The intervention validity of cognitive assessment batteries is considered within an historical context to identify what the evidence supports (knowns), what cannot be known (unknowables), and what is not yet known (unknowns). Two ways cognitive batteries could inform intervention are identified: a disordinal (i.e., aptitude-treatment interaction) model and an ordinal (i.e., g) model. Existing research provides little support for disordinal models and modest to strong support for ordinal models when applied to conditions of incomplete instruction. Limitations to what can be known (e.g., a failure to prove is not proof of failure) are identified to avoid holding intervention validity research to inappropriate evidential standards. Finally, issues that are within the realm of knowledge but for which there is currently insufficient or no evidence are identified as logical next steps toward understanding the intervention validity of cognitive assessment batteries.
American Educational Research Association, American Psychological Association, & National Council on Measurement in Education. (1999). Standards for educational and psychological testing (3rd ed.). Washington, DC: American Educational Research Association.
2.
Ardilla, A., Pineda, D., & Roselli, M. (2000). Correlation between intelligence test scores and executive function measures. Archives of Clinical Psychology , 15, 31-36.
3.
Ayres, R., & Cooley, E. (1986). Sequential versus simultaneous processing on the K-ABC: Validity in predicting learning success. Journal of Psychoeducational Assessment, 4, 211-220.
4.
Benbow, C., & Stanley, J. (1996). Inequity in equity: How "equity" can lead to inequity for high-potential students. Psychology, Public Policy, and Law, 2, 249-292.
5.
Berg, C., & Sternberg, R. (1992). Adults' conceptions of intelligence across the adult life span. Psychology and Aging, 7, 221-231.
6.
Blair, C. (2006). How similar are fluid cognition and general intelligence? A developmental neuroscience perspective on fluid cognition as an aspect of human cognitive ability. Behavioral and Brain Sciences, 29, 109-160.
7.
Bleske-Rechek, A., Lubinski, D., & Benbow, C. (2004). Meeting the educational needs of special populations: Advanced placement's role in developing exceptional human capital. Psychological Science, 15, 217-224.
8.
Braden, J.P. (1994). Deafness, deprivation, and IQ. New York: Plenum.
9.
Braden, J.P. (2005). Using the WISC-IV with clients who are hard-of-hearing or deaf. In D. Saklofske, A. Prifitera, L. Weiss , & E. Rolfhus (Eds.), WISC IV clinical use and interpretation (pp. 351-380). New York: Academic Press.
10.
Braden, J.P. (in press). Fluid intelligence. In N. Salkind (Ed.), Encyclopedia of educational psychology . Thousand Oaks, CA: Sage.
11.
Braden, J.P., & Athanasiou, M.S. (2005). A comparative review of nonverbal measures of intelligence. In D. P. Flanagan & P. L. Harrison (Eds.), Contemporary intellectual assessment: Theories, tests and issues (2nd ed., pp. 557-577). New York: Guilford.
12.
Braden, J.P., & Kratochwill, T.R. (1997). Treatment utility of assessment: Myths and realities. School Psychology Review, 26, 475-485.
13.
Braden, J.P., & Neibling, B.C. (2005). Using joint test standards to evaluate the validity evidence for intelligence tests. In D. P. Flanagan & P. L. Harrison (Eds.), Contemporary intellectual assessment: Theories, tests, and issues (3rd ed., pp. 615-630). New York: Guilford.
14.
Braden, J.P., & Ouzts, S.A. (2005). A review of the Kaufman Assessment Battery for Children-2nd Ed. In R. A. Spies & B. S. Plake (Eds.), The sixteenth mental measurements yearbook (pp. 517-520). Lincoln, NE: Buros Institute of Mental Measurements, University of Lincoln Press.
15.
Braden, J.P., & Shernoff, E.S. (in press). Why the need for evidence-based interventions? In R. M. Morris & N. M. Mather (Eds.), Evidence-based interventions for students with learning and behavioral challenges . Mawah, NJ: Lawrence Erlbaum.
16.
Carpenter, D.M. (2005). Presidential rhetoric and the purpose ofAmerican education. The Educational Forum, 69, 278-290.
17.
Ceci, S.J., & Papierno, P.B. (2005). The rhetoric and reality of gap-closing: When the "have nots" gain but the "haves" gain even more. American Psychologist, 60, 149-160.
18.
Coffee, G.H. (2005). The effects of instructional level matching and praise on elementary students' challenging behaviors. Unpublished master's thesis, University of Wisconsin-Madison.
19.
Dehn, M.J. (2006). Essentials of processing assessment. Hoboken, NJ: John Wiley.
20.
Elliott, J. (2003). Dynamic assessment in educational settings: Realising potential. Educational Review, 55, 15-32.
21.
Foschi, R., & Cicciola, E. (2006). Politics and naturalism in the 20th century psychology of Alfred Binet. History of Psychology, 9, 267-289.
22.
Frisby, C.L. (1999). Culture and test session behavior: PartI. School Psychology Quarterly, 14, 263-280.
23.
Frisby, C. L., & Braden, J. P. (Eds.) (1999). Straight talk about diversity and assessment [special issue]. School Psychology Quarterly , 14(3).
