Teacher nominations of students are commonly used in gifted and talented identification systems to supplement psychometric measures of reasoning ability. In this study, second grade teachers were requested to nominate approximately one fourth of their students as having high learning potential in the year prior to the students’ participation in a randomized control trial of an advanced mathematics curriculum intervention. Treatment students completed researcher-developed unit pretests and posttests intended to measure higher order conceptual mathematical problem solving. Results from multilevel analyses indicate that third grade treatment students who were nominated during second grade significantly outperformed their un-nominated peers on these posttest measures, after controlling for students’ composite reasoning scores and pretest scores. This finding supports the view that teachers perceive student qualities beyond cognitive factors that facilitate student success with atypically challenging mathematics content, reinforcing prior recommendations to include teacher nominations as one component of gifted and talented identification systems.

Ashman, S. S., Vukelich, C. (1983). The effect of different types of nomination forms on teachers’ identification of gifted children. Psychology in the Schools, 20, 518-527.
Google Scholar | Crossref | ISI
Bandura, A. (1977). Social learning theory. Oxford, UK: Prentice Hall.
Google Scholar
Barber, C., Torney-Purta, J. (2008). The relation of high-achieving adolescents’ social perceptions and motivation to teachers’ nominations for advanced programs. Journal of Advanced Academics, 19, 412-443.
Google Scholar | SAGE Journals
Benjamini, Y., Hochberg, Y. (1995). Controlling the false discovery rate: A practical and powerful approach to multiple testing. Journal of the Royal Statistical Society. Series B (Methodological), 57, 289-300.
Google Scholar
Bianco, M., Harris, B., Garrison-Wade, D., Leech, N. (2011). Gifted girls: Gender bias in gifted referrals. Roeper Review, 33, 170-181.
Google Scholar | Crossref
Blalock, H. M. (1984). Contextual-effects models: Theoretical and methodological issues. Annual Review of Sociology, 10, 353-372.
Google Scholar | Crossref | ISI
Carman, C. A. (2011). Stereotypes of giftedness in current and future educators. Journal for the Education of the Gifted, 34, 790-812.
Google Scholar | SAGE Journals
Common Core State Standards Initiative . (2010). Common core state standards for mathematics. Retrieved from http://www.corestandards.org/Math/Practice
Google Scholar
Curby, T. W., Rudasill, K. M., Rimm-Kaufmann, S. E., Konold, T. R. (2008). The role of social competence in predicting gifted enrollment. Psychology in the Schools, 45, 729-744. doi:10.1002/pits.20338
Google Scholar | Crossref | ISI
Dai, D. Y. (2011). Hopeless anarchy or saving pluralism? Reflections on our field in response to Ambrose, VanTassel-Baska, Coleman, and Cross. Journal for the Education of the Gifted, 34, 705-730. doi:10.1177/0162353211416437
Google Scholar | SAGE Journals
Diamond, A., Barnett, W. S., Thomas, J., Munro, S. (2007). Preschool program improves cognitive control. Science, 318, 1387-1388.
Google Scholar | Crossref | Medline | ISI
Duckworth, A. L., Seligman, M. E. P. (2005). Self-discipline outdoes IQ in predicting academic performance of adolescents. Psychological Science, 16, 939-944.
Google Scholar | SAGE Journals | ISI
Enders, C. K., Tofighi, D. (2007). Centering predictor variables in cross-sectional multilevel models: A new look at an old issue. Psychological Methods, 12, 121-138. doi:http://dx.doi.org/10.1037/1082-989X.12.2.121.supp
Google Scholar
Fitz-Gibbon, C. T. (1974). The identification of mentally gifted, “disadvantaged” students at the eighth grade level. The Journal of Negro Education, 43, 53-66.
Google Scholar | Crossref
Gagné, F. (1994). Are teachers poor talent detectors? Comments on Pegnato and Birch’s (1959) study of the effectiveness and efficiency of various identification techniques. Gifted Child Quarterly, 38, 124-126.
Google Scholar | SAGE Journals | ISI
Gavin, M. K., Casa, T. M., Adelson, J. L., Carroll, S. R., Sheffield, L. J. (2009). The impact of advanced curriculum on the achievement of mathematically promising elementary students. Gifted Child Quarterly, 53, 188-202.
Google Scholar | SAGE Journals | ISI
Gavin, M. K., Casa, T. M., Adelson, J. L., Carroll, S. R., Sheffield, L. J., Spinelli, A. M. (2007). Project M3: Mentoring mathematical minds: A research-based curriculum for talented elementary students. Journal of Advanced Academics, 18, 566-585.
Google Scholar | SAGE Journals
Gear, G. H. (1976). Accuracy of teacher judgment in identifying intellectually gifted children: A review of the literature. Gifted Child Quarterly, 20, 478-490.
