#8 | Supporting learners with ADHD

After reading "Stolen Focus" by Johann Hari, which highlights the growing difficulty in maintaining focus in today's society, I became intrigued by the potential of generative AI to support learners who struggle with attention, particularly those with ADHD.

How might we leverage generative AI to support learners with ADHD?

According to the CDC, 9.8% of children in the US are diagnosed with ADHD. Of course, this figure should be interpreted cautiously as it does not account for undiagnosed cases and potential misdiagnoses. Furthermore, statistics for ADHD in adults are not reported by the CDC, despite studies suggesting that less than 20% of adults with ADHD are aware of their condition (source: WebMD).

As someone who recently discovered my own ADHD, I delved into the fascinating science behind it, during which I came across the ICNU framework proposed by William Dodson, M.D..

ICNU - Interest, Challenge, Novelty, and Urgency

Dr. Dodson explains that while neurotypical individuals make decisions based on Importance, Rewards, and Consequences, those with ADHD often prioritize Interest, Challenge, Novelty, and Urgency (ICNU) in their decision-making process.

Here are some ways Generative AI can effectively leverage the ICNU criteria to support individuals with ADHD:

Interest

Generative AI can adapt content to align with personal interests. For instance, when teaching percentages and probabilities, the same math problem can be framed differently based on individual preferences. An avid basketball fan might engage with the topic through the probabilities of the San Antonio Spurs' first-round draft pick, while a student fascinated by whales might explore the probabilities of humpbacks migrating at specific times and locations.

Challenge

Vygotsky's theory of the zone of proximal development suggests that learning is optimized when individuals work on tasks slightly beyond their comfort zone with appropriate guidance. Generative AI enables real-time adjustment of the level of challenge based on learners' performance and can provide tailored guidance to support learning and sustain attention.

Novelty

Although more challenging, generative AI can introduce novelty to learning experiences through gamified elements and varied interactions with the content.

Urgency

While urgency can be incorporated through gamified elements such as time counters that adjust based on previous iterations - which directly relates to the notion of challenge - and increase focus and attention, it may not be the most suitable approach for increasing learning outcomes. Prioritizing interest, challenge, and novelty can enhance focus and attention without compromising the learning process.

• Content Relevance: Personalized content poses the challenge of ensuring its reliability, pedagogical relevance, and safety. Thorough testing and continuous improvement of the algorithms, along with safeguard measures, are crucial to maintaining educational quality.

• Distractions: Striking the right balance between attention-enhancing tools and potential distractions is vital. Learning objectives should always remain the priority, and any added elements must align with the goal of facilitating such learning.

• Educator Involvement: Generative AI tools should not replace educators but rather empower them to better apply their content to each learner's context. Local monitoring of the tools’ output is essential to ensure educational soundness.

I believe generative AI holds significant promise in designing tools that can assist learners with ADHD in staying focused and on task, thereby enhancing their learning capacity.