Embracing AI in Education

As educators, we are constantly seeking ways to enhance our teaching methods, streamline our workload, and create a more inclusive learning environment. One of the most promising advancements in education technology is the integration of artificial intelligence (AI). AI can be a powerful tool to save time and personalize learning, but in order to get AI to work properly, the prompts you create must be very concrete and specific. People will often try AI for a task and find that its’s OK, but not great. The more specific directives you give the software, the better it does. The way AI processes language shares some intriguing similarities with how autistic students process information. Understanding these parallels can offer valuable insights into both AI utilization and inclusive teaching strategies.

The AI-Autism Connection: Clear and Explicit Instructions

Artificial intelligence, much like autistic students, requires clear and explicit instructions to function effectively. This need for precision offers a unique perspective on how we can approach teaching and technology integration in a more thoughtful and inclusive manner.

1. Explicit Instructions: The Foundation of AI and Autism

AI algorithms thrive on explicit, unambiguous instructions.

To prove this, I would like you to input two prompts into chat-GPT and think about which prompt is more robust and would help your students produce more thoughtful and aligned content. Which prompt is more useful to you?

1. Create an IEP goal for a student

2. Create IEP goals for a student in grade ______ who struggles with ___________ for the following subjects: _____________, ____________, and ______________.

Solid useful prompts can seem very long and wordy, but with longer prompts, the results that are produced are often much more aligned with what you were hoping for, whereas the shorter prompts are more generalized. The AI can only think about what you are telling it to think about (at least for now).

Similarly, autistic students often benefit from direct and explicit instructions. Ambiguities or implied meanings can create confusion and anxiety. Teachers of students on the autism spectrum may be familiar with the following situation-the teacher says to the class “everyone, line up!” All of the students head to the door and line up, except for the student on the autism spectrum. Because students on the spectrum process language in a very literal way, that student may not even be aware he or she is included in everyone, because you were not specific enough! Who is “everyone,” anyway? It doesn’t truly mean everyone, because all of the billions of the people on this earth are not actually lining up at the door. “Everyone” is a term that seems confusing, contradictory, and meaningless to some young brains. When teachers use this term, they don’t appear to say what they mean, and as a result, the student may choose to ignore it.

Often, to ensure that the autistic student follows the direction, the teacher may have to add, “Johnny, that means you too. You are a part of everyone!”

Johnny may need a social story presented to him a few times before he realizes that the term “everyone” means all of the people in the room (although confusingly, it still doesn’t mean the teacher or the teaching assistant who is in the room….)

On the other hand, if the teacher says “I would like every student in this classroom to line up at the door!” Johnny is more likely to follow through with the directive. Rather than a nebulous (and wrong) “everyone,” the teacher has made it much clearer that everyone who is a student needs to line up.

Of course, in this situation, if Johnny still doesn’t line up, he may be tired, sick, or having trouble communicating his needs, but the point is that the more specific we are with these types of students, the more likely we are to reach them and have them understand our intention.

These examples illustrate that ensuring that instructions are clear and detailed, we can support the learning processes of autistic students and AI language models.

2. Structured Environments: AI Workflows and Classroom Management

AI systems operate best within structured environments where variables are controlled, and processes are consistent. In a previous blog entry, I shared an insight from AI expert Stuart Russell on how AI models function when there are obstacles.

“There’s a big difference between asking a human to do something and giving that as the objective to an AI system. When you ask a human to get you a cup of coffee, you don’t mean this should be their life’s mission, and nothing else in the universe matters. Even if they have to kill everybody else in Starbucks to get you the coffee before it closes— they should do that. No, that’s not what you mean. All the other things that we mutually care about, they should factor into your behavior as well. And the problem with the way we build AI systems now is we give them a fixed objective.The algorithms require us to specify everything in the objective.”

In the example above, the AI would certainly not begin by killing everyone in the Starbucks. However, if the people in the Starbucks provided too many obstacles for the AI, it would not rule out doing so. After all, the primary goal is to complete the objective.

Similarly, students on the autism spectrum can often perseverate on a single topic and become very focused on this topic. When they are in this state of mind, they have a harder time contextualizing other important information that might govern their behaviour. Consider the following fictional anecdote:

A Dedicated Puzzle Solver:

In Mrs. Green's 3rd-grade classroom, there was a student named Jack who was on the autism spectrum. Jack had a remarkable ability to focus intensely on tasks he found interesting, often to the exclusion of everything else around him. One particular day, Mrs. Green introduced a challenging jigsaw puzzle to the class as a team activity. The puzzle was an intricate map of the world, meant to encourage teamwork and geographical learning.

