1. Associate Professor
  2. Educational Psychology & Methodology
Email Addresss.dai@wsu.edu
LocationCleveland Hall 354
Phone509-335-0958
Website

Biography

Shenghai Dai, Ph.D.

Google Scholar || Research Gate || LinkedIn

Research Interests

My research interests primarily focus on investigating the performance and utility of current and emerging measurement frameworks that can provide formative and diagnostic information about student learning and achievement in various assessment settings. Particularly, I am interested in both methodological and applied aspects of (multidimensional) item response theory models, cognitive diagnostic models (CDMs), subscore reporting, differential item functioning (DIF), and large-scale assessment. I am also interested in applying statistical methods, such as missing data analysis, structural equation modeling, machine learning, and (longitudinal) multilevel modeling in broad educational and psychological contexts. Currently, I am the director of the WSU Large-Scale Data (LSD) Laboratory.

Education

  • Ph.D., Inquiry Methodology, Indiana University Bloomington
  • M.S., Applied Statistics, Indiana University Bloomington
  • M.A., Language Testing, Beijing Language and Culture University
  • B.A., Teaching Chinese as a Second Language, Beijing Language and Culture University

Teaching

  • ED RES 565 Quantitative Research
  • ED PSYCH 508 Educational Statistics
  • ED PSYCH 511 Classical and Modern Test Theory
  • ED PSYCH 512 Data Management & Visualization
  • ED PSYCH 569 Multivariate Data Analysis
  • ED PSYCH 576 Factor Analytics Procedures
  • ED PSYCH 577 Item Response Theory
  • ED PSYCH 578 Advanced Item Response Theory
  • ED PSYCH 579 Large-Scale Surveys in Education
  • ED PSYCH 581 Machine Learning Applications in Education

