Leveraging AI in Accessible Design to Transform Digital Learning
Share This Post
AI-driven tools like ChatGPT and DALL.E have only been around for a short time. However, they are already must-haves in the Accessible Design for Learning toolkit. And that’s just the tip of the iceberg. In this fast-changing world, other powerful AI platforms regularly come onstream. The words transformational and revolutionise are often overused. However, eLearning is indeed undergoing a sea change, especially when it comes to developing an inclusive digital learning environment.
In the latest of our series exploring the impact of AI on digital learning, we turn the spotlight onto Accessible Design and Universal Design for Learning (UDL). Universal Design aims to make things accessible and usable to as many people as possible, regardless of their abilities. And UDL uses these principles to create engaging, effective and accessible learning experiences for all.
Today’s post explores the relationship between AI and Accessible or Universal Design and its impacts on eLearning. We highlight the positives and the potential pitfalls. And we finish by exploring the top AI tools in UDL.
Understanding the Foundations: AI for Accessible Design in Digital Learning
UDL evolved from the Universal Design movement, which aimed to make buildings and products accessible to all. The term UDL was coined in the 1980s by researchers at the Center for Applied Special Technology. UDL has three main goals:
Representation: The aim here is to give learners various ways to acquire information and knowledge.
Action and expression: This principle is about providing learners with different ways to demonstrate what they know.
Engagement: Learning should tap into the individual’s interests, challenge them appropriately and motivate them to learn.
UDL’s guidelines help instructional designers plan programs to meet the diverse needs of all learners. And that includes those with disabilities, language barriers or different learning preferences. Content is accessible, understandable and usable for all.
And when it comes to Universal Design in digital learning, AI can personalise learning experiences, provide real-time feedback and adapt content to suit the individual’s needs. AI-driven UDL solutions ensure learners have even more opportunities to represent, express and engage in learning.
The power of AI in eLearning has already been unleashed. There’s a wealth of AI-driven UDL solutions in the digital learning space. Examples include the translation tool DeepL and Murf, which converts text-based content to audio. Later on, we’ll explore more real-world AI applications in digital learning.
Current Mechanisms: How AI and Accessible Design Interact in Today’s Digital Design
AI plays a pivotal role in shaping today’s digital learning landscape. As we’ve seen, by seamlessly integrating with Universal Design principles, AI helps create more inclusive and personalised learning experiences.
However, there are three main areas where the interaction between AI and Universal Design is having the most impact:
adaptive learning environments
voice and language technologies
Let’s take a closer look at the exciting potential of AI in each of these areas.
Adaptive Learning Environments
AI algorithms can analyse data from individual learners. Everything from their progress, preferences and performance are evaluated, and content and resources are tailored accordingly. Each learner receives a customised learning path that matches their pace, preferences and learning needs.
Voice and Language Technologies
AI-powered voice recognition and translation tools are revolutionising accessibility in digital learning. These platforms break down language barriers as AI translation tools can instantly convert content into any language, making eLearning more accessible to a global audience. Furthermore, voice recognition enables learners with disabilities to navigate and engage with digital learning platforms using voice commands.
Assistive technologies are any products, services or systems that help a person with a disability to perform a task. And in digital learning, assistive technologies, like optical character recognition and text-to-speech, captioning and subtitling, or gesture and motion recognition, are making a massive impact. These tools ensure digital learning content is more accessible and tailored to individual needs.
Navigating the Challenges: Obstacles in Merging AI and Accessible Design for Digital Learning
While there are many exciting possibilities, there are also challenges to consider. And perhaps the top concern is the ethical use of AI.
AI systems collect and analyse huge amounts of data about learners. Safeguarding personal information is paramount. Striking a balance between using data for personalised learning and data privacy is complex. However, there are steps you can take.
Informed consent is the first one. Make sure learners know what’s being collected and why. And give them the option to opt-out if they want to. Use data anonymisation and encryption techniques and delete no longer needed data. Finally, conduct regular audits to ensure compliance with privacy regulations.
It’s important to acknowledge that technological barriers are still at play, especially for institutions with limited resources.
Not everyone has access to high-speed internet. Coverage in rural locations is often patchy. And many learning institutions, let alone learners, need the latest hardware to make the most of AI applications.
Furthermore, developing and maintaining AI systems is resource intensive. A lack of in-house expertise can be a barrier, especially if you have legacy learning management systems created before the advent of AI.