As soon as Jack saw the puzzle, he became captivated. He loved maps and geography, and the idea of piecing together the world excited him beyond measure. He immediately sat down and began sorting the pieces by color and shape, his concentration unwavering.

Hours passed, and while the other students took breaks, played, and even went to lunch, Jack remained at his spot, meticulously working on the puzzle. He was so engrossed in fitting each piece perfectly that he didn't notice the bell ringing for recess or the calls of his friends inviting him to join their games. Mrs. Green, recognizing Jack’s deep engagement, decided to keep a discreet eye on him to ensure he was okay while allowing him to continue.

By the end of the day, Jack had completed a significant portion of the puzzle, but he hadn't eaten his lunch or gone outside for fresh air. Mrs. Green gently reminded Jack about the importance of taking breaks and eating, but she also praised his dedication and impressive progress. Jack looked up, somewhat surprised to see that the day had passed, but he was proud of what he had accomplished.

This experience highlighted Jack's ability to hyper-focus on a goal he was passionate about, demonstrating both his unique strengths and the need for support in balancing his intense focus with other important daily activities.

3. Data-Driven Personalization: AI Insights and Differentiated Instruction

AI excels at analyzing data to provide personalized recommendations and insights. For instance, AI can track student performance over time, identify areas where they struggle, and suggest targeted interventions. This data-driven approach aligns with the principles of differentiated instruction, which seeks to tailor teaching methods to meet the diverse needs of students.

Autistic students often have unique learning profiles that require personalized strategies. They are often very strong in certain areas, devoting a lot of brain energy and focus to those areas. Other areas are significantly weaker. Basically, their strengths are super strengths and their weaknesses can be particularly pronounced in comparison. Although other neurodivergent students may experience gaps between different skills, the more pronounced the gap, the more likely it is that you may be dealing with the profile of a student on the autism spectrum.

This post was, of course, meant in good fun and was not meant to dehumanize anyone. Students on the autism spectrum are human beings and can often they have a great deal of empathy and sensitivity, particularly towards animals, small children, or other vulnerable beings. They often have a strong sense of justice and aren’t afraid to go to bat for the people they love, even if it is socially risky. These are qualities that an AI will never be able to replicate. My point was, however, that the language you use to communicate matters. And whether you are communicating with AI language model or a student on the autism spectrum, the more clear and specific you are in your language, the more aligned your results will be.

Practical Tips for Integrating AI and Supporting Autistic Students at the Same Time!

1. Develop Clear, Detailed Prompts for AI Tools:

When using AI tools, ensure that prompts and instructions are specific and detailed to minimize errors and maximize effectiveness. Growing this practice can also serve as a model for providing clear instructions to students.

2. Create Predictable Classroom Routines:

Implementing consistent routines and clear expectations can help both AI systems and autistic students. In the case of students, structured environments reduce anxiety and improve focus, facilitating a more productive learning experience for all.

3. Use AI for Personalized Learning Paths:

Utilize AI to analyze student data and create personalized learning plans. This approach can help identify and address the individual needs of autistic students, providing tailored support that enhances their learning outcomes.

4. Leverage AI for Administrative Efficiency:

Automate time-consuming administrative tasks with AI, freeing up more time for teachers to focus on personalized instruction and student engagement. This efficiency can also reduce stress and create a more supportive learning environment for all students, particularly Autistic students.

5. Foster an Inclusive Mindset:

Embrace the parallels between AI and autism as an opportunity to develop more inclusive teaching practices. Recognizing the value of explicit instructions and structured environments can enhance the learning experience for all students.

Conclusion: A Synergistic Approach

The intersection of AI technology and autism-informed teaching strategies offers a powerful framework for enhancing education. By drawing on the similarities between how AI processes information and how autistic students learn, educators can develop more effective, inclusive, and innovative teaching methods while also saving time by offloading a lot of administrative, planning and marking work to AI. Embracing this synergistic approach not only leverages the potential of AI to save time and personalize learning but also fosters a classroom environment where every student can thrive.