AI’s Role in Education: Beyond Efficiency and Correctness
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AI in Education: A Growing Force
2023 was a breakthrough year for artificial intelligence, with explosive growth in generative AI tools. Since researchers at Carnegie Mellon University helped invent AI in the 1950s, AI has changed the way we learn, work, and play—and that change is now happening at breakneck speed.
Over the last 30 years, I have witnessed the evolving landscape of AI in education. Many early AI efforts focused on using computers to model human thinking to confirm our understanding of how the human mind works. For example, Herb Simon and others studied how chess masters played the game to understand problem solving. They discovered that much of their ability came from developing perceptual skills that allowed them to look at a chessboard and immediately recognize possible moves, rather than scanning through all possible moves.
Over time, AI split into two streams: replicating human intelligence and expertly performing tasks thought to be the preserve of humans. AI chess programs, like many AI programs, focused more on playing the game well and less on playing it the way humans do.
Focusing on Cognitive Modeling in Education
In education, the focus of AI continues to be on cognitive modeling. Unlike chess, where the point is to play the game well, education systems need to track students’ reasoning to help them build expertise. It’s not about speed or efficiency in finding the right answer; It’s about developing a student’s understanding and conceptual understanding.
The experience of creating AI that models human thinking is perhaps more relevant in education than in other fields. So how do we ensure that AI supports the fundamental goal of advancing a student’s understanding rather than just focusing on speed, efficiency, or correctness?
Key Questions for Evaluating Educational AI
Does the AI think like a student?
Education is all about making connections with students. Because every student has different backgrounds, experiences, and interests, good teachers tailor their lessons to each student’s needs. Good educational AI must do the same.
This is where empathy and data meet. An effective AI program should capture the student’s perspective and identify where they stumble and why.
Take mathematics for example. Many students create common denominators to multiply fractions even when it is not necessary. A good teacher will recognize this error as an indication of a lack of conceptual understanding of what multiplying fractions means and how it differs from adding. AI should do this too. An advanced AI program has a cognitive model that helps it understand why students might confuse the two operations, so it can intervene with hints, detect common errors, and guide students toward deeper understanding.
In this way, AI can also help teachers by acting as a one-on-one coach for students. The AI can adapt to students’ every action to meet them where they are and help them progress at a very granular, skill level.
Does it provide teachers with important data to help them guide students in real time?
There are some things that technology excels at, like collecting data, and other things that teachers excel at, like teaching and motivating students. AI equipped with a live moderation tool can provide teachers with up-to-date data, such as when students are working or inactive. Real-time alerts can indicate when students need additional support or have reached milestones.
When teachers have actionable insights into how their students are working and performing on specific skills or standards—as well as predictions about how much progress they are likely to make by the end of the year—they can manage, guide, coach, and intervene more effectively.
Does it allow students to track their own progress?
In addition to providing data to teachers, AI aims to enable students to see their own progress. As students see their abilities improve in each skill, their confidence grows and they become motivated by their results. They begin to develop a sense of ownership over their learning and a sense of responsibility for their success.
Is the AI unbiased?
Despite its benefits, AI can also pose ethical challenges for education. For example, some AI tools have been shown to be biased. Even if this bias is unintentional, it can reinforce stereotypes about race and gender.
There are many ways to protect against bias in data sets. First, organizations developing and leading AI models for education – or any other field – should have diverse teams. They should also test their programs thoroughly to identify potential biases and then continually monitor them.
Is the technology safe and effective?
As with any technology, AI programs should protect student safety and privacy and comply with all applicable laws.
Additionally, participation in the program should result in better outcomes and support for students, including those who have been historically underserved. Like other education and edtech programs, AI-powered software should be built on evidence-based research and research on how the brain learns to provide students with the best possible learning experience. It should also be proven through research to measurably improve student learning, development, and achievement.
Looking Ahead
AI has enormous potential to transform teaching and learning. It is time for the field of AI in education to move beyond mere efficiency and correctness. The real revolution lies in using AI to empower and nurture the minds of our students.
For more news on AI in education, visit eSN’s Digital Learning page. Here
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