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Research Designs

Samo Kropivnik
samo.kropivnik@fdv.uni-lj.si

University of Ljubljana

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 Topic Details
Monday - session 2 Key factors differentiating research designs

World-view families nowadays (contemporary ontology and epistemology): positivism, interpretative and critical view, and pragmatism.


Purpose(s) of the research: exploratory, descriptive and explanatory.
Scope of the research: basic and applied. Research range and time aspect. The researcher.

Tuesday - session 1 Seminar (Part 1)

Students working in groups discussing, determining and justifying ontological and epistemological foundations of made-up research problems.

Tuesday - session 2 Collecting data I.: Assets of methods and techniques as research design building blocks

Primary and secondary data.
Typology of data collection strategies (with examples and research practice reality): communication vs. observation, structured vs. unstructured methods, method of administration, disguised vs. undisguised methods, the setting.

Wednesday - session 1 Collecting data II.: Assets of methods and techniques as research design building blocks

(continued from Day 2)
Units: the logic of sampling (probability and nonprobability samples: SR, stratified, cluster, convenience, purposive, judgemental) and the logic of casing. Reliability and validity, and related terms.

Wednesday - session 2 Seminar (Part 2)

Students working in groups discussing, determining and justifying data collection strategies for research problems made-up in Part 1.

Friday - session 1 Seminar (Part 3)

Students working in groups discussing, determining and justifying data collection strategies for research problems – defining alternatives to designs from Part 2.

Friday - session 2 Seminar (Part 4)

Students working in groups discussing, determining and justifying data analysis strategies for research problems made-up in Part 1 and the data specified in Part 2 or 3.

Time permitting: SPSS and QDA Miner demonstration.

Monday - session 1 Introduction Variety of designs and classifications

Structure of the course, open issues in students’ projects, references.

Building on different data and methods usage (e.g., analysing units or variables, analysing words or numbers, drawing on big or small N) and on different assumptions and approaches (e.g., heuristic and reductionist approach, inductive and deductive reasoning).

Multiple dimensions of quan – qual continuum.

Thursday - session 1 Analysing and interpreting data I.: Assets of methods and techniques as research design building blocks

Overlap between data collection and analysis.

Variables: conceptualization, operationalization and measurement. Univariate analyses (frequencies and distributions; graphs), bivariate analyses (correlation, t-test and contingency; testing hypothesis) and multivariate analysis (regression, clustering, and factor analysis).

Thursday - session 2 Analysing and interpreting data II.: Assets of methods and techniques as research design building blocks

Interviews, focus groups, projection techniques, ethnography, producing thick descriptions, analytical reading through set lenses, annotating, associating and integrating, coding (pre-set codes; open, axial and selective coding). Generalizations.

Taxonomies, typologies and families of research designs.


Guidelines and recommendations.

Day Readings
Note

CRESWELL, J.W. (2009). Research design. Qualitative, Quantitative, and Mixed-Methods Approaches. Third Edition. London: SAGE


della PORTA, D. & M. KEATING (ed., 2008). Approaches and Methodologies in the Social Sciences. A Pluralist Perspective. Cambridge: Cambridge University Press

NEUMAN, W.L (2006). Social Research Methods. Qualitative and Quantitative Approaches. Sixth Edition. Boston: Pearson

Monday

CRESWELL, 2009: 3 – 21 (Part 1/1), 49 – 71 (Part 1/3), 97 – 110 (Part 2/5), 111 – 127 (Part 2/6), 129 – 143 (Part 2/7)


della PORTA & KEATING, 2008: 1 – 7 (Introduction) , 17 – 39 (Part 1/2)

NEUMAN, 2006: 13 – 20 (Ch1/3&4), 23 – 41 (Ch2/1), 79 – 109 (Ch4), 151 – 178 (Ch6/2,3,4&5)

Tuesday

Written assignment (2 – 3 pages; see Seminar 1)

Wednesday

CRESWELL, 2009: 145 – 171 (Part 2/8), 173 – 202 (Part 2/9), 203 – 225 (Part 2/10)

NEUMAN, 2006: 179 – 218 (Ch7), 219 – 245 (Ch8)


Written assignment (1 – 2 pages; see Seminar 2)

Thursday

della PORTA & KEATING, 2008: 80 – 98 (Part 1/5), 177 – 197 (Part 2/10), 316 – 322 (Part 2/16)


NEUMAN, 2006: 343 – 377 (Ch12), 378 – 417 (Ch13), 457 – 489 (Ch15)

Friday

Written assignment (3 – 4 pages; see Seminar 3 and 4)

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.

Literature

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

Recommended Courses to Cover Before this One

<p>Basics / Introduction of Statistics</p> <p>Introduction of Qualitative Interpretative Methods</p> <p>Refresher / Software courses: SPSS or STATA and&nbsp; QDAMiner or Atlas or NVivo</p>


Additional Information

Disclaimer

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 at the time of change.

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, please contact us before registering.