Методология и логика социологического исследования

Магистратура 2026/2027

Статус: Курс обязательный (Аналитика данных и прикладная статистика / Data Analytics and Social Statistics)

Кто читает: Международная лаборатория прикладного сетевого анализа

Где читается: Факультет социальных наук

Когда читается: 1-й курс, 2 модуль

Охват аудитории: для своего кампуса

Язык: английский

Кредиты: 3

Контактные часы: 28

Full Syllabus Ask Question

Abstract

The purpose of the course is to provide insight into the main stages of the development of sociological research and to offer practically useful tools and approaches. The course will be useful for those who do not have special training in empirical sociological research, but they need to work with research data, evaluate the validity of research project conclusions, and make decisions based on confirmed or unconfirmed hypotheses. The course presents conceptual and operational definitions and their relations to one another, how variables are expressed distinctively, and how to formulate hypotheses that back up scientific findings. Additionally, the course examines the possibilities of AI agents for use at different stages of sociological research. It is based on the principle that we think first, then use the capabilities of AI. Students will be asked to try out a particular tool and method for solving typical practical tasks of a researcher. Students will work on their own research issues throughout the course to apply the theoretical understanding to their practical applications.

Learning Objectives

Goal 1. To master the foundational epistemology and internal logic of social research design. This goal aims at developing a comprehensive understanding of the goals and functions of social research, enabling students to deconstruct the logical sequence of the research process from problem formulation to operationalization and measurement. Students will learn to critically appraise the internal coherence of published designs, explicitly differentiating between quantitative, qualitative, and mixed-methods architectures, and justifying methodological choices based on ontological and epistemological grounds rather than convenience.
Goal 2. To acquire advanced competencies in systematic literature synthesis. This goal aims at equipping master students in data analytics with rigorous, replicable methods for navigating, mapping, and synthesizing existing knowledge. This includes executing bibliometric network analyses (using OpenAlex and library science tools) to identify intellectual frontiers, and applying the statistical logic of meta-analysis in R (effect sizes, heterogeneity, publication bias) in strict adherence to PRISMA guidelines, thereby transforming scattered literature into a defensible, quantitative foundation for new research.
Goal 3. To equip the students with rigorous empirical strategies for sampling, data preprocessing, and methodological alignment. This goal aims at building understanding and practical proficiency in constructing a complete empirical blueprint (formulating coherent data-collection protocols that strategically align sampling strategies, specifying transparent data-preprocessing routines to address missing data and measurement errors). This goal ensures that every empirical decision is logically linked to the overarching research design.
Goal 4. To develop cultivate persuasive scientific communication and critical digital methodological literacy. This goal aims at preparing students to synthetically translate complex empirical findings into compelling, logically structured scientific presentations that clearly bridge "results" with "meaning", while defending their entire research architecture against peer-review scrutiny. Additionally, this goal assumes developing skills of machine-human digital communications through reasonable and justified use of AI services assisting in scientific research.

Expected Learning Outcomes

Articulates the epistemological foundations and logical sequence of the social research process, explicitly distinguishing between different elements of the research design.
Deconstructs the internal architecture of quantitative, qualitative, and mixed-methods designs, and justifies the selection of a specific design based on the research question's ontological and epistemological grounding.
Applies criteria of critical appraisal to judge the internal coherence of a published study, identifying threats to validity and logical fallacies in the link between findings and interpretations.
Critically evaluates the affordances and limitations of generative AI as a "scientific consultant" by formulating precise, theory-driven prompts for design critique, literature screening, and data extraction, while justifying human oversight over machine-generated summaries and methodological suggestions.
Differentiates between the types of literature review and executes a systematic bibliometric literature review using network analysis and maps intellectual structures of the research domain.
Applies the statistical logic of meta-analysis (effect sizes, heterogeneity, publication bias) using R, and integrates this with PRISMA guidelines to ensure transparent and reproducible literature synthesis.
Strategically deploys AI-assisted tools to accelerate quantitative and qualitative workflows, while systematically auditing AI outputs for bias, misinterpretation, and alignment with disciplinary methodological standards.
Understands a rigorous sampling and data-preprocessing blueprint that aligns sampling logic with the study's goals as well as how to address issues with missing data and measurement errors.
Synthesizes empirical results into a coherent scientific narrative (oral/poster/written) that articulates theoretical, practical, and policy implications, while defending methodological trade-offs against mock peer-review scrutiny.
Utilizes AI applications to enhance scientific presentations and public speaking (e.g., structure refinement, slide design, speech practice), while critically appraising AI-generated narrative suggestions against the researcher's authentic argumentative logic and evidence basis.

