Research Techniques
Code: 42277 ECTS Credits: 10| Degree | Type | Year |
|---|---|---|
| 4313335 Political Science | OB | 0 |
Contact
- Name:
- Danislava Milkova Marinova
- Email:
- dani.marinova@uab.cat
Teachers
- Eva Kristine Ostergaard-Nielsen
- Roberto Pannico
- Gabriela de Carvalho
- Lara Ivana Maestripieri
Teaching groups languages
You can view this information at the end of this document.
Prerequisites
The quantitative part of the course assumes no prior knowledge other than a minimal mathematical background. Students who have not taken any type of quantitative course since high school should read the following text before the course starts:
Bolker, E. D., & Mast, M. 2015. Common Sense Mathematics. Mathematical Association of America. Available at http://www.cs.umb.edu/~eb/qrbook/qrbook.pdf.
Those who want to gain some more statistical insight are also strongly encouraged to read:
Wheelan, C. 2013. Naked Statistics: Stripping the Dread from the Data. New York: WW Norton & Company.
Objectives and Contextualisation
Aim of course
The aim of this course is for the students to be familiar with and know how to apply a series of the main social science research techniques of collecting and analysing data. In order to meet these objectives we include both quantitative and qualitative techniques. We cannot cover all the research techniques of the social sciences, but centre on those that can be found in the main social science journals. We prioritize issues of practical training and interpretation over very mathematical questions.
ACQUIRED SKILLS
Specific skills
- To identify and know how to affront the main methodological difficulties that occur in a political science analysis
- To work with a complex and diverse set of data and sources of information
- To design a research project that satisfies criteria of excellence and rigorous analysis.
- To apply those qualitative and quantitative research techniques which are necessary for a systematic and rigorous analysis of political reality.
Transversal skills
- To be able to evaluate applied or academic research with relevant criteria.
- To be able to design academic and applied research projects in an independent manner and using the relevant terminology, argumentation and analytical framework.
- Demonstrate the ability to read and understand specialized texts in English.
Competences
- Apply the qualitative and quantitative techniques necessary for the systematic and rigorous analysis of specific aspects of politics today.
- Demonstration reading comprehension for specialist texts in English.
- Design a research project that satisfies the criteria of rigour and academic excellence.
- Design and write projects and technical and academic reports autonomously using the appropriate terminology, arguments and analytical tools in each case.
- Identify the main methodological difficulties that arise in political analysis and know how to deal with them using the existing tools.
- Manage a set of political science data and specific sources, such as statistics, surveys or other documents.
- Using the appropriate criteria make an individual evaluation of reports, documents and research carried out by third parties.
Learning Outcomes
- Access data sources appropriate for the analysis of political science.
- Demonstration reading comprehension for specialist texts in English.
- Design and write projects and technical and academic reports autonomously using the appropriate terminology, arguments and analytical tools in each case.
- Identify appropriate to answer a research question and analyze qualitative data using the main techniques of analysis and appropriate software coding qualitative techniques.
- Identify the main advantages and difficulties with respect to the validity and reliability of the techniques selected.
- Identify the most appropriate statistical method to respond to a research question with the data available and analyse quantitative data using the appropriate statistical software.
- Make socio-political phenomena observable and/or quantifiable.
- Process and prepare data collected for analysis using the corresponding software.
- Relate one of more quantitative and/or qualitative techniques to a research question and justify why this was the most appropriate selection.
- Understand the current debates and challenges of the main quantitative and qualitative research techniques.
- Understand the main qualitative and quantitative research techniques.
- Using the appropriate criteria make an individual evaluation of reports, documents and research carried out by third parties.
Content
QUALITATIVE METHODS (Convenor: Eva Ostergaard)
Introduction:
Session 1. Introduction to qualitative research techniques
What are the main characteristics of qualitative research? How to assess validity and reliability in qualitative research? What kind of research questions can we ask using qualitative research techniques? Which types of qualitative techniques can best be combined and how may they be triangulated?
