For more details on the courses, please refer to the Course Catalog
| Code | Course Title | Credit | Learning Time | Division | Degree | Grade | Note | Language | Availability |
|---|---|---|---|---|---|---|---|---|---|
| MCJ5122 | Network Analysis for Communication Research | 3 | 6 | Major | Master/Doctor | 1-4 | Media and Communication | Korean | Yes |
| The primary goal of this course is to explore theories and concepts of network analysis in communication perspectives. Moreover, this course will practice with data and network analysis programs to show how network analysis can be used to understand various communication phenomena and problems. | |||||||||
| MCJ5128 | Meta-Analysis | 3 | 6 | Major | Master/Doctor | 2-4 | Media and Communication | - | No |
| Meta-analysis refers to the quantitative analysis of study outcomes. Meta-analysis consists of a collection of techniques that attempt to analyze and integrate effect sizes (indices of the association between an independent variable and a dependent variable) that accrue from research studies. This course deals with the process of performing meta-analysis and how to interpret analysis results. Students will have an opportunity to conduct meta-analysis on research topics of interest using meta-analysis software and to write a research paper based on the analysis results. | |||||||||
| PAD3018 | Civil Society and Governance | 3 | 6 | Major | Bachelor | 3-4 | Public Administration | Korean | Yes |
| This course studies increasing roles of civil society in democratic governance. It reviews changes in government and civil society under pressures civil society demands of globalization and participatory democracy. The role of NGO?NPO in local, national, and global governance will be focused to understand new governance. | |||||||||
| PHL2010 | Philosophy of Science | 3 | 6 | Major | Bachelor | 2-3 | Philosophy | - | No |
| It seeks to show wherein scientific rationality lies; what is distinctive about its explanations and theoretical constructions; what marks it off from guesswork and pseudo-science and makes its predictions and technologies worthy of confidence; whether its theories can be taken to reveal the truth about a hidden objective reality. | |||||||||
| PSD2013 | Study of Korea Politics | 3 | 6 | Major | Bachelor | 2-3 | Political Science and Diplomacy | Korean | Yes |
| In this course, students study Korean government and politics by emphasizing the confluence of historical legacies, institution and international environments. Topics include the nature of the traditional state, impact of colonialism, influences of U. S. A, and Japan, political culture, political parties and elections, congress and bureaucracy. | |||||||||
| PSD5113 | Future Social Risks and Political Theory | 3 | 6 | Major | Master/Doctor | Political Science | Korean | Yes | |
| This course diescusses the new developments in future, the risks they bring about and proper strategies for coping with them. The topics include the climate changes, natural disastors, demographic changes, new discoveries and developments in sciences and technologies and their impacts on our society. The goal of this course is to deliberate on how to react to those changes and challenges properly, which may determine the tufure of individual societies as well humankind. | |||||||||
| PSD5120 | Data Science and Study in Political Science) | 3 | 6 | Major | Master/Doctor | 1-4 | Political Science | - | No |
| The scientific study of political science has been one of the most noted fields that so-called `big data revolution’ and a rapid development in computational approaches have changed the way we understand our world. This course aims at introducing fundamental techniques of data science from a social science perspective, with a focus on political science. In this course, we will discuss a set of cutting-edge methods related to data science, including text analysis/mining, network analysis, machine learning, information extraction methods and data visualization techniques. We will then shift to an in-depth discussion on how to apply them to various research topics in politics such as political behavior, the roles of media and interest groups, and more. Students will also learn basic data analysis tools using R programming language or Python through problem sets. | |||||||||
| PSY3006 | Group Dynamics | 3 | 6 | Major | Bachelor | 3-4 | Psychology | Korean | Yes |
| Group psychology studies how people think, feel, and behave in groups. This course aims to promote students' understanding of key concepts and theories of small group processes. This course emphasizes the dynamic nature of group processes by reviewing major research topics such as group structure and development, task performance and decision making in groups, conflict within and between groups, and social influence. Students will perform various in-class group activities, from which they will develop deeper understanding of group process and gain insights into how to improve group outcomes. | |||||||||
| PSY4007 | Multivariate analysis and statistical learning | 3 | 6 | Major | Bachelor/Master | Psychology | - | No | |
| This course covers principles and practice of multivariate data analysis in psychology and related fields. Applications of multiple regression, logistic regression, principal component analysis, factor analysis, cluster analysis and other multivariate techniques for psychological research will be illustrated. In addition, supervised learning and unsupervised learning will be discussed in relation to the multivariate techniques. This course is designed for graduate students or 3rd- or 4th-year undergraduate students in psychology. | |||||||||
| PSY5136 | Structural Equation Modeling and Related Methods | 3 | 6 | Major | Master/Doctor | 1-4 | Psychology | - | No |
| This course is an introduction to structural equation modeling(SEM) which is quite broad and deep as a multivariate method. Students are required to understand the basic theory of SEM and to analyze multivariate data with hypotheses of linear structural relations. Also they are trained to be able to understand published articles demonstrating use of SEM as the major analytic method. | |||||||||
| PSY5188 | Structural Equation Modeling | 3 | 6 | Major | Master/Doctor | Psychology | Korean | Yes | |
| This course covers fundamentals of latent variable modeling, path analysis, and structural equation modeling, combining theoretical and practical perspectives. The course is designed to provide details of structural equation modeling, from the statistical underpinnings to how to conduct various types of structural equation analyses. | |||||||||
| SIC5005 | Methods in Sociological Research | 3 | 6 | Major | Master/Doctor | Convergence for Social Innovation | Korean | Yes | |
| Survey of methods and techniques of empirical research in sociology. Topics include the nature of scientific knowledge, principles and techniques of measurement, sample survey, experimental designs, and other research procedures and techniques. | |||||||||
| SIC5011 | Collaborative Research Workshop | 3 | 6 | Major | Master/Doctor | Convergence for Social Innovation | Korean | Yes | |
| Individual research project on closing multiple gaps including economic gap, health/life cycle gap, and AI information technology gap. The topic will be determined under the guidance of an advisor. | |||||||||
| SIC5012 | Social Innovation Convergence Internship | 3 | 6 | Major | Master/Doctor | Convergence for Social Innovation | Korean | Yes | |
| This course is intended to teach students how to translate knowledge learned from the first two semesters to social innovation practices. Students will learn methods for applying theoretical knowledge to real-world industrial settings and making decisions using information. | |||||||||
| SIC5020 | Longitudinal Data Analysis | 3 | 6 | Major | Master/Doctor | Convergence for Social Innovation | - | No | |
| This course covers empirical frameworks for drawing causal inferences from longitudinal data. Topics include longitudinal study design, exploring longitudinal data, random effects and fixed effects models; and quasi-experimental research design such as diff-in-diffs regression, propensity score matching, and regression discontinuity design. | |||||||||