can discuss about the activity being performed, collaborate with each other through the exchange of ideas that may arise, propose new resolution mechanisms, justify and refine their own contributions, and as a result, acquire new knowledge. Considering these benefits, current educational organizations incorporate on-line discussions into web-based courses as part of the very rationale of their pedagogical models. However, in-class collaborative assignments are usually greatly participated and contributed, which makes the monitoring and assessment tasks by tutors and moderators time-consuming, tedious and error-prone. Specially hard if not impossible by human tutors is to manually deal with the sequences of hundreds of contributions making up the discussion threads and the relations between these contributions. Consequently, tutoring tasks during on-line discussions usually restrict to offer evaluation results of the contributing effort and quality after the collaborative learning activity takes place and thus neglect the essential issue of constantly considering the process of knowledge building while it is still being performed. In this paper, we propose a multidimensional model based on data analysis from online collaborative discussion interactions that provides a first step towards an automatic evaluation in just-in-time fashion. The context of this study is a real on-line discussion experience that took place at the Open University of Catalonia.10aAutomatic evaluation10aCollaborative learning10aGroupware10aKnowledge discovery10aMachine learning1 aCaballé, S.1 aLapedriza, À.1 aMasip, D.1 aXhafa, F.1 aAbraham, A.  uhttp://www.scopus.com/inward/record.url?eid=2-s2.0-79960216812&partnerID=40&md5=0f38528ca7e6fa26bdcaf9c0b81206c902545nas a2200241   4500008004100000245011500041210006900156260000900225300001400234490000600248520174100254653002501995653002702020653001402047653002402061653002102085100001702106700001902123700001402142700001402156700001602170856011702186       2009                        eng d00aEnabling automatic just-in-time evaluation of in-class discussions in on-line collaborative learning practices0 aEnabling automatic justintime evaluation of inclass discussions   c2009  a289 - 2960 v73 aLearning by discussion when applied to on-line collaborative learning settings can provide significant benefits for students in education in general. Indeed, the discussion process plays an important social task in collaborative learning practices. Participants can discuss about the activity being performed, collaborate with each other through the exchange of ideas that may arise, propose new resolution mechanisms, justify and refine their own contributions, and as a result, acquire new knowledge. Considering these benefits, current educational organizations incorporate on-line discussions into web-based courses as part of the very rationale of their pedagogical models. However, in-class collaborative assignments are usually greatly participated and contributed, which makes the monitoring and assessment tasks by tutors and moderators time-consuming, tedious and error-prone. Specially hard if not impossible by human tutors is to manually deal with the sequences of hundreds of contributions making up the discussion threads and the relations between these contributions. Consequently, tutoring tasks during on-line discussions usually restrict to offer evaluation results of the contributing effort and quality after the collaborative learning activity takes place and thus neglect the essential issue of constantly considering the process of knowledge building while it is still being performed. In this paper, we propose a multidimensional model based on data analysis from online collaborative discussion interactions that provides a first step towards an automatic evaluation in just-in-time fashion. The context of this study is a real on-line discussion experience that took place at the Open University of Catalonia.10aAutomatic evaluation10aCollaborative learning10aGroupware10aKnowledge discovery10aMachine learning1 aCaballé, S.1 aLapedriza, À.1 aMasip, D.1 aXhafa, F.1 aAbraham, A.  uhttp://www.scopus.com/inward/record.url?eid=2-s2.0-77953238102&partnerID=40&md5=6dce6350dd861170e2133b9b2f597627