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Research Design in Political Science

Code: 45817
Credits: 5
2026/2027
Degree programme Type Course
Political Science OB 1

Contact lecturer

Name :
Carol Galais Gonzalez
Email :
carolina.galais@uab.cat

Teaching staff

Sergio Villamayor Tomas

Group languages

You can consult this information at the end of the document.

Prerequisites

Students are expected to hold a degree in political science or a related social science discipline. Basic familiarity with academic reading in English is strongly recommended.


Objectives

This course introduces students to the principles of research design in political science. It aims to equip students with the tools necessary to formulate original research questions, construct theoretical frameworks, and select appropriate methodological strategies for empirical inquiry. By the end of the course, students should be able to critically evaluate the research designs of published studies, understand the epistemic foundations underlying different methodological traditions, and produce an original research proposal for their Master's thesis.


Learning outcomes

  • CA01 (Design coherent research projects by creating a question, a theoretical framework and methodology.) Design coherent research projects by creating a question, a theoretical framework and methodology.
  • CA02 (Communicate research designs and results in an ethical, structured, and inclusive manner.) Communicate research designs and results in an ethical, structured, and inclusive manner.
  • KA01 (Describe the principles of research design in political science, formulating relevant questions and ensuring coherence between theory, methodology and empirical analysis.) Describe the principles of research design in political science, formulating relevant questions and ensuring coherence between theory, methodology and empirical analysis.
  • SA01 (Formulate research questions, build solid theoretical frameworks, and design rigorous studies that contribute to scientific practice.) Formulate research questions, build solid theoretical frameworks, and design rigorous studies that contribute to scientific practice.
  • SA02 (Select and evaluate research designs, identifying methodological strengths and limitations.) Select and evaluate research designs, identifying methodological strengths and limitations.

Contents

Block 1 – Foundations of research design (Sessions 1–3): What is social science? Quality standards and good practices. Research objects and research questions. The anatomy of a scholarly paper.

Block 2 – From theory to hypotheses (Session 4-6): Conceptualization and operationalization. Literature review.Theories and hypotheses. Derivation and testing of hypotheses.

Block 3 – Qualitative research designs (Sessions 7–8): Epistemological foundations of qualitative research. Case studies and process tracing. Comparative methods and mixed-method strategies. [Sergio Villamayor]

Block 4 – Quantitative research designs (Sessions 9–10): Observational research and causality. Quasi-experimental and experimental designs.

Learning activities and methodology

Title Hours ECTS Learning outcomes
Lectures and in-class activities 30 1.2 CA01, CA02, KA01, SA01
Tutorials and assignment feedback 35 1.4 CA01, KA01, SA01
Reading and assignment preparation 60 2.4 CA01, KA01, SA01, SA02

The course is structured around weekly two-and-a-half-hour sessions, each divided into two parts. The first half consists of a lecture introducing the key concepts and analytical tools of the session. The second half is typically devoted to a practical in-class exercise or participatory activity — such as analysing a research design, discussing a methodological problem, or applying concepts from the lecture to a concrete case. These in-class activities are not graded. When a reading is listed as required in the syllabus, students are expected to come to that session having read it; these are exemplary published articles chosen to illustrate how methodological choices play out in actual research, rather than to provide substantive coverage of a topic.







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

Continuous assessment activities

Title Weight Hours ECTS Learning outcomes
Active participation in class discussions and in-class activities. 10% 0 0 CA02, KA01, SA01, SA02
Timed Written Proof (2 hours, in-person). 40% 0 0 CA01, CA02, KA01, SA02
Assignment 2: Essay on qualitative methodology (~2,000 words). Individual written assignment 25% 0 0 CA01, CA02, KA01
Assignment 1: Research proposal outline (research question, hypotheses, and research gap). Individual written assignment. 25% 0 0 CA02, SA01, SA02

Continuous assessment

Students must attend at least 80% of sessions to be eligible for continuous assessment. With ten sessions in total, this means that up to two absences are permitted without justification. Medically certified absences do not count toward this limit, provided appropriate documentation is submitted to the instructor in a timely manner.


The course is assessed through three graded activities:

  • Assignment 1: Research proposal outline (research question, hypotheses, and research gap). Individual written assignment. 25% of the final grade.
  • Assignment 2: Essay on qualitative methodology (~2,000 words). Individual written assignment. 25% of the final grade.
  • Timed Written Proof (2 hours, in-person). Students receive a research question at the start of the session and must produce a complete original research design from memory. Choice of one among four examples provided. Graded on internal coherence and methodological adequacy. Individual. 40% of the final grade.
  • Active participation in class discussions and in-class activities. Individual. 10% of the final grade.

Individual assessment accounts for 100% of the final grade. No single activity exceeds 50% of the final grade. Grades will be returned within 20 working days of submission or completion.


Use of AI tools

The use of Generative AI tools is permitted only for support tasks such as brainstorming, text editing, grammar correction, and translation. The core intellectual work — formulating research questions, deriving hypotheses, selecting and justifying a research design — must be the student's own. Where AI tools have been used, students must clearly identify which parts were assisted, specify the tools used, and include a brief critical reflection on how these influenced the final output. Lack of transparency regarding AI use will be considered academic dishonesty and may result in a partial or total penalty on the activity grade, or more serious sanctions in severe cases. The use of any AI tools or electronic devices during the Timed Written Proof is strictly prohibited.


Recovery

Students who have failed the course (grade<5) but have been assessed on activities totalling at least two-thirds of the final grade are entitled to a recovery process, provided they have obtained a minimum average grade of 3.5. The recovery process will consist of a written in-person exam (2 hours). The maximum grade obtainable through recovery is 5.


Non-assessable grade

A student will be graded as Non-Assessable (NA) if they have not submitted assessable work totalling more than 50% of the final grade.


Single assessment

This course does not offer single assessment (avaluació única).


Repeat students

From the second enrolment, students may request a final synthesis exam (prova de síntesi), in accordance with UAB academic regulations (Art. 267).

Bibliography

Baglione, L. (2008). Doing good and doing well: Teaching research-paper writing by unpacking the paper. PS: Political Science & Politics, 41(3), 595–602.

Gerring, J. (1999). What makes a concept good? A criterial framework for understanding concept formation in the social sciences. Polity, 31(3), 357–393.

King, G., Keohane, R. O., & Verba, S. (1994). Designing social inquiry. Princeton University Press.

Lake, D. A. (2025). How to Write an Academic Article in Political Science. IGCC Essays, 2025.

Toshkov, D. (2016). Research design in political science. Bloomsbury Publishing.

Webster, J., & Watson, R. T. (2002). Analyzing the past to prepare for the future: Writing a literature review. MIS Quarterly, 26(2), xiii–xxiii.

Software

No specific software is required for this course. Students are expected to bring a personal laptop to each session with word-processing and spreadsheet software installed, internet access to connect to the UAB Campus Virtual, and an AI tool of their choice for in-class activities where its use is permitted.


Course groups and languages

The information provided is provisional until November 30. After this date, you will be able to consult the language of each group through this link. To access the information, you will need to enter the course CODE