GRAPPLE - Generic Responsive Adaptive Personalized Learning Environment
People
(Responsible)
Abstract
The GRAPPLE project aims at delivering to learners a technology-enhanced learning (TEL) environment that guides them through a life-long learning experience, automatically adapting to personal preferences, prior knowledge, skills and competences, learning goals and the personal or social context in which the learning takes place. The same TEL environment can be used/accessed at home, school, work or on the move (using mobile/handheld devices). GRAPPLE will include authoring tools that enable educators to provide adaptive learning material to the learners, including adaptive interactive components (visualizations, simulations, virtual reality). Authoring includes creating or importing content, assigning or extracting meaning from that content, designing learning activities and defining pedagogical properties of and adaptation strategies for the content and activities. To ensure the wide adoption of adaptation in TEL GRAPPLE will work with Open Source and commercial learning management system (LMS) developers to incorporate the generic GRAPPLE functionality in LMSs. Evaluation experiments in higher education and in industry will be performed to verify the usability of the GRAPPLE environment (for authoring and delivery) and to verify the benefits of using adaptive TEL for the learning outcome. Apart from stimulating the use of adaptive TEL by making it available to every organization using a (popular) LMS the GRAPPLE consortium will also organize training/evaluation events to help higher education institutes and companies with the adaptive learning design needed to create adaptive learning material, and to receive usability feedback which the project will use to improve the user interfaces. A distributed user modeling service architecture will help end-users to stay in control of their user profile while at the same time allowing them to use the profile to get personalized access to learning applications offered through different LMSs by different organizations.
Additional information
Publications
- Mazzola L., Mazza R. (2011) Visualizing Learner Models through data aggregation: a test case. . Red-conference, rethinking education in the knowledge society, Monte Verità, Switzerland, March 7-10, pp.372- 380, ISBN 978-88-6101-010-9
- Mazzola L., Mazza R. (2010) An infrastructure for creating graphical indicators of the learner profile by mashing up different source. Proceedings of the working conference on Advanced Visual Interfaces, AVI 2010
- Mazzola L., Mazza R. (2010) GVIS: A Facility for Adaptively Mashing Up and Representing Open Learner Models. "Sustaining TEL: From Innovation to Learning and Practice" Lecture Notes in Computer Science, Volume 6383/2010, pp. 554-559, Proceedings of EC-TEL 2010, DOI: 10.1007/978-3-642-16020-2_53
- Mazzola L., Mazza R. (2009) Supporting Learners in Adaptive Learning Environments through the Enhancement of the Student Model.. Human-Computer Interaction. Interacting in Various Application Domains, 13th International Conference, HCI International 2009, San Diego, CA, USA, July 19-24, 2009, Proceedings, Part IV. Lecture Notes in Computer Science 5613 Springer 2009, ISBN 978-3-642-02582-2: 166-175
- Mazzola L., Mazza R. (2009) Toward Adaptive Presentations of Student Models in eLearning Environments.. 14th International Conference on Artificial Intelligence in Education, AIED 2009, July 6-10, 2009, Brighton, UK. Frontiers in Artificial Intelligence and Applications 200 IOS Press 2009, ISBN 978-1-60750-028-5 : 761-762
- Mazzola L. (2009) Towards Adaptive representations of Open Learner Models.. Doctoral Consortium of UMAP2009
