For more details on the courses, please refer to the Course Catalog
| Code | Course Title | Credit | Learning Time | Division | Degree | Grade | Note | Language | Availability |
|---|---|---|---|---|---|---|---|---|---|
| SIC5033 | Using big data to address social and cultural inequality | 3 | 6 | Major | Master/Doctor | - | No | ||
| Thiscoursereviewsthesocialinnovationresearchinwhichmachinelearningtechniquesareusedasaprimaryempiricaltoolforanalysis.Topicsincludeequalityofopportunity,education,health,environment,criminaljustice,andpossiblyothersdependingonthecharacteristicsofclass.Inthecontextofthesetopics,thecourseprovidesanintroductiontobasicdataanalytictechniquesandmachinelearningmethods,includingregressionanalysis,quasi-experimentalmodeling,artificialneuralnetworks,andtree-basedmethods. | |||||||||
| SIC5034 | Hierarchical Linear Modeling | 3 | 6 | Major | Master/Doctor | 2-8 | English | Yes | |
| The purpose of this course is to develop the skills necessary to identify an appropriate technique, estimate models, and interpret results for independent research and to critically evaluate contemporary social research using hierarchical linear modeling. Social research focuses on issues that examine the relationship between individuals and the social contexts in which they work, live, or learn. This involves multilevel research, which investigates individuals within groups. In multilevel research, the nature of the data structure is hierarchical. For example, in educational research, the data typically consists of schools and pupils within these schools. In this example, pupils are nested within schools. When analyzing multilevel data, we need special statistical skills and techniques, because single-level analysis of multilevel data brings about misleading standard errors and significance tests. The hiearchical linear modeling addresses this issue, accurately dealing with a hierarchical data set, often individuals within groups. This course will be applied in the sense that we will focus on estimating models and interpreting the results, rather than understanding in detail the mathematics behind the techniques. | |||||||||
| SIC5035 | Multivariate Regression Analysis | 3 | 6 | Major | Master/Doctor | 1-8 | Korean | Yes | |
| Introduction to data analysis via linear models. Topics include basic assumptions of the linear model, methods for transforming data, estimation and interpretation of the classical linear model, derivations of the estimators of interest, and diagnostics of results and/or potential fixes for violations of assumptions. This course lays the foundations for more advanced statistical modeling techniques used in data science and academic research. | |||||||||
| SIC5036 | Consumer Health Behavior | 3 | 6 | Major | Master/Doctor | 1-8 | Korean | Yes | |
| This course introduces theoretical models that can predict and evaluate consumers' behaviors in health and analyzes empirical studies applied these models. This course aims to find a way to improve consumer health empowerment applied to theoretical health models. First, this course evaluates the appropriateness of the theoretical models in recent health-related studies, such as the Health Belief Model, Risk Perception Attitude Framework, Optimal Bias, Knowledge-Attitude-Practice (KAP), and Dunning-Kruger Effect. Second, this course seeks to apply these health-related theoretical models to improve consumer health empowerment. Finally, this course suggests implications for consumer health policy and education based on consumer health behavior analysis. | |||||||||
| SIC5037 | Studies on Digital Environment and Distribution in Consumer Markets | 3 | 6 | Major | Master/Doctor | 1-8 | - | No | |
| Understanding the characteristics of diverse online & offline distribution structures in the consumer markets, learning the effects of distribution innovations on consumer behavior, and further investigating how distribution is managed to extend consumer benefits in the digital era. | |||||||||
| SIC5038 | Longitudinal Categorical Data Analysis | 3 | 6 | Major | Master/Doctor | 1-8 | Korean | Yes | |
| This course will cover the foundations of longitudinal categorical data. Upon successful completing of this course, students will be able to (a) understand the types of hypotheses and research questions for which categorical data analytical produces are used, (b) perform number of cross sectional and longitudinal analytical procedures including regression with binary, ordinal, and multinomial outcomes, survival analysis, (first- and second-order) growth curve modeling with categorical data, and (c) read and evaluate research articles regarding testing of for which cross-sectional and longitudinal categorical data analytcial procedures are used. The course topics are as follows: Review of basic regression model. Introduction to Logistic and Profit Regression. Introduction to Count Data. Introduction to Latent Growth Model. Latent Class (Transition) Model. Growth Mixture Model with categorical data. Introduction to Survival Analysis. | |||||||||
| SIC5039 | Information security and privacy | 3 | 6 | Major | Master/Doctor | Korean | Yes | ||
| This course covers security-related theory, real-world security-related practices such as passwords, and trends in information security technology to help students learn about realistic threats and countermeasures. Students understand the importance of privacy and security and learn the ethical aspects of being socially responsible when using IT. The course is participatory, with research and case presentations. | |||||||||