24.
Geary, D.C. (2005). The origin of mind: Evolution of brain, cognitive, and general intelligence. Washington, DC: American Psychological Association.
25.
Good, R., Vollmer, M., Creek, R., Katz, L., & Chowdri, S. (1993). Treatment utility of the Kaufman Assessment Battery for Children: Effects of matching instruction and student processing strength . School Psychology Review, 22, 8-26.
26.
Gorin, J.S. (2006). Test design with cognition in mind. Educational Measurement: Issues and Practice, 25, 21-35.
27.
Gottfredson, L.S. (2002). g: Highly general and highly practical. In R. J. Sternberg & E. L. Grigorenko (Eds.), The general factor of intelligence: How general is it? (pp. 331-380). Mahwah, NJ: Lawrence Erlbaum.
28.
Gottfredson, L.S. (2007). Applying double standards to "divisive" ideas . Perspectives on Psychological Science, 2, 216-220.
29.
Gresham, F.M. (1987). On the malleability of intelligence: Unnecessary assumptions, reidentification, and inclusion. School Psychology Review, 15, 245-255.
30.
Gresham, F.M. (2007, March). Treatment integrity/fidelity: A crucial feature of the RTI process. Invited address to the annual meeting of the National Association of School Psychologists, New York.
31.
Gresham, F.M., & Witt, J.C. (1997). Utility of intelligence tests for treatment planning, classification, and placement decisions: Recent empirical findings and future directions. School Psychology Quarterly, 12, 249-267.
32.
Haladyna, T.M., & Downing, S.M. (2004). Construct-irrelevant variance in high stakes testing . Educational Measurement: Issues and Practice, 23(1), 17-27.
33.
Hassiotis, A., Ukoumunne, O., Tyrer, P., Piachaud, J., Gilvarry, C., Harvey, K., et al. (1999). Prevalence and characteristics of patients with severe mental illness and borderline intellectual functioning: Report from the UK700 randomised controlled trial of case management. British Journal of Psychiatry, 175, 135-140.
34.
Herrnstein, R.J., & Murray, C. (1994). The bell curve. New York: Free Press.
35.
Iverson, G.L., Mendrek, A., & Adams, R.L. (2004). The persistent belief that VIQ-PIQ splits suggest lateralized brain damage. Applied Neuropsychology, 11, 85-90.
36.
Jenkins, J.R., Dale, P.S., Mills, P.E., Cole, K.N., Pious, C., & Ronk, J. (2006). How special education preschool graduates finish: Status at 19 years of age. American Educational Research Journal , 43, 737-781.
37.
Jensen, A.R. (1998). The g factor: The science of mental ability. Westport, CT: Praeger.
38.
Kamphaus, R.W. (2005). Clinical assessment of child and adolescent intelligence (2nd ed.). New York: Springer.
39.
Kane, M.J. (2005). Full frontal fluidity? Looking in on the neuroimaging of reasoning and intelligence. In W. Oliver & R. W. Engle (Eds.), Handbook of understanding and measuring intelligence (pp. 141-163). Thousand Oaks, CA: Sage.
40.
Kaufman, A.S., & Kaufman, N.L. (1983). Kaufman Assessment Battery for Children. Circle Pines, MN: American Guidance Service.
41.
Kuncel, N., & Sackett, P. (2007). Selective citation mars conclusions about test validity and predictive bias. American Psychologist, 62, 145.
42.
Leighton, J.P., & Gierl, M.J. (2007). Defining and evaluating models of cognition used in educational measurement to make inferences about examinees' thinking processes . Educational Measurement: Issues and Practice, 26(2), 3-16.
43.
Leighton, J.P., Gierl, M.J., & Hunka, S. (2004). The attribute hierarchy model: An approach for integrating cognitive theory with assessment practice. Journal of Educational Measurement, 41, 205-236.
44.
Macmann, G.M., Barnett, D.W., Lombard, T.J., Belton-Kocher, E., & Sharpe, M.N. (1989). On the actuarial classification of children: Fundamental studies of classification agreement. Journal of Special Education , 23, 127-149.
45.
McDaniel, M.A. (2005). Big-brained people are smarter: A meta-analysis of the relationship between in vivo brain volume and intelligence. Intelligence, 33, 337-346.
46.
McFall, R.M. (2005). Theory and utility-Key issues in evidence-based assessment: Comment on the special section. Psychological Assessment, 17, 312-323.
47.
McFall, R.M., & Townsend, J.T. (1998). Foundations of psychological assessment: Implications for cognitive assessment in clinical science. Psychological Assessment, 10, 316-330.
48.
Mills, P.E., Dale, P.S., Cole, K.N., & Jenkins, J.R. (1995). Follow-up of children from academic and cognitive preschool curricula at age 9. Exceptional Children, 61, 378-393.
Neisser, U., Boodoo, G., Bouchard, T.J., Boykin, A.W., Brody, N., Ceci, S.J., et al. (1996). Intelligence: Knowns and unknowns. American Psychologist, 51, 77-101.
