NA_RDC Research of Digital Cultures and AI

University of Finance and Administration
Winter 2024
Extent and Intensity
1/2/0. 6 credit(s). Type of Completion: zk (examination).
Teacher(s)
Mgr. Jitka Cirklová, M.A., Ph.D. (seminar tutor)
Guaranteed by
Mgr. Jitka Cirklová, M.A., Ph.D.
Subdepartment of Social Sciences – Department of Social Sciences – Departments – University of Finance and Administration
Contact Person: Bc. Kateřina Konupková
Timetable of Seminar Groups
NA_RDC/cNCPH: each odd Tuesday 15:45–16:29 E307, each odd Tuesday 16:30–17:15 E307, each odd Tuesday 17:30–18:14 E307, each odd Tuesday 18:15–19:00 E307, J. Cirklová
NA_RDC/pNCPH: each even Tuesday 17:30–18:14 E307, each even Tuesday 18:15–19:00 E307, except Tue 1. 10. ; and Mon 14. 10. 14:00–15:30 E305, J. Cirklová
Course Enrolment Limitations
The course is offered to students of any study field.
Course objectives
This course explores the intersection of digital cultures and artificial intelligence (AI), using sociological research methods to examine how digital technologies shape contemporary social life. By employing netnography and art-based research methods, students will critically investigate AI's impact on identity, community, and culture in online environments.
Learning outcomes
Course Objectives To introduce students to research methods suitable for studying digital cultures and AI. To develop the ability to critically analyze the role of AI in social interactions and cultural practices. To provide hands-on experience in designing and conducting sociological research in digital contexts. To enhance students’ skills in writing prompts and analyzing AI-generated content. To enable students to present their research findings in a clear and structured manner. Learning Outcomes Upon completion of this course, students will be able to: Understand and apply sociological research methods, including netnography and art-based research, in digital contexts. Critically assess the cultural implications of AI technologies. Design and conduct a research project focused on digital cultures or AI. Write and evaluate AI prompts effectively in relation to sociological research. Defend their research findings through a structured research report and oral presentation.
Syllabus
  • Week 1: Introduction to Digital Cultures and AI Lecture Topic: Overview of Digital Cultures and AI in Society Seminar Activity: Discussion on digital sociology and AI in everyday life. Learning Objectives: Understand the course framework and objectives. Explore key concepts of digital culture and AI. Assignment: Read assigned articles on digital cultures and prepare a summary. Week 2: Sociological Research Methods for Digital Contexts Lecture Topic: Introduction to Classic Sociological Research Methods Seminar Activity: Application of methods in digital environments. Learning Objectives: Understand sociological research methods. Discuss adaptation of methods for studying digital platforms. Assignment: Select a digital space for potential research (e.g., social media, forums). Week 3: Netnography – Introduction Lecture Topic: Netnography as a Research Method Seminar Activity: Analyzing online communities and their cultural implications. Learning Objectives: Learn the foundations of netnography. Identify key aspects of online communities. Assignment: Choose an online community for research and begin initial observation. Week 4: Art-Based Research Methods Lecture Topic: Creative Approaches to Digital Culture Research Seminar Activity: Exploring art-based research through AI-generated content. Learning Objectives: Understand the principles of art-based research. Analyze digital culture through creative methodologies. Assignment: Create a brief artistic interpretation of digital content using an AI tool. Week 5: Ethical Considerations in Digital Research Lecture Topic: Ethics in Digital Research and AI Applications Seminar Activity: Case studies on ethical dilemmas in online and AI-based research. Learning Objectives: Recognize ethical challenges in digital culture research. Discuss solutions for ethical dilemmas in AI usage. Assignment: Write a reflective essay on ethical issues in a selected digital platform. Week 6: AI Prompt Writing – Introduction Lecture Topic: The Role of Prompts in AI Interaction Seminar Activity: Hands-on workshop on crafting effective AI prompts. Learning Objectives: Learn how AI responds to different types of prompts. Develop basic skills in prompt writing. Assignment: Write three prompts for use in a research study. Week 7: Research Design – Defining Research Questions Lecture Topic: Developing Research Questions and Hypotheses Seminar Activity: Group discussion on research questions related to digital culture. Learning Objectives: Formulate strong research questions for digital environments. Critically evaluate different approaches to research design. Assignment: Develop a research question related to a digital platform or AI application. Week 8: Data Collection in Digital Research Lecture Topic: Strategies for Collecting Data in Online Contexts Seminar Activity: Gathering and organizing data from digital sources. Learning Objectives: Learn different data collection methods in digital research. Practice organizing and preparing data for analysis. Assignment: Collect a small dataset from an online community or AI platform. Week 9: Data Analysis in Digital Culture Research Lecture Topic: Analyzing Digital Culture and AI-Generated Data Seminar Activity: Introduction to qualitative and quantitative analysis tools. Learning Objectives: Understand the basics of data analysis in digital research. Apply qualitative methods to analyze digital content. Assignment: Analyze the collected dataset using a selected method. Week 10: Interpreting Results and Writing the Research Report Lecture Topic: Presenting Findings from Digital Research Seminar Activity: Writing workshops to structure the research report. Learning Objectives: Learn how to present research findings effectively. Practice writing and structuring a research report. Assignment: Begin writing the research report based on your data analysis. Week 11: Presenting and Defending Research Findings Lecture Topic: Techniques for Presenting Research in Digital Studies Seminar Activity: Mock presentations and peer feedback. Learning Objectives: Develop presentation skills for defending research. Gain feedback on research presentation techniques. Assignment: Finalize the research report and prepare for the defense. Week 12: Final Exam – Defense of Research Report Activity: Oral defense of the research project. Learning Objectives: Demonstrate a thorough understanding of research methods. Defend the research findings clearly and logically. Assessment: Presentation and oral defense of the research report.
Teaching methods
Teaching Methods Lectures providing theoretical grounding. Seminars focused on discussion and application of research methods. Group activities and hands-on exercises in prompt writing and digital research. Art-based research projects exploring AI-generated content.
Assessment methods
Assessment Methods Research Project (70%): Conduct a research study during the semester, applying methods learned in class. Research Report (20%): Submit a written report detailing the research findings. Oral Defense (10%): Present and defend the research findings in the final exam.
Language of instruction
English
Further comments (probably available only in Czech)
The course can also be completed outside the examination period.
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