A project led by Prof. Min Wang in the Department of Human Development and Quantitative Methodology within the University of Maryland's College of Education is examining the relationship between socioeconomic status (SES), statistical learning (an intrinsic cognitive skill to detect probabilistic cues from environment), and reading development using a rigorous, two-wave longitudinal design among native Chinese-speaking children spanning ages 8–9 years. Research findings from the project, which is funded by the Grand Challenges Grants program, have educational implications for developing targeted statistical learning interventions to reduce SES disparities in literacy development in poor areas and regions across the world.
Dr. Wang has recently submitted a manuscript for review and publication entitled 'Statistical learning as a buffer: Investigating its impact on the link between home environment and reading achievement.' In this study, Dr. Wang’s team recruited a sample of 191 eight-year-old Chinese children from diverse SES backgrounds who completed assessments of vocabulary knowledge, language related skills, nonlinguistic visual and auditory statistical learning, Chinese written language related statistical learning, reading outcomes, nonverbal reasoning, and verbal working memory. The key finding from the study is that children who are better in written language statistical learning were less affected by SES disparities. Written language related statistical learning may mitigate the effects of lower SES on reading development. The study provides initial evidence regarding the potential role of language-specific statistical learning as a buffer against the impact of SES disparity on reading achievement.
Dr. Wang also has published two other studies related to this project:
Ren, J., Wang, M., Conway, C. M. (2024). Can explicit instruction boost statistical learning? A meta-analytical review. Journal of Educational Psychology,116(7), 1215–1237. https://doi.org/10.1037/edu0000897
Ren, J., & Wang, M. (2024). Contribution of statistical learning in reading across languages. PLoS ONE, 19(3), e0298670. https://doi.org/10.1371/journal.pone.0298670
In addition to these publications, Dr. Wang’s doctoral student Jinglei Ren, a key contributor to this Grand Challenges project, has recently received an offer for a post-doctoral position at the Haskins Laboratory at Yale University, starting January 2025, demonstrating a successful case of student training funded by this grant.
For more information, visit: https://research.umd.edu/ses-reading