The purpose of this study was to extend the research on the Tests of Early Numeracy Curriculum-Based Measurement (TEN-CBM) tools by examining concurrent and predictive relations from kindergarten through third grade. Using a longitudinal sample of 535 students, this study included logistic regression, latent cluster, and latent transition analyses to examine the patterns and trends of student performance on all four TEN-CBM measures in kindergarten and first grade, math CBM (M-CBM) in first grade, and mathematics performance on a statewide high-stakes assessment in third grade. Results suggest that two of the TEN-CBM tools, Quantity Discrimination and Missing Number, are most robust at predicting later math performance. Longitudinal analysis indicated that students who are low performing in early numeracy at the beginning of kindergarten tend to be low performing in math at third grade. Low-achieving students also demonstrated a greater decrease in math skills over summer months when compared to higher-achieving peers.

Baglici, S. P., Codding, R., Tryon, G. (2010). Extending the research on the Tests of Early Numeracy: Longitudinal analyses over two school years. Assessment for Effective Intervention, 35, 89102. doi:10.1177/153450840934605310.1177/1534508409346053
Google Scholar | SAGE Journals
Baldi, S., Jin, Y., Skemer, M., Green, P., Hergert, D., Xie, H. (2007). Highlights from PISA 2006: Performance of the U.S. 15-year-old students in science and mathematics literacy in an international context. Washington, DC: National Center for Education Statistics, Institute of Education Sciences, U.S. Department of Education.
Google Scholar
Chard, D. J., Clarke, B., Baker, S., Otterstedt, J., Braun, D., Katz, R. (2005). Using measures of number sense to screen for difficulties in mathematics: Preliminary findings. Assessment for Effective Intervention, 30, 314. doi:10.1177/07372477050300020210.1177/073724770503000202
Google Scholar | Crossref
Clarke, B., Baker, S., Smolkowski, K., Chard, D. J. (2008). An analysis of early numeracy curriculum-based measurement: Examining the role of growth in student outcomes. Remedial and Special Education, 29, 4657. doi:10.1177/074193250730969410.1177/0741932507309694
Google Scholar | SAGE Journals | ISI
Clarke, B., Shinn, M. R. (2004). A preliminary investigation into the identification and development of early mathematics curriculum-based measurement. School Psychology Review, 33, 234248.
Google Scholar | ISI
Clements, D. H. (2004). Major themes and recommendations. In Clements, D. H., Sarama, J. (Eds.), Engaging young children in mathematics: Standards for early childhood mathematics education (pp. 776). Mahwah, NJ: Lawrence Erlbaum.
Google Scholar
Clements, D. H., Sarama, J. (2009). Learning and teaching early math: The learning trajectories approach. Florence, KY: Routledge.
Google Scholar
Cooper, H., Nye, B., Charlton, K., Lindsay, J., Greathouse, S. (1996). The effects of summer vacation on achievement test scores: A narrative and meta-analytic review. Review of Educational Research, 66, 227268. doi:10.3102/0034654306600322710.3102/00346543066003227
Google Scholar | SAGE Journals | ISI
DiStefano, C., Kamphaus, R. W. (2006). Investigating subtypes of child development: A comparison of cluster analysis and latent class cluster analysis in typology creation. Educational and Psychological Measurement, 66, 778794. doi:10.1177/001316440528403310.1177/0013164405284033
Google Scholar | SAGE Journals | ISI
Duncan, G. J., Claessens, A., Huston, A. C., Pagani, L.S., Engel, M., Sexton, H., . . . Duckworth, K. (2007). School readiness and later achievement. Developmental Psychology, 43, 14281446.
Google Scholar | Crossref | Medline | ISI
Enders, C. K. (2010). Applied missing data analysis. New York: Guilford.
Google Scholar
Foegen, A., Jiban, C., Deno, S. (2007). Progress monitoring in mathematics: A review of the literature. Journal of Special Education, 41, 121139. doi:10.1177/0022466907041002010110.1177/00224669070410020101
Google Scholar | SAGE Journals | ISI
Fuchs, L. S., Fuchs, D., Hosp, M. K., Hamlett, C. L. (2003). The potential for diagnostic analysis within curriculum-based measurement. Assessment for Effective Intervention, 28, 1322. doi:10.1177/07372477030280030310.1177/073724770302800303
Google Scholar | Crossref
Gersten, R., Chard, D. (1999) Number sense: Rethinking arithmetic instruction for students with mathematical disabilities. Journal of Special Education, 3, 1829. doi:10.1177/00224669990330010210.1177/002246699903300102
Google Scholar | SAGE Journals | ISI
Indiana Department of Education . (2010). 2010-2011 ISTEP+ program manual: Policies and procedures for Indiana’s assessment system. Retrieved from http://www.doe.in.gov/assessment/docs/ProgramManual.pdf
Google Scholar
Kaplan, D. (2008). An overview of Markov chain methods for the study of stage-sequential developmental processes. Developmental Psychology, 44, 457467. doi:10.1037/0012-1649.44.2.45710.1037/0012-1649.44.2.457
Google Scholar | Crossref | Medline | ISI
Kidd, J. K., Pasnak, R., Gadzichowski, M., Ferral-Like, M., Gallington, D. (2008). Enhancing early numeracy by promoting the abstract thought involved in the oddity principle, seriation and conservation. Journal of Advance Academics, 19, 164200.