Professional Positions

Selected Accomplishments

Peer-Reviewed Journal Articles (* with students)
  • Measurement & Psychometrics
    • *Zheng, X., Dai, S., Kirakosian, A.T. (2026). When the sandwich makes you hesitate, replicate: On sampling variance estimation of multilevel models under complex sample design. Large-scale Assessment in Education, 14 (14). https://doi.org/10.1186/s40536-026-00285-y.
    • *Ramazan, O., Dai, S., & Danielson, R. (2025). Exploring validity evidence for mathematics self-concept of adolescents: Key findings from PISA 2022. Journal of Psychoeducational Assessment, Advanced online publication. https://doi.org/10.1177/07342829251333844 
    • *Vo, T., Dai, S., & French, B.F. (2024). Black girls’ mathematics and science identities using large-scale assessment and survey data: A QuantCrit framework. Methods in Psychology, 11, 100158. https://doi.org/10.1016/j.metip.2024.100158
    • Danielson, R.W., Gale, M.S., Dai, S., Seyranian, V., Heddy, B., Marsh, J., & Polikoff, M.S. (2023). The development and validation of the elementary activity interest measure. Journal of Experimental Education, 93(2), 396–418. https://doi.org/10.1080/00220973.2023.2276933
    • Svetina Valdivia, D. & Dai, S. (2023). Number of response categories and sample size requirements in polytomous IRT models. Journal of Experimental Education. 92 (1), 154-185. https://doi.org/10.1080/00220973.2022.2153783
    • *Kehinde, O.J., Dai, S., French, B. (2022). Item parameter estimation for multidimensional graded response model under complex structure. Frontiers in Education – Assessment, Testing and Applied Measurement. 7, 947581. https://www.frontiersin.org/articles/10.3389/feduc.2022.947581
    • Dai, S. & Svetina Valdivia, D. (2022). Dealing with missing responses in cognitive diagnostic modeling. Psych. 4(2), 318-341. https://doi.org/10.3390/psych4020028.
    • *Dai, S., Vo, T., Kehinde, O.J., He, H., Xue, Y., Demir, C., & Wang, X. (2021). Performance of polytomous IRT models with rating scale data: An investigation over sample size, instrument length, and missing data. Frontiers in Education – Assessment, Testing and Applied Measurement. 6, 721963. https://www.frontiersin.org/articles/10.3389/feduc.2021.721963
    • Dai, S. (2021). Handling missing responses in psychometrics: Methods and software. Psych. 3(4), 673-693. https://doi.org/10.3390/psych3040043.
    • Svetina, D., Dai, S., & Wang, X. (2017). Use of cognitive diagnostic model to study differential item functioning in accommodations. Behaviormetrika, 44(2), 313-349. doi:10.1007/s41237-017-0021-0.
  • Education
    • Ardasheva, Y., Dai, S., & Kangas, S. (2025). Opportunity gap at the intersection of language, disability, and science. Science Education, 110(2), 400-417. https://doi.org/10.1002/sce.70011
    • *Taylor, J.P., Ramazan, O., Whittenburg, H.N., Sheftel, A., & Dai, S. (2025). Career and technical educational experiences and career trajectories of youth with disabilities: An examination of High School Longitudinal Study data. Career and Technical Education Research.
    • Kangas, S., Dai, S., & Ardasheva, Y. (2024). The Intersection of language and disability: Progress of English learners with disabilities on NAEP reading. The Journal of Special Education, 58(2), 88-99. https://doi.org/10.1177/00224669231213054
    • *Ramazan, O., Dai, S., Danielson, R., Ardasheva, Hao, T., & Y. Austin, B., (2023). Students’ 2018 PISA reading self-concept: Identifying predictors and examining model generalizability for emergent bilinguals. Journal of School Psychology. 101, 101254. https://doi.org/10.1016/j.jsp.2023.101254.
    • *Dai, S., Hao, T., Ardasheva, Y., Ramazan, O., Danielson, R., & Austin, B. (2023). PISA reading achievement: Identifying predictors and examining model generalizability for multilingual students. Reading and Writing. 36, 2763–2795. https://doi.org/10.1007/s11145-022-10357-4
    • *Zhang, X., Dai, S., & Ardasheva, Y. (2020). Contributions of (de)motivation, engagement, anxiety in English listening and speaking. Learning and Individual Differences, 79, 101856. https://doi.org/10.1016/j.lindif.2020.101856
  • Psychology
    • *Luna, K., Dai, S., Pagan, C., Liu, C., & Schmitter-Edgecombe, M. (2025). Examining intra-individual variability of ecological momentary assessment with multilevel modeling: A systematic review and recommendations for research and practice. The Clinical Neuropsychologist. Advance online publication. https://doi.org/10.1080/13854046.2025.2592660.
    • *Rahman, S., Dai, S., Libon, D.J., Woo, E., & D. Schmitter-Edgecombe, M. (2025). Cutoffs of the instrumental activities of daily living – compensation (IADL-C) scale for identification of functional limitations consistent with mild cognitive impairment and dementia. Archives of Clinical Neuropsychology, 40 (6), 1101-1111. https://doi.org/10.1093/arclin/acaf028.
    • *Schmitter-Edgecombe, M., Luna, C., Beech, B., Dai, S., & Cook, D. (2025). Capturing cognitive capacity in the everyday environment across a continuum of cognitive decline using a smartwatch n-back task and ecological momentary assessment. Neuropsychology, 39(1), 28–43. https://doi.org/10.1037/neu0000984. [APA Editor’s Choice selection].
    • *Schmitter-Edgecombe, M., Luna, C., Dai, S., & Cook, D. (2024). Predicting daily cognition and lifestyle behaviors for older adults using smart home data and ecological momentary assessment. The Clinical Neuropsychologist, 1-25. https://doi.org/10.1080/13854046.2024.2330143.
    • * Dai, S., Kehinde, O.J., Schmitter-Edgecombe, M., & French, B. (2023). Modeling daily fluctuations in everyday cognition and health behaviors at general and person-specific levels: A GIMME analysis. Behaviormetrika. 50, 563-583. https://doi.org/10.1007/s41237-022-00191-x
  • Kinesiology
    • Catena, R.D., Dai, S., Allaire, B.T., Occhino, A., Banks, J.J., & Anderson, D.E. (2025). Obesity as a moderator of lumber spine posture change during pregnancy. Gait & Posture. Advanced online publication. https://doi.org/10.1016/j.gaitpost.2025.08.063
    • Stewart, B.C., Dai, S., Havens, K., Eggleston, J.D., Bagwell, J., Deering, R.E., Little, E.E., & Catena, R. (2023). Determining fall risk change throughout pregnancy: The accuracy of postpartum survey and relationship to fall efficacy. Ergonomics, 68(1), 85–94. https://doi.org/10.1080/00140139.2023.2296827
Book
  • Finch, W. H., French, B. F., Immekus, J., & Dai, S. (2025). Educational and psychological measurement (2nd ed.). Routledge. www.routledge.com/9781032575230
Software Packages
Contracts, Grants, & Funding
  • 2025-2027, Statistician/Senior Personnel, Real-time dynamics of stress, promotive factors, and academic and mental health outcomes among racially/ethnically minoritized students during the transition to high school, PI: C. Liu. Spencer Research Grant. Amount requested: $49,976.
  • 2025-2029, Co-Principal Investigator & Program Evaluator, Certifying and advancing multilingual teachers by increasing numbers through three grow-your-own strands (CAMINOS). PI: Y. Ardasheva. Department of Education Office of English Language Acquisition – National Professional Development Grant. Amount: $3,067,509.
  • 2023-2024, Statistician, Creating adaptive, wearable technologies to assess and intervene for individuals with ADRDs. PI: Schmitter-Edgecombe, M. National Institute on Aging (#R35 AG071451), 2021-2026, Amount: $4,590,000.
  • 2023-2024, Statistician, Multi-modal assessment and intervention for functional independence. PI: Schmitter-Edgecombe, M. National Institute on Aging (#R01 AG065218), 2020-2025, Amount: $2,992,391.