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Creating Innovative Tests: Applying Universal Design to Assessment Practices. Assessment Colloquium November 30, 2007. Manju Banerjee, Ph.D. Assistant Professor in Residence Special Education. Just imagine --- If there were no tests, no assessment, no accountability as we know it?

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slide1

Creating Innovative Tests:

Applying Universal Design to Assessment

Practices

Assessment Colloquium

November 30, 2007

Manju Banerjee, Ph.D.

Assistant Professor in Residence

Special Education

slide2

Just imagine ---

If there were no tests, no assessment, no accountability as we know it?

Student perspective:

Teacher perspective:

Policy maker perspective:

slide3

“Opportunities borne of new technologies, desires borne of new understandings of learning ---- a new generation of assessment beckons. To realize the vision, we must reconceive how we think about assessment, from purposes and designs to production and delivery.”(Mislevy, Steinberg, & Almond, 1999, p.6)

slide4

Computer-based tests (CBT) are the “next frontier” in high

stakes assessment(Thompson, Johnstone, & Thurlow, 2002)

slide5

What is the appeal of computer-based tests?

Opportunity to create tests that support accessibility needs of diverse test takers -- Universal Design (UD)

UD is anchored in the belief that a design that works well for examinees with disabilities, improves usability for all individuals (Center for an Accessible Society, 2006)

  • What is universal design? (Center for Universal Design, 1997)
  • What makes a test universally designed?
  • * Seven Elements of a universally designed test (Thompson, Johnstone, & Thurlow, 2002)
slide6

Application of Universal Design to High Stakes Tests

Maximum usability

Widest range

of consumers

Without design

adaptations

Minimize construct

irrelevant features

Disabilities, ELL,

Non-traditional age

Built-in from

the start

Include test taking

features

EXAMINEE CHOICE

  • Examinee choice is “flexibility to access and express in
  • the mode or methods that best suit the individual”(Hall, 2005, p. 2)
  • (Russell, Goldberg, & O’Conner, 2003)
slide7

1. Objective of Study

  • Inform product development of high stakes tests
  • Based on current research on features that support “examinee choice” in high stakes test design

Test taking tools

On-screen item

display tools

Access tools

  • Bridgeman, Lennon, &
  • Jackenthal, 2002
  • Mazzeo & Harvey, 1988
  • Pommerich, 2004
  • Pommerich & Burden, 2004
  • Goldberg & Pedula, 2002
  • Peak, 2005
  • Lunz & Bergstrom, 1994
  • Vispoel et al., 2000
  • Mandinach et al., 2005
  • Sireci, Li, & Scarpati, 2003
  • Tindal & Fuchs, 2000
slide8

II. Background Information

Features of Examinee Choice

  • Tindal, 1998
  • CTB/McGraw-Hill, 2004

Construct neutral

Construct related

Test taking tools

Access tools

On-screen item

display

slide9

II. Background Information (Cont.)

  • U D increased accessibility for all examinees
  • Accessibility is maximized when examinees have choice over features of test design
  • Research on features of test design fall into three broad categories:
  • (1)Test taking tools (2)Item Display (3) Access tools
  • Some features are construct neutral/construct irrelevant; others are construct related (including test accommodations)
  • Allowing examinees to choose features of test design based on individual preferences needs to be explored for a wide range of features including features that affect test construct
  • U D suggest a framework but research is still emerging on the application of UD to high stakes CBTs.
slide11

III. Methodology and Procedures (cont.)

Research Design, Instrumentation, Pilot Study

slide12

III. Methodology and Procedures (contd.)

Instrumentation – Test Features

slide15

III. Methodology and Procedures (contd.)

Instrumentation- Creating the 1st choice exercise

  • Given 4x3x7 (features) = 84 combinations
  • Select a unique group of 4 from 84 combinations
slide16

III. Methodology and Procedures (contd.)

Data Analysis

Research Question 1

Research Question 2

Rank-ordered choice

exercise data

Voluntary top feature choice

exercise data

Rank-ordered Logit

Regression

Multinomial Logit

Regression

slide17

III. Methodology and Procedures (contd.)

Data Analysis – Rank-ordered logit regression

slide18

III. Methodology and Procedures (contd.)

Data Analysis – Rank-ordered logit regression

slide19

III. Methodology and Procedures (contd.)

Data Analysis – Multinomial logit regression

slide21

IV. Results - Model 1

*p<0.10, **p<0.05, ***p<0.01

slide22

IV. Results - Model 1 (contd.)

*p<0.10, **p<0.05, ***p<0.01

slide23

IV. Results - Model 2

*p<0.10, **p<0.05, ***p<0.01

slide24

IV. Results - Model 2 (contd.)

*p<0.10, **p<0.05, ***p<0.01

slide27

IV. Results (contd.)

Test of equality of regression coefficients for LD/ADHD status

slide30

V. Summary of Results and

Discussion (contd.)

slide31

V. Summary of Results and

Discussion (contd.)

slide34
*****

END OF PRESENTATION