Representing Computer-Supported Collaborative Learning macro-scripts using IMS Learning Design
| (2007). Representing Computer-Supported Collaborative Learning macro-scripts using IMS Learning Design. In Proceedings of the 2nd European Conference on Technology Enhanced Learning. Citeseer. |
BibTex
BibTex
@inproceedings{hernandez-leo2007representing,
author = {Hernández-Leo, Davinia and Burgos, Daniel and Tattersall, Colin and Koper, Rob},
booktitle = {Proceedings of the 2nd European Conference on Technology Enhanced Learning},
date-added = {2014-03-20 13:47:55 +0000},
date-modified = {2014-03-20 13:47:55 +0000},
organization = {Citeseer},
title = {Representing Computer-Supported Collaborative Learning macro-scripts using IMS Learning Design},
year = {2007},
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Highlights (8%)
Computer software for supporting scripted Collaborative Learning (CL) is designed with the aim of scaffolding social interactions among participants [1]. CSCL macroscripts structure CL scenarios by defining the composition of groups, the distribution of roles and resources as well as the coordination of the activities that make up the learning process [2], [3], [4]. Up to now, these scripts are “hardwired” in specific CSCL applications. p. 1
LD is broadly accepted as de facto standard to formally model interoperable Units of Learning (UoL). p. 1
some researchers are proposing alternative languages to describe CL scenarios [7]. p. 2
Altogether, the main drawback of scripts is their associated “risky” flexibility restrictions p. 2
[1]. Inflexible extrinsic constraints, such as the duration of activities, can spoil a satisfactory enactment of the learning scenario [9]. It requires modifications on the fly regarding the time structure, the resources or even the activities themselves and their order. These flexibility requirements are being deeply analyzed concerning adaptive situations for individual learning [6], [12]. Nonetheless, a common flexibility-demanding characteristic that significantly appears in CSCL scripts refers to flexible group composition. A typical problem of CL is the variability of students’ participation. It is often impossible to guess the precise amount of participants that are attending a particular session, if they will be an even or odd number, whether some of them will join the class afterwards or cannot participate in a specific moment [9]. These situations require unexpected group composition modifications. p. 2
Table 1. Requirements of CSCL macro-scripts, Universanté script
* Anchored Note, page 3 Nice table p. 3
