Assessing Classroom Emotional Climate in STEM Classrooms: Developing and Validating a Questionnaire

Autor/inn/en	Fraser, Barry J.; McLure, Felicity I.; Koul, Rekha B.
Titel	Assessing Classroom Emotional Climate in STEM Classrooms: Developing and Validating a Questionnaire
Quelle	In: Learning Environments Research, 24 (2021) 1, S.1-21 (21 Seiten)Infoseite zur Zeitschrift PDF als Volltext Verfügbarkeit
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	1387-1579
DOI	10.1007/s10984-020-09316-z
Schlagwörter	Classroom Environment; Psychological Patterns; STEM Education; Test Construction; Test Validity; Factor Analysis; Test Reliability; Predictive Validity + Suchen Sie Ihr Suchwort? Klassenklima; Unterrichtsklima; STEM; Testaufbau; Testvalidität; Faktorenanalyse; Testreliabilität
Abstract	In an attempt to engage more students in Science, Technology, Engineering and Mathematics (STEM) subjects, schools are encouraged by STEM educators and professionals to introduce students to STEM through projects which integrate skills from each of the STEM disciplines. Because little is known about the learning environment of STEM classrooms, we developed and validated a Classroom Emotional Climate (CEC) questionnaire. Initially, the questionnaire was pilot tested with six focus groups of students from three schools to obtain feedback to incorporate into a revision of the CEC. Next, the modified CEC questionnaire was administered to 698 students participating in STEM activities in 57 classes in 20 schools. Exploratory factor analysis (principal component analysis) led to reduction of the CEC to 41 items in seven dimensions: Consolidation, Collaboration, Control, Motivation, Care, Challenge and Clarity. The structure of the CEC was then further explored using confirmatory factor analysis. Internal consistency reliability, concurrent validity (ability to differentiate between classrooms), discriminant validity (scale intercorrelations) and predictive validity (associated with student attitudes) were satisfactory. Finally, Rasch analysis of data for each dimension revealed good model fit and unidimensionality of the items describing each latent variable. (As Provided).
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Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2024/1/01