Google Scholar | SAGE Journals | ISI
Graziano, P. A., Reavis, R. D., Keane, S. P., Calkins, S. D. (2007). The role of emotion regulation in children’s early academic success. Journal of School Psychology, 45, 3-19.
Google Scholar | Crossref | Medline | ISI
Gubbins, E. J., McCoach, D. B., Foreman, J., Massicotte, C., Bruce-Davis, M., Rubenstein, L., . . . Waterman, C. (2013). What works in gifted education mathematics study: Impact of pre-differentiated and enriched curricula on general education teachers and their students [RM13242]. Storrs: University of Connecticut, The National Research Center on the Gifted and Talented.
Google Scholar
Hedges, L., Hedberg, E. C. (2007). Intraclass correlation values for planning group-randomized trials in education. Educational Evaluation and Policy Analysis, 29, 60-87.
Google Scholar | SAGE Journals | ISI
Hernández-Torrano, D., Prieto, M. D., Ferrándiz, C., Bermejo, R., Sáinz, M. (2013). Characteristics leading teachers to nominate secondary students as gifted in Spain. Gifted Child Quarterly, 57, 181-196.
Google Scholar | SAGE Journals | ISI
Hunsaker, S. L., Finley, V. S., Frank, E. L. (1997). An analysis of teacher nominations and student performance in gifted programs. Gifted Child Quarterly, 41, 19-24.
Google Scholar | SAGE Journals | ISI
Jarosewich, T., Pfeiffer, S. I., Morris, J. (2002). Identifying gifted students using teacher rating scales: A review of existing instruments. Journal of Psychoeducational Assessment, 20, 322-336.
Google Scholar | SAGE Journals | ISI
Kaplan, S. N. (2009). The grid: A model to construct differentiated curriculum for the gifted. In Renzulli, J. S., Gubbins, E. J., McMillen, K. S., Eckert, R. D., Little, C. A. (Eds.), Systems and models for developing programs for the gifted and talented (2nd ed., pp. 235-251). Mansfield Center, CT: Creative Learning Press.
Google Scholar
Lee, V. E. (2000). Using hierarchical linear modeling to study social contexts: The case of school effects. Educational Psychologist, 35, 125-141.
Google Scholar | Crossref | ISI
Leeson, P., Ciarrochi, J., Heaven, P. C. L. (2008). Cognitive ability, personality, and academic performance in adolescence. Personality and Individual Difference, 45, 630-635.
Google Scholar | Crossref | ISI
Lohman, D. F. (2003). The Woodcock–Johnson III and the Cognitive Abilities Test (Form 6): A concurrent validity study. Retrieved from http://faculty.education.uiowa.edu/docs/dlohman/CogAT_WJIII_final_2col-2r.pdf
Google Scholar
Lohman, D. F., Hagen, E. P. (2001). Cognitive Abilities Test (Form 6). Itasca, IL: Riverside.
Google Scholar
Lohman, D. F., Lakin, J. M. (2011). Intelligence and reasoning. In Sternberg, R. J., Kaufman, S. B. (Eds.), The Cambridge handbook of intelligence (pp. 419-441). New York, NY: Cambridge University Press.
Google Scholar | Crossref
McBee, M. T. (2006). A descriptive analysis of referral sources for gifted identification screening by race and socioeconomic status. The Journal of Secondary Gifted Education, 17, 103-111.
Google Scholar | SAGE Journals
McCoach, D. B., Gubbins, E. J., Foreman, J., Rambo, K. E., Rubenstein, L. D. (2014). Evaluating the efficacy of using pre-differentiated and enriched mathematics curricula for grade 3 students. Gifted Child Quarterly, 58(4), 272-286.
Google Scholar | SAGE Journals | ISI
Moon, T. R., Brighton, C. M. (2008). Primary teachers’ conceptions of giftedness. Journal for the Education of the Gifted, 31, 447-480.
Google Scholar | SAGE Journals
National Association for Gifted Children . (2014). Gifted by state. Retrieved from http://www.nagc.org/resources-publications/gifted-state
Google Scholar
National Council of Teachers of Mathematics . (2000). Principles and standards for school mathematics. Reston, VA: Author.
Google Scholar
Neber, H. (2004). Teacher identification of students for gifted programs: Nominations to a summer school for highly-gifted students. Psychology Science, 46, 348-362.
Google Scholar
Neisser, U., Boodoo, G., Bouchard, T. J., Boykin, A. W., Brody, N., Ceci, S. J., . . . Urbina, S. (1996). Intelligence: Knowns and unknowns. American Psychologist, 51, 77-101.
Google Scholar | Crossref | ISI
Neuenschwander, R., Cimeli, P., Röthlisberger, M., Roebers, C. M. (2013). Personality factors in elementary school children: Contributions to academic performance over and above executive functions? Learning and Individual Differences, 25, 118-125. doi:http://dx.doi.org/10.1016/j.lindif.2012.12.006
Google Scholar
O’Connor, M. C., Paunonen, S. V. (2007). Big five personality predictors of post-secondary academic performance. Personality and Individual Differences, 43, 971-990.
