Academic Writing

The lecture covers the fundamentals of academic writing and introduces the typology of scientific publications (empirical articles, literature reviews, and meta-analyses). Specific methodologies and international standards for each article type (e.g., PRISMA guidelines) are explained. Particular attention is devoted to the logic of using reference management software (Zotero, Mendeley) and Artificial Intelligence (AI) tools, analyzing the boundaries of academic integrity in literature search and text editing. The lecture provides a methodological roadmap for applying university requirements and APA style in the development of scientific manuscripts.

The practical sessions aim to develop students' analytical and technical skills in handling scientific information. Students practically analyze the structures of various publication types ("Structure Detective") and critically evaluate the methodological quality of published research ("The Critical Reader"). In a workstation format, students master effective literature retrieval by comparing traditional databases with AI tools (Elicit, Consensus) and practice automated citation formatting. Emphasis is placed on the ability to independently create a bibliographic database and integrate in-text citations according to APA style and methodological guidelines.

The lecture covers the practical steps for initiating an empirical study by transforming a theoretical research project into an actionable operational plan. It analyzes the specifics of various research designs (descriptive, correlational, experimental) and their alignment with research objectives. The lecture provides an in-depth examination of research ethics and legal requirements in psychology, including the preparation of ethics committee applications and the management of informed consent protocols. Students learn data management planning in accordance with Open Science principles, covering the data life cycle, confidentiality assurance, and secure data archiving.

The objective of the practical sessions is the technical revision of the research project and the approbation of research instruments. During the sessions, students conduct a "research project audit," refining the alignment between hypotheses and data analysis methods while assessing project feasibility. In the second stage, students develop technical skills in the digitalization of research instruments by creating electronic surveys on research platforms (e.g., RedCap, Google Forms). Through a real-world pilot study with a small sample, students practically verify instrument functionality and prepare datasets for subsequent statistical analysis.

Within the lecture, students refresh and consolidate previously acquired knowledge of statistical data analysis, focusing on its purposeful integration into the research process. Principles of "data hygiene" and the verification of psychometric properties are discussed as prerequisites for high-quality interpretation of results. The lecture reactivates the logic of selecting statistical methods based on research design, preparing students for evidence-based data explanation and the development of meaningful scientific discussion.

In the practical session, students practically apply and refine their skills using analysis software (JASP, Jamovi, or SPSS), with an emphasis on the academic presentation of results. The primary task is to develop the ability to transform statistical software outputs into logical and methodologically sound academic prose. Students consolidate their skills in creating tables and figures according to APA style requirements, learning to integrate statistical indices into a scientific report so that they directly and clearly address the research questions.

The lecture focuses on various formats of scientific communication and their specifics. Students analyze the differences between oral presentations, poster presentations, and scientific publications, acquiring "soft skills" for engaging an audience. Special attention is devoted to developing the concluding sections of a publication—Discussion and Conclusions—learning how to integrate research findings into a broader theoretical and practical context. Additionally, principles of visual communication (data visualization) and the development of a researcher's digital identity are examined.

The practical session is organized as a simulated scientific conference, where students present the independently prepared results of their pilot studies. Emphasis is placed on refining skills to present data in a concise and visually accessible manner (using posters or slide presentations). The objective of the session is to train students' ability to provide reasoned answers to questions, critically discuss research limitations, and defend their conclusions before a professional audience, thereby synthesizing the academic writing and research skills acquired throughout the course.

The lecture covers the fundamentals of academic writing and introduces the typology of scientific publications (empirical articles, literature reviews, and meta-analyses). Specific methodologies and international standards for each article type (e.g., PRISMA guidelines) are explained. Particular attention is devoted to the logic of using reference management software (Zotero, Mendeley) and Artificial Intelligence (AI) tools, analyzing the boundaries of academic integrity in literature search and text editing. The lecture provides a methodological roadmap for applying university requirements and APA style in the development of scientific manuscripts.

The practical sessions aim to develop students' analytical and technical skills in handling scientific information. Students practically analyze the structures of various publication types ("Structure Detective") and critically evaluate the methodological quality of published research ("The Critical Reader"). In a workstation format, students master effective literature retrieval by comparing traditional databases with AI tools (Elicit, Consensus) and practice automated citation formatting. Emphasis is placed on the ability to independently create a bibliographic database and integrate in-text citations according to APA style and methodological guidelines.

The lecture covers the practical steps for initiating an empirical study by transforming a theoretical research project into an actionable operational plan. It analyzes the specifics of various research designs (descriptive, correlational, experimental) and their alignment with research objectives. The lecture provides an in-depth examination of research ethics and legal requirements in psychology, including the preparation of ethics committee applications and the management of informed consent protocols. Students learn data management planning in accordance with Open Science principles, covering the data life cycle, confidentiality assurance, and secure data archiving.

The objective of the practical sessions is the technical revision of the research project and the approbation of research instruments. During the sessions, students conduct a "research project audit," refining the alignment between hypotheses and data analysis methods while assessing project feasibility. In the second stage, students develop technical skills in the digitalization of research instruments by creating electronic surveys on research platforms (e.g., RedCap, Google Forms). Through a real-world pilot study with a small sample, students practically verify instrument functionality and prepare datasets for subsequent statistical analysis.

Within the lecture, students refresh and consolidate previously acquired knowledge of statistical data analysis, focusing on its purposeful integration into the research process. Principles of "data hygiene" and the verification of psychometric properties are discussed as prerequisites for high-quality interpretation of results. The lecture reactivates the logic of selecting statistical methods based on research design, preparing students for evidence-based data explanation and the development of meaningful scientific discussion.

In the practical session, students practically apply and refine their skills using analysis software (JASP, Jamovi, or SPSS), with an emphasis on the academic presentation of results. The primary task is to develop the ability to transform statistical software outputs into logical and methodologically sound academic prose. Students consolidate their skills in creating tables and figures according to APA style requirements, learning to integrate statistical indices into a scientific report so that they directly and clearly address the research questions.

The lecture focuses on various formats of scientific communication and their specifics. Students analyze the differences between oral presentations, poster presentations, and scientific publications, acquiring "soft skills" for engaging an audience. Special attention is devoted to developing the concluding sections of a publication—Discussion and Conclusions—learning how to integrate research findings into a broader theoretical and practical context. Additionally, principles of visual communication (data visualization) and the development of a researcher's digital identity are examined.

The practical session is organized as a simulated scientific conference, where students present the independently prepared results of their pilot studies. Emphasis is placed on refining skills to present data in a concise and visually accessible manner (using posters or slide presentations). The objective of the session is to train students' ability to provide reasoned answers to questions, critically discuss research limitations, and defend their conclusions before a professional audience, thereby synthesizing the academic writing and research skills acquired throughout the course.