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A multiple constraints framework for collaborative learning flow orchestration

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dc.contributor.author Manathunga, Kalpani
dc.contributor.author Hernández Leo, Davinia
dc.date.accessioned 2016-10-21T17:49:20Z
dc.date.available 2016-10-21T17:49:20Z
dc.date.issued 2016
dc.identifier.citation Manathunga K, Hernández-Leo D. A multiple constraints framework for collaborative learning flow orchestration. In: Dickson KW C, Marenzi I, Nanni U, Spaniol M, Temperini M, editors. Advances in Web-Based Learning – ICWL 2016. 15th International Conference, Rome, Italy, October 26–29, 2016, Proceedings. Heidelberg: Springer, 2016. p. 225-35. (LNCS, no. 10013). DOI: 10.1007/978-3-319-47440-3_25
dc.identifier.uri http://hdl.handle.net/10230/27422
dc.description Paper presented at ICWL 2016, 15th International Conference, Rome, Italy, October 26–29, 2016.
dc.description.abstract Collaborative Learning Flow Patterns (e.g., Jigsaw) offer sound pedagogical strategies to foster fruitful social interactions among learners. The pedagogy behind the patterns involves a set of intrinsic constraints that need to/nbe considered when orchestrating the learning flow. These constraints relate to the organization of the flow (e.g., Jigsaw pattern - a global problem is divided into sub-problems and a constraint is that there need to be at least one expert group working on each sub-problem) and group formation policies (e.g., groups solving the global problem need to have at least one member coming from a different previous expert group). Besides, characteristics of specific learning situations such as learners’ profile and technological tools used provide additional parameters that can be considered as context-related extrinsic constraints relevant to the orchestration (e.g., heterogeneous groups depending on experience or interests). This paper proposes a constraint framework that considers different constraints for orchestration services enabling adaptive computation of orchestration aspects. Substantiation of the framework with a case study demonstrated the feasibility, usefulness and the expressiveness of the framework.
dc.description.sponsorship This work has been partially funded by the Spanish Ministry of Economy and Competitiveness/n(TIN2014-53199-C3-3-R; MDM-2015-0502).
dc.format.mimetype application/pdf
dc.language.iso eng
dc.publisher Springer
dc.relation.ispartof Dickson KW C, Marenzi I, Nanni U, Spaniol M, Temperini M, editors. Advances in Web-Based Learning – ICWL 2016. 15th International Conference, Rome, Italy, October 26–29, 2016, Proceedings. Heidelberg: Springer, 2016. p. 225-35. (LNCS, no. 10013).
dc.rights © Springer The final publication is available at Springer via/nhttp://dx.doi.org/10.1007/978-3-319-47440-3_25
dc.title A multiple constraints framework for collaborative learning flow orchestration
dc.type info:eu-repo/semantics/bookPart
dc.identifier.doi http://dx.doi.org/10.1007/978-3-319-47440-3_25
dc.subject.keyword CSCL
dc.subject.keyword Collaborative Learning Flow Pattern(s)
dc.subject.keyword Macro scripts
dc.subject.keyword Jigsaw
dc.subject.keyword Learning flow orchestration
dc.relation.projectID info:eu-repo/grantAgreement/ES/1PE/TIN2014-53199-C3-3-R
dc.relation.projectID info:eu-repo/grantAgreement/ES/1PE/MDM-2015-0502
dc.rights.accessRights info:eu-repo/semantics/openAccess
dc.type.version info:eu-repo/semantics/acceptedVersion


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