Getting Messy with Data

Autor/inn/en	Rosenburg, Joshua; Edwards, Alex; Chen, Bodong
Titel	Getting Messy with Data
Quelle	In: Science Teacher, 87 (2020) 5, S.30-34 (5 Seiten) PDF als Volltext Verfügbarkeit
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	0036-8555
Schlagwörter	Science Instruction; Data Analysis; Teaching Methods; Data Collection; Educational Technology; Technology Uses in Education + Suchen Sie Ihr Suchwort? Teaching of science; Science education; Natural sciences Lessons; Naturwissenschaftlicher Unterricht; Auswertung; Teaching method; Lehrmethode; Unterrichtsmethode; Data capture; Datensammlung; Unterrichtsmedien; Technology enhanced learning; Technology aided learning; Technologieunterstütztes Lernen
Abstract	Analyzing and interpreting data is essential to the practice of scientists and is also an essential science and engineering practice for science teaching and learning. Although working with data has benefits for student learning, it is also challenging, particularly with respect to aspects of work with data that are not yet very common in schools, such as developing quantitative models, understanding variation in data, and using larger, complex data sources. In this article, we aim to describe tools for engaging students to work with data in your class as well as three general strategies, including understanding how data is collected, experiencing the transformation of messy data sets in preparation for analysis, and modeling the data to answer a question. We show how these strategies can be employed using the freely-available, browser-based Common Online Data Analysis Platform, and outline connections to curricular standards. (As Provided).
Anmerkungen	National Science Teachers Association. 1840 Wilson Boulevard, Arlington, VA 22201-3000. Tel: 800-722-6782; Fax: 703-243-3924; e-mail: membership@nsta.org; Web site: http://www.nsta.org
Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2024/1/01