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SB101 - Research Designs

Instructor Details

Instructor Bio

Samo Kropivnik has gained his PhD in the field of political science at the University of Ljubljana (UL) in 1997. Currently he is Associate Professor of Social Sciences Methodology at Faculty of Social Sciences (UL) and Senior Researcher at Institute of Social Sciences (UL FSS), teaching various courses on marketing research and political science methodology and contributing to research projects on political participation and communications by dealing pragmatically with research approaches and designs, with exploratory and descriptive research methods and techniques in general and in particular with multivariate methods such as clustering, factor analysis and regression.

Course Dates and Times

Monday 1 to Friday 5 August 2016
Generally classes are either 09:00-12:30 or 14:00-17:30
15 hours over 5 days

Prerequisite Knowledge

Some experiences with commonly referenced research designs and their building blocks are appreciated. The more students know about applicability of various methods and techniques the more they can gain from the course.

Short Outline

In an applied manner, the course addresses the question “How to design a research in the non-paradigmatic social sciences?”. The logic and principles behind the crucial tasks that have to be performed when conducting a research, from problem definition and recognition of different research strategies (approaches) to harmonised selection of data collection, analysis and interpretations methods, will be presented during the lectures to enable future research planning in a form of a research design. During the seminar part students are expected to prepare and discuss the backbone of a research design: a made-up case, approached with different strategies, recognized as being predominately qualitative and predominately quantitative.
In the introductory part of the course, factors that decisively shape major characteristics of the intended research are introduced and discussed to deal with highly abstract and idealised concept of various predetermined types of research designs, without discriminating any of them in favour of the other. In the main part, research-design-relevant characteristics of different (sometimes conflicting) methods and techniques that can typically be applied in various steps of a research process are presented, discussed and illustrated with examples from diverse fields of social sciences.

Long Course Outline

superficial one- dimensional divisions, building on different data and methods usage, like e.g., between analysing units or variables, analysing words or numbers, drawing on big or small N etc. are challenged to introduce more constructive and flexible multidimensional distinctions, drawing on different assumptions and approaches, like e.g. between heuristic and reductionist approach, between inductive and deductive reasoning etc. that can be more productively applied as guidelines in research practice and in designing a research process. In so doing the popular qualitative - quantitative continuum is defined as reduced to essentials but useful concept, subject to understanding its multiple dimensions fundament.

To enable informed decision making regarding research design, the main world-view families, like prevailing positivism with its modernized derivations, interpretative approach and critical approach, both with variants, as well as pragmatism as a potential alternative are introduced and discussed together with purpose(s) of the research, being exploratory, descriptive or causal and with the scope of the research, being applied or basic, not neglecting research range and time aspect as well as the researcher him/herself.

Positions on above key issues have to be determined before analytical methods and techniques can be composed in a sound and coherent research design. But soundness and coherence still cannot be achieved without awareness of basic features of methods and techniques available to researchers. Therefore, research- design-relevant characteristics of methodologies, methods and techniques that can typically be applied in various steps of a research process are presented, illustrated with examples from wide-ranging field of social sciences and discussed, e.g. 1) data (evidence) collection methods and techniques, based on communication or observation, further characterised by degree of structure, method of administration, degree of disguise and the setting, using logic of sampling or casing (including field work, interviews, focus groups, projections, as well as surveys, web surveys and selection of secondary data, taking into account conceptualization and operationalization of variables) and 2) data analysis methods, including univariate (frequencies and distributions), bivariate (correlation, t-test and contingency) and multivariate methods (clustering, regression and factor analysis) for analysis of variables, as well as production of thick descriptions, analytical reading through set lens and coding (using pre-set codes or going through open, axial and selective coding phase). The course concludes with highly abstract and idealised concept of various predetermined types of research designs, without discriminating any of them in favour of the other.

Designed at intermediate level, the course certainly cannot provide expertise in elements of a research design (e.g. expertise in methods, not even in selected ones) but can swiftly review most of them to create a holistic picture of the architecture of research designs. At the end students are expected to better understand the variety of opportunities and existing designs and be able to take advantage of distinctions between them in their own research projects by making informed decisions. These basic competences are expected to grow with further study of various methods and techniques and with experiences gained in continuous research work.


Day-to-Day Schedule

Day-to-Day Reading List

Software Requirements

Examples will be presented but students will not use any particular software. Use of notebooks with standard software is recommended.

Hardware Requirements

Participants should bring their own laptop.


The list will be supplemented

1. BRYMAN, A. (2008). Social Research Methods. Oxford: Oxford University Press

2. EDMONDS, W. Alex and Tom D. KENNEDY (2012). An Applied Reference Guide to Research Designs. Quantitative, Qualitetive and Mixed Methods. Thousand Oaks: Sage.

3. MYATT, G.J. (2007). Making Sense of Data. A Practical Guide to Exploratory Data Analysis and Data Mining. New Jersey: Wiley

4. THEODOULOU, O'B. (1999): Methods of Political Inquiry: The Discipline, Philosophy and Analysis of Politics. Prentice Hall

The following other ECPR Methods School courses could be useful in combination with this one in a ‘training track .
Recommended Courses Before

Basics / Introduction of Statistics

Introduction of Qualitative Interpretative Methods

Refresher / Software courses: SPSS or STATA and  QDAMiner or Atlas or NVivo

Additional Information


This course description may be subject to subsequent adaptations (e.g. taking into account new developments in the field, participant demands, group size, etc). Registered participants will be informed in due time.

Note from the Academic Convenors

By registering for this course, you confirm that you possess the knowledge required to follow it. The instructor will not teach these prerequisite items. If in doubt, contact the instructor before registering.

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