Monthly Archives: July 2025

Doktorand:innenkurs SPSS für Einsteiger – HSU Hamburg

Einführung SPSS

Kursbeschreibung:

Wie lassen sich erhobene Daten zielführend auswerten? In der Veranstaltung werden grundlegende Kenntnisse zu Statistiksoftware SPSS vermittelt. Im Vordergrund stehen dabei die Programmoberfläche und einfache Auswertungsverfahren der Deskriptiv- und Inferenzstatistik.

Themen
  • Erstellung von Datenmasken und Dateneingabe
  • Uni- und bivariate deskriptive Statistik
  • Zusammenhangs- und Unterschiedsmessungen; Signifikanztests
  • Durchführung von Berechnungen; z.B. Erzeugung neuer Variablen, etwa
Indizes
  • Verknüpfung von Dateien (Quer- und Längsschnitt)
  • Übersicht zu Befragungssoftware, die Datensätze in SPSS anbieten

(Unipark, Sociosurvey)

Dozentin: Dr. Elke Goltz (HSU Hamburg)

Kurssprache: Deutsch

Termine: 15.09. bis 16.09.2025 (10:00 – 17:00 Uhr)

Voraussetzungen:

1. Kenntnisse in deskriptiver Statistik wünschenswert (Lage- und Streuungsmaße, Zusammenhangsmessungen)

2. Labtop/Tablet mit Zugang zur Campus-Lizenz SPSS (Einrichtung über Intranet – Rechenzentrum, Software- und Campuslizenzen)

Anmeldeprozess: Wenn Sie sich für den Kurs anmelden möchten, schreiben Sie bitte eine Email an meisterc@hsu-hh.de.

 

 

PHD Workshop zu Wissenschaftskommunikation an der HSU Hamburg

PHD WORKSHOP ZU WISSENSCHAFTSKOMMUNIKATION

AUFBAU

  • 3 Blockseminare in Präsenz (jeweils 2 Tage, Do & Fr), verteilt über 3 Trimester • Start im Herbsttrimester 2025: 1. Block am 25.09. und 26.09. im Mensaraum M001 • Termin für den 2. Block: 13.11. und 14.11. 2025 • Termin für den 3. Block: 29.01. und 30.01.2026
  • jedes Blockseminar besteht aus (1) theoretischem Input, (2) praktischen Übungen und Diskussionen, und (3) geführter Projektarbeit • Teilnehmende nehmen an allen drei Terminen teil und erarbeiten im Verlauf des Kurses ein individuelles Kommunikationsprodukt (z.B. Zeitungsartikel, Blogpost, Social Media Posts, Podcast)

INHALTE

Blockseminar I:

Von Forschung zu Expertise – Rolle als Kommunikator:in definieren

Wissenschaftskommunikation kann Brücken schlagen in die Gesellschaft, in Verwaltung und Politik. Doch wirkungsvolle Kommunikation setzt ein klares Verständnis der eigenen Expertise und ihrer Relevanz außerhalb der Wissenschaft voraus. Dieses erste Blockseminar führt in zentrale Konzepte der Wissenschafts(kommunikations)forschung ein und beleuchtet besonders öffentliche Erwartungen an Sozial- und Geisteswissenschaftler:innen. In praktischen Übungen reflektieren die Teilnehmenden ihre eigene Expertise und identifizieren konkrete Kontexte und Zielgruppen, für die diese Expertise relevant ist. Das Blockseminar wird mit einer Skizze eines individuellen WissKomm-Projekts der Teilnehmenden abgeschlossen, das sie im Rahmen des Kurses realisieren werden.

Blockseminar II:

Wissenschaft verständlich und ansprechend vermitteln

Eine zentrale Herausforderung der Wissenschaftskommunikation besteht darin, komplexe Inhalte verständlich und ansprechend zu vermitteln oder sogar in konkrete Handlungsempfehlungen zu übersetzen. Das zweite Blockseminar gibt einen Überblick über verschiedene Kommunikationsformate, -kanäle und -stile. In praktischen Übungen testen die Teilnehmenden, welche Kommunikationsformen und -infrastrukturen sich am besten für ihre Ziele und persönlichen Präferenzen eignen – von geschriebenem Text zu gesprochenem Wort, Live-Event, Artikel, oder Social Media Beitrag. In der Projektarbeit vertiefen sie die inhaltliche Umsetzung, entwickeln ein erstes konkretes Kommunikationsprodukt, und verfeinern Sprache und Struktur.

Dieses Kommunikationsprodukt werden sie dann bis zum dritten und letzten Blockseminar finalisieren.

