Explore our programs — offering exceptional academic preparation, opportunities for growth, and the tools to make an impact.
Find everything you need to apply for and finance your graduate education.
Stories, strategies, and actionable knowledge — putting HGSE's powerful ideas into practice.
With deep expertise that connects research, practice, and policy, HGSE faculty are leaders in the field.
Get to know our community — and all the ways to learn, collaborate, connect, develop your career, and build your network.
Faculty-led programs to deepen your impact and build your effectiveness as an educator and leader.
Access the premiere education subject library for Harvard University.
Access the Office of Student Affairs, the Office of the Registrar, Career Services, and other key resources.
Explore opportunities to grow, build connections, and create change.
Ed.D., Harvard University, (2002)
James Kim is an expert on literacy intervention and experimental design. His professional mission is to conduct a systematic program of policy relevant research in literacy that focuses on improving outcomes for low-income students and struggling readers. He leads the READS Lab (Research Enhances Adaptations Designed for Scale in Literacy), a research-based collaborative initiative to identify and scale adaptive solutions for improving children’s literacy learning opportunities and outcomes. As part of the Reach Every Reader (RER) Initiative, the READS Lab is partnering with practitioners in the Charlotte-Mecklenburg Schools (CMS) and researchers at the MIT Integrated Learning Initiative (MITili) and Florida State University to improve Kindergarten to Grade 3 reading outcomes. His current research priority is to understand how building children’s domain knowledge and reading engagement can foster long-term improvements in reading comprehension. He serves on the editorial boards of Reading Research Quarterly, the Journal of Educational Psychology, and the Journal of Research on Educational Effectiveness. Prior to graduate school, he was a middle school U.S. history teacher.
Click here to see a full list of James Kim's courses.
Personalized learning is an emerging movement in education, generating both optimism and skepticism in the field. We are optimistic because of the enormous possibilities implicit in helping every learner reach his or her full potential by leveraging advances in technology, but we also recognize challenges to large-scale change due to the thin evidence base and constraining policy and practice environments. We share with many in education a deep commitment to the principles of equity and excellence motivating much of the move to personalized learning. Building on a joint planning process begun in January 2017, the Harvard Graduate School of Education (HGSE) and MIT are pleased to submit this proposal for a $30 million joint initiative to improve early literacy through personalized diagnosis and intervention. Because we believe that personalized learning will take root and expand only if it can make demonstrable progress in addressing pressing education challenges, we will focus on applying principles of personalization toward the goal that all children achieve mastery of foundational literacy skills by the end of third grade.
Dr. Kim will be directing the evaluation of the core knowledge program and helping postdocs and research assistants run the impact analyses. Specifically, he will work with the PI and core project staff to develop an analysis plan, direct the evaluation of the efficacy of the Core Knowledge Language Arts Listening and Learning Read Aloud Program, articulate the fully specified multi-level models used to estimate treatment impacts on child-level vocabulary, listening comprehension and domain knowledge outcomes, and guide the secondary analyses that examine whether the quality of read alouds mediate treatment effects on child outcomes and the baseline, child-level moderators of treatment effects. A research assistant will be supervised by Dr. Kim and will be responsible for organizing a student-level data set that will be used for the impact analyses, cleaning the data set at each wave of data collection, monitoring and reporting attrition across waves, and conducting descriptive analyses to check for baseline equivalence, attrition across waves, and posttest differences on the child-level outcomes. Dr. Kim will train the RA to follow the principles outlined in Scott Longs The Workflow of Data Analysis Using Stata to ensure that data files are organized to produce replicable results.