Do Won Kwak
Korea University · Social Sciences
About the Lab
Professor Do Won Kwak's research lab specializes in applied econometrics, service innovation, and educational technology, with a strong focus on evaluating the impact of policy interventions and technological innovations—particularly artificial intelligence and blended learning—on educational outcomes and organizational performance. The lab conducts rigorous empirical studies using experimental designs, panel data analysis, and causal inference methods to understand how AI and educational reforms affect student learning, teacher adaptability, and institutional effectiveness. Current research also explores the role of gender composition in educational settings and the long-term impacts of international development assistance programs.
Research Overview
Research Output Trend
Figures are computed from collected data and may differ slightly.
Selected Papers
15Despite a rising interest in artificial intelligence (AI) technology, research in services marketing has not evaluated its role in helping firms learn about customers’ needs and increasing the adaptability of service employees. Therefore, the authors develop a conceptual framework and investigate whether and to what extent providing AI assistance to service employees improves service outcomes. The randomized controlled trial in the context of tutoring services shows that helping service employee
This paper assesses quantitatively the impact on student performance of a blended learning experiment within a large undergraduate first‐year course in statistics for business and economics students. We employ a difference‐in‐differences method, which controls for differences in student characteristics and course delivery method, to evaluate the impact of blended learning on student performance. Our results suggest that the impact of blended learning on student performance depends on whether the
Abstract We examine the conditional logit estimator for binary panel data models with unobserved heterogeneity. A key assumption used to derive the conditional logit estimator is conditional serial independence (CI), which is problematic when the underlying innovations are serially correlated. A Monte Carlo experiment suggests that the conditional logit estimator is not robust to violation of the CI assumption. We find that higher persistence and smaller time dimension both increase the magnitud
To separately identify the effects of single-sex "schooling" versus single-sex "schools", we exploit two unusual experiments in South Korea: students are randomly assigned to academic high schools within districts regardless of school types, and some schools changed their types from single-sex to coeducational over time. While the overall effects of attending a single-sex school are positive for both boys and girls, these are driven by the differences in resources between school types, rather th
Many students enrolled in first year introductory statistics courses believe learning statistics is a waste of time and fear they will fail. In this study, we explored the impacts on learning outcomes for students in an introductory statistics course by allowing students to arbitrarily choose their own sequence of learning from three key learning activities, namely tutorials, Peer-Assisted Study Sessions and Computer-Managed Learning quizzes. Unlike the old regime where the learning activities f
Precisely measuring the impact of official development assistance (ODA) programs is considered important, however, it has been a challenge for practitioners and politicians because of the lack of available data. While the Korea International Cooperation Agency (KOICA) Master’s Degree Scholarship (MDS) Program has run for many years, a formal system to assess its impact remains undeveloped. Thus, we evaluate the MDS program’s effect on participants’ individual outcomes (e.g. promotion, salary inc
Research Areas
Dive deeper into Do Won Kwak's research on Nubint
Open this lab's papers in the app to read with AI, summarize, and cite in your writing.