Assessing High-School Students' Modeling Performance on Newtonian Mechanics

Autor/in	Zhai, Xiaoming
Titel	Assessing High-School Students' Modeling Performance on Newtonian Mechanics
Quelle	In: Journal of Research in Science Teaching, 59 (2022) 8, S.1313-1353 (41 Seiten)Infoseite zur Zeitschrift PDF als Volltext Verfügbarkeit
Zusatzinformation	ORCID (Zhai, Xiaoming)
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	0022-4308
DOI	10.1002/tea.21758
Schlagwörter	High School Students; Mechanics (Physics); Science Instruction; Scientific Concepts; Task Analysis; Science Achievement; Models + Suchen Sie Ihr Suchwort? High school; High schools; Student; Students; Oberschule; Schüler; Schülerin; Studentin; Mechanik; Teaching of science; Science education; Natural sciences Lessons; Naturwissenschaftlicher Unterricht; Aufgabenanalyse; Analogiemodell
Abstract	Assessing scientific modeling competence (SMC) is challenging because of the multi-dimensionality of the construct and the potential variability of student performance across tasks. To deal with the challenges, this study applied Kane's validity framework to assess high-school students' SMC in Newtonian mechanics and examined how students' performance depended on tasks. We first specified students' SMC in three dimensions: "Conceptualization," "Deploying Scientific Knowledge," and "Representation," incorporating 11 components (e.g., "conceptualization of objects"). We assessed 305 high-school students' modeling performance on two Newtonian mechanics tasks, taking task dependency into account. We applied the Many-facet Rasch measurement (MFRM) to examine students' ability and discriminate students' performance variability across tasks. MFRM analyses revealed that among the three dimensions of SMC, "Representation" is most challenging for students to achieve compared to "Conceptualization" and "Deploying Scientific Knowledge," especially among higher-performing students. Five out of the 11 SMC components were task-dependent, suggesting significant score variance due to the variability of tasks. After excluding task variance, we found that students were grouped into four levels (i.e., primitive non-model, intuitive model, qualitative model, and quantitative model), and the majority of students were distributed at the medium two levels. We conclude the study by introducing three putative theories that may account for task dependency: "depth of cognition," "knowledge transfer," and "construct irrelevant interest." The study suggests that task dependency does not necessarily compromise the interpretation of scores, as long as assessors appropriately consider potential theories in their interpretive arguments when designing tasks and interpreting scores. (As Provided).
Anmerkungen	Wiley. Available from: John Wiley & Sons, Inc. 111 River Street, Hoboken, NJ 07030. Tel: 800-835-6770; e-mail: cs-journals@wiley.com; Web site: https://www.wiley.com/en-us
Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2024/1/01