About Us

 
About Us

ABOUT US

 

Optimal Identification represents a fusion of several strands of prior work on student identification done by several team members. This work includes:

  • development of a mathematical framework and software tools for modeling and calculating identification system performance
  • alternative norm or comparison groups, including local norms and building norms
  • identification-to-service alignment
  • access for underrepresented gifted students (e.g., low-income, students of color, rural).

Taken together, these approaches illustrate how it is possible to:

  • fundamentally improve the gifted identification process
  • minimize assessment costs
  • improve alignment between identification and services
  • dramatically improving sensitivity
  • reduce disproportionality across race and income categories

We refer to this concept as “Optimal Identification” because it can be shown mathematically that no other two-stage identification process achieves higher performance or cost efficiency.

 

See our current team's work:

Stambaugh, T., Lee, L. E., Makel, M., Peters, S., & Johnson, K. R. (2024). How Does Your Identification System Measure Up? A Guide to Applying the CASA Criteria to Gifted and Talented Identification Systems. Gifted Child Today, 47(4), 246–259. https://doi.org/10.1177/10762175241263983

Peters, S. J., Makel, M. C., Lee, L. E., Stambaugh, T., McBee, M. T., McCoach, D. B., & Johnson, K. R. (2024). What Makes for an Effective Gifted and Talented Screener? Gifted Child Today, 47(2), 98-107. https://doi.org/10.1177/10762175231222301

Makel, M. C., Peters, S. J., Lee, L. E., Stambaugh, T., McBee, M. T., McCoach, D. B., & Johnson, K. R. (2024). Effective Identification Through Multiple Criteria. Gifted Child Today, 47(2), 108-118. https://doi.org/10.1177/10762175231222300

Peters, S. J., Stambaugh, T., Makel, M. C., Lee, L. E., McBee, M. T., McCoach, D. B., & Johnson, K. R. (2023). The CASA Criteria for evaluating gifted and talented identification systems: Cost, alignment, sensitivity, and access. Gifted Child Quarterly, 67(2), 137–150. https://doi.org/10.1177/00169862221124887 (see preprint here)

Lee, L. E., & Peters, S. J. (2022). Universal screening: A process to promote equity. In S. Johnsen, & J. VanTassel-Baska (Eds.), Handbook on Assessments for Gifted Learners. Prufrock Press.

See prior work:

McBee, M. T., Peters, S. J., & Waterman, C. (2014). Combining scores in multiple-criteria assessment systems: The impact of combination rule. Gifted Child Quarterly, 58(1), 69–89. https://doi.org/10.1177/0016986213513794

McBee, M. T., Peters, S. J., & Miller, E. M. (2016). The impact of the nomination stage on gifted program identification: A comprehensive psychometric analysis. Gifted Child Quarterly, 60(4), 258–278. https://doi.org/10.1177/0016986216656256

Peters, S. J., Gentry, M., Whiting, G. W., & McBee, M. T. (2019). Who Gets Served in Gifted Education? Demographic representation and a call for action. Gifted Child Quarterly, 63(4), 273–287. https://doi.org/10.1177/0016986219833738

Peters, S. J., Makel, M. C., & Rambo-Hernandez, K. (2021). Local norms for gifted and talented student identification: Everything you need to know. Gifted Child Today, 44(2), 93–104. https://doi.org/10.1177/1076217520985181

Peters, S. J., Matthews, M. S., McBee, M. T., & McCoach, D. B. (2014). Beyond gifted education: Designing and implementing advanced academic programs. Prufrock Press.

Peters, S., Rambo-Hernandez, K.E., Makel, M., Matthews, M., & Plucker, J., (2018). The effect of local norms on racial and ethnic representation in gifted education. AERA Open, 5(2), 1-18. https://files.eric.ed.gov/fulltext/EJ1220745.pdf

Stambaugh, T., & Olszewski-Kubilius, P. (2020). Unlocking potential: Identifying and serving gifted students from low-income households. Routledge.

Lee, L. E., Rinn, A. N., & Rambo-Hernandez, K. E. (2024). What Happens After Nomination? Evaluating the Probability of Gifted Identification With the Torrance Test of Creative Thinking. Gifted Child Quarterly, 68(2), 119-136. https://doi.org/10.1177/00169862231222886

MEET THE OPTIMAL ID TEAM

Kiana Johnson

Kiana R. Johnson, Ph.D., MSEd, MPH

East Tennessee State University

Associate Professor

Lindsay Lee

Lindsay Lee, Ph.D.

East Tennessee State University

Assistant Research Professor

Matthew Makel

Matthew C. Makel, Ph.D.

John Hopkins University

Associate Research Professor

Matthew McBee

Matthew T. McBee, Ph.D.

SMG

VP of Research & Analytics

Betsy McCoach

D. Betsy McCoach, Ph.D.

University of Connecticut

Professor

Scott Peters

Scott J. Peters, Ph.D.

HMH

Senior Research Scientist

Tamra Stambaugh

Tamra Stambaugh, Ph.D.

Whitworth University

Associate Professor

 

 

This work was supported by a grant from the U.S. Department of Education (award number S206A200007 – 21) as part of the Jacob K. Javits Gifted and Talented Students Education Program. The contributors to this site include Kiana Johnson, Lindsay Lee, Matt Makel, Matthew McBee, Betsy McCoach, Scott Peters, & Tamra Stambaugh.