Google Scholar | SAGE Journals
Lanza, S. T., Flaherty, B. P., Collins, L. M. (2003). Latent class and latent transition analysis. In Schinka, J. A., Velicer, W. F. (Eds.), Handbook of psychology: Research methods in psychology (Vol. 2, pp. 663685). Hoboken, NJ: Wiley.
Google Scholar | Crossref
Lee, J., Grigg, W., Dion, G. (2007). The nation’s report card: Mathematics 2007. Washington, DC: National Center for Education Statistics, Institute of Education Sciences, U.S. Department of Education.
Google Scholar
Lubke, G. H., Muthén, B. O. (2007). Performance of factor mixture models as a function of model size, covariate effects, and class-specific parameters. Structural Equation Modeling, 14, 2647. doi:10.1207/s15328007sem1401_210.1207/s15328007sem1401_2
Google Scholar | Crossref | ISI
Martínez, R. S., Missall, K. M., Graney, S. B. K., Aricak, T., Clarke, B. (2009). Technical adequacy of early numeracy curriculum-based measurement in kindergarten. Assessment for Effective Intervention, 34, 116125. doi:10.1177/153450840832620410.1177/1534508408326204
Google Scholar | SAGE Journals
Mazzocco, M. M. M., Thompson, R. E. (2005). Kindergarten predictors of math learning disability. Learning Disabilities Research & Practice, 20, 142155. doi:10.0000/j.1540-5826.2005.00129.x10.0000/j.1540-5826.2005.00129.x
Google Scholar | Crossref | Medline
McKelvey, R. D., Zavoina, W. (1975). A statistical model for the analysis of ordinal level dependent variables. Journal of Mathematical Sociology, 4, 103120. doi:10.1080/0022250X.1975.998984710.1080/0022250X.1975.9989847
Google Scholar | Crossref | ISI
Muthén, B. O. (2001). Latent variable mixture modeling. In Marcoulides, G., Schumacker, R. (Eds.), New developments and techniques in structural equation modeling (pp. 133). Mahwah, NJ: Lawrence Erlbaum.
Google Scholar
Muthén, L. K., Muthén, B. O. (2010). Mplus user’s guide (6th ed.). Los Angeles CA: Author.
Google Scholar
National Council for Teachers of Mathematics . (2006). Curriculum focal points for prekindergarten through grade 8 mathematics: A quest for coherence. Reston, VA: author.
Google Scholar
National Mathematics Advisory Panel . (2008). Foundations for success: The final report of the National Mathematics Advisory Panel. Washington, DC: U.S. Department of Education.
Google Scholar
Olson, J. F., Martin, M. O., Mullis, I. V. S. (Eds.). (2008). Trends in international mathematics and science study 2007 technical report. Chestnut Hill, MA: TIMSS & PIRLS International Study Center, Boston College.
Google Scholar
Perie, M., Grigg, W., Dion, G. (2005). The nation’s report card: Mathematics 2005 (NCES 2006-453). U.S. Department of Education, National Center for Education Statistics. Washington, DC: U.S. Government Printing Office.
Google Scholar
Shinn, M. R. (2004). Administration and scoring of Mathematics Computation Curriculum-Based Measurement (M-CBM) and math fact probes for use with AIMSweb. Eden Prairie, MN: Edformation.
Google Scholar
Thurber, R. S., Shinn, M. R., Smoklowski, K. (2002). What is measured in mathematics tests? Construct validity of curriculum-based mathematics measures. School Psychology Review, 31, 498513.
Google Scholar | ISI
VanDerHeyden, A. M., Burns, M. K. (2009). Performance indicators in math: Implications for brief experimental analysis of academic performance. Journal of Behavioral Education, 18, 7191. doi:10.1007/s10864-009-9081-x10.1007/s10864-009-9081-x
Google Scholar | Crossref
Wagner, D., Davis, B. (2010). Feeling number: Grounding number sense in a sense of quantity. Educational Studies in Mathematics, 74, 3951. doi:10.1007/s10649-009-9226-910.1007/s10649-009-9226-9
Google Scholar | Crossref | 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

AEI-article-ppv for $15.00