Courses
UX Research Methodology
(GSI7560-01) | English
This course provides a comprehensive introduction to user experience (UX) and human–computer interaction (HCI) research methodologies and techniques. Students will learn how to plan and conduct UX research, analyze data, and effectively present their findings. The curriculum covers a range of methods including user interviews, surveys, observations, field research, personas, user scenarios, low- and high-fidelity prototyping, and user testing. In addition, students will develop skills in communicating research results, writing research papers, and responding to peer reviews to refine their work. By the end of the course, each student will complete a UX/HCI paper on a topic of their choice.
Understanding Digital Cultural Content
(GSI7468-01-00) | Korean
Digital cultural content refers to expressions created or shared using digital technologies, encompassing a wide variety of forms, such as artworks, music, films, video games, digital art, webcomics, podcasts, and social media content. The use of generative AI technology is heralding significant changes in the production, consumption, and impact of digital cultural content. This course explore digital cultural content and investigate the potential uses of generative AI in this field. Ultimately, the course aims to design digital cultural content services using UX methodologies based on generative AI.
Generative AI Application
(GSI7689-01-00) | Korean
This course aims to provide a foundational understanding of generative AI and its practical applications across various professional tasks. Students will begin by examining the core concepts and history of artificial intelligence, followed by an in-depth look at contemporary issues in generative AI, including Large Language Models (LLMs), in-context learning, prompt engineering, LangChain, retrieval-augmented generation (RAG), and fine-tuning. Building on this theoretical grounding, students will then gain hands-on experience using leading generative AI tools—such as ChatGPT, MidJourney, Stable Diffusion, Flux, and Runway—to create and manipulate text, images, and videos. Through these practical exercises, participants will learn how to apply generative AI technologies in their own professional or research contexts, ultimately gaining insight into the real-world value and impact of AI-driven solutions.
UX Design and Strategic Management
(CTM2005-01-00) | English
This course provides a comprehensive introduction to UX design, focusing on core concepts and methods while also exploring how they can be integrated into broader business strategies. Students will learn about user research, prototyping, and usability testing, as well as strategic management principles for overseeing UX design projects from planning to implementation. By the end of the course, participants will have a solid foundation in both UX design principles and IT service management, enabling them to create products and services that effectively align user needs with business objectives. This course is ideal for anyone aiming to pursue a career in UX design or to enhance their expertise in this rapidly evolving field.
AI-UX Seminar
(GSI7336) | English
This seminar-style course delves into the intersection of AI and UX, examining how these two fields can be seamlessly integrated to develop more effective, efficient, and user-centered AI products and services. Students will engage in critical discussions on a range of core topics, including the foundational principles of AI-UX design, the distinctive characteristics of AI systems, and best practices for personalizing AI-driven experiences. The curriculum also covers the ethical and moral considerations surrounding the use of AI in UX, as well as the emerging role of generative AI technologies. Each week, students will present and discuss exemplary CHI papers relevant to these themes, ultimately progressing their own research to produce and present an academic paper by the end of the course.
Data Driven UX
(GSI7444) | Korean
This course offers a comprehensive exploration of statistical concepts and theories commonly applied in UX and HCI research, with a strong emphasis on practical implementation using Python. Students will begin by mastering foundational Python skills for data processing, cleaning, and visualization. Building on these basics, they will learn to conduct a variety of statistical tests—ranging from descriptive analysis to more advanced inferential methods—and interpret the results within the context of UX and HCI. In addition, the course includes reviews of research papers that demonstrate how these methods are used in published studies, guiding students in designing and executing analyses for their own research. By the end of the semester, participants will be able to plan and carry out robust data analyses specifically tailored to their UX or HCI projects, equipping them with the tools to make data-driven decisions and contribute meaningful insights in academic or professional settings.
Generative AI UX
(GSI7468-01-00) | English
This course provides a foundational exploration of generative AI and UX, combining theoretical concepts with practical exercises. Students will begin by gaining a solid understanding of generative AI models and their underlying mechanisms, followed by an introduction to text-, image-, and video-based generative technologies. Practical assignments will involve hands-on work with commercially available tools such as ChatGPT, DALL·E, MidJourney, and Runway, demonstrating real-world applications in both everyday and professional contexts.
Building on this technical groundwork, the course will examine critical issues in AI-UX design, including autonomy, interaction modalities, legal and intellectual property considerations, anti-discrimination measures, and broader ethical responsibilities. Students will also present relevant research papers and collaborate on a team project that produces creative works using generative AI. By the end of the course, participants will be well-equipped to harness the power of generative AI responsibly and user-centrically, combining technical expertise with ethical awareness.