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Resource-Adaptive Design of Visualizations for Supporting the Comprehension of Complex Dynamics in the Natural Sciences

Multimodal Interaction


January 2007 - December 2009


Pact for Research and Innovation of the Competition Fond 2006 of the Leibniz-Association


Research Plan

The basic idea of the research project was that a successful knowledge acquisition with dynamic visualizations is a resource intensive process which requires simultaneous and optimized availability of different learning resources. This particularly comprises different processing capabilities of the cognitive system, functionalities of the applied computer technology and didactically substantiated contents and representations. Accordingly, the instructional potential of dynamic visualizations can only effectively evolve if these different learning resources are available in a coordinated way for a concrete knowledge acquisition scenario. This hypothesis was investigated in formal learning settings (e.g. school, university) as well as in informal learning settings (e.g. aquarium, diving excursion) for a natural sciences domain, the locomotion of fish.

Scientific domain

International comparative educational studies (PISA, TIMSS) have clearly shown that the performances of German pupils could be improved considerably in natural sciences, particularly in the area of understanding complex dynamic relations. Understanding difficulties in natural sciences often refers to the complexity, speed or scale of dynamic contexts and the balancing act between concrete object configurations and the underlying abstract of scientific concepts and theories.

With the domain fish locomotion, a particularly suitable content area has been singled out to test the instructional capability of dynamic visualizations for the understanding of scientific relations, because

  • complex dynamic relations can be observed from interdisciplinary perspectives (e. g. biology and physics),
  • curriculum-relevant concepts of high importance to society could be introduced (e. g. evolution, conservation of biodiversity, ecosystems),
  • issues that are relevant for different age groups could be addressed at different levels of complexity

Concrete subject matters of the domain, with which the effectiveness for learning of dynamic visualizations were tested, are i.e. the classification of different fish locomotion forms and the underlying physical principles and forces of fish locomotion. These two contents are also basic elements to understand the relations of evolutionary adaptation of various fishes and the associated fish movements.

Physical Principles: underlying kinematics
Physical principles
Biodiversity: classification of locomotion

Theoretical and Experimental Questions

The aim of the project was to support the understanding of complex dynamic processes in the Natural Sciences. Thereby we drew attention to conducive design of dynamic visualizations while considering and developing findings from cognitive and media psychology. Within this context we studied the following topics:

  • mental resources
    • processing capacity, working memory
    • attention
    • modality- and codality-based processing channels
  • learner requirements
    • domain specific knowledge structures within long-term memory
    • expertise regarding cognitive and metacognitive processing strategies
    • spatial ability, visual literacy

Several studies aimed at pros and cons of dynamic and static visualizations and the question which degree of realism a conducive learning environment should have. Furthermore, we studied process-oriented approaches of visualization processing (eye-tracking, verbal protocols), the function of prior knowledge (different expertise levels) as well as the training of these processes via eye movement modeling.

Examples of materials used in different experiments:
Examples of materials

Networking Character of the Project and its Advantages

Structure of project
  • Interdisciplinary optimization of resources in learning from dynamic visualizations
  • Development of instructional materials that meet high standards in regard to
    • the scientific content domain
    • the computer technology
    • the constraints of the cognitive system
  • Innovative learning scenarios (e.g. situated mobile learning)
  • assembling a final product for complex and situated learning (e.g. aquariums, diving excursions)

Cooperation partner

Network 1: group Tuebingen

Network 2: international partners

  • CNTI: Cyprus Neuroscience and Technology Institute
    (Nicosia, Cyprus, Yiannis Laouris, Loredana Ioana Mihalka)
  • Curtin University (Perth, Australia, Ric Lowe)
  • OTEC: Onderwijstechnologisch Expertisecentrum of the Open University of the Netherlands
    (Heerlen, The Netherlands, Fred Paas, Tamara van Gog)
  • LEAD (CNRS): Laboratoire D'etude del'apprentissage et du developpement
    (Dijon, France, Jean-Michel Boucheix, Emmanuel Schneider)
  • TECFA: Technologies de Formation et Apprentissage
    (Geneve, Switzerland, Mireille Betrancourt, Cyril Rébetez)
  • University of Rotterdam (Rotterdam, The Netherlands, Huib Tabbers, Björn de Koning)
  • LSRI: Learning Sciences Research Institute
    (Nottingham, GB, Shaaron Ainsworth)

Network 3: extramural partners

  • Aquarium of the Zoological and Botanical Garden Wilhelma, Stuttgart