2024-03-29T11:03:36Zhttps://uvadoc.uva.es/oai/requestoai:uvadoc.uva.es:10324/314062021-10-19T18:23:32Zcom_10324_1191com_10324_931com_10324_894col_10324_1381
Rodríguez Triana, María Jesús
Prieto, Luis P.
Martínez Monés, Alejandra
Asensio Pérez, Juan Ignacio
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.
Ministerio de Economía, Industria y Competitividad (Projects TIN2014-53199-C3-2-R and TIN2017-85179-C3-2-
R)
Junta de Castilla y León (programa de apoyo a proyectos de investigación – Ref. VA082U16)
Ministerio de Educación, Cultura y Deporte (PRX17/00410)
application/pdf
eng
info:eu-repo/semantics/restrictedAccess
Monitoring Collaborative Learning Activities: Exploring the Differential Value of Collaborative Flow Patterns for Learning Analytics
ICALT 2018
International Conference on Advanced Learning Technologies, ICALT 2018 (8º.2018. Bombay, India)
info:eu-repo/semantics/conferenceObject