Applying the Rule Space Model to Develop a Learning Progression for Thermochemistry

Autor/inn/en	Chen, Fu; Zhang, Shanshan; Guo, Yanfang; Xin, Tao
Titel	Applying the Rule Space Model to Develop a Learning Progression for Thermochemistry
Quelle	In: Research in Science Education, 47 (2017) 6, S.1357-1378 (22 Seiten)Infoseite zur Zeitschrift PDF als Volltext Verfügbarkeit
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	0157-244X
DOI	10.1007/s11165-016-9553-7
Schlagwörter	Chemistry; High School Students; Secondary School Science; Correlation; Thermodynamics; Heat; Scientific Concepts; Scientific Principles; Standards; Models; Test Items; Psychometrics; Difficulty Level; Reliability; Validity; Classification; Learning Processes; Mastery Learning + Suchen Sie Ihr Suchwort? Chemie; High school; High schools; Student; Students; Oberschule; Schüler; Schülerin; Studentin; Korrelation; Thermodynamik; Hitze; Standard; Analogiemodell; Test content; Testaufgabe; Psychometry; Psychometrie; Schwierigkeitsgrad; Reliabilität; Gültigkeit; Classification system; Klassifikation; Klassifikationssystem; Learning process; Lernprozess
Abstract	We used the Rule Space Model, a cognitive diagnostic model, to measure the learning progression for thermochemistry for senior high school students. We extracted five attributes and proposed their hierarchical relationships to model the construct of thermochemistry at four levels using a hypothesized learning progression. For this study, we developed 24 test items addressing the attributes of exothermic and endothermic reactions, chemical bonds and heat quantity change, reaction heat and enthalpy, thermochemical equations, and Hess's law. The test was administered to a sample base of 694 senior high school students taught in 3 schools across 2 cities. Results based on the Rule Space Model analysis indicated that (1) the test items developed by the Rule Space Model were of high psychometric quality for good analysis of difficulties, discriminations, reliabilities, and validities; (2) the Rule Space Model analysis classified the students into seven different attribute mastery patterns; and (3) the initial hypothesized learning progression was modified by the attribute mastery patterns and the learning paths to be more precise and detailed. (As Provided).
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Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2020/1/01