| SIC5040 | Understanding Problem Solving Techniques | 3 | 6 | Major | Master/Doctor | Korean | Yes | ||
| This course provides an overview of data structures, algorithms, and system design for solving computing problems based on solving algorithmic and system design problems. To solve computing problems, students should have an understanding of basic programming techniques that use simple data structures to analyze and process data, as well as an understanding of high-level programming techniques that use complex data structures and high-level algorithms. This course aims to improve students' understanding of methodologies for solving computing problems through the process of '1) problem analysis, 2) analysis of advantages and disadvantages of methodologies, and 3) discussion of performance and results' by selecting algorithmic problems appropriate to the level and technique. In addition, the course introduces big data processing platforms such as clouds and data centers, and system problems that may occur in the process of performing big data processing, and discusses the design of big data processing systems to solve them. This course aims to improve students' understanding of the computing technologies utilized in the implementation of such systems, and to acquire a methodology to increase efficiency through an analytical approach when planning and developing new systems. | |||||||||
| SOC4009 | Sociology of Sustainable Development | 3 | 6 | Major | Bachelor/Master | Sociology | - | No | |
| This course deals with a sociological approach to international development cooperation, especially focusing on official development assistance (ODA) from the standpoint of sustainable development goals(SDGs). We seek to examine theoretical and methodological foundations of the sociological understanding of international development cooperation and to explicate the major theoretical and practical issues involving the planning, delivery, outcome, and assessment of ODA. Among others, the major issues include philosophical debates on the concept of development, the diffusion of international development norms, aid-effectiveness, development and public opinion, the aid delivery structure, development contents, clarifying determinants of ODA, managing priority countries, and the assessment of aid-effectiveness. | |||||||||
| SOC4010 | Artificial Intelligence and Human Rights | 3 | 6 | Major | Bachelor/Master | 1-4 | Sociology | Korean | Yes |
| This course aims to explore the development of AI and its positive and negative impacts on human rights. It further aims to explore and suggest desirable human rights and normative standards for the new digital age. AI is seen as a double-edged sword in that the associated technologies could enhance human conditions and the livelihood of the marginalized but they also serve as catalysts for worsening the digital gap, gender inequality, and algorithmic bias. This course explores various AI models employing machine learning and deep learning techniques for improving human rights, and also surveys the studies demonstrating the biases within AI and the ways of detecting and minimizing them. This course will help students broaden their understanding of human rights standards for an inclusive and sustainable future of the intelligent and information society. | |||||||||
| SOC5002 | Classical Sociological Theory | 3 | 6 | Major | Master/Doctor | 1-4 | Sociology | Korean | Yes |
| The main purpose of this course is to review classical sociological theories. Major theories to be covered in this course include Comte, Spencer, Marx, Weber, Durkheim, Simmel, Pareto and such structural-functional theorists as Parsons and Merton. | |||||||||
| SOC5021 | Seminar in Sociology of Culture | 3 | 6 | Major | Master/Doctor | 1-4 | Sociology | Korean | Yes |
| This course deals with major up-to-date theoretical discussions and empirical results concerned with Sociology of Culture in terms of intensive discussions and independent researches. | |||||||||
| SOC5057 | sociology of aging | 3 | 6 | Major | Master/Doctor | 1-4 | Sociology | - | No |
| This course is designed to give students insight into the social construction of the aging process and being "old" by exploring the social dimensions of aging. The question is, how do social factors influence the ways our bodies age and grow old? How do they shape the consequences of this? As we explore these thematic questions, you will come to appreciate the wide diversity among individuals whom we term "elderly persons,” and how this diversity is social in nature. To help instill the social character of aging, and to further your understanding of the aging process, cross-cultural comparisons will be made where possible. | |||||||||
| SOC5061 | Elementary/Intermediate Statistics | 3 | 9 | Major | Master/Doctor | Sociology | Korean | Yes | |
| This class provides the Graduate-level, social-science majoring students with a variety of Elementary and Intermediate levels of statistics, besides Advanced statistics, which include descriptive and a variety of inferential statistics (e.g., z-test, t-test, χ2-test, F-test, Simple Regression, Multiple Regression, Logistic Regression, etc.). | |||||||||
| SOC5062 | Factor Analysis / Covariance Structure Analysis | 3 | 9 | Major | Master/Doctor | Sociology | - | No | |
| This class provides the Graduate-level, social-science majoring students with a variety of Advanced Statistics (besides Elementary & Intermediate Statistics), which includes, most importantly, Factor Analysis (EFA & CFA) and Covariance Structure Analysis. | |||||||||