The Role of Self-monitoring in Learning Chemistry with Dynamic Visualizations

  • Jennifer L. Chiu
  • Marcia C. Linn
Part of the Contemporary Trends and Issues in Science Education book series (CTISE, volume 40)


This chapter explores ways to help students monitor and regulate their learning of difficult chemistry concepts. Dynamic visualizations can illustrate complex, unobservable phenomena such as bond breaking and bond formation. To develop robust, integrated understanding when learning with visualizations, students need cognitive understanding of the phenomena as represented in the visualization. They also need metacognitive skills to decide whether they understand the visualization and determine when to revisit the visualization to clarify their interpretations. We investigate the development of integrated understanding using the Technology-Enhanced Learning in Science (TELS) chemical reactions inquiry unit that combines the pedagogical support of the Web-based Inquiry Science Environment (WISE) with dynamic visualizations from Molecular Workbench. Our first study combining judgments of learning and explanation prompts revealed that visualizations may fail to add new ideas because they are often deceptively clear. Students typically overestimated their understanding of visualizations while gaining only superficial ideas. In our second study we refined both cognitive and metacognitive guidance to encourage students to distinguish and reflect upon their ideas. The results suggest that strengthening self-monitoring skills can overcome deceptive clarity and lead to coherent understanding. These studies suggest that the metacognitive skills of monitoring understanding of complex visualizations and determining when to return to the visualization contribute to the development of integrated understanding and can be supported by careful design of technology-enhanced instruction. The notion of metacognition applied in this study refers to monitoring and evaluating one’s understanding, to the regulation/control function of metacognition, and to the self-knowledge functions of metacognition.


Knowledge Integration Metacognitive Skill Dynamic Visualization Metacognitive Activity External Feedback 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.



The authors thank the TELS research group, partners, and schools for their dedication to improving science learning. We would also like to thank Sophia Rabe-Hesketh for her help with the analysis. This material is based upon work supported by the National Science Foundation under grant ESI-0242701. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the National Science Foundation.


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Copyright information

© Springer Science +Business Media B.V. 2012

Authors and Affiliations

  1. 1.Curry School of EducationUniversity of VirginiaCharlottesvilleUSA
  2. 2.Graduate School of EducationUniversity of CaliforniaBerkeleyUSA

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