Institution: see Organisers & Supporters

Programme of study: International Research Workshop

Lecturer: Dr. Jana Bövers (University of Bielefeld)

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 workshop offers a comprehensive introduction to Grounded Theory, considering its possible application in manifold fields and contexts of study and the feasibility of combining it with diverse research techniques (mainly qualitative and ethnographic ones). The focus will be on the basic methodological stance and the entire process, starting with the research design, the collection of material with an explorative character, up to the multi-layered process of analysis, which leads to the results theorisation with a so-called medium range. The workshop is as much oriented to “beginners” interested in learning about the basic epistemological perspective of Grounded Theory and its practice as to participants that already have deeper knowledge about Grounded Theory or even have already applied this methodology in research and wish to discuss specific aspects or questions that arose in research practice. Experience has shown that this diversity of participants means that all groups can benefit from each other’s experiences and questions, as well as doubts. Accordingly, the workshop will be adjusted to participants’ needs.

Hence, we will first discuss basic concepts and procedures such as research design, data collection, coding, categorisation, memo writing, theoretical sampling and theoretical saturation. Afterwards, these concepts will be clarified through practical exercises using examples ideally provided by the participants. Therefore, participants with concrete research projects (be they planned or already put into practice) are invited to share their ideas, design and material to (further) develop the research practice among the group. If you are interested in presenting examples, please contact Gilberto Rescher in English, German, Spanish or Portuguese (gilberto.rescher@uni-hamburg.de).

Gilberto Rescher will also stress his own research experiences in areas such as diversity, politics, migration and gender, with a focus on Latin America, to show how grounded theory can be used as an important guideline for research and analysis in a broader methodological framework. Accordingly, also exemplary cases from the literature will be drawn upon.

For successful participation, engaging in a qualitative, exploratory paradigm and a discussion of the cases presented in the workshop is necessary.

In addition to your registration, please answer the following questions (English or German):

• What is your current status (e.g. PhD student?)
• What is the focus of your interest in Grounded Theory?
• What sort of content and feedback do you expect?

As a brief preparation for the workshop, the short text on Anselm Strauss or on Grounded Theory can be read in one of the editions of “Qualitative Forschung: Ein Handbuch” by Flick et al.

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

Institution: see Organisers & Supporters

Programme of study: International Research Workshop

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

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 purpose of this course is to familiarise participants with the basic characteristics of qualitative research. The course introduces methodological and practical aspects of different forms of qualitative research like case studies, discourse analyses, interviews, observations, and qualitative meta-synthesis.

theory building, and sampling strategies. It also discusses practical challenges like the
development of research questions, the use of different coding approaches, technical tools and ethical questions.

Recommended literature and pre-readings:

• Adler, P. S., Forbes, L. C., & Willmott, H. (2007). Critical management studies. Academy of Management Annals, 1(1), 119-179.
• Alvesson, M., & Karreman, D. (2000). Varieties of discourse: On the study of organizations through discourse analysis. Human Relations, 53(9), 1125-1149.
• Corbin, J., & Strauss, A. (2014). Basics of qualitative research: Techniques and procedures for developing grounded theory. Sage publications.
• Eisenhardt, K. M. (1989). Building theories from case study research. Academy of Management Review, 14(4), 532-550.
• Flick, U., von Kardoff, E., & Steinke, I. (Eds.). (2004). A companion to qualitative research. Sage.
• Hoon, C. (2013). Meta-synthesis of qualitative case studies: An approach to theory building. Organizational Research Methods, 16(4), 522-556.
• Mayring, P. (2004). Qualitative content analysis. A companion to qualitative research. Forum: Qualitative Social Research, 1, 159-176.
• Sandelowski, M., & Barroso, J. (2006). Handbook for synthesizing qualitative research. Springer Publishing.
• Wodak, R., & Meyer, M. (Eds.). (2015). Methods of critical discourse studies. Sage.
• Yin, R. K. (2017). Case study research and applications: Design and methods. Sage publications.

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

Institution: see Organisers & Supporters

Programme of study: International Research Workshop

Lecturer: Tobias Gramlich (Hesse State Statistical Office)

Date: see Workshop Programme

Max. number of participants: 20

Credit Points: 5 CP for participating in the whole IRWS

Language of instruction: English

Contents: Stata is a statistical program package widely used (not only) in the social and economic sciences; it is used for data management, statistical graphics, and quantitative data analysis. Statistical concepts will not be part of the course, so participants should have basic knowledge of statistics. The course should enable participants to prepare their data for analysis, perform adequate analysis using a statistical computer program, and document these tasks to keep them reproducible.

For Beginners with no or very little Stata knowledge!

