Магистерская диссертация: основы научно-исследовательской деятельности

• ФЕДОРОВА Анна Владимировнастарший преподаватель Московского государственного института международных отношений (университет) МИД России (МГИМО), Москва, Россияa.fedorova@my.mgimo.ru

В статье рассматриваются теоретические и методические основы научно-исследовательской деятельности (НИД) магистрантов в области экономических наук. Анализируются ключевые понятия НИД, структура магистерской диссертации по экономике, включая теоретическую, эмпирическую и прикладную части. Обоснованы педагогические условия формирования НИД у магистрантов-экономистов: интеграция учебного процесса с исследовательской практикой, применение цифровых технологий и аналитических инструментов, организация наставничества и мониторинга прогресса. Проведено экспериментальное исследование, подтвердившее эффективность этих условий для повышения уровня НИД, роста компетенций на 28% и улучшения качества диссертационных работ. Результаты имеют практическую значимость для совершенствования подготовки магистрантов в условиях цифровизации экономики и глобализации рынков.

Ключевые слова: научно-исследовательская деятельность, магистерская диссертация, экономические науки, педагогические условия, цифровые технологии, эмпирический анализ, компетенции магистрантов

Introduction

In the context of the rapid digitalization of the economy, globalization of financial markets, and the transition to sustainable development, research activity (RA) among master’s students becomes a key element in training specialists capable of solving complex tasks in the field of economic analysis, forecasting, and management. A master’s thesis in economics represents not only a final work but also a tool for developing skills in independent research, critical thinking, and applying theoretical knowledge to real problems, such as inflation, unemployment, innovation growth, or integration into international economic unions.

Traditional approaches to teaching master’s students often focus on theoretical courses; however, in the modern economy, integration of RA with practical skills is required: data collection and analysis, modeling of economic processes, use of software (e.g., Stata, R, Python), and interpretation of results in the context of global challenges. Insufficient development of RA leads to low quality of theses, poor readiness for a scientific career, and difficulties in adapting to the labor market.

The goal of this article is to theoretically substantiate and empirically confirm the pedagogical conditions and methodological approaches to forming RA among master’s students-economists within the framework of preparing a master’s thesis. The relevance of the topic is determined by the need to improve the quality of economic education in Russia, where master’s students face a deficit in skills of empirical analysis and innovative research, especially in the conditions of sanctions and structural reforms.

1. Theoretical Foundations of Research Activity in Economic Sciences Research activity (RA) in economics represents a systematic process of obtaining new knowledge about the patterns of functioning of economic systems, their modeling, and forecasting. According to the definition proposed in the works of domestic economists [1; 2], RA includes stages: problem formulation, data collection and analysis, hypothesis development, empirical verification, and interpretation of results. In the context of a master’s thesis, RA is aimed at solving topical tasks, such as assessing the effectiveness of macroeconomic policy, analyzing market trends, or optimizing business processes. Key features of RA in economic sciences:

– Empirical orientation: use of statistical methods (regression analysis, panel data, econometric models) to test theories. For example, the Solow model for analyzing economic growth or game theory for studying competitive strategies [3].

– Interdisciplinarity: integration of economics with mathematics, statistics, informatics, and sociology, which requires master’s students to master tools like Excel, SPSS, or specialized platforms (e.g., Bloomberg for financial analysis).

– Practical applicability: research results should contribute to solving real problems, such as reducing poverty, increasing labor productivity, or sustainable development of regions.

In Russian economic science, RA among master ’s students has evolved from descriptive works to analytical ones, with an emphasis on the use of big data and machine learning [4]. However, studies show that many master’s students experience difficulties with methodology: selecting adequate models, data processing, and result interpretation, which reduces the quality of theses and their contribution to science [5].

2. Structure of a Master’s Thesis in Economics: Foundations of Research Activity A master’s thesis in economics is built on the principles of RA and includes several mandatory sections reflecting the logic of the research. The structure is based on the requirements of the Higher Attestation Commission of the Russian Federation (VAK RF) and international standards (e.g., APA or Harvard), with an emphasis on originality and empirical base [6].

– Introduction: problem statement, relevance, goals and objectives, object and subject of research, hypotheses, methodology. Here, the master’s student demonstrates understanding of RA by formulating a research question (e.g., “How does digitalization affect the export indicators of Russian regions?”).

– Theoretical chapter: literature review, analysis of concepts and models. The master’s student conducts a critical analysis of existing theories (e.g., Ricardo’s theory of comparative advantages or Romer’s endogenous growth), identifying gaps and justifying their own approach. This is a stage of developing analytical skills in RA.

