sow964 Advanced Social Research Methods (Vollständige Modulbeschreibung)

sow964 Advanced Social Research Methods (Vollständige Modulbeschreibung)

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Modulbezeichnung Advanced Social Research Methods
Modulkürzel sow964
Kreditpunkte 6,0 KP
Verantwortliche Einrichtung Institut für Sozialwissenschaften
Zuständige Personen
Modulverantwortung:
Sebastian Schnettler
Prüfungsberechtigt:
Die im Modul Lehrenden
Teilnahmevoraussetzungen
sow944 for courses with a quantitative focus; sow945 for classes with a focus on qualitative methods; and both sow944 and sow945 for clases with a focus on combining quantitative and qualitative methods in mixed methods designs.
Unterrichtssprache Englisch
Lernergebnisse/Kompetenzen
After successful completion of this module, students will have a solid understanding of the advanced social research methods offered in the particular class in this module. This will enable them to understand and critically engage with empirical research using advanced social research designs and methods. Also, students will be able to apply these advanced social research methods to their own empirical research projects. In most classes offered within this module, students will also obtain the necessary software skills to apply or assist the advanced methods taught in class.
Modulinhalte
After successful completion of this module, students will have a solid understanding of the advanced social research methods offered in the particular class in this module. This will enable them to understand and critically engage with empirical research using advanced social research designs and methods. Also, students will be able to apply these advanced social research methods to their own empirical research projects. In most classes offered within this module, students will also obtain the necessary software skills to apply or assist the advanced methods taught in class.
Literaturempfehlungen
  • Edlund, John E., und Austin Lee Nichols, Hrsg. 2019. Advanced research methods for the social and behavioral sciences. Cambridge, United Kingdom ; New York, NY: Cambridge University Press.
  • Healy, Kieran. 2019. Data visualization: a practical introduction. Princeton, NJ: Princeton University Press.
  • Huntington-Klein, Nick. 2022. The effect: an introduction to research design and causality. Boca Raton: CRC Press, Taylor & Francis Group.
  • Salganik, Matthew J. 2018. Bit by bit: social research in the digital age. Princeton: Princeton University Press.
  • Wickham, Hadley, und Garrett Grolemund. 2016. R for data science: import, tidy, transform, visualize, and model data. First edition, second release. Beijing Boston Farnham Sebastopol Tokyo: O’Reilly.    
Zu erbringende Leistungen
Prüfungsart, -umfang, -dauer
1 Portfolio consisting of
↵Short exam + take-home exercises or
↵Short exam + short research report of own data analytics project or
↵Take-home exercises + short research report of own data analytics project
Prüfungszeiten
Dauer in Semestern 1 Semester
Angebotsrhythmus Winter- oder Sommersemester (1., 2. oder 3. FS)
Workload
Arbeitsaufwand gesamt Davon Präsenzzeit
180 h
Lehrveranstaltungsform
Veranstaltungsart SWS Angebotsrhythmus Workload Präsenzzeit
Vorlesung -- 0 h
Seminar 25 SoSe oder WiSe 28 h
Arbeitsgruppe 2 SoSe oder WiSe 28 h
Zusätzliche Hinweise

Aufnahmekapazität:
unbegrenzt
Verwendbarkeit des Moduls
  • Master Social Sciences > Wahlpflichtmodule