Course Contents

Topic 1. Foundations of social research design and major research issues
Topic 2. Bibliometric approach in literature review
Topic 3. Meta-analysis as a quantitative approach in literature studies
Topic 4. Methods in social studies
Topic 5. Data collection. Sampling.
Topic 6. Presenting and discussing scientific results

Assessment Elements

From social problem to research problem: identifying a gap in literature and a contribution
Bibliometric iterature review in OpenAlex for the topic of your term paper
The task aims to support reflection on term paper. Students will need to conduct a short bibliometric study of the literature in OpenAlex on the topic of the term paper and to analyze bibliometric networks built in VOSviewer.
Meta analysis in R from a selection of problems
Reflective Essay on Operationalization and Research Design
This assignment requires you to engage in deep methodological reflection on a research study of your choice (either your own term paper proposal or a published study you have encountered). The focus is exclusively on operationalization (how abstract theoretical constructs are translated into measurable or observable indicators) and research design (the overall architectural blueprint that connects your research question to your methods).
In-Class Presentation – Operationalization and Research Design Defense
In-class presentation assignment based directly on your written reflective essay. It transforms the written analysis into an oral defense, requiring students to visually communicate their methodological reasoning and respond to peer/instructor questioning in a "mock peer-review" format.

Interim Assessment

2026/2027 2nd module
0.25 * Meta analysis in R from a selection of problems + 0.35 * Bibliometric iterature review in OpenAlex for the topic of your term paper + 0.15 * From social problem to research problem: identifying a gap in literature and a contribution + 0.15 * Reflective Essay on Operationalization and Research Design + 0.1 * In-Class Presentation – Operationalization and Research Design Defense

Bibliography

Recommended Core Bibliography

Borenstein, M. (2009). Introduction to Meta-Analysis. Chichester, U.K.: Wiley. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsebk&AN=274641
Bynner, J. M., & Stribley, K. M. (2017). Research Design : The Logic of Social Inquiry. London: Routledge. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsebk&AN=1608766
Hancké, B. (2009). Intelligent Research Design : A Guide for Beginning Researchers in the Social Sciences. Oxford: OUP Oxford. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsebk&AN=299002
HU, C.-P., & CHANG, Y.-Y. (2017). John W. Creswell, Research Design: Qualitative, Quantitative, and Mixed Methods Approaches. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsbas&AN=edsbas.BCEBF1CE
Methodological thinking : basic principles of social research design, Loseke, D. R., 2017
Research methods : the basics, Walliman, N., 2018
Research synthesis and meta-analysis : a step-by-step approach, Cooper, H., 2017
Rice, R. A. (2017). How to Write a Literature Review. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsbas&AN=edsbas.7550A4E6
Sampling: design and analysis, Lohr, S. L., 2010
Sara Efrat Efron, & Ruth Ravid. (2019). Writing the Literature Review : A Practical Guide. The Guilford Press.
Schoonenboom, J. (Department of E. F. of P. and E. U. of V., Johnson, R. B. (Department of P. S. U. of S. A., & R. Burke Johnson. (2017). How to Construct a Mixed Methods Research Design. https://doi.org/10.1007/s11577-017-0454-1
Schwarzer, G., Carpenter, J. R., & Rücker, G. (2015). Meta-Analysis with R. Cham: Springer. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsebk&AN=1079134
Self, R. (2016). Giving effective academic presentations. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsbas&AN=edsbas.EB2D8CDD
Sharon L. Lohr. (2019). Sampling : Design and Analysis: Vol. Second edition. Chapman and Hall/CRC.
Ted Gournelos, Joshua R. Hammonds, & Maridath A. Wilson. (2019). Doing Academic Research : A Practical Guide to Research Methods and Analysis. Routledge.

