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Digital Accessibility:

Improving Accessibility of Digital Learning Environments through Technology

Andrias Susanto

Ph.D. Student in Applied Linguistics in Technology

& Ph.D. Student in Human Computer Interaction

ENGL/LING 1200 - Computer & Language Course Instructor

IOWA STATE UNIVERSITY

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Tim Berners-Lee�(the “www.” Creator)

“The power of the Web is in its universality. Access by everyone regardless of disability

is an essential aspect.”

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Contents

  1. Accessibility
  2. Importance of Accessibility
  3. Core Point of Accessibility
  4. Digital Learning Environment (DLE)
  5. Improving Accessibility
  6. Samples of Accessibility Evaluation
  7. Improving DLE Accessibility with Technology

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  1. What is Accessibility?

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2. Why is Accessibility important?

  • Inclusivity and Equal Opportunity
  • Legal Compliance and Avoidance of Discrimination
  • Expanded Audience Reach and Market Share
  • Improved User Experience for Everyone
  • Enhanced Reputation and Brand Image

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3. What is the Core Point of Accessibility?

  • Universal Design for Learning

1. Multiple means of Engagement (the “WHY”)

2. Multiple means of Representation (the “WHAT”)

3. Multiple means of Action and Expression (the “HOW”)

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4. What is Digital Learning Environment?

  • “A dynamic space where digital technology, education, and student engagement converge to facilitate learning.”
  • The DLE includes tools, software, applications, websites, and platforms that support instruction, collaboration, communication, and learning.

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5. What are Aspects to Improve Accessibility?

The POUR principle:

  • Perceivable

(text alternatives, time-based media, adaptable, distinguishable)

  • Operable

(keyboard accessible, enough time, seizures and physical reactions, navigable, input modalities)

  • Understandable

(readable, predictable, input assistance)

  • Robust

(compatible)

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6. Samples of Accessibility Evaluation

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6. Samples of Accessibility Evaluation

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6. Samples of Accessibility Evaluation

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7. Improving DLE Accessibility with Technology

  1. Automated Alt Text Generation
  2. Natural Language Processing (NLP) for Content Accessibility
  3. Voice User Interfaces (VUIs)
  4. Chatbots for Support and Navigation
  5. Automated Testing and Remediation
  6. User Interaction Tracking
  7. Machine Learning for Predictive Accessibility
  8. Real-time Captioning and Transcription
  9. Learning Management System Accessibility Feature
  10. Generative AI

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Example 1. Automated Alt Text Generation

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Example 2. NLP for Content Accessibility

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Example 3. Voice User Interfaces

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Example 4. Chatbots for Support & Navigation

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Example 5. Automated Testing & Remediation

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Example 6. User Interaction Tracking

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Example 7. Machine Learning for Predictive Accessibility

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Example 8. Real-time Captioning & Transcription

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Example 9. LMS Accessibility Feature (Canvas)

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Example 10. Improving Accessibility Using AI

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References

Checrallah, M., Sonnett, C., & Desgres, J. (2020). Evaluating Cost, Privacy, and Data. Accessed from: https://edtechbooks.org/digitaltoolsapps/evaluatingcostprivacydata

Fitzpatrick, J., Sanders, J. & Worthen, B. (2011). Program Evaluation: Alternative Approaches and Practical Guidelines (4th ed.). New York: Pearson.

Frederico, A., Shaikh, K., & Wang, M. (2020). Evaluating Accessibility. Accessed from: https://edtechbooks.org/digitaltoolsapps/evaluatingaccessibility

Rasmussen, J., & Andersen, H. B. (1991). Human-computer interaction: An introduction. In J. Rasmussen, H. B. Andersen, & N. O. Bernsen (Eds.), Human-computer interaction. Research directions in cognitive science. European perspectives. Vol. 3 (Vol. EUR-11768(v.3), pp. 1-26). Lawrence Erlbaum Associates.�Rubin, J. & Chisnell, D. (2008). Handbook of Usability Testing: How to Plan, Design, and Conduct Effective Tests (2nd ed.). Indianapolis, IN: Wiley.

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Thank you!

Andrias Susanto

andrias@iastate.edu

Ross Hall 321

527 Farm House Lane, Ames - Iowa, USA

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