PREP: An AI-Enabled Document Remediation Solution Designed to Make STEM and Complex Content Accessibility More Intuitive

Handouts

Scheduled at 10:30am in Colorado I-J on Friday, November 18.

#36207

Speaker(s)

  • Vijayshree Vethantham, Vice-President, Partner Engagements, Continual Engine US LLC
  • Rajiv Narayana, Chief Learning Officer, Continual Engine

Session Details

  • Length of Session: 1-hr
  • Format: Lecture
  • Expertise Level: Beginner
  • Type of session: General Conference

Summary

Higher education institutions adopt multiple tools to address the same need – i.e. document remediation. In the long run multiple tools create inefficiencies. If it involves a steep learning curve, it imposes a burden on accessibility teams and faculty. Also, accessibility solutions rarely focus on complex content that are hard to make accessible - STEM, tables, and lists. Let’s look at how PREP is evolving to make STEM and complex content accessible easily while lowering the learning curve.

Abstract

With growing recognition about accessibility, more organizations and individuals want to make their documents and online content inclusive. When accessibility is no longer a trend but an essential practice, technology needs to incorporate usability for a whole new audience previously not considered. 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 can present a new challenge, rather than a practical or easy solution. PREP is an artificial intelligence-enabled document remediation tool designed with accessibility experts and users of accessibility technology tools, developed with the goal of making document remediation intuitive, quick, and easily scalable by: Accelerating the time involved in making complex documents accessible Automating and limiting the need for manual decision-making during remediation, especially for complex STEM content, tables, and lists Shortening the learning curve for new or part-time users Making it easily understandable and accessible for non-expert users On-demand learning through built-in video resources Incorporating existing approaches and best practices in document remediation Supporting scale, multiple document formats, structures, and complexities In 2020, Continual Engine engaged with a couple of leading institutions including George Mason University to test, validate, and improve 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) 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 solution for document remediation.

Keypoints

  1. AI solutions that improve user experience in document remediation can accelerate institutional accessibility
  2. Accessibility solutions need to address complex content which take up disproportionate time to make accessible
  3. PREP was developed with the community to make the document remediation process intuitive and easier

Disability Areas

Cognitive/Learning, Other, Vision

Topic Areas

Accessible Educational Materials, Alternate Format, Assistive Technology, Faculty Development & Support, Uncategorized

Speaker Bio(s)

Vijayshree Vethantham

Vijayshree has over 15 years of experience leading multidisciplinary teams, and managing key client partnerships in higher education and accessibility as part of the founding team of two education-based start-ups – ansrsource and Continual Engine. Her experience includes building impactful partnerships with large publishers and institutions, understanding their content and learning goals, and guiding solutions to enable scalable, and accessible learning experiences. Vijayshree leverages her deep knowledge of start-ups, higher education, and custom content development along with the potential of AI and technology in education to create thriving engagements with higher education organizations and partners. Over the last couple of years, Vijayshree has dedicated her time to exploring how robust and pragmatic educational technology, designed with the intention of solving a problem, can enable transformation, inclusion, diversity, accessibility, and affordability for all learners.

Rajiv Narayana

Rajiv has 16 years of experience leading a team of learning content designers and developers as a co-founder of ansrsource. He has also worked with the artificial intelligence learning organization Continual Engine as its Chief Learning Officer. He brought his journalism experience in large scale editorial environments to learning at a time when there were not many firms specializing in digital learning design and development. The combination of speed, scale, and sophistication set ansrsource apart, and is why Rajiv has been able to forge strong relationships with the largest and most progressive learning organizations in the world. Rajiv has used this knowledge and trust earned over years of producing high quality learning experiences to bring new approaches to accessibility to leading Universities and Publishers.

Handout(s)

  • AI Solution to Make Complex PDFs Accessible._11.17.2022_Handout

    Session on PREP - Artificial Intelligence-Based PDF and Document Remediation Platform

    Session on PREP - Artificial Intelligence-Based PDF and Document Remediation Platform that has been trained, tested, and vetted for significantly improving efficiencies for complex documents such as STEM documents, scanned pages, documents with tables and lists, and forms.

AI Solution to Make Complex PDFs Accessible._11.17.2022_Handout