Blockseminar III:

Rolle als Kommunikator:in reflektieren und im Forschungsalltag verankern

Wissenschaftskommunikation bietet Forschenden neue Möglichkeiten der Sichtbarkeit und gesellschaftlichen Teilhabe, bringt aber auch ethische, professionelle und strategische Herausforderungen mit sich. Dieses dritte und letzte Blockseminar behandelt solche Fragen zu verantwortungsvoller Kommunikation, Vereinbarkeit mit anderen beruflichen Verpflichtungen (v.a. Forschung und Lehre), oder dem Umgang mit Kritik oder sogar wissenschaftsfeindlichen Angriffen. Durch Übungen und Diskussionen reflektieren die Teilnehmenden, wie sie Wissenschaftskommunikation nachhaltig in ihren Berufsalltag integrieren und strategische Netzwerke aufbauen können. In der Projektarbeit präsentieren sie ihr finales (oder vorläufiges) Kommunikationsprodukt, erhalten Feedback und entwickeln eine Strategie zur Veröffentlichung.

Die Kurssprache ist deutsch.

Dozentinnen: Clarissa Walter, Katharina Berr (Weizenbaum Institut, Berlin)

Anmeldeprozess: Wenn Sie sich für den dreiteiligen Workshop anmelden möchten, schicken Sie bitte eine Email an meisterc@hsu-hh.de.

Quantitative Text Analytics

Institution: see Organisers & Supporters

Programme of study: International Research Workshop

Lecturer: Assoc. Prof. Dr Fabian Hattke (University of Bergen)

Date: see Workshop Programme

Max. number of participants: 20

Credit Points: 5 CP for participating in the whole IRWS

Language of instruction: English

Contents: This course provides a basic introduction to the field of quantitative text analysis and natural language processing (NLP). It offers a theoretical introduction and hands-on exercises to explore the potential utility of different approaches to textual data (e.g., closed vs. open vocabulary text mining, sentiment analysis, topic detection, and data visualisation). The course teaches students to extract and process text from documents and to analyse the data by means of quantitative methods.

Software Installations: The course requires no coding or programming skills or prior experience with NLP tools. However, if students want to actively participate in the practical exercises and use their own datasets, they must install the following software on their personal laptops prior to the course.

  • Linguistic Inquiry and Word Count (LIWC) https://www.liwc.app/
    [The cheapest academic license is valid for 30 days and costs €18.95]
  • A generic statistics program like Stata, SPSS, or R.

Recommended literature:

  • Eichstaedt, J. C., Kern, M. L., Yaden, D. B., Schwartz, H. A., Giorgi, S., Park, G., … & Ungar, L. H. (2021). Closed-and open-vocabulary approaches to text analysis: A review, quantitative comparison, and recommendations. Psychological Methods, 26(4), 398-427.
  • Grimmer, J., & Stewart, B. M. (2013). Text as data: The promise and pitfalls of automatic content analysis methods for political texts. Political Analysis, 21(3), 267-297.
  • Hickman, L., Thapa, S., Tay, L., Cao, M., & Srinivasan, P. (2022). Text preprocessing for text mining in organizational research: Review and recommendations. Organizational Research Methods, 25(1), 114-146.
  • Indurkhya, N., & Damerau, F. J. (Eds.). (2010). Handbook of Natural Language Processing
    (Vol. 2). CRC Press Wilkerson, J., & Casas, A. (2017). Large-scale computerized text analysis in political science: Opportunities and challenges. Annual Review of Political Science, 20, 529-544.
  • Wilkerson, J., & Casas, A. (2017). Large-scale computerized text analysis in political science:
    Opportunities and challenges. Annual Review of Political Science, 20, 529-544.

You have to register for the International Research Workshop to participate in this course.

Academic English Writing

Institution: see Organisers & Supporters

Programme of study: International Research Workshop

Lecturer: Dr. Jonathan Mole (Europa-Universität Flensburg)

Date: see Workshop Programme

Max. number of participants: 20

Credit Points: 5 CP for participating in the whole IRWS

Language of instruction: English

Contents: Writing an academic text is a complex task. It requires knowledge of a range of accepted writing conventions and the ability to construct sentences that are not only idiomatically and grammatically correct but also suitably connected to one another. An awareness of the requirements and a degree of practice are necessary.

