Abstract
The Test of Early Mathematics Ability–Third Edition (TEMA-3) is a commonly used measure of early mathematics knowledge for children aged 3 years to 8 years 11 months. In spite of its wide use, research on the psychometric properties of TEMA-3 remains limited. This study applied the Rasch model to investigate the psychometric properties of TEMA-3 from three aspects: technical qualities, internal structure, and convergent evidence. Data were collected from 971 K1 children in Singapore. Item fit statistics suggested a reasonable model-data fit. The TEMA-3 items were found to demonstrate generally good technical qualities, interpretable internal structure, and reasonable convergent evidence. Implications for test development, test use, and future research are further discussed.
|
Bock, R. D., Aitkin, M. (1981). Marginal maximum likelihood estimation of item parameters: Application of an EM algorithm. Psychometrika, 46, 443-459. Google Scholar | Crossref | ISI | |
|
Briggs, D. C., Wilson, M. (2003). An introduction to multidimensional measurement using Rasch models. Journal of Applied Measurement, 4, 87-100. Google Scholar | Medline | |
|
Chen, W. H., Lenderking, W., Jin, Y., Wyrwich, K. W., Gelhorn, H., Revicki, D. A. (2014). Is Rasch model analysis applicable in small sample size pilot studies for assessing item characteristics? An example using PROMIS pain behavior item bank data. Quality of Life Research, 23, 485-493. Google Scholar | Crossref | Medline | ISI | |
|
Daniel, M. H. (1999). Behind the scenes: Using new measurement methods on the DAS and KAIT. In Embretson, S. E., Hershberger, S. L. (Eds.), The new rules of measurement: What every psychologist and educator should know (pp. 37-63). Mahwah, NJ: Lawrence Erlbaum. Google Scholar | |
|
Duncan, G. J., Dowsett, C. J., Claessens, A., Magnuson, K., Huston, A. C., Klebanov, P., . . . Japel, C. (2007). School readiness and later achievement. Developmental Psychology, 43, 1428-1446. Google Scholar | Crossref | Medline | ISI | |
|
Ebel, R. L. (1965). Measuring educational achievement. Englewood Cliffs, NJ: Prentice Hall. Google Scholar | |
|
Embretson, S. E., Reise, S. P. (2000). Item response theory for psychologists. Mahwah, NJ: Lawrence Erlbaum. Google Scholar | |
|
Fuchs, L. S., Geary, D. C., Compton, D. L., Fuchs, D., Hamlett, C. L., Bryant, J. D. (2010). The contributions of numerosity and domain-general abilities to school readiness. Child Development, 81, 1520-1533. Google Scholar | Crossref | Medline | ISI | |
|
Geary, D. C., Bailey, D. H., Hoard, M. K. (2009). Predicting mathematical achievement and mathematical learning disability with a simple screening tool: The number sets test. Journal of Psychoeducational Assessment, 27, 265-279. Google Scholar | SAGE Journals | ISI | |
|
Gelman, R., Gallistel, C. R. (1986). The child’s understanding of number. Cambridge, MA: Harvard University Press. Google Scholar | |
|
Ginsburg, H. P., Baroody, A. J. (2003). Test of early mathematics ability (3rd ed.): Examiner’s manual. Austin, TX: PRO-ED. Google Scholar | |
|
Ginsburg, H. P., Lee, J. S., Boyd, J. S. (2008). Mathematics education for young children: What it is and how to promote it. Social Policy Report, 22(1), 3-22. Google Scholar | |
|
Jordan, N. C., Kaplan, D., Ramineni, C., Locuniak, M. N. (2009). Early math matters: Kindergarten number competence and later mathematics outcomes. Developmental Psychology, 45, 850-867. Google Scholar | Crossref | Medline | ISI | |
|
Kelley, T., Ebel, R., Linacre, J. M. (2002). Item discrimination indices. Rasch Measurement Transactions, 16, 883-884. Google Scholar | |
