Science communication professionals make decisions based on their experiences, their knowledge of best practices, implicit theoretical knowledge, comments of their peers, creativity and inspiration. Using decision support systems (DSS) aligns all those variables or sources and increases the quality and efficiency of the decisions made on science communication policies and strategies. We developed, and partly tested, in practice two preliminary DSSs: a decision aid for health communication professionals and a DSS to assess the evaluability of science communication projects. These DSSs have structuring and designing properties, but function also as a platform to bridge science communication practice and theory.

One of the main issues in communication in general and science communication in particular is to deal with uncertainties in the science communication process and outcomes. If a science communication professional can assess these uncertainties at forehand, expectations of commissioners and stakeholders could be managed more efficiently. To assess this kind of uncertainty, DSSs we have developed form the very beginning of science communication process simulation. This kind of simulation makes various possible outcomes of the science communication process tangible for science communication professionals. For example, we theoretically designed science communication process simulation for the implementation of smart energy grids in the city of London from a consumer behaviour perspective.

In the paper we will present our first results on DSS and modeling. Our results are a platform, as we see it, for developing a profound bridge between theory and practice of science communication. This bridge finally enhances both science communication practice and theory in real time and in a tangible way.

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Public Communication of Science and Technology

 

Decision modeling in science communication

Maarten Sanden   Delft University of Technology

Frans Meijman   VU University Medical Center

Science communication professionals make decisions based on their experiences, their knowledge of best practices, implicit theoretical knowledge, comments of their peers, creativity and inspiration. Using decision support systems (DSS) aligns all those variables or sources and increases the quality and efficiency of the decisions made on science communication policies and strategies. We developed, and partly tested, in practice two preliminary DSSs: a decision aid for health communication professionals and a DSS to assess the evaluability of science communication projects. These DSSs have structuring and designing properties, but function also as a platform to bridge science communication practice and theory.

One of the main issues in communication in general and science communication in particular is to deal with uncertainties in the science communication process and outcomes. If a science communication professional can assess these uncertainties at forehand, expectations of commissioners and stakeholders could be managed more efficiently. To assess this kind of uncertainty, DSSs we have developed form the very beginning of science communication process simulation. This kind of simulation makes various possible outcomes of the science communication process tangible for science communication professionals. For example, we theoretically designed science communication process simulation for the implementation of smart energy grids in the city of London from a consumer behaviour perspective.

In the paper we will present our first results on DSS and modeling. Our results are a platform, as we see it, for developing a profound bridge between theory and practice of science communication. This bridge finally enhances both science communication practice and theory in real time and in a tangible way.

A copy of the full paper has not yet been submitted.

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