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37th Annual CSUN Assistive Technology Conference Has Concluded

Role of Champions in Accessibility Technology Innovation

Date & Time
Wednesday, March 16, 2022 - 9:20 AM PST  
Platinum 9-10  

Higher education institutions understand the importance of equal access for all students. While the ideal approach is to incorporate UDL principles across the institution, this is not always possible. Therefore, institutions spend hundreds of thousands of dollars each year in adopting new technologies for remediation and accessibility. Often institutions license or purchase multiple tools to address the same requirement – for instance, document remediation.

While this may offer a short-term solution, in the long run using multiple tools creates inefficiencies, involves a steep learning curve, and imposes added burden on accessibility teams and faculty. Also, most accessibility teams or faculty are working on competing priorities without access to full-time staff. In this case, having access to an efficient, easy, and intuitive tool can be a huge benefit.

Another important factor to understand is how accessibility stakeholders and institutions are making decisions for equal access under immense pressures – addressing student needs, managing costs, struggling with limited time, and/or the threat of lawsuits. Another innovative tool or technology initially presents a new challenge, rather than a practical or easy solution.

Therefore, the critical considerations for building an impactful and efficient accessibility technology solution comes from working in close collaboration with accessibility experts, teams, champions, and key stakeholders.

In this presentation, we discuss the positive outcome of an innovation in accessibility technology that incorporated champions and the community. We will present the journey of PREP – an intuitive, AI-based PDF Remediation Platform – that utilized key user feedback from accessibility teams at leading higher educational institutions such as George Mason University.

In 2020, Continual Engine and George Mason University engaged in a beta trial to test, validate, and enhance PREP’s capabilities. These pilots played a critical role in gaining a deep understanding of existing solutions, workflows, and approaches, understanding where to incorporate collaborative intelligence approaches (technologies built for humans to provide context), and gathering feedback and use cases from end-users throughout the process to vet, test, and make improvements.

The result was a robust, intelligent, and intuitive technology solution for document remediation. It is the marriage of innovative technology closely developed with end-users that leads to effective accessibility solutions that can easily scale and lift up thousands of learners who would otherwise be left behind.

This Presentation Link is provided by the Presenter(s) and not hosted by the Center on Disabilities at CSUN. The Center on Disabilities has confirmed, as of April 1, 2022, content linked is relevant to the presentation, but has not been reviewed for accessibility nor will the Center on Disabilities attempt to remediate any accessibility issues in the linked content. Please contact the Presenter(s) with any accessibility concerns.

  • Higher Education
  • K-12 Education
  • Government
  • Finance & Banking
  • Administration & Business Support
Audience Level
Session Summary (Abstract)
Continual Engine and George Mason University share their journey on how user feedback supported the development of PREP - an artificial intelligence-based intuitive solution for document remediation (PDFs, Word, PowerPoints, etc). This session highlights the impact of early collaboration; role of focus groups; and using data to measure success.  
Session Type
General Track  
  • Artificial Intelligence (AI) & Machine Learning (ML)
  • Blind/Low Vision
  • Cognitive & Learning Disabilities
  • Digital Accessibility
  • Evaluation & Remediation


  • Vijayshree Vethantham
    Continual Engine US LLC
  • Korey Singleton
    George Mason University
  • Rajiv Narayana
    Continual Engine US LLC

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