Many advantages are claimed for learning environments that use multiple external representations (like graphs, tables, animations, etc.) but research assessing their impact on learning has produced mixed results.
My main contribution to this project was to develop a simulation-based learning environment (DEMIST, Design Environment for Multi-representational Instructional Simulation Technology) as a research platform and use it for further understanding of the use of multiple representations. During the design process, particular attention was put on an architecture suitable for this kind of learning environment (i.e. supporting the authoring of models for the simulation, instruction and interaction), on the user interface, and on the implementation of the conceptual framework that underlies the project.
The DeFT framework (Design, Functions, Tasks) requires an extensive and flexible manipulation of design parameters such as number of maximum or co-present representations, degree of support for learners' translation across representations, etc. During this project, I also designed, ran and analysed lab-based experiments to examine the complexity of information processing faced by users when learning with multiple representations.
- Ainsworth, S. E., and Van Labeke, N. (2004). Multiple forms of dynamic representation. Learning and Instruction 14(3), pp. 241-255. [PDF] [DOI]
- Ainsworth, S. E., and Van Labeke, N. (2002). Using a multi-representational design framework to develop and evaluate a dynamic simulation environment. In Proceedings of the International Workshop on Dynamic Visualizations and Learning (Tubingen, Germany). [PDF]
- Van Labeke, N., and Ainsworth, S. E. (2002). Representational Decisions When Learning Population Dynamics with an Instructional Simulation. In Proceedings of the 6th International Conference on Intelligent Tutoring Systems (ITS'02 - Biarritz, France). Springer-Verlag, pp. 831-840. [PDF] [DOI]
- Van Labeke, N., and Ainsworth, S. E. (2001). Applying the DeFT Framework to the Design of Multi-Representational Instructional Simulations. In Proceedings of the 10th International Conference on Artificial Intelligence in Education (AIED'01 - San Antonio, TX). IOS Press, pp. 314-321. [PDF]