Abstract
Test accessibility is defined as the extent to which a test and its constituent item set permit the test-taker to demonstrate his or her knowledge of the target construct (Beddow, Elliott, & Kettler, 2009). The principles of accessibility theory (Beddow, in press) suggest the measurement of achievement involves a multiplicity of interactions between test-taker characteristics and features of the test itself. Beddow argued achievement test results are valid to the degree the test event controls these interactions and yields scores from which inferences reflect the amount of the target construct possessed by the test-taker. Test score inferences typically are based on the assumption that the test event was optimally accessible; therefore, the validity of an achievement test result depends both on the precision of the test score and the accuracy of subsequent inferences about the test-taker’s knowledge of the tested content after accounting for the influence of any access barriers. In essence, the accessibility of a test event is proportional to the validity of test results.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Anderson, L. W. (2002). Curricular alignment: A re-examination. Theory into Practice, 41(4), 255–260.
Baddeley, A. (2003). Working memory: Looking back and looking forward. Neuroscience, 4, 829–839.
Beddow, P. A. (2010). Beyond universal design: Accessibility theory to advance testing for all students. In M. Russell (Ed.), Assessing students in the margins:  Challenges, strategies, and techniques (1st ed., pp. 383–407). New York: Information Age Publishing.
Beddow, P. A., Elliott, S. N., & Kettler, R. J. (2009). TAMI accessibility rating matrix (ARM). Nashville, TN: Vanderbilt University.
Beddow, P. A., Elliott, S. N., & Kettler, R. J. (2010). Test accessibility and modification inventory (TAMI) technical supplement. Nashville, TN: Vanderbilt University.
Beddow, P. A., Kettler, R. J., & Elliott, S. N. (2008). Test accessibility and modification inventory (TAMI). Nashville, TN: Vanderbilt University.
Chandler, P., & Sweller, J. (1991). Cognitive load theory and the format of instruction. Cognition and Instruction, 8, 293–332.
Chandler, P., & Sweller, J. (1996). Cognitive load while learning to use a computer program. Applied Cognitive Psychology, 10, 151–170.
Clark, R. C., Nguyen, F., & Sweller, J. (2006). Efficiency in learning: Evidence-Based guidelines to manage cognitive load. San Francisco: Jossey-Bass.
Elliott, S. N., Kettler, R. J., Beddow, P. A., Kurz, A., Compton, E., McGrath, D., et al. (2010). Effects of using modified items to test students with persistent academic difficulties. Exceptional Children , 76, 475–495.
Elliott, S. N., Kurz, A., Beddow, P., & Frey, J. (2009, February). Cognitive load theory: Instruction-Based research with applications for designing tests. Paper presented at the national association of school psychologists’ annual convention, Boston.
Haladyna, T. M., Downing, S. M., & Rodriguez, M. C. (2002). A review of multiple-choice item-writing guidelines for classroom assessment. Applied Measurement in Education, 15, 309–333.
Johnstone, C. J., Bottsford-Miller, N. A., & Thompson, S. J. (2006). Using the think aloud method (cognitive labs) to evaluate test design for students with disabilities and English language learners (Technical report 44). National Center on Educational Outcomes, University of Minnesota, 25.
Kettler, R. J., Elliott, S. N., & Beddow, P. A. (2009). Modifying achievement test items: A theory-guided and data-based approach for better measurement of what students with disabilities know. Peabody Journal of Education, 84, 529–551.
Kettler, R. J., Rodriguez, M. R., Bolt, D. M., Elliott, S. N., Beddow, P. A., & Kurz, A. (in press). Modified multiple-choice items for alternate assessments: Reliability, difficulty, and differential boost. Applied Measurement in Education.
Ketterlin-Geller, L. R. (2008). Testing students with special needs: A model for understanding the interaction between assessment and student characteristics in a universally designed environment. Educational Measurement: Issues and Practice , 27, 3–16.
Kurz, A., & Elliott, S. N. (2011). Overcoming barriers to access for students with disabilities: Testing accommodations and beyond. In M. Russell (Ed.), Assessing students in the margins: Challenges, strategies, and techniques. Charlotte, NC: Information Age Publishing.
Mace, R. L. (1991). Definitions: Accessible, adaptable, and universal design (Fact Sheet). Raleigh, NC: Center for Universal Design, NCSU.
