A Learning Progression for Understanding Interdependent Relationships in Ecosystems

Sara J. Dozier (), Anna MacPherson, Linda Morell, Perman Gochyyev and Mark Wilson
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Sara J. Dozier: Department of Science Education, California State University, Long Beach, CA 90840-9504, USA
Anna MacPherson: American Museum of Natural History, New York, NY 10024-5102, USA
Linda Morell: Graduate School of Education, University of California, Berkeley, CA 94720-1670, USA
Perman Gochyyev: Graduate School of Education, University of California, Berkeley, CA 94720-1670, USA
Mark Wilson: Graduate School of Education, University of California, Berkeley, CA 94720-1670, USA

Sustainability, 2023, vol. 15, issue 19, 1-23

Abstract: This paper describes a hypothesized learning progression for how secondary students understand interdependent relationships in ecosystems, a key concept in the field of ecology and for public understanding of science. In this study, a hypothetical learning progression was developed and empirically investigated using Rasch modeling of data from 1366 students in a large, diverse, urban school district. We found that the empirical evidence supported the general structure of the hypothesized learning progression for relationships in ecosystems. There were notable exceptions, and we describe the ways in which we altered the items and the learning progression to address empirical inconsistencies with our a priori conceptions. The assessment items developed through this study are immediately available online for formative assessment purposes, and the learning progression can support teachers’ thinking about students’ understanding of ecosystems. In particular, the upper reach of the learning progression offers a more complete description of the ways in which students might develop their understanding of complex interactions in ecosystems, beyond what is currently offered in the literature and standards documents about students’ understanding.

Keywords: science education; learning progression; ecology; ecosystems; Rasch model; item response theory; validity (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2023
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