Building a Model for Integrative Computational Social Science Research

Autor/in	Spry, Amber
Titel	Building a Model for Integrative Computational Social Science Research
Quelle	In: Journal of Political Science Education, 19 (2023) 4, S.611-626 (16 Seiten)Infoseite zur Zeitschrift PDF als Volltext Verfügbarkeit
Zusatzinformation	ORCID (Spry, Amber)
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	1551-2169
DOI	10.1080/15512169.2023.2177548
Schlagwörter	Social Science Research; Computation; Information Literacy; Data; Undergraduate Students; Student Research; Public Opinion; Best Practices + Suchen Sie Ihr Suchwort? Social scientific research; Sozialwissenschaftliche Forschung; Informationskompetenz; Daten; Studentenforschung; Öffentliche Meinung
Abstract	Universities are increasingly interested in providing courses that equip students with data science skills and engage experiential learning, particularly in the social sciences. However, these courses can be costly to implement and time-consuming for instructors to develop. This article describes an integrative learning model for teaching computational social science skills to undergraduate students. There are three elements to the model: content delivery through collaborative learning, skill development in an applied lab setting, and student mentorship. I apply this model to an experiential course where undergraduate students learn to create and conduct a national public opinion poll. The model addresses the need for university classes that equip undergraduate students with computational social science skills, and provides a pathway for training student researchers as teaching assistants for future courses. This model builds the research capacity of faculty, graduate assistants, and undergraduates, invests in data science by providing an infrastructure for the collection of large scale data over time, and integrates experiences inside and outside of the classroom. This model is replicable at other institutions and will be of benefit to programs seeking to implement best practices and maximize learning effectiveness through research integration. (As Provided).
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Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2024/1/01