Prediction and Adaption in Science|Environment|Health Contexts
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Autor:innen
Zeyer, Albert
Álvaro, Nuria
Bauer, Deidre
Devetak, Iztok
Devetak, Sonja Posega
Gavidia, Valentin
Kremer, Kerstin
Mayoral, Olga
Tajnšek, Tina Vesel
Autor:in (Körperschaft)
Publikationsdatum
2021
Typ der Arbeit
Studiengang
Typ
04B - Beitrag Konferenzschrift
Herausgeber:innen
Levrini, Olivia
Tasquier, Giulia
Amin, Tamer G.
Branchetti, Laura
Levin, Mariana
Herausgeber:in (Körperschaft)
Betreuer:in
Übergeordnetes Werk
Engaging with Contemporary Challenges through Science Education Research: Selected papers from the ESERA 2019 Conference
Themenheft
DOI der Originalpublikation
Link
Reihe / Serie
Reihennummer
Jahrgang / Band
Ausgabe / Nummer
Seiten / Dauer
19-30
Patentnummer
Verlag / Herausgebende Institution
Springer
Verlagsort / Veranstaltungsort
Cham
Auflage
Version
Programmiersprache
Abtretungsempfänger:in
Praxispartner:in/Auftraggeber:in
Zusammenfassung
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.
Schlagwörter
Fachgebiet (DDC)
Veranstaltung
Startdatum der Ausstellung
Enddatum der Ausstellung
Startdatum der Konferenz
Enddatum der Konferenz
Datum der letzten Prüfung
ISBN
978-3-030-74490-8
ISSN
Sprache
Englisch
Während FHNW Zugehörigkeit erstellt
Ja
Zukunftsfelder FHNW
Publikationsstatus
Veröffentlicht
Begutachtung
Peer-Review der ganzen Publikation
Open Access-Status
Closed
Lizenz
Zitation
ZEYER, Albert, Nuria ÁLVARO, Julia ARNOLD, Deidre BAUER, Iztok DEVETAK, Sonja Posega DEVETAK, Valentin GAVIDIA, Kerstin KREMER, Olga MAYORAL, Tina Vesel TAJNŠEK und Alla KESELMAN, 2021. Prediction and Adaption in Science|Environment|Health Contexts. In: Olivia LEVRINI, Giulia TASQUIER, Tamer G. AMIN, Laura BRANCHETTI und Mariana LEVIN (Hrsg.), Engaging with Contemporary Challenges through Science Education Research: Selected papers from the ESERA 2019 Conference. Cham: Springer. 2021. S. 19–30. ISBN 978-3-030-74490-8. Verfügbar unter: https://irf.fhnw.ch/handle/11654/33061