Curriculum-Based Measurement (CBM) is a direct method of academic assessment used to screen and evaluate students’ skills and monitor their responses to academic instruction and intervention. Interventioncentral.org offers a math worksheet generator at no cost that creates randomly generated math curriculum-based measures (M-CBMs). In this study, we examined the test–retest reliability and alternate-form reliability of four parallel, randomly generated M-CBMs designed to assess multiple arithmetic skills (addition, subtraction, multiplication, and division). The participants (N = 283 sixth-grade students) completed each M-CBM worksheet twice during a semester. According to our results, these M-CBMs have moderate test–retest and alternate-form reliability. Applying the Spearman–Brown Prophecy Formula revealed that aggregating M-CBMs increases the reliability of these measures to acceptable levels for progress monitoring (i.e., above .80).
ArbuckleJ. L. (1996). Full information estimation in the presence of incomplete data. In MarcoulidesG. A.SchumackerR. E. (Eds.), Advanced structural equation modeling (pp. 243-277). Mahwah, NJ: Lawrence Erlbaum.
3.
BrownW. (1910). Some experimental results in the correlation of mental abilities. British Journal of Psychology, 3, 296–322. doi:10.1111/j.2044-8295.1910.tb00207.x
4.
ChristT.Johnson-GrosK.HintzeJ. (2005). An examination of alternate assessment durations when assessing multiple-skill computational fluency: The generalizability and dependability of curriculum-based outcomes within the context of educational decisions. Psychology in the Schools, 42, 615–622. doi:10.1002/pits.20107
5.
CohenJ.CohenP.WestS.AikenL. (2003). Applied multiple regression/correlation analysis for the behavioral sciences (3rd ed.). London, England: Lawrence Erlbaum.
DenoS. L. (1985). Curriculum-based measurement: The emerging alternative. Exceptional Children, 52, 219–232.
8.
DenoS. L. (2003). Developments in curriculum-based measurement. The Journal of Special Education, 37, 184–192. doi:10.1177/00224669030370030801
9.
EasyCBM Lite Edition. (2014). Available from www.easycbm.com
10.
ElliotJ.LeeS. W.TollefsonN. (2001). A reliability and validity study of the dynamic indicators of basic early literacy skills-modified. School Psychology Review, 30, 33–49.
11.
FoegenA.DenoS. L. (2001). Identifying growth indicators for low-achieving students in middle school mathematics. The Journal of Special Education, 35, 4–16. doi:10.1177/002246690103500102
12.
FoegenA.JibanC.DenoS. (2007). Progress monitoring measures in mathematics. The Journal of Special Education, 41, 121–139. doi:10.1177/00224669070410020101
13.
FuchsL. S. (2004). The past, present, and future of curriculum-based measurement research. School Psychology Review, 33, 188–192.
14.
FuchsL. S.FuchsD. (2002). What is scientifically-based research on progress monitoring? (Technical report). Nashville, TN: Vanderbilt University.
15.
GrafmanJ. M.CatesG. L. (2010). The differential effects of two self-managed math instruction procedures: Cover, copy, and compare versus copy, cover, and compare. Psychology in the Schools, 47, 153–165. doi:10.1002/pits.20459
16.
GregoryR. J. (2011). Psychological testing: History, principles, and applications (6th ed.). Boston, MA: Pearson.
17.
HintzeJ. M.ChristT. J.KellerL. A. (2002). The generalizability of CBM survey-level mathematics assessments: Just how many samples do we need?School Psychology Review, 31, 514–528.
18.
HospM. K.HospJ. L.HowellK. W. (2007). The ABCs of CBM: A practical guide to curriculum-based measurement. New York, NY: Guilford Press.
19.
Individuals With Disabilities Education Improvement Act (2004). Public Law 108–446 (20 U.S.C. 1400 et seq.).
No Child Left Behind Act of2001, Public Law 107–110 (20 U.S.C. et seq. 6301 2002).
24.
NunallyJ. C. (1978). Psychometric theory. New York, NY: McGraw-Hill.
25.
SchaferJ. L.GrahamJ. W. (2002). Missing data: Our view of the state of the art. Psychological Methods, 7, 147–177. doi:10.1037/1082-989X.7.2.147
26.
ShapiroE. S. (2011). Academic skills problems: Direct assessment and intervention (4th ed.). New York, NY: Guilford Press.
27.
SpearmanC. (1910). Correlation calculated from faulty data. British Journal of Psychology, 3, 271–295. doi:10.1111/j.2044-8295.1910.tb00206.x
28.
StraitG. (2008). Psychometric properties of a brief basic math skill assessment for middle school students: Simultaneous assessment of addition, subtraction, multiplication, and division (Master’s thesis). Available from ProQuest Dissertations and Theses database. (UMI No. 1459909)
