Students Do Not Always Mean What We Think They Mean: A Questioning Strategy to Elicit the Reasoning behind Unexpected Causal Patterns in Student System Models

Autor/inn/en	Stephens, A. Lynn; Roderick, Steven; Shin, Namsoo; Damelin, Daniel
Titel	Students Do Not Always Mean What We Think They Mean: A Questioning Strategy to Elicit the Reasoning behind Unexpected Causal Patterns in Student System Models
Quelle	In: International Journal of Science and Mathematics Education, 21 (2023) 5, S.1591-1614 (24 Seiten)Infoseite zur Zeitschrift PDF als Volltext Verfügbarkeit
Zusatzinformation	ORCID (Stephens, A. Lynn)
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	1571-0068
DOI	10.1007/s10763-022-10308-z
Schlagwörter	Chemistry; Science Instruction; High School Students; Scientific Concepts; Models; Concept Formation; Questioning Techniques; Cognitive Processes; Logical Thinking + Suchen Sie Ihr Suchwort? Chemie; Teaching of science; Science education; Natural sciences Lessons; Naturwissenschaftlicher Unterricht; High school; High schools; Student; Students; Oberschule; Schüler; Schülerin; Studentin; Analogiemodell; Concept learning; Begriffsbildung; Befragungstechnik; Fragetechnik; Cognitive process; Kognitiver Prozess
Abstract	An ability to engage in system thinking is necessary to understand complex problems. While many pre-college students use system modeling tools, there is limited evidence of student reasoning about causal relationships that interact in diverging and converging chains, and how these affect system behavior. A chemistry unit on gas phenomena was implemented in two successive years with 73 high school students. Although the phenomena could be explained with simple linear causal reasoning, many student models included surprising and problematic causal chains and non-linear patterns. Commonly, discussion about student models in classrooms and interviews focuses on individual causal relationships. However, in our experience, this can fail to bring to the surface conceptual issues that result from the combination of two or more relationships. Using interview data from 19 students, we looked for instances where students explained their conceptions and we identified questioning strategies that elicited these explanations. Questions that appeared most productive asked about distal relationships between nonadjacent variables in model substructures of three to four variables. In response to these questions, eight students expressed their thinking about relationship combinations, including unexpected reasoning that had not emerged during classroom instruction. Using exemplars from three interviews, we argue that students engage in complex causal reasoning that may be implicit and unexpected, and that if this is not recognized, it cannot be responded to during instruction. We suggest that using model substructures as a mutual visual referent along with a simple questioning strategy shows promise for helping students make their causal reasoning explicit. (As Provided).
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Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2024/1/01