AI has many implications for the future of education. My project specifically focuses on how AI applications, like Large Language Models (LLMs) and Adaptive Tutoring Software can help bridge educational and cognitive deficits in neurodivergent learners.
Target Audience
The target audience for this project is educators and learning and development professionals who focus on teaching or creating instructional material for diverse learners. Diversity is an important component to both academic and professional settings. These new technologies, or improvements, can help tremendously.
Topic
I will be focusing on two specific technologies: LLMs and Adaptive Tutoring Technology, and explore use cases for their effectiveness at treating cognitive and social challenges in neurodiverse populations. Additionally, the research is geared mostly towards post-secondary and adult learners, but could expand based on current academic literature.
Use Cases
I expect educators and instructional designers to use my findings in order to optimize learning material and strategies for neurodivergent learners. I would like to provide insight on how the design process can be adapted to suit these individuals.
Sustainability
I plan on using volunteer researchers in order to sustain the project, and if necessary, acquire funding through grants to maintain the project over time.
Importance
Neurodivergent learners historically fall through the cracks in educational settings, both academic and professional. It's imperative that our design and facilitation practices change as we begin to understand more about neurodivergence and how people think.
Incorporated Project Technologies
We will explore both modern LLM programs available, such as ChatGPT, Perplexity, and Claude, as well as exploring Adaptive Tutoring Technologies that do not function the same as LLMs. We will also use web video platform services to make sure all information is available to the public.