Supporting students' learning with multiple representations in a dynamic simulation-based learning environment

Jan van der Meij, Ton de Jong

Research output: Contribution to journalArticleAcademicpeer-review

206 Citations (Scopus)


In this study, the effects of different types of support for learning from multiple representations in a simulation-based learning environment were examined. The study extends known research by examining the use of dynamic representations instead of static representations and it examines the role of the complexity of the domain and the learning environment. In three experimental conditions, the same learning environment, that of the physics topic of moments, was presented with separate, non-linked representations (S-NL condition), with separate, dynamically linked representations (S-DL condition), and with integrated, dynamically linked representations (I-DL condition). The learning environment was divided into low complexity and high complexity parts. Subjects were 72 students from middle vocational training (aged 16–18). Overall, the I-DL condition showed the best learning performance. Subjects in the I-DL condition, compared to the S-NL condition, showed better learning results on posttest items measuring domain knowledge. A trend in favor of the I-DL condition compared to the S-NL condition was found on posttest items measuring subjects' ability to translate between different representations. A subjective measure of experienced difficulty showed that subjects in the I-DL condition experienced the learning environment as easiest to work with. The complexity of the learning environment and domain interacted with the effects of the experimental conditions. Differences between conditions were only found on the test items that corresponded to the high complexity part of the learning environment.
Original languageEnglish
Pages (from-to)199-212
JournalLearning and instruction
Issue number3
Publication statusPublished - 2006


  • Multiple representations
  • Instructional technology
  • Scientific discovery learning
  • Simulation-based learning environments


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