Arnold, Julia

Arnold, Julia


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  • Publikation
    Prediction and Adaption in Science|Environment|Health Contexts
    (Springer, 2021) Zeyer, Albert; Álvaro, Nuria; Arnold, Julia; Bauer, Deidre; Devetak, Iztok; Devetak, Sonja Posega; Gavidia, Valentin; Kremer, Kerstin; Mayoral, Olga; Tajnšek, Tina Vesel; Keselman, Alla; Levrini, Olivia; Tasquier, Giulia; Amin, Tamer G.; Branchetti, Laura; Levin, Mariana [in: Engaging with Contemporary Challenges through Science Education Research: Selected papers from the ESERA 2019 Conference]
    The term Science|Environment|Health (S|E|H) stands for a pedagogy of mutual benefit between science education, environmental education, and health education. Complexity is an important aspect of most S|E|H issues. In the natural sciences, and thus in science education, prediction plays a central role. Yet, complex systems usually do not allow for full prediction. “Don’t predict, adapt!” is a famous slogan in complexity talk. But what does adaption look like in complex systems and what role can scientific knowledge play in it? This paper features a symposium where three S|E|H examples were presented in which the relationship between prediction and adaption is important. The paper also includes a theoretical contribution that discusses the concept of dual-process theories as a potential theoretical framework. The main outcome of the symposium is that while understanding “as prediction” plays the central role in traditional science, understanding “as interpretation” is at least as equally important in S|E|H contexts. In terms of dual-process theories, the first is a type 2 process, while the second is type 1. Good decision-making in S|E|H contexts involves a complementary interplay between these two types of understanding science.
    04B - Beitrag Konferenzschrift