Alternate Assessments on Alternate Achievement Standards Student Population

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Alternate Assessments on Alternate Achievement
StandardsStudent Population
Jacqueline F. Kearns, Ed.D. Elizabeth
Towles-Reeves, MS
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The Assessment Triangle Validity
Evaluation Marion Pellegrino (2006)

• Assessment System
• Test Development
• Administration
• Scoring

• Reporting
• Alignment
• Item Analysis DIF/Bias
• Measurement error
• Scaling and Equating
• Standard Setting

• VALIDITY EVALUATION
• Empirical evidence
• Theory logic (argument)
• Consequential features

• Student Population
• Academic content
• Theory of Learning

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Cognition Vertex Validity Questions

• Is the assessment appropriate for the students
  for whom it was intended?
• Is the assessment being administered to the
  appropriate students?
• Both are important for the validity evaluation

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More Different Than Alike
SOURCE Education Week analysis of data from the
U.S. Department of Education, Office of Special
Education Programs, Data Analysis System, 2002-03
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Issues in Teaching/Assessing Students in
Alternate Assessments

• Varied levels of symbolic communication
• Attention to salient features of stimuli
• Memory
• Limited motor response repertoire
• Generalization
• Self-Regulation
• Meta-cognition
• Skill Synthesis
• Sensory Deficits
• Special Health Care Needs
• Kleinert, H., Browder, D., Towles-Reeves, E.
  (2005). The assessment triangle and students with
  significant cognitive disabilities Models of
  student cognition. National Alternate Assessment
  Center, Human Development Institute, University
  of Kentucky, Lexington. (PDF File)

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Previous Data

• 165 Students across 7 states
• Extensive documentation through 111 item
  inventory
• Findings suggest
• 64 routinely use verbal language
• 46 routinely understand pictures used to
  represent objects
• 11 dont understand pictures used to represent
  objects.
• Almond Bechard (2005) An In Depth Look at
  students who take alternate assessments What do
  we know. Colorado EAG.

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Learner Characteristics Demographic Variables

• Learner Characteristics (all on a continuum of
  skills)
• Expressive Language
• Receptive Language
• Vision
• Hearing
• Motor
• Engagement
• Health Issues/Attendance
• Reading
• Mathematics
• Use of an Augmentative Communication System
  (dichotomous variable)

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Methodology

• Four partner states chose to participate
• States 1, 2, and 3
• gathered data in the administration process for
  their AA-AAS via scannable document (i.e.,
  bubble-sheet)
• State 4
• gathered data using Zoomerang, an online survey
  package.
• N 7,075

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States LCI Response Rates
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Alternate Assessment Participation Rates
Total population
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Most significant cognitive disabilities
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Expressive Language
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Receptive Language
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Use of Augmented Communication
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Reading
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Mathematics
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Who are the Kids?

• Represent 1 or less of the total assessed
  population
• All disability categories were represented but
  primarily 3 emerge,
• Mental Retardation
• Multiple Disabilities
• Autism
• Highly varied levels of expressive/receptive
  language use
• Most students in the population use symbolic
  communication
• Level of symbolic language distribution is
  similar across grade-bands
• Only about 50 of the pre and emerging symbolic
  language users use ACS
• Pre-symbolic expressive language users are more
  likely to have additional complex
  characteristics.
• Most of the population read basic sight words and
  solve simple math problems with a calculator.
• Lack of skill progression in reading across grade
  bands (elementary, middle high)
• Skill progression apparent in mathematics across
  grade bands but still small

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Limitations

• Only four state participants
• Small sample size
• Global items in reading and math
• Participation rates at 1 or less

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Cognition Vertex Validity Evaluation Essential
Questions

• Who is the population being assessed?
• How do we document and monitor the population?
• What do we know about how they learn (theory of
  learning) academic content?
• What do our assessment results tell us about how
  the population is learning academic content?
• Are our data about the population and theory of
  learning consistent with student performances on
  the assessment?
• If not, what assumptions are challenged?
• What adjustments should be made?
• Participation
• Theory of Learning
• Student Performance

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References

• Agran, M., Fodor-Davis, Moore, Martella,
  (1992). Effects of peer-delivered
  self-instructional training on a lunch-making
  task for students with severe disabilities.
  Education and Training in Mental Retardation, 27,
  230-240.
• Billingsley, F., Gallucci, C., Peck, C.,
  Schwartz, I., Staub, D. (1996).  "But those
  kids can't even do math  An alternative
  conceptualization of outcomes in special
  education.  Special Education Leadership Review,
  3 (1), 43-55.
• Brown, L., Nisbet, J., Ford, A., Sweet, M.,
  Shiraga, B., York, J., Loomis, R. (1983). The
  critical need for non-school instruction in
  educational programs for severely handicapped
  students. Journal of the Association of the
  Severely Handicapped. 8, 71-77.
• CAST (2002).
• Fox, (1989). Stimulus Generalization of skills
  and persons with profound mental handicaps.
  Education and Training in Mental Retardation,
  24,219-299.
• Haring, N. (1988). Generalization for students
  with severe handicaps Strategies and solutions.
  Seattle, WA University of Washington Press.
• Hughes, C. Agran, M. (1993). Teaching persons
  with severe disabilities to use self-instruction
  in community settings An analysis of the
  applications. Journal of the Association for
  Persons with severe Handicaps, 18, 261-274.
• Hughes, C., Hugo, K., Blatt, J. (1996).
  Self-instructional intervention for teaching
  generalized problem-solving with a functional
  task sequence. American Journal of Mental
  Retardation, 100 565-579.
• Westling, D., Fox, L. (2004). Teaching Students
  with Severe Disabilities. Columbus Pearson
  (Merrell).
• Whitman, T. L. (1990). Self-regulation and
  mental retardation. American Journal on Mental
  Retardation, 94, 347-362.

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Contact Information

• Jacqueline Kearns, Ed.D.

• Elizabeth Towles-Reeves, MS

• 1 Quality Street, Suite 722
• Lexington, Kentucky 40507
• 859-257-7672 X 80243
• 859-323-1838
• Jacqueline.kearns_at_uky.edu

• 1 Quality Street, Suite 722
• Lexington, Kentucky 40507
• 859-257-7672 X 80255
• 859-323-1838
• Liztowles-reeves_at_uky.edu

www.naacpartners.org