This workshop is primarily for people who are in the process of writing an academic text in English – a proposal, abstract, article, thesis, etc. It allows you to obtain individual feedback on a text you submit before the workshop. In the workshop, assistance will be given to enable you to self-correct any issues which have been highlighted (structure, understanding, logic, language, etc.). In addition, an overview of the important characteristics of academic English writing will be discussed. If required, exercises will be available to highlight topics such as academic style (formality, impersonal and objective language, passive voice, caution, nominalisation); structure of a sentence, paragraph and document level; reporting verbs and their forms; coherence and cohesion; and citation and reference styles.

A requirement of students: Please supply a maximum of 2 pages of text at least two weeks before the workshop begins. English language skills at CEFR level B2/C1 are required.

Recommended literature and pre-reading: None.

You must register for the International Research Workshop to participate in this course.

Principles of Data Visualization

Institution: see Organisers & Supporters

Programme of study: International Research Workshop

Lecturer: Prof. Dr. Daniel Schnitzlein (University of Applied Labour Studies & Innside Statistics)

Date: see Workshop Programme

Max. number of participants: 20

Credit Points: 5 CP for participating in the whole IRWS

Language of instruction: English

Contents: Results of scientific research are often (and increasingly) complex and challenging to understand for a non-scientific audience. However, at the same time, the transfer of results from academic research to non-academic recipients, such as politics, private foundations, or private firms providing research funding, as well as the interested public, is becoming increasingly important. Probably the most important skill in this context is the ability to create a clear visual representation of your main (quantitative data-based) results.

Today, data are everyday companions in almost all scientific and professional fields. The graphical representation of data is both an elementary step in the analysis process and an important component in communicating the results. The course Principles of Data Visualization trains this ability and leads you away from the standard diagrams of common office/statistics packages to clear and concise data representations with the help of many practice-oriented examples. The course consists of 50% lectures and 50% hands-on sessions. The methods trained in this course apply to all visualisation tasks, regardless of the software package used. The exercises in the hands-on sessions can be carried out using your preferred software tool.

Requirement of students: Basic knowledge of empirical (quantitative) social and economic research is beneficial but not strictly necessary.

You must register for the International Research Workshop to participate in this course.

Qualitative Comparative Analysis (QCA)

Institution: see Organisers & Supporters

Programme of study: International Research Workshop

Lecturer: Dr. Jonas Buche (Lower Saxony Ministry of Science and Culture)

Date: see Workshop Programme

Max. number of participants: 20

Credit Points: 5 CP for participating in the whole IRWS

Language of instruction: English

Contents: Since publishing the seminal work “The Comparative Method” by Charles Ragin in 1987, set-theoretic methods and primarily Qualitative Comparative Analysis (QCA) have become a common research strategy in the social sciences. Set-theoretic methods analyse cases concerning the identification of sufficient and necessary conditions and assume set relations to be equifinal, conjunctural, and asymmetric. Since the introduction of so-called fuzzy sets to the method, there has been a growing interest in QCA as a welcome alternative to both small-n case studies and large-n statistical analyses. In short, QCA is recommended if ‘if…then’ hypotheses are analysed, if the goal is to derive sufficient and necessary conditions, if a comparison is planned, and if there is a mid-sized number of cases (between 10 and 60+).

The course provides a comprehensive introduction to QCA, offering a conceptual and technical orientation. It begins with an overview of the basics of set theory and distinguishes QCA as a case-oriented method from both the quantitative and interpretive-qualitative research paradigms. The single elements are built into the Truth Table Algorithm through the notion of necessary and sufficient conditions and truth tables. However, this algorithm is not free of problems. Therefore, some pitfalls and strategies for overcoming them are presented. The software tool fsQCA will be introduced and applied to published studies on the third day.

A requirement of students: No prior knowledge is required. We will use the software fsQCA, which can be downloaded at www.fsqca.com.

Recommended literature and pre-readings:

You must register for the International Research Workshop to participate in this course.

Questionnaire Design

Institution: see Organisers & Supporters

Programme of study: International Research Workshop

Lecturer: Prof. Dr. Daniel Schnitzlein (University of Applied Labour Studies & Innside Statistics)

Date: see Workshop Programme

Max. number of participants: 20

Credit Points: 5 CP for participating in the whole IRWS

Language of instruction: English

Contents: The course provides an overview of the theoretical basics and empirical evidence of questionnaire design. The cognitive process of survey responding, including the challenges of designing effective survey questions —such as proper question wording and optimal response formats —will be discussed, as well as pretest techniques for evaluating survey questions. A practical part will accompany the lecture.

You must register for the International Research Workshop to participate in this course.

