2026-04-14T21:01:47Zhttps://uvadoc.uva.es/oai/request
oai:uvadoc.uva.es:10324/314062025-09-23T08:26:09Zcom_10324_1191com_10324_931com_10324_894col_10324_1381
UVaDOC author Rodríguez Triana, María Jesús author Prieto Santos, Luis Pablo author Martínez Monés, Alejandra author Asensio Pérez, Juan Ignacio author Dimitriadis Damoulis, Ioannis 2018-09-05T15:09:57Z 2018-09-05T15:09:57Z 2018 http://uvadoc.uva.es/handle/10324/31406 Collaborative learning flow patterns (CLFPs) en code solutions to recurrent pedagogical problems, which have been successfully applied to the design of learning experiences. However, the pedagogical knowledge encoded in these patterns has seldom been exploited in learning analytics (LA). This paper analyzes four of the most common CLFPs to extract the intrinsic constraints that lead to a successful collaborative learning activity, and use them to enhance existing LA solutions. To understand the added value of applying such codified knowledge in LA, we present evidence from five authentic case studies in which such constraints aided university teachers in monitoring complex collaborative scripts. The results not only illustrate quantitatively such added value but also unearth qualitative benefits, such as raising practitioners awareness about how the current state of activities may affect future phases of the script. eng Monitoring collaborative learning activities: exploring the differential value of collaborative flow patterns for learning analytics info:eu-repo/semantics/conferenceObject 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URL https://uvadoc.uva.es/bitstream/10324/31406/1/2018-ICALT-CLFPs%28preprint%29%281%29.pdf File MD5 c6e55f53c549b8d02a4f875f0cebc953 1449404 application/pdf 2018-ICALT-CLFPs(preprint)(1).pdf