Yaacov Petscher, Ph.D.

Yaacov Petscher, Ph.D.

Contact Information

Office Location
2010 Levy Avenue | Suite 100 | Tallahassee, FL 32310
Associate Director
Associate Professor of Social Work
Deputy Director, National Comprehensive Center to Improve Literacy for Students with Disabilities

EDUCATION

  • Ph.D., 2009, Florida State University; Developmental Psychology
  • M.S., 2005, Florida State University; Measurement and Statistics
  • M.S., 2004, Florida State University; Educational Psychology
  • B.S., 2001, Florida State University, Psychology

 

PEER REVIEWED ARTICLES

Petscher, Y., & Koon, S. (in press). Moving the needle on multivariate screening: Comparisons between machine learning and logistic regression. Assessment for Effective Intervention.

Petscher, Y., Justice, L., & Hogan, T. (in press). Modeling the early language trajectory of language development when the measures change and its relation to poor reading comprehension. Child Development.

Al Otaiba, S., Petscher, Y., Wanzek, J., Lan P, & Rivas, B. (in press). I?m not throwing away my shot: What Alexander Hamilton can tell us about standard reading interventions. Learning Disabilities Research and Practice.

Catts, H.W., & Petscher, Y. (in press). Early identification of dyslexia: Current advancements and future directions. Perspectives.

Petscher, Y., Foorman, B.R., & Truckenmiller, A.J. (2017). The impact of item dependency on the efficiency of testing and reliability of student scores from a computer adaptive assessment of reading comprehension. Journal of Research on Educational Effectiveness, 10, 408-423. Doi: 10.1080/19345747.2016.1178361.

Petscher, Y., Al Otaiba, S., Wanzek, J., Rivas, B., & Jones, F. (2017). The relation between global and specific growth mindset with elementary school students? reading performance. Scientific Study of Reading, 21, 376-391.

Petscher, Y., Quinn, J., & Wagner, R.K. (2016). Modeling the co-development of correlated processes with longitudinal and cross-construct effects. Developmental Psychology, 52, 1690-1704. Doi: 10.1037/dev0000172.

Petscher, Y. (2016). Do our means of inquiry match our intentions? Frontiers in Psychology, 7. Doi: 10.3389/fpsyg.2016.01048.

Petscher, Y. Mitchell, A., & Foorman, B.R. (2015). Improving the precision of student scores from assessments by using response times: An illustration of conditional item response theory. Reading and Writing, 28, 31-56. DOI: 10.1007/s11145-014-9518-z.

 

BOOKS PUBLISHED

Cummings, K.D., & Petscher, Y. (Eds.). (2016). The fluency construct. New York: Springer.

Petscher, Y., Schatschneider. C., & Compton, D.L. (Eds). (2013). Applied quantitative analysis in education and social sciences. New York: Routledge.

 

SELECTED GRANTS

Co-Principal Investigator, Reach Every Reader Project, Chan Zuckerberg Initiative; Subcontract to Harvard University. January 1, 2018-December 31, 2022. Total award: $30 million. Principal Investigator Elizabeth City.

Co-Principal Investigator, What Does it Take to Develop Writing Skills for Spanish-speaking English learners? A Longitudinal Examination of Co-development of Language, Reading, and Writing Skills, Institute of Education Sciences; Subcontract to University of California - Irvine. July 1, 2018-June 30, 2021. Total award: $1.4 million. Principal Investigator Young-Suk Kim.

Co-Principal Investigator, Improving Response to Intervention in Students With or At-Risk of Reading Disabilities, National Institute of Child Health and Human Development Subcontract to Vanderbilt University. August 2017-May 2021. Total award: $2.2 million. Principal Investigator Jeanne Wanzek.

Co-Principal Investigator, National Comprehensive Center to Improve Literacy for Students with Disabilities, Office of Special Education Research and Rehabilitative Services; Subcontract to University of Oregon: $1.6 million. October 2016-September 2021. Total award: $7.5 million. Principal Investigator Hank Fien.

 

RESEARCH INTERESTS

Applied Quantitative Methods Research Design Psychometrics Reading and Language Development Screening and Identification Computer Adaptive Testing