My interests are in the areas of labor economics, program evaluation, and the economics of education. Currently my research focuses on college student debt accumulation and the subsequent risk of default, the effect of tuition subsidies on college attendance, the influence of family wealth on college attendance and completion, the effect of financial aid packages on college attendance, completion and subsequent labor market earnings, the influence of education on job displacement and subsequent earnings, the impact of unemployment insurance rules on unemployment durations and re-employment wages, and the determinants and consequences of repeat use of the unemployment insurance system.
Vu-Minh Chieu is an assistant research scientist at the GRIP (Geometry, Reasoning, and Instructional Practices) laboratory, directed by Patricio Herbst at the School of Education. Chieu’s research focuses on personalized learning, intelligent tutoring systems, computer-based simulations, human–computer interaction, and technology-enhanced professional learning. Chieu’s research aims at describing and explaining how theories of learning and instruction can be applied to the design of learning technologies as well as how technologies can be designed to build, test, and refine theories of learning and instruction. Patricio Herbst and Chieu has designed and developed LessonSketch (www.lessonsketch.org), a virtual lab that supports practice-based learning for mathematics teacher development. Chieu and his colleagues has been developing computational models and tools to support the collection of learners’ interaction with LessonSketch and with each other (e.g., their use of resources and tools in LessonSketch, contents they create, and logs of their forum discussions), to analyze the collected data (e.g., analysis of correlations between their use of resources and the quality of their discussions), and to use the analyzed data to inform the design of learning technologies as well as to personalize learning experiences for learners (e.g., the design of software features to improve the quality of forum discussions).
I am a data scientist, with extensive and various experience drawing inference from large data sets. In education research, I work to understand and improve postsecondary student outcomes using the rich, extensive, and complex digital data produced in the course of educating students in the 21st century. In 2011, we launched the E2Coach computer tailored support system, and in 2014, we began the REBUILD project, a college-wide effort to increase the use of evidence-based methods in introductory STEM courses. In 2015, we launched the Digital Innovation Greenhouse, an education technology accelerator within the UM Office of Digital Education and Innovation. In astrophysics, my main research tools have been the Sloan Digital Sky Survey, the Dark Energy Survey, and the simulations which support them both. We use these tools to probe the growth and nature of cosmic structure as well as the expansion history of the Universe, especially through studies of galaxy clusters. I have also studied astrophysical transients as part of the Robotic Optical Transient Search Experiment.