Google Scholar | Crossref | ISI
Pegnato, C. W., Birch, J. W. (1959). Locating gifted children in junior high schools: A comparison of methods. Exceptional Children, 25, 300-304.
Google Scholar | SAGE Journals | ISI
Peterson, J. S. (1999). Gifted—Through whose cultural lens? An application of the postpositivistic mode of inquiry. Journal for the Education of the Gifted, 22, 354-383.
Google Scholar | SAGE Journals | ISI
Peugh, J. L., Enders, C. K. (2005). Using the SPSS mixed procedure to fit cross-sectional and longitudinal multilevel models. Educational and Psychological Measurement, 65, 717-741. doi:10.1177/0013164405278558
Google Scholar | SAGE Journals | ISI
Pressey, S. L. (1926). Simple apparatus which gives tests and scores, and teaches. School and Society, 23, 373-376.
Google Scholar
Raudenbush, S. W., Bryk, A. S. (2002). Hierarchical linear models: Applications and data analysis methods. In Leeuw, J. D. (Series Ed.), Advanced quantitative techniques in the social sciences (2nd ed.). Thousand Oaks, CA: Sage.
Google Scholar
Renzulli, J. S., Delcourt, M. A. B. (1986). The legacy and logic on the identification of gifted persons. Gifted Child Quarterly, 30, 20-23.
Google Scholar | SAGE Journals | ISI
Renzulli, J. S., Reis, S. M. (1994). Research related to the schoolwide enrichment triad model. Gifted Child Quarterly, 38, 7-20.
Google Scholar | SAGE Journals | ISI
Renzulli, J. S., Reis, S. M. (1997). The schoolwide enrichment model: A how-to guide for educational excellence (2nd ed.). Mansfield, CT: Creative Learning Press.
Google Scholar
Renzulli, J. S., Smith, L. H., White, A. J., Callahan, C. M., Hartman, R. K., Westberg, K. L., . . .Sytsma, R. E. (2004). Scales for rating the behavioral characteristics of superior students. Technical and administration manual (3rd ed.). Mansfield, CT: Creative Learning Press.
Google Scholar
Rosenthal, R., Jacobson, L. (1968). Pygmalion in the classroom. The Urban Review, 3, 16-20.
Google Scholar | Crossref
Schoenfeld, A. H. (2006). What doesn’t work: The challenge and failure of the What Works Clearinghouse to conduct meaningful research of studies of mathematics curricula. Educational Researcher, 35, 13-21.
Google Scholar | SAGE Journals
Schroth, S. T., Helfer, J. A. (2008). Identifying gifted students: Educator beliefs regarding various policies, processes, and procedures. Journal for the Education of the Gifted, 32, 155-179.
Google Scholar | SAGE Journals
Siegle, D., Moore, M., Mann, R. L., Wilson, H. E. (2010). Factors that influence in-service and preservice teachers’ nominations of students for gifted and talented programs. Journal for the Education of the Gifted, 33, 337-360.
Google Scholar | SAGE Journals
Siegle, D., Powell, T. (2004). Exploring teacher biases when nominating students for gifted programs. Gifted Child Quarterly, 48, 21-29.
Google Scholar | SAGE Journals | ISI
Skinner, B. F. (1958). Teaching machines. Science, 128, 969-977. doi:10.1126/science.128.3330.969
Google Scholar | Crossref | Medline | ISI
Stockford, S. M. (2009). Meta-analysis of intraclass correlation coefficients from multilevel models of educational achievement (Unpublished doctoral dissertation). Arizona State University, Phoenix.
Google Scholar
Tomlinson, C. A., Jarvis, J. M. (2009). Differentiation: Making curriculum work for all students through responsive planning and instruction. In Renzulli, J. S., Gubbins, E. J., McMillen, K. S., Eckert, R. D., Little, C. A. (Eds.), Systems and models for developing programs for the gifted and talented (2nd ed., pp. 599-628). Mansfield Center, CT: Creative Learning Press.
Google Scholar
Tong, Y., Kolen, M. J. (2010). Scaling: An ITEMS module. Educational Measurement: Issues and Practice, 29, 39-48.
Google Scholar | Crossref
Tuttle, F. B., Becker, L. A., Sousa, J. A. (1988). Characteristics and identification of gifted and talented students (3rd ed.). Washington, DC: National Education Association.
Google Scholar
Vygotsky, L. S. (1978). Mind in society: The development of high psychological process. Cambridge, MA: Harvard University Press.
Google Scholar
Worrell, F. C., Olszewski-Kubilius, P., Subotnik, R. F. (2012). Important issues, some rhetoric, and a few straw men: A response to comments on “Rethinking Giftedness and Gifted Education.” Gifted Child Quarterly, 56, 224-231. doi:10.1177/0016986212456080
Google Scholar | SAGE Journals | ISI
View access options

My Account

Welcome
You do not have access to this content.



Chinese Institutions / 中国用户

Click the button below for the full-text content

请点击以下获取该全文

Institutional Access

does not have access to this content.

Purchase Content

24 hours online access to download content

Your Access Options


Purchase

JOA-article-ppv for $36.00