Teaching Note--Data Science in the MSW Curriculum: Innovating Training in Statistics and Research Methods

Autor/inn/en	Perron, Brian E.; Victor, Bryan G.; Hiltz, Barbara S.; Ryan, Joseph
Titel	Teaching Note--Data Science in the MSW Curriculum: Innovating Training in Statistics and Research Methods
Quelle	In: Journal of Social Work Education, 58 (2022) 1, S.193-198 (6 Seiten)Infoseite zur Zeitschrift PDF als Volltext Verfügbarkeit
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	1043-7797
DOI	10.1080/10437797.2020.1764891
Schlagwörter	Teaching Methods; Social Work; Counselor Training; Statistics Education; Data Analysis; Data Collection; Instructional Innovation; Curriculum Development; Masters Programs; Graduate Students; Research Methodology + Suchen Sie Ihr Suchwort? Teaching method; Lehrmethode; Unterrichtsmethode; Soziale Arbeit; Auswertung; Data capture; Datensammlung; Educational Innovation; Bildungsinnovation; Curriculum; Development; Curriculumentwicklung; Lehrplan; Entwicklung; Magister course; Magisterstudiengang; Graduate Study; Student; Students; Aufbaustudium; Graduiertenstudium; Hauptstudium; Studentin; Research method; Forschungsmethode
Abstract	Recent and rapid technological advances have given rise to an explosive growth of data, along with low-cost solutions for accessing, collecting, managing, and analyzing data. Despite the advances in technology and the availability of data, social work organizations routinely encounter data-related problems that have an impact on their opportunities for making data-driven decisions. Although training in research methods and statistics is important for social work students, these courses often do not address the needs organizations face in collecting, managing, and using data for data-driven decision making. In this teaching note, we propose innovating the social work curriculum using a data science framework as a way to address the day-to-day challenges organizations face regarding data. We provide a description of data science, along with four examples of MSW student projects that were based on a data science framework. (As Provided).
Anmerkungen	Routledge. Available from: Taylor & Francis, Ltd. 530 Walnut Street Suite 850, Philadelphia, PA 19106. Tel: 800-354-1420; Tel: 215-625-8900; Fax: 215-207-0050; Web site: http://www.tandf.co.uk/journals
Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2024/1/01