A learning analytics framework for practice-based learning

Research output: Chapter in Book/Report/Conference proceedingArticle in proceedingsResearchpeer-review

The role of the PELARS Learning Analytics System (LAS) system is to collect information from students performing project-based tasks, reason on such information and provide visualization to teachers and students, that is usable for understanding the learning process. The information collected by the LAS comprises pieces of information collected directly by the Students, and other collected by the System automatically. In this work we will provide a comprehensive description of the framework and the motivations behind the various decisions. The software framework will be described starting from the broad vision of the context and then the different components will be described in detail.

Original languageEnglish
Title of host publicationExploring the Material Conditions of Learning : Computer Supported Collaborative Learning Conference 2015, CSCL 2015 - Conference Proceedings
EditorsOskar Lindwall, Paivi Hakkinen, Timothy Koschmann, Pierre Tchounikine, Sten Ludvigsen
Number of pages2
PublisherInternational Society of the Learning Sciences (ISLS)
Publication date2015
Pages741-742
ISBN (Electronic)9780990355076
Publication statusPublished - 2015
Externally publishedYes
Event11th International Conference on Computer Supported Collaborative Learning: Exploring the Material Conditions of Learning, CSCL 2015 - Gothenburg, Sweden
Duration: 7 Jun 201511 Jun 2015

Conference

Conference11th International Conference on Computer Supported Collaborative Learning: Exploring the Material Conditions of Learning, CSCL 2015
LandSweden
ByGothenburg
Periode07/06/201511/06/2015
SponsorGothenburg and Co, National Science Foundation, Taylor and Francis, The City of Gothenburg, The International Society of the Learning Sciences, University of Gothenburg, Faculty of Education and the Linnaeus Centre for Research on Learning, Interaction and Mediated Communication in Contemporary Society (LinCS)
SeriesComputer-Supported Collaborative Learning Conference, CSCL
Volume2
ISSN1573-4552

    Research areas

  • Action recognition, Arduino, Kinect, Learning analytics, Software framework

ID: 256264990