JUCS - Journal of Universal Computer Science 19(6): 805-830, doi: 10.3217/jucs-019-06-0805
LeadFlow4LD: A Method for the Computational Representation of the Learning Flow and Data Flow in Collaborative Learning
expand article infoLuis Palomino-Ramírez, Miguel L. Bote-Lorenzo§, Juan I. Asensio-Pérez§, Laurence Vignollet|, Yannis Dimitriadis
‡ ITESM, Campus Guadalajara, Guadalajara, Mexico§ University of Valladolid, Valladolid, Spain| University of Savoie, Annecy, France¶ Universidad de Valladolid, Valladolid, Spain
Open Access
A computer representation of teaching-learning processes in collaborative learning settings consists of modelling not only the sequence of learning activities and educational resources as existing learning design languages propose, but also modelling both the sequence of invocations of tools needed to carry out the learning activities and the flow of data among those tools. Existing data flow approaches only model data with activities but not data with tools. In this paper, we present LeadFlow4LD, a learning design and workflow-based method to achieve such a computational representation of collaborative learning processes in an interoperable and standard way. The proposed method has been assessed through the specification and enactment of a variety of non-trivial collaborative learning situations. The experimental results indicate that the level of expressiveness of the proposal is adequate in order to represent the flow of tools invocations and data which was missing in other existing research approaches.
data flow, learning design, learning flow, workflow, IMS LD, CSCL