Data collection:
Session 2. Field research
This class will examine methodological and practical issues of ethnographic research. It will cover: typologies of field research, the fieldwork entry, the (participant) observation, the collection of information, and the analyses of qualitative evidence.
Session 3. Interviews I
What are the characteristics and differences between structured, semi-structured and open-ended/narrative interviews? How may the researcher sample the interviewees in a qualitative research project?
Session 4. Interviews II -
Session 5. Interviews III - Focus Group
In this class, there will be an introduction to focus group, taking into account conceptual considerations, best practices and how to design it.
Session 6. Further issues in Qualitative Research
We will cover ethical issues, sensitive topics, and transparency in qualitative research (active citation and archiving).
Data analysis:
Session 7. Discourse analysis
This session will clarify what discourses are, how they function and how we can analyse them. In addition, we will deal with the types of discourse analysis and we will reflect upon the kinds of data we can examine discursively.
Sessions 8, 9, and 10. Analysis of Interviews
QUANTITATIVE METHODS (Convenor: Danislava Marinova)
Sesión A: Introducción al análisis de datos cuantitativos
Sesión B: estadística descriptiva
Sesión 1: Análisis bivariante básico
Sesión 2: Introducción a la inferencia estadística
Sesión 3: Pruebas de hipótesis bivariadas
Sesión 4: Correlación y regresión bivariadas
Sesión 5, 6: Regresión múltiple (I)
Sesión 7, 8: Regresión múltiple (II): variables independientes categóricas
Sesión 9: Regresión múltiple (II): Interacciones
Sesión 10, 11: Regresión logística (I)
Sesión 12 & 13: Límites y Extensión de los modelos de regresión
Session 14, 15: Postestimación, gráficos, tablas: Sesiones prácticas
Activities and Methodology
| Title | Hours | ECTS | Learning Outcomes |
|---|---|---|---|
| Type: Directed | |||
| Collective tutoring/discussion of projects | 5 | 0.2 | 5, 9, 11, 12 |
| In-class practice | 25 | 1 | 1, 6, 8, 11, 12 |
| Lecture | 25 | 1 | 5, 6, 10, 11 |
| Type: Supervised | |||
| Individual tutoring | 10 | 0.4 | 3, 5, 6, 8, 9, 11 |
| Type: Autonomous | |||
| Qualitative data analysis | 30 | 1.2 | 3 |
| Qualitative data collection/generation | 30 | 1.2 | 3, 8, 11 |
| Quantitative data analysis | 30 | 1.2 | 3, 5, 6, 8, 11 |
| Readings | 30 | 1.2 | 2, 5, 10, 11, 12 |
| Writing essays/reports | 30 | 1.2 | 2, 3, 5, 10, 11, 12 |
The sessions on quantitative and qualitative research techniques will be taught in parallel over the 8 weeks of the course. The classes combine theoretical lectures with seminars and sessions of practicing different techniques. An important part of the course takes place outside of the classroom in order to consolidate the use of a selection of the research techniques.
Annotation: Within the schedule set by the centre or degree programme, 15 minutes of one class will be reserved for students to evaluate their lecturers and their courses or modules through questionnaires.
Assessment
Continous Assessment Activities
| Title | Weighting | Hours | ECTS | Learning Outcomes |
|---|---|---|---|---|
| Assignments quantitative part | 60% | 20 | 0.8 | 1, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12 |
| Exercises qualitative part | 40% | 15 | 0.6 | 1, 2, 4, 8 |
To receive a passing grade in the module, students need a passing grade in each of the module's two parts (qualitative part and quantitative part). The 10% penalty grade applies to each day that the student is late with a submission grade.
QUALITATIVE PART (40% of final grade for the module)
Students will be evaluated based on four assignments in qualitative methods:
• Exercise 1 (30% of the qualitative part), Fieldwork/observational techniques
• Exercise 2 (30% of the qualitative part), Interview exercise
• Exercise 3 (30% of the qualitative part), Data analysis (using Atlas.ti in the software to support the analysis is optional)
• Exercise 4 (10% of the qualitative part), Group presentation on the research process
To receive a passing grade in the qualitative part of the module, students must meet all four of the following requirements:
1. attend at least 80% of the class sessions;
2. turn in all four assignments;
3. receive a passing grade (5 or higher) on three of the four assignments;
4. have an average grade greater than 5 on the four works.
