LeadFlow4LD: A Method for the Computational Representation of the Learning Flow and Data Flow in Collaborative Learning
            
            
               Luis Palomino-Ramírez (ITESM, Campus Guadalajara, Mexico)  
              
             
            
            
               Miguel L. Bote-Lorenzo (University of Valladolid, Spain)  
              
             
            
            
               Juan I. Asensio-Pérez (University of Valladolid, Spain)  
              
             
            
            
               Laurence Vignollet (University of Savoie, France)  
              
             
            
            
               Yannis A. Dimitriadis (University of Valladolid, Spain)  
              
             
                    
            
              Abstract: 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. 
             
            
              Keywords: CSCL, IMS LD, data flow, learning design, learning flow, workflow 
             
            Categories: L.3.0, L.3.6  
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