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:

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)

Makel, M. C., Peters, S. J., Lee, L. E., Stambaugh, T., McBee, M., McCoach, D. B., & Johnson, K. (2023, January 13). Effective identification through multiple criteria. https://doi.org/10.35542/osf.io/48nv7

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.