Case Study Research

Institution: see Organisers & Supporters

Programme of study: International Research Workshop

Lecturer: Prof. Dr. Kamil Marcinkiewicz (University of Wroclaw, Poland)

Date: see Workshop Programme

Max. number of participants: 20

Credit Points: 5 CP for participating in the whole IRWS

Language of instruction: English

Contents: Case study research is frequently applied in the social sciences. The ubiquity of the case study research contrasts with the scarcity of theoretical reflection on its core methodological aspects. Moreover, it is often unclear what these core methodological aspects are, as the term is used in different ways by (qualitative and quantitative) researchers. Furthermore, the benefits of comparative analysis are often underestimated. In this course, participants will have the opportunity to learn more about what case study research is, its strengths and weaknesses, and how to approach the core question in designing a case study, including the selection of cases. The course combines lectures with practical exercises and student project discussions.

A requirement for students: Please be prepared to discuss your projects. Please bring your laptop computer.

Recommended literature and pre-readings:

  • Gerring, J. (2007). Case Study Research: Principles and Practices (pp. 17-63).
    Cambridge: Cambridge University Press.
  • George, A. L., & Bennett, A. (2005). Case Studies and Theory Development in the Social
    Sciences (pp. 1-34). Cambridge, MA: MIT Press.
  • Rueschemeyer, D. (2003). Can One or a Few Cases Yield Theoretical Gains? In J.
    Mahoney and D. Rueschemeyer (Eds.), Comparative Historical Analysis in the Social
    Sciences (pp. 305-337) Cambridge: Cambridge University Press.
  • Yin, R.K. (2009). Case Study Research. Design and Methods. Los Angeles: Sage

You must register for the International Research Workshop to participate in this course.

Data Analysis with R

Institution: see Organisers & Supporters

Programme of study: International Research Workshop

Lecturer: Dr Marco Lehmann (Oviva AG)

Date: see Workshop Programme

Max. number of participants: 20

Credit Points: 5 CP for participating in the whole IRWS

Language of instruction: English

Contents: The course introduces the programming language R, which is used for statistical analyses. The beginning of each lecture features a demonstration of programming and statistical functions that will be elaborated upon throughout the study. The students will then practice with many statistical examples. In addition to statistical functions, the course will introduce the definition of R as a programming language and its syntax rules. Students will further learn to use R’s scripting capabilities. Successful participation requires basic knowledge of descriptive and inferential statistics. Students are encouraged to bring their laptops with the free software R (www.r-project.org) and RStudio (www.rstudio.com) installed.

prerequisite for students: Basic knowledge of descriptive and inferential statistics is recommended.

Recommended literature and pre-readings:

  • Please read Chapter 1 in Lehmann, M. (2022). Complete Data Analysis Using R. Your Applied Manual. SAGE Publications Ltd.

You have to register for the International Research Workshop to participate in this course.

Writing Your Literature Review

Institution: see Organisers & Supporters

Programme of study: International Research Workshop

Lecturer: Prof. Dr. Sylvia Rohlfer (IMC University of Applied Sciences Krems)

Date: see Workshop Programme

Max. number of participants: 20

Credit Points: 5 CP for participating in the whole IRWS

Language of instruction: English

Contents: Unlock the Secrets of Crafting Compelling Literature Reviews!

Embark on a journey to master the art of literature review writing in this upcoming workshop course tailored exclusively for PhD students! Are you ready to conquer the daunting task of navigating through vast seas of scholarly literature? Look no further! Join us for an enlightening 3-day workshop where you will be equipped with invaluable strategies and techniques to tackle this crucial aspect of your thesis (and subsequent research articles).

In this dynamic course, you will dive deep into the heart of effective literature review writing. From unravelling the characteristics of extensive bibliographies to synthesising diverse perspectives, you will be armed with a toolkit brimming with tips, tricks, and cutting-edge tools. We will also cover the role and possibilities that machine learning and online tools might add to your work. Say goodbye to feeling overwhelmed by the sheer volume of scholarly discourse – you will see how you can navigate it with finesse and precision.

But wait, there’s more! You will not only hone your ability to sift through mountains of research but also refine your writing habits for maximum impact. Through engaging sessions filled with hands-on activities and group collaborations, you will receive personalised peer feedback to elevate your skills to new heights.

No prior reading is required – come with an open mind and a willingness to dive headfirst into the world of academic exploration. Shortly before the course begins, you will receive more detailed instructions and the material to be downloaded for each day of the course. However, to ensure a tailored learning experience, I kindly request that you submit an extended abstract of your research project (two pages maximum, in English, German, or Spanish) to sylvia.rohlfer@imc.ac.at at least one week before the workshop starts.

Secure your spot today and unlock the doors to scholarly excellence.

You must register for the International Research Workshop to participate in this course.