Mace, R. (1997). The principles of universal design (2nd Ed.). Raleigh, NC: Center for Universal Design, College of Design. Retrieved May 20, 2010, from http://www.design.ncsu.edu/cud/pubs_p/docs/poster.pdf
Mace, R. L., Hardie, G. J., & Place, J. P. (1996). Accessible environments: Toward universal design. Retrieved May 20, 2010, from http://www.design.ncsu.edu/cud/pubs_p/docs/ACC%20Environments.pdf
Mayer, R. E., Bove, W., Bryman, A., Mars, R., & Tapangco, L. (1995). When less is more: Meaningful learning from visual and verbal summaries of science textbook lessons. Journal of Educational Psychology, 88, 54–73.
Mayer, R. E., & Moreno, R. (2003). Nine ways to reduce cognitive load in multimedia learning. Educational Psychologist, 38, 43–52.
Miller, G. A. (1956). The magical number seven, plus or minus two: Some limits on our capacity for processing information. Psychological Review , 63, 81–97.
Moreno, R., & Mayer, R. E. (1999). Cognitive principles of multimedia learning: The role of modality and contiguity. Journal of Educational Psychology, 91, 348–368.
Mousavi, S. Y., Low, R., & Sweller, J. (1995). Reducing cognitive load by mixing auditory and visual presentation modes. Journal of Educational Psychology, 87, 319–334.
National Center for Education Statistics. (2011). The Nation’s Report Card: Science 2009 (NCES 2011–451). Washington, DC: Institute of Education Sciences, U.S. Department of Education.
Plass, J. L., Moreno, R., & Brunken, R. (Eds.). (2010). Cognitive load theory. New York: Cambridge University Press.
Porter, A. C. (2006). Curriculum assessment. In J. L. Green, G. Camilli & P. B. Elmore (Eds.), Handbook of complementary methods in education research (pp. 141–159). Mahwah, NJ: Lawrence Erlbaum.
Roach, A. T., Beddow, P. A., Kurz, A., Kettler, R. J., & Elliott, S. N. (2010). Incorporating student input in developing alternate assessments based on modified academic achievement standards. Exceptional Children , 77, 61–80.
Rodriguez, M. C. (1997, August). The art & science of item-writing: A meta-analysis of multiple-choice item format effects. Paper presented at the annual meeting of the American Education Research Association, Chicago, IL.
Rodriguez, M. C. (2005). Three options are optimal for multiple-choice items: A meta-analysis of 80 years of research. Educational Measurement: Issues and Practice, 24, 3–13.
Rose, D. H., & Meyer, A. (2002). Teaching every student in the digital age: Universal design for learning. Alexandria, VA: Association for Supervision and Curriculum Development.
Sweller, J. (2010). Cognitive load theory: Recent theoretical advances. In J. L. Plass, R. Moreno & R. Brunken (Eds.), Cognitive load theory (pp. 29–47). New York: Cambridge University Press.
Sweller, J., & Chandler, P. (1994). Why some material is difficult to learn. Cognitive Instruction, 12, 185–233.
Thompson, S. J., Johnstone, C. J., Anderson, M. E. & Miller, N. A. (2005). Considerations for the development and review of universally designed assessments (Technical report 42). Minneapolis, MN: University of Minnesota, National Center on Educational Outcomes.
Thompson, S. J., Johnston, C. J., & Thurlow, M. L. (2002). Universal design applied to large-scale assessments (Synthesis Report 44). Minneapolis, MN: University of Minnesota, National Center on Educational Outcomes.
Torcasio, S., & Sweller, J. (2010). The use of illustrations when learning to read: A cognitive load theory approach. Applied Cognitive Psychology , 24(5), 659–672.
Webb, N. L. (2002, April). An analysis of the alignment between mathematics standards and assessments for three states. Paper presented at the american educational research association annual meeting, New Orleans, LA.
Wright, N. (2009). Towards a better readability measure – The Bog index. Retrieved June 5, 2010, from http://www.clearest.co.uk/files/TowardsABetterReadabilityMeasure.pdf
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2011 Springer New York
About this chapter
Cite this chapter
Beddow, P.A., Kurz, A., Frey, J.R. (2011). Accessibility Theory: Guiding the Science and Practice of Test Item Design with the Test-Taker in Mind. In: Elliott, S., Kettler, R., Beddow, P., Kurz, A. (eds) Handbook of Accessible Achievement Tests for All Students. Springer, New York, NY. https://doi.org/10.1007/978-1-4419-9356-4_9
Download citation
DOI: https://doi.org/10.1007/978-1-4419-9356-4_9
Published:
Publisher Name: Springer, New York, NY
Print ISBN: 978-1-4419-9355-7
Online ISBN: 978-1-4419-9356-4
eBook Packages: Behavioral ScienceBehavioral Science and Psychology (R0)