Plagiarism: Cheating on an assignment will result in a zero for that assignment and the student will have to take the remedial exam.
Remedial exam: students who have an average grade of less than 5 may take the recovery exam if they meet the following two requirements:
1. have attended 80% of the class sessions AND
2. have delivered the four assignments.
The remedial exam is graded on a pass-or-fail basis. If students pass the remedial exam, they can receive, at best, a final mark of 5 for the qualitative part of the module.
QUANTITATIVE PART (60% of the final grade of the module)
Students will be evaluated based on five take-home assignments in applied statistics. Each task will have the same weight for the final grade.
To receive a passing grade, students must meet the following four requirements:
- attend at least 80% of class sessions;
- hand in all five assignments;
- receive a passing grade (5 or higher) on at least three of the five assignments;
- have an average grade higher than 5 on the five assignments.
Plagiarism: Cheating on a paper will result in a zero for that paper and the student will have to take the remedial exam.
Remedial exam: Students who have an average grade below 5 on all five papers or have cheated on any of the five assignments can take the make-up exam if they meet the following two requirements:
- have attended 80% of the class sessions AND
- have submitted the five assignments.
The remedial exam is graded on a pass-or-fail basis. If students pass the remedial exam, they can receive, at best, a final mark of 5 for the quantitative part of the module.
Bibliography
Core readings
Qualitative
Bryman, A. 2001. Social Research Methods. Oxford University Press
Creswell, J. 2007. Qualitative Inquiry and research design. Choosing Among Five Approaches
Della Porta, D. & M. Keating, M. 2008. Approaches and Methodologies in the Social Sciences: A Pluralist Perspective. Cambridge: Cambridge University Press.
Kapiszewski, Diana, MacLean, Lauren M., Read, Benjamin L. 2015. Field Research in Political Science: Practices and Principles. Cambridge. Cambridge University Press.
Hesse-Biber, S. And Leavy, P. 2004. Approaches to Qualitative Research. A reader on theory and practice. Oxford. Oxford University Press
Hesse-Biber, S. And Leavy, P. 2006. The practice of qualitative research. Sage.
Denzin, N. K., & Y. S. Lincoln (Eds.). 2012. Strategies of Qualitative Inquiry, 4th ed. Thousand Oaks, CA: Sage.
Sarantakos, S. 2005. Social Research (third edition). Palgrave Macmillan
Relevant Journals:
International Journal of Qualitative methods http://www.sagepub.in/journals/Journal202499#tabview=manuscriptSubmission
Qualitative Research Journal http://www.emeraldinsight.com/toc/qrj/15/4
Quantitative
Acock, A. C. 2014. A Gentle Introduction to Stata, 4th ed. College Station, TX: Stata Press.
Agresti, A. 2009. Statistical Methods for the Social Sciences, 4th ed. Pearson Prentice Hall.
Kellstedt, P. M. & G. D. Whitten. 2013. The Fundamentals of Political Science Research, 2nd ed. Cambridge: Cambridge University Press.
Lewis-Beck,M. (1980) Applied regression: An introduction. Thousand Oaks: Sage Publications.
Long, J. S. & J. Freese. 2014. Regression Models for Categorical Dependent Variables Using Stata, Third Edition. College Station, TX: Stata Press.
Pollock, P. H. 2016. The Essentials of Political Analysis, 5th ed. Washington, DC: CQ Press.
Pollock, P. H. 2015. A Stata Companion to Political Analysis, 3rd ed. Washington, DC: CQ Press.
Software
Qualitative
- Nvivo
- Atlas-ti
Quantitative
- STATA (16)
Language list
| Name | Group | Language | Semester | Turn |
|---|---|---|---|---|
| (TEm) Theory (master) | 1 | English | second semester | morning-mixed |