51.
Nelson, J.R., Benner, G.J., & Gonzales, J. (2003). Learner characteristics that influence the treatment effectiveness of early literacy interventions: A meta-analytic review. Learning Disabilities: Research & Practice, 18, 255-267.
Ouzts, S.M. (2007). Response processes validity of the Stanford Binet Intelligence Scales, Fifth Edition. Unpublished master's thesis, North Carolina State University, Raleigh.
55.
Reed, T.E., Vernon, P.A., & Johnson, A.M. (2004). Confirmation of correlation between brain nerve conduction velocity and intelligence level in normal adults. Intelligence, 32, 563-572.
56.
Reschly, D.J. (1997a). Diagnostic and treatment utility of intelligence tests. In D. P. Flanagan, J. L. Genshaft, & P. L. Harrison (Eds.), Contemporary intellectual assessment: theories, tests, and issues (pp. 437-456). New York: Guilford.
57.
Reschly, D.J. (1997b). Utility of individual ability measures and public policy choices for the 21st century. School Psychology Review , 26, 234-241.
58.
Reschly, D.J., & Grimes, J.P. (2002) Best practices in intellectual assessment. In A. Thomas & J. P. Grimes (Eds.), Best practices in school psychology IV (4th ed., pp. 1337-1350). Bethesda, MD: National Association of School Psychologists.
Rosenthal, R., & Jacobson, L. (1968). Pygmalion in the classroom: Teacher expectation and pupils' intellectual development. New York: Holt.
61.
Rujescu, D., Meisenzahl, E.M., Krejcova, S., Giegling, I., Zetzsche, T., Reiser, M., et al. (2007). Lexin B3 is genetically associated with verbal performance and white matter volume in human brain. Molecular Psychiatry, 12, 190-194.
62.
Sattler, J.M. (2001). Assessment of children: Cognitive applications (4th ed.). San Diego, CA: Author.
63.
Schumm, J.S., & Arguelles, M.E. (2006). No two learners learn alike: The importance of assessment and differentiated instruction. In J. S. Schumm (Ed.), Reading assessment and instruction for all learners (pp. 27-58). New York: Guilford.
64.
Shah, K.G., & Braden, J.P. (2004, March). Treatment utility of the Woodock-Johnson-III Cognitive Battery for selecting reading interventions in first-graders. Poster at the annual meeting of the National Association of School Psychologists, Dallas, TX.
65.
Shaw, S.R. (in press). An educational programming framework for a subset of students with diverse learning needs: Borderline intellectual functioning. Intervention in School and Clinic.
66.
Smith, C.P. (1964). Relationship between achievement-related motives and intelligence, performance level, and persistence. Journal of Abnormal and Social Psychology, 68, 523-532.
67.
Smith, G.T. (2005). On construct validity: Issues of method and measurement . Psychological Assessment, 17, 396-408.
68.
Sobol, T. (1997). Beyond standards: The rest of the agenda. Teachers College Record, 98, 629-636.
69.
Spitz, H. (1999a). Attempts to raise intelligence. In M. Anderson (Ed.), The development of intelligence (pp. 275-293). Hove, UK: Psychology Press, Taylor & Francis.
70.
Spitz, H. (1999b). Beleaguered "Pygmalion": A history of the controversy over claims that teacher expectancy raises intelligence. Intelligence, 27, 199-234.
71.
Stanovich, K.E. (1986). Matthew effects in reading: Some consequences of individual differences in the acquisition of literacy. Reading Research Quarterly, 21, 360-406.
72.
Sternberg, R.J., Grigorenko, E.L., Ferrari, M., & Clinkenbeard, P. (1999). A triarchic analysis of an aptitude-treatment interaction. European Journal of Psychological Assessment, 15, 3-13.
73.
Thorndike, R.M. (2005). Review of the Kaufman Assessment Battery for Children -2nd Edition. In R. A. Spies & B. S. Plake (Eds.), The sixteenth mental measurements yearbook (pp. 520-522). Lincoln, NE: Buros Institute of Mental Measurements, University of Lincoln Press.
74.
Van Leeuwen, M., Van den Berg, S.M., Hoekstra, R.A., & Boomsma, D.I. (2007). Endophenotypes for intelligence in children and adolescents. Intelligence, 35, 369-380.
75.
Wai, J., Lubinski, D., & Benbow, C. (2005). Creativity and occupational accomplishments among intellectually precocious youths: An age 13 to age 33 longitudinal study. Journal of Educational Psychology, 97, 484-492.
76.
Wasserman, J.D., & Tulsky, D.S. (2005). A history of intelligence assessment. In D. P. Flanagan & P. L. Harrison (Eds.), Contemporary intellectual assessment (2nd ed., pp. 1-23). New York: Guilford.
77.
Wickstrom, K., Jones, K., LaFleur, L., & Witt, J. (1998). An analysis of treatment integrity in school-based behavioral consultation. School Psychology Quarterly, 13, 141-154.
78.
Wigfield, A. (1994). Expectancy-value theory of achievement motivation: A developmental perspective. Educational Psychology Review , 6, 49-78.