In addition, most AI systems come at a cost. Ongoing subscriptions or licensing fees can be an issue for L&D departments operating on tight budgets.
Finally, there’s also an ongoing debate about whether AI-driven UDL solutions retain the depth and nuance of traditional teaching methods.
Some commentators argue that AI’s introduction has fuelled the ongoing personalisation vs. standardisation debate. They say that personalisation can come at the expense of consistency and equity.
Furthermore, traditional teaching relies heavily on human interaction. Instructors and learners share insights in face-to-face discussions and group activities. There are question marks over whether AI-UDL solutions can replicate the richness of these shared experiences.
Critics also contend that AI-powered UDL focuses on content delivery and assessment at the expense of creativity. They argue that traditional instruction methods do a better job of developing learners’ critical-thinking skills.
The Unique Value Proposition: How AI Amplifies Accessible Design in Digital Learning
Despite the obstacles we’ve just outlined, in the hands of trained learning professionals, AI can transform eLearning into a more inclusive, adaptable and effective experience.
Unlike the static learning materials of old, AI-ULD is dynamic. It adapts in real time to meet the changing needs of individual learners. And that’s gold for learners with disabilities or specific learning requirements.
Let’s break down the unique value proposition.
AI-powered accessibility tools like speech recognition, text-to-speech and image recognition level the playing field for learners with disabilities. These features support Universal Design’s goal of catering to individual needs and providing support when needed.
AI excels at analysing large data sets quickly and accurately. And this capability helps designers create highly personalised learning experiences at scale. AI amplifies the core principles of Universal Design to provide multiple means of representation, engagement and expression.
AI helps designers to make data-informed decisions. Trends and patterns in learner behaviour and engagement ensure designers continuously refine and adapt their approach to Universal Design. The result is improved learning outcomes for all.
Proceeding with Caution: Potential Pitfalls of AI in Universal Design for Digital Learning
AI undoubtedly holds enormous potential. However, before going full steam ahead, consider the following potential pitfalls.
Over-reliance on Technology
Rather than replacing humans altogether, AI should be seen as a tool to enhance the learning process. The role of instructors and fellow learners in building meaningful connections and sparking fresh insights shouldn’t be underestimated.
Furthermore, AI does not have emotional intelligence. Only people can respond to learners’ emotional and social needs essential to overall wellbeing.
AI algorithms learn from historical data. And if the data contains biases, AI-driven platforms can unintentionally perpetuate biases. This can result in certain groups of learners being disadvantaged or experiencing unfair outcomes.
Content Authenticity and Integrity
AI tools are not foolproof. There is a risk that AI-driven UDL solutions lack depth or accuracy and may even generate misinformation. What’s more, over-reliance on AI-generated content may lead to the loss of human expertise and creativity. And the richness and quality of digital learning is at stake.
Download our AI Toolkit to stay on top of the latest AI tools in Digital LearningDownload Now
Top Tools to Explore: Leading AI Platforms in Accessible Design for Digital Learning
Despite the pitfalls and obstacles, an exciting range of tools is available. The following platforms are revolutionising digital learning by incorporating the principles of Universal Design. To make things easier, we have grouped the top tools by themes.
Adaptive Learning Platforms
These platforms analyse learner behaviour and create personalised learning pathways with targeted content. Top picks here include Nolej, 360 Learning and PrepAI.
Make learning content more accessible with these must-have tools. Synthesia creates visual versions of content for visual learners. Opus is another versatile platform and helps ensure content is structured, designed and presented to accessibility standards. And use 7Taps to ensure your eLearning is mobile-friendly.
When it comes to assistive technologies, there are an exciting range of options. Our top picks here include Grammarly. This readily available platform offers literacy support to students with cognitive or language disabilities. Captioning and transcription tools like Otter.ai or Caption.Ed are also essential. And image recognition apps, such as Mercury 13 are a godsend for people with low vision.
Conclusion: The Road Ahead
The road ahead for digital learning is fast-changing and exciting, so hold on tight. Integrating AI into Universal Design can transform eLearning into a more inclusive and effective experience for all learners.
Educators, designers, technologists and policymakers should work together to harness the power of AI effectively and ethically. The potential is there to create a more inclusive digital learning environment. And we have a collective responsibility to seize the moment.
Want to find out more about how you can incorporate AI into your design practice? Check out our Professional Diploma in Digital Learning Design. Explore all the latest AI-driven UDL solutions in our comprehensive practice-led program.
Read more about how AI is affecting different facets in Digital Learning in our latest blogs!