|
Kendall, M. G., Gibbons, J. D. (1990). Rank correlation methods (5th ed.). London, England: Griffin. Google Scholar | |
|
Lee, K., Bull, R. (2015). Developmental changes in working memory, updating, and math achievement. Journal of Educational Psychology. Advance online publication. doi.org/10.1037/edu0000090 Google Scholar | |
|
Levine, S. C., Jordan, N. C., Huttenlocher, J. (1992). Development of calculation abilities in young children. Journal of Experimental Child Psychology, 53, 72-103. Google Scholar | Crossref | Medline | ISI | |
|
Linacre, J. M. (1994). Sample size and item calibration stability. Rasch Measurement Transactions, 7(4), 328. Google Scholar | |
|
Martin, R. B., Cirino, P. T., Sharp, C., Barnes, M. (2014). Number and counting skills in kindergarten as predictors of grade 1 mathematical skills. Learning and Individual Differences, 34, 12-23. Google Scholar | Crossref | Medline | ISI | |
|
Mislevy, R. J., Wu, P. (1996). Missing responses and IRT ability estimation: Omits, choice, time limits, and adaptive testing (RR 96-30-ONR). Princeton, NJ: Educational Testing Service. Google Scholar | |
|
Mix, K. S., Huttenlocher, J., Levine, S. C. (2002). Quantitative development in infancy and early childhood. New York, NY: Oxford University Press. Google Scholar | Crossref | |
|
Murphy, M. M., Mazzocco, M. M., Hanich, L. B., Early, M. C. (2007). Cognitive characteristics of children with mathematics learning disability (MLD) vary as a function of the cutoff criterion used to define MLD. Journal of Learning Disabilities, 40, 458-478. Google Scholar | SAGE Journals | ISI | |
|
Passolunghi, M. C., Lanfranchi, S., Altoe, G., Sollazzo, N. (2015). Early numerical abilities and cognitive skills in kindergarten children. Journal of Experimental Child Psychology, 135, 25-42. Google Scholar | Crossref | Medline | ISI | |
|
Rasch, G. (1960). Probabilistic models for some intelligence and attainment tests. Copenhagen: Danmarks Paedogogiske Institute. (Reprinted 1980 by University of Chicago Press) Google Scholar | |
|
Ryoo, J. H., Molfese, V. J., Brown, E. T., Karp, K. S., Welch, G. W., Bovaird, J. A. (2015). Examining factor structures on the Test of Early Mathematics Ability—3: A longitudinal approach. Learning and Individual Differences, 41, 21-29. Google Scholar | Crossref | ISI | |
|
Ryoo, J. H., Molfese, V. J., Heaton, R., Zhou, X., Brown, E. T., Prokasky, A., Davis, E. (2014). Early mathematics skills from prekindergarten to first grade score changes and ability group differences in Kentucky, Nebraska, and Shanghai samples. Journal of Advanced Academics, 25, 162-188. Google Scholar | SAGE Journals | |
|
Watts, T. W., Duncan, G. J., Siegler, R. S., Davis-Kean, P. E. (2014). What’s past is prologue: Relations between early mathematics knowledge and high school achievement. Educational Researcher, 43, 352-360. Google Scholar | SAGE Journals | ISI | |
|
Wilson, M. (2005). Constructing measures: An item response modeling approach. Mahwah, NJ: Lawrence Erlbaum. Google Scholar | |
|
Wright, B. D., Linacre, J. M. (1994). Reasonable mean-square fit values. Rasch Measurement Transactions, 8(3), 370. Google Scholar | |
|
Wright, B. D., Masters, G. N. (1982). Rating scale analysis. Chicago, IL: MESA Press. Google Scholar | |
|
Wright, B. D., Stone, M. H. (1979). Best test design: Rasch measurement. Chicago, IL: MESA Press. Google Scholar | |
|
Wu, M. L., Adams, R. J., Wilson, M. R., Haldane, S. A. (2007). ACER ConQuest version 2.0: Generalised item response modelling software. Camberwell, Victoria: Australia Council for Educational Research Press. Google Scholar |

