“One of my greatest challenges is to synthesize two types of research approach—theory-driven research and data-driven research— and utilize their strengths in my research.”
Some individuals enjoy finding ways to challenge their breadth of knowledge and range of experience. Meet Ya Mo. She is a Research Associate at NISS working on projects that involve data associated with the National Council of Education Statistics (NCES). She is one of those individuals.
Before pursuing graduate studies in the U.S. Ya was a lecturer at Hunan University of Technology in China where she taught English language to Chinese college students. While she received awards for her outstanding teaching, more importantly, her teaching experience spurred her to learn more about teaching. Attending Boston University on a merit-based fellowship to obtain a Master’s degree in Teaching English to Speakers of Other Languages (TESOL) gave her this chance to understand more about pedagogy. From there she accepted a fellowship opportunity to engage in further graduate studies at Michigan State University (MSU). It was at MSU that her interest in statistics began while taking graduate-level quantitative methods classes.
“I kept hearing the phrase, “… assuming a normal distribution …”. While I was amazed by what statistics could do, I also wondered why we made those assumptions."
This curiosity drove her complete a Master’s degree in Statistics, and later combined this with her interests and experience in teaching and learning into a dual PhD in Quantitative Methods and Measurement, and Curriculum, Instruction and Educational Policy.
This led to five years as a research assistant conducting research on connections between reading and writing for students’ struggling in elementary schools in the U.S., as well as researching the alignment between writing standards and writing assessments in all 50 states and how that alignment can predict student performance in NAEP writing assessments. She also examined the alignment between content standards and professional standards for Michigan teachers as an intern with the Michigan Department of Education.
Prior to writing her dissertation, she also pursued research on how English writing prompts impacted English as a Second Language (ESL) students’ writing performance. Using discourse analysis, she examined several states’ writing assessment prompts in terms of their cohesion, specificity, and cultural accommodation. She also explored the National Assessment of Educational Progress (NAEP) prompts and their impact on the writing performance of ESL students and native English speakers through quantitative methods like t-tests, ANCOVA, and logistic regression, and through psychometric measures, such as Differential Item Functioning (DIF). This study won the Midwest Association of Language Testers (MwALT) Graduate Student Award for Excellence in Language Assessment Research.
Her dissertation research examined constructs of writing proficiencies in state and national assessments in the U.S. through content analysis of writing prompts and rubrics; predicted students’ writing performance on the National Assessment of Educational Progress (NAEP) from assessment variations using Hierarchical Linear Modeling (HLM); and explored genre demands in state writing assessments through syntactic analysis of writing prompts and content analysis of rubrics and state standards.
Now at NISS since 2015, she conducts research on quantitative methods, psychometric measures, and survey statistics. She also applies quantitative research methods to study substantive topics in education using National Center of Education Statistics (NCES) restricted-use datasets. As one example of this work, she analyzed data from the 2011 ECLS-K assessments to investigate factors from students’ demographic backgrounds and their relationship to students’ academic performance in reading and math by the spring of their kindergarten year and also their relationship with the gains made in each subject during the kindergarten year.
“Statistics provide tools for me to examine interesting phenomena in education. One of my research interests is in large-scale assessments. It requires an understanding of assessment, measurement, educational statistics, and survey statistics, so statistics are at the core of the knowledge and skills that I need to examine large-scale assessments.”
Ya Mo has developed into a circumspect researcher who recognizes that to move forward she often needs to bring together additional areas of understanding.
When she is not involved in her research Ya enjoys reading, watching a movie, hiking, relaxing on the beach or exploring restaurants trying new foods. She has backpacked in 11 countries in Europe and has visited 28 states in the U.S.!
“I appreciate all the opportunities that NISS has given me to learn and to grow as a researcher as well as allowing me to apply my knowledge and skills to study interesting educational phenomena.”