Ming Ming Chiu
Learning and Instruction
- Analysis of complex data sets (Big Data)
- Social metacognition in group processes of students and teachers
- Ecological models of social stratification
- Statistical Discourse Analysis
- Ph.D., Mathematics Education, University of California, Berkeley, 1996
- Ed.M., Interactive Technology, Harvard University, 1990
- B.S., Computer Science, magna cum laude, Columbia University, 1988
Ming Ming Chiu studies classroom conversations and inequality mechanisms with advanced statistics. Specifically, he examines how teachers' and classmates' social metacognitive processes affect classroom conversations. To analyze these conversations, he invented a statistical discourse analysis method. In addition, he studies inequality mechanisms that reduce the learning of both rich and poor students.
Much research has focused on individual metacognitive processes (planning, monitoring progress, and evaluating ideas) rather than social metacognitive processes. Using his theoretical framework of individual actions during social interactions, Chiu showed how algebra teachers' and classmates' metacognitive actions improved students' creation of correct, new ideas (micro-creativity) and group problem solving. Building on this theoretical framework, he plans to examine how teachers' and classmates' evaluations of ideas, questions, and uses of formal and informal mathematics language might also influence students' thinking and learning during classroom discussions.
Furthermore, Chiu invented a statistical discourse analysis method (Dynamic Multilevel Analysis or DMA) that he used to model student actions, identify watershed events, and test for differences across time periods, students, teachers, and classrooms. Specifically, he uses DMA to model how recent sequences of teacher and student actions (micro-time context) influence the characteristics of each student action at each conversation turn. Using DMA, he can also identify watershed events (breakpoints) that radically change the classroom conversation, and divide it into significantly different time periods. For example, three types of breakpoints (creative ignitors, creative dampeners, and on-task ↔ off-task transitions) divided students' group problem solving processes into high and low micro-creativity time periods. Lastly, DMA can test whether the effects differ across time periods, students, teachers, or classrooms.
Many studies have shown that greater economic inequality widens the mathematics achievement gap among the richest and the poorest students. Extending this line of research, Chiu has shown that three types of inequality (family inequality, school inequality, and schoolmate inequality) reduced both rich and poor students' learning in 41 countries. Next, he plans to examine the inequality mechanisms responsible for these results. Possible candidates include weaker student solidarity, fewer educational resources, weaker student discipline, and diminishing marginal returns. He is testing these hypotheses on primary school and high school students in other countries, using several large international data sets (e.g., PIRLS, PISA).
Funded by 23 grants totaling over $ 4 million, he disseminated his research through 126 academic publications (including 69 journal articles), 15 radio interviews and broadcasts, 3 TV broadcasts, and 146 news articles in 20 countries and regions. His work has also been recognized through many awards (e.g., Young Researcher 2005, National Academy of Education post-doctoral fellowship, 2000).
View selected articles by Dr. Chiu
- Flowing toward correct contributions during group problem solving: A statistical discourse analysis
- Adapting teacher interventions to student needs during cooperative learning: How to improve student problem solving and time on-task
- A new method for analyzing sequential processes: Dynamic multilevel analysis
- Group problem-solving processes: Social interactions and individual actions
- Effects of argumentation on group micro-creativity: statistical discourse analyses of algebra students' collaborative problem solving
- Effects of resources, inequality, and privilege bias on achievement: Country, school, and student level analyses
- Families, economies, cultures, and science achievement in 41 countries: Country-, school-, and student-level analyses
- Universals and specifics in learning strategies: Explaining adolescent mathematics, science, and reading achievement across 34 countries
- Gender, context, and reading: A comparison of students in 43 countries
- Leadership for social justice in Hong Kong schools: Addressing mechanisms of inequality