Faculty Profiles

Dr. Yi-Hsin Chen

Professor, educational measurement and research

chen headshot

Email: ychen5@usf.edu
Office: 新澳门六合彩内幕信息Tampa campus, EDU 362
Curriculum Vitae

Yi-Hsin Chen is a Professor of Educational Measurement and Research. Dr. Chen's primary research focuses are in the following related areas:

  • Applications of cognitive psychometric models (e.g., generalized DINA, LCDM, RUMM) which incorporate cognitive information into psychometric models.
  • Exploration of validating approaches (e.g., DIF, internal and external score validity) for Q-matrices and cognitive diagnostic profiles.
  • Examination of accuracy and precision of robust statistical approaches for traditional t-tests and ANOVA tests.
  • Applications of multilevel modeling (MLM) approaches (e.g., IRT, Rasch, and SEM) to achievement data and psychological data.

Dr. Chen's work has been published in Journal of Educational Measurement, Educational and Psychological Measurement, International Journal of Testing, Journal of Experimental Education, Journal of Modern Applied Statistical Methods, and Educational Research and Evaluation as well as in Monograph series.

TEACHING

  • EDF 6432: Foundations of Measurement (Online)
  • EDF 6407: Statistical Analysis for Educational Research I (Online)
  • EDF 7439: Item Response Theory
  • EDF 7469: Computer-Based Testing
  • EDF 7436: Rasch Models

Selected Publications 

Warrican, S. J., Alleyne, M., Smith, P., Esperat, T., Zaidi, R., Chen, Y.-H., & Yin, Y. (2021, Accepted). Cultural alloys and heterogenous mixes: Contextualized and comparative language differences in the literacy assessment of U.S. and Canadian youth. Research in Comparative and International Education. [Impact Factor: 1.50]

Chen, Y.-J., Chen, Y.-H., Anthony, J., & Erazo, N. (2021, Accepted). Evaluation of the computer-based orthographic processing assessment: An application of cognitive diagnostic modeling. Journal of Psychoeducational Assessment.

Cao, C., Kim, E. S., Chen, Y.-H., & Ferron, J. (2021). Examining the impact of and sensitivity of fit indices to omitting covariates interaction effects in multilevel MIMIC models. Educational and Psychological Measurement, 81(5), 817-846. [SSCI, SCIE | 2018IF = 2.21 | 2018SJR = 1.747 | Q1]

Yi, Z., Chen, Y.-H. Yin, Y., Cheng, K., Wang, Y., Nguyen, D. T., Pham, T., & Kim, E. S. (2020; OnlineFirst). Brief research report: A comparison of robust tests for homogeneity of variance in factorial ANOVA. The Journal of Experimental Education. [SSCI | 2019IF:2.107 | 2019SJR:1.28 | h-index:54 | Q1]

Wu, Y.-J., Kiefer, S., & Chen, Y.-H. (2020). The relationships of learning strategies with self-efficacy and mathematics performance: A cross-cultural comparison. International Journal of School and Educational Psychology, 8(S1), 91-103.  [2018IF: 1.64 | 2019SJR: 0.34 | h-index:11 | Q2]

Pham, T., Kromrey, J. D., Chen, Y.-H., Nguyen, D. T., Kim, E. S., & Wang, Y., (2020). ANOVA_Robust: A SAS庐 macro for various robust approaches to testing mean differences in one-factor ANOVA models. Journal of Statistical Software, 95, Code Snippet 2. [SCIE | 2018IF = 10.30 | 2018SJR = 17.569 | Q1]

Recent Presentations

 

Rosengrant, D., Matthews, G., Feldman, A., Chen, Y.-H., & Alsultan, J. (2021 August). Preliminary results on a video-based force concept inventory. Physics Education Research Conference, Poster. Virtual Format.

Yin, Y., Chen, Y.-H., & Dedrick, R. (2020, April). Exploring the moderation effects of technology on Gender DIF of reading comprehension. NCME Annual Meeting, Poster. San Francisco, California.

Chen, Y.-H., Yi, Z., & Thompson, D. R. (2020, April). Investigating attribute hierarchical relations with multilevel mediation measurement modeling. NCME Annual Meeting, Paper Session. San Francisco, California.

Hsu, C.-L., Wu, Y.-J., & Chen, Y.-H. (2020, April). Exploring skill hierarchical relationships of the van Hiele theory: An application of diagnostic classification modeling. AERA Annual Meeting, Poster Session. San Francisco, CA.

Cao, C., Kim, E., Chen, Y.-H., & Ferron, J. M. (2020, April). Exploring the impact of omitting covariates interaction effect in multilevel multiple indicators, multiple causes (MIMIC) models. AERA Annual Meeting, Paper Session. San Francisco, CA.