Recommended Additional Bibliography

Advanced research methods for the social and behavioral sciences edited by John E. Edlund (Rochester Institute of Technology), Austin Lee Nichols (Connection Lab). (2019). Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edswao&AN=edswao.1032497149
Advances in meta-analysis, Pigott, T. D., 2012
Armstrong, C. S., & Kepler, J. D. (2018). Theory, research design assumptions, and causal inferences. Journal of Accounting and Economics, (2), 366. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsrep&AN=edsrep.a.eee.jaecon.v66y2018i2p366.373
Eck, N. J. P. (Nees J. van, & Waltman, L. (Ludo). (2010). Software survey: VOSviewer, a computer program for bibliometric mapping. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsbas&AN=edsbas.3AC7DCD5
Elsbach, K. D., & Knippenberg, D. (2020). Creating High‐Impact Literature Reviews: An Argument for “Integrative Reviews.” Journal of Management Studies (John Wiley & Sons, Inc.), 57(6), 1277–1289. https://doi.org/10.1111/joms.12581
Good, P. I. (2013). Introduction to Statistics Through Resampling Methods and R (Vol. Second edition). Hoboken, New Jersey: Wiley. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsebk&AN=522954
Günbayi, I., & Sorm, S. (2018). Social Paradigms in Guiding Social Research Design: The Functional, Interpretive, Radical Humanist and Radical Structural Paradigms. Online Submission, 9(2), 57–76. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=eric&AN=ED585253
Hackett, P. (2019). Quantitative Research Methods in Consumer Psychology : Contemporary and Data Driven Approaches. New York, NY: Routledge. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsebk&AN=1853813
Handbook of research design and social measurement, , 2002
Hicks, D., Wouters, P., Waltman, L., de Rijcke, S., & Rafols, I. (2017). Bibliometrics: The Leiden Manifesto for research metrics. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsbas&AN=edsbas.320942A0
I. Korotkina B., & И. Короткина Б. (2017). Academic Literacy and Methods of Global Scientific Communication ; Академическая грамотность и методы глобальной научной коммуникации. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsbas&AN=edsbas.8C60FBE4
Knopf, J. W. (2006). Doing a Literature Review. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsbas&AN=edsbas.6DDBE740
McNabb, D. E. . V. (DE-588)128628677, (DE-627)376934980, (DE-576)185381413, aut. (2021). Research methods for political science quantitative, qualitative and mixed methods approaches David E. McNabb.
Paul S. Levy, & Stanley Lemeshow. (2008). Sampling of Populations : Methods and Applications: Vol. 4th ed. Wiley.
Practical social investigation : qualitative and quantitative methods in social research, Pole, C.J., 2002
Rebecca Killick. (2016). Introductory Statistics and Analytics: A Resampling Perspective. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsbas&AN=edsbas.69FBF820
Snyder, H. (2019). Literature review as a research methodology: An overview and guidelines. https://doi.org/10.1016/j.jbusres.2019.07.039
Social research methods by example : applications in the modern world, Besen-Cassino, Y., 2018
Каракчиева В.Л., Орлова О.Г. - Академическая презентация. Academic Presentation - 978-5-7782-4319-4 - Новосибирский государственный технический университет - 2020 - https://znanium.ru/catalog/document?id=397602 - 397602 - ZNANIUM
Сальная Л.К., Сидельник Э.А., Краснощекова Г.А. - Get Ready for Scientific Communication - 978-5-9275-3573-6 - Южный федеральный университет - 2020 - https://znanium.ru/catalog/document?id=375035 - 375035 - ZNANIUM

Authors

PAVLOVA IRINA ANATOLEVNA

Course Syllabus