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ERIC Number: EJ1332236
Record Type: Journal
Publication Date: 2022
Pages: 6
Abstractor: As Provided
ISBN: N/A
ISSN: ISSN-1043-7797
EISSN: N/A
Teaching Note--Data Science in the MSW Curriculum: Innovating Training in Statistics and Research Methods
Perron, Brian E.; Victor, Bryan G.; Hiltz, Barbara S.; Ryan, Joseph
Journal of Social Work Education, v58 n1 p193-198 2022
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.
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
Publication Type: Journal Articles; Reports - Descriptive
Education Level: Higher Education; Postsecondary Education
Audience: N/A
Language: English
Sponsor: N/A
Authoring Institution: N/A
Grant or Contract Numbers: N/A