Can he think like your students do?

Key points:

2023 was a decisive year for artificial intelligence, with ai-in-2023-generative-ais-breakout-year_vf.pdf” target=”_blank” rel=”noreferrer noopener”>explosive growth of generative ai tools.

Since researchers at Carnegie Mellon University helped invent ai in the 1950s, ai has been transforming the way we learn, work and play, and that change is now occurring at breakneck speed.

Over the past 30 years, I have witnessed the evolution of the ai ​​landscape in education. Many early ai efforts focused on using computers to model human thinking as a way 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 skill involved developing perceptual skills that allowed them to look at a chess board and immediately see potential moves, rather than searching for every possible move.

Over time, ai split into two tracks: replicating human intelligence and expertly performing tasks thought to be unique to humans. ai chess programs, like much of ai, focused more on playing the game well and less on playing it like humans do.

In education, ai maintains its focus on cognitive modeling. Unlike chess, where the important thing is to play well, educational systems need to track students' reasoning to help them gain experience. It's not about speed or efficiency in arriving at the right answer; it is about fostering student understanding and conceptual understanding.

The experience of creating an ai that models human thinking is, perhaps, more relevant in education than in other fields. So how can we ensure that ai supports the fundamental goal of fostering student understanding, rather than simply focusing on speed, efficiency or correctness?

Here are some questions to consider when researching and evaluating ai programs for the classroom.

Does ai think like a student?

Education is about making connections with students. Because each student has different backgrounds, experiences, and interests, good teachers adjust their instruction to meet each student's needs. Good educational ai should do the same.

This is where empathy and data intersect. An effective ai program must capture the student's perspective, identifying where they stumble and why.

Take mathematics as an example. Many students form common denominators to multiply fractions, although they do not have to do so. A good teacher will recognize that this error indicates a lack of conceptual understanding of what it means to multiply fractions and how it is different from adding them. ai should do this too. An advanced ai program will have a cognitive model that helps it understand why students may confuse the two operations so that it can intervene with suggestions, recognize common errors, and guide students to a deeper understanding.

In this way, ai can also help teachers by acting as a personalized coach for students. ai can adapt to every action students take to meet them where they are and help them progress at a very granular level, skill by skill.

Does it provide teachers with critical 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 built with a live facilitation tool can provide teachers with in-the-moment data, such as when students are working or idle. Real-time alerts can indicate when students need additional support or when they have reached milestones.

When teachers have working knowledge about how their students are working and performing on specific skills or standards, as well as predictions of how much progress they are expected to make at the end of the year, they can manage, guide, coach, and intervene more effectively. .

Do you allow students to track their own progress?

In addition to providing data to teachers, ai should allow students to see their own progress. As students see their proficiency improve in each skill, their confidence grows and they feel motivated by their results. They begin to develop a sense of ownership of their learning and a sense of responsibility for their success.

Is ai impartial?

Despite its benefits, ai can also provide ethical challenges to education. For example, some ai tools have been shown to be biased. Even if that bias is unintentional, it can amplify ai-bias/” target=”_blank” rel=”noreferrer noopener”>stereotypes about race and gender.

There are many ways to protect against bias in data sets. To start, organizations that develop and deliver ai models for education (or any field) should have diverse teams. They should also rigorously test their programs to identify potential biases and then continually monitor them.

Is the technology safe and effective?

As with any technology, ai programs must protect the safety and privacy of students and comply with all applicable laws.

Additionally, participation in the program should result in better outcomes and better support for students, including those who have historically been underserved. Like other educational and edtech programs, ai-powered software should be based on evidence-based research, as well as research on how the brain learns, to give students the best possible learning experience. It must also be demonstrated through research that it measurably improves student learning, growth, and achievement.

Looking to the future

ai has immense potential to transform teaching and learning. It is time for the field of ai in education to evolve beyond mere efficiency and correctness. The real revolution lies in using ai to empower and elevate the minds of our students.