– Empirical chapter: data collection (from Rosstat, World Bank, Eurostat), their processing and analysis. Application of methods: correlation analysis, regressions, cluster analysis. The master’s student builds models (e.g., panel regression to assess the impact of investments on GDP), interprets results, and tests hypotheses. This section requires mastery of software and data visualization skills.

– Applied chapter: recommendations for practice (economic policy, business strategies). The master’s student proposes solutions based on results, for example, measures to stimulate innovation in regions.

– Conclusion: conclusions, contribution to science, prospects.

– List of literature and appendices: at least 50-70 references, including monographs, articles, and databases.

Formation of RA in the thesis occurs through step-by-step skill development: from literature to 5 empirics, which promotes systemic thinking and readiness for scientific activity. However, without pedagogical support, master’s students often limit themselves to description without deep analysis [7].

3. Pedagogical Conditions for Forming Research Activity among Master’s Students-Economists Based on literature analysis and personal experience [8; 9], pedagogical conditions that contribute to the development of RA in a master’s thesis in economics have been identified. These conditions integrate learning with practice, are adapted to the specifics of economic sciences, and are oriented toward digitalization.

3.1. Integration of the Educational Process with Research Practice Educational courses (econometrics, macroeconomics) should include practical assignments on data collection and modeling. For example, master’s students analyze real economic indicators (inflation, GDP) using open databases. This develops skills in empirical research and motivates independent RA. 3.2. Application of Digital Technologies and Analytical Tools Introduction of platforms (Google Colab, Jupyter Notebook) for data analysis, simulators of economic models, and online courses (Coursera on data science). Master’s students learn to visualize data (charts in Tableau) and apply machine learning for forecasting. This condition is adapted to economics, where data is the basis of RA.

3.3. Organization of Mentoring and Individual Support Each master’s student receives a scientific supervisor for regular consultations on the thesis. Mentoring includes weekly meetings where RA stages are discussed: from topic selection to result interpretation. This promotes the development of critical thinking and overcoming difficulties.

3.4. Monitoring Progress and Reflection Regular assessment of thesis stages (rubrics, self-assessment, peer review). Master’s students keep a research diary, analyzing mistakes and successes. This forms self-control skills and improves the quality of RA.

3.5. Formation of Motivation and Ethical Norms Discussion of RA’s contribution to the economy (solving poverty problems, sustainability), research ethics (plagiarism, data confidentiality). Motivation increases through presentations of results and publications in student journals.

These conditions are interconnected and ensure comprehensive development of RA adapted to economic sciences.

4. Research Methodology

To verify the effectiveness of pedagogical conditions, an experimental study was conducted on the basis of the Faculty of International Economic Relations at MGIMO.

4.1. Goal and Objectives

Goal: to assess the impact of pedagogical conditions on the formation of RA among master’s students-economists.

Objectives: develop a program with integrated conditions; conduct RA diagnostics; compare results in experimental and control groups.

4.2. Participants

60 master’s students of 1-2 years in the “Economics ” direction. Experimental group (n=30) — with implementation of conditions; control (n=30) — traditional education.

4.3. Methods

– RA testing (questionnaires on analysis and modeling skills; Likert scale).

– Thesis analysis (criteria: originality, empirics, conclusions).

– Interviews and process observation.

4.4. Experiment Organization

In the experimental group: course integration with practice, use of Python for analysis, mentoring, monitoring. Duration — 1 academic year. In the control — standard lectures without integration.

5. Research Results

According to the experiment results:

– The average RA score in the experimental group increased by 28% (from 4.2 to 5.4 on a 10-point scale), in the control — by 8% (from 4.1 to 4.7).

– Quality of theses: the experimental group showed deeper analysis (average score 8.5 vs 6.8), with use of econometric models and recommendations.

– Interviews revealed an increase in motivation and confidence in skills (85% of experimental group participants noted improvement).

Statistical analysis (t-test) confirmed the significance of differences (p<0.05).

6. Discussion

The results confirm the effectiveness of pedagogical conditions for developing RA in economics.

Integration with practice and technologies contributed to empirical skills, mentoring — to individualization. This aligns with studies [10; 11], where the role of digitalization in education is emphasized. However, limitations: small sample, focus on one university. Prospects: expansion to online platforms for distance learning.

7. Conclusions

1. RA in a master’s thesis in economics is the basis for developing competencies in analysis and forecasting.

2. The thesis structure includes theoretical, empirical, and applied sections requiring a systematic approach.

3. Pedagogical conditions (integration, technologies, mentoring, monitoring) are effective for increasing RA by 28%.

4. The experiment confirmed the growth in thesis quality and motivation.

5. Recommendations: implementation in master’s programs for training competitive economists.

Список литературы

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