Course topics cover:

• “What You Type Is What You Get”: Basic Stata Command syntax
• Getting (and Understanding) Help within Stata: Stata Built-in Help System
• Basic Data Management: Load and Save Stata Datasets, Generate and Manipulate Variables, Describe and Label Data and Variables, Perform Basic uni- and bivariate Analyses, and Change the Structure of your Data.
• Basic Stata Graphics: Scatterplot, Histogram, Bar Chart
• Working with “Do-” and “Log-” Files

A requirement for students: Statistical concepts will not be part of the course, so participants should have some basic knowledge of statistics.

Recommended literature and pre-readings: None.

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

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 analytics
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 visualization). The
course teaches students to extract and process text from documents and analyse the data through quantitative methods.

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

• Linguistic Inquiry and Word Count (LIWC) https://www.liwc.app/
• Meaning Extraction Helper (MEH) https://www.ryanboyd.io/software/meh/
• 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.

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

Institution: see Organisers & Supporters

Programme of study: International Research Workshop

Lecturer: Dr Daniel Lüdecke (UKE Hamburg)

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 teaches how to fit multilevel regression models with the statistical programming language R. First, simple (generalized) linear regression models are introduced to show important basic principles of modelling, like simple regression, interaction terms, non-linear relationships between predictors and outcome (polynomial and spline terms). Later, the application of these principles in a multilevel framework is demonstrated. Furthermore, the graphical representation of complex mixed models is covered, which helps communicate complicated models even for a broad audience less familiar with such techniques. Successful participation requires basic knowledge of regression modelling techniques. Students are encouraged to bring their own laptops with the free software R (www.r-project.org/) and RStudio (www.rstudio.com/) installed. All source code to run the examples is provided in preparation for the course.

Requirements: Knowledge of classic regression modelling (familiarity with terms like dependent and independent variables, linear and logistic regression, estimate, …)

Recommended readings:

• Harrison, X. A., Donaldson, L., Correa-Cano, M. E., Evans, J., Fisher, D. N., Goodwin, C. E. D., … Inger, R. (2018). A brief introduction to mixed-effects modelling and multi-model inference in ecology. PeerJ, 6, e4794. https://doi.org/10.7717/peerj.4794
• Bolker, B. M., Brooks, M. E., Clark, C. J., Geange, S. W., Poulsen, J. R., Stevens, M. H. H., & White, J.-S. S. (2009). Generalized linear mixed models: a practical guide for ecology and evolution. Trends in Ecology & Evolution, 24(3), 127–135. https://doi.org/10.1016/j.tree.2008.10.008

Required R packages:

• Modelling: lme4, glmmTMB, GLMMadaptive
• Visualization: ggeffects, sjPlot, see
• Summaries and Statistics: parameters, effectsize
• Model Quality: performance
• Data preparation: sjmisc, dplyr, tidyr

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

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 used for statistical analyses. The beginning of each lecture comes with a demonstration of programming and statistical functions that will be elaborated on in the course of 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. The students are encouraged to bring their own laptops with the free software R (www.r-project.org/) and RStudio (www.rstudio.com/) installed.

A requirement for students: Basic descriptive and inferential statistics knowledge 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.

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.

Institution: see Organisers & Supporters

Programme of study: International Research Workshop

Lecturer: Prof. Dr. Daniel Schnitzlein (Leibniz University Hannover & 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 hard to understand for a non-scientific audience. However, at the same time, the transfer of results from academic research to an outside-academia recipient, for example, politics, private foundations or private firms providing research funding, but also the interested public, gets more and more important. Probably the most important skill in this context is the ability to create good visualization 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 are applicable to all visualization tasks independent of the applied software package. 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.

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 especially Qualitative Comparative Analysis (QCA) have become a common research strategy in the social sciences. Set-theoretic methods analyse cases concerning identifying sufficient and necessary conditions and assume set relations to be equifinal, conjunctural and asymmetric. Since so-called fuzzy sets have been introduced to the method, there has been a rising 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 offers a comprehensive introduction to QCA and is conceptually and technically oriented. It starts off with an overview of the basics of set theory and demarcates QCA as a case-oriented method from both the quantitative and the 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 on how to overcome 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:

• Buche, Jonas. 2017. “Assessing the Quality of Qualitative Comparative Analysis (QCA) – Evaluation, Improvement, Application”. Hannover: Leibniz Universität (https://www.researchgate.net/publication/323749578_Assessing_the_Quality_of_Qualitative_Comparative_Analysis_QCA_Evaluation_Improvement_Application)
• Cebotari, Victor, and Maarten P. Vink (2013). “A Configurational Analysis of Ethnic Protest in Europe.” International Journal of Comparative Sociology, Vol. 54(4), 298-324.
• Schneider, Carsten Q./Wagemann, Claudius, 2012. Set-Theoretic Methods for the Social Sciences. A Guide to Qualitative Comparative Analysis. Cambridge: Cambridge University Press.

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