How do we ensure that AI supports the fundamental goal of fostering a student’s understanding, rather than simply focusing on speed, efficiency, or correctness, questions Dr. Steve Ritter of Carnegie Learning, writing in eSchool News.
Here are a few considerations:
Does AI think like a student?
Good teachers adjust their instruction to match each student’s needs. Good educational AI needs to do the same thing. This is where empathy and data intersect. An effective AI program should understand the student’s perspective, identify where they stumble and why.
In math, many students form common denominators to multiply fractions, even though they do not need to do so. A good teacher recognizes this error indicates a lack of conceptual understanding about what multiplying fractions means and how it differs from adding them. An advanced AI program will have a cognitive model that helps it understand why students might confuse the two operations so it can intervene with hints, recognize common errors, and guide students toward a deeper understanding.
AI can also assist teachers by acting as a one-to-one coach for students. AI can adjust to every action students take, meeting them where they are and helping them progress at a very detailed, skill-by-skill level.
Does it give teachers data to help them guide students in real-time?
Some things technology excels at, like collecting data. And other things teachers excel at, like teaching and motivating students. AI that is 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 extra support or when they’ve reached milestones.
Give teachers actionable insights into how their students are working and performing on specific skills or standards–as well as predictions of how far they are expected to progress by the end of the year–and they can manage, guide, coach, and intervene more effectively.
Can students track their own progress?
AI should enable students to see their own progress. When students see their proficiency improve in each skill, their confidence grows, and they are motivated by their results. They begin to own their learning and possess a sense of responsibility for their success.
Is there the potential for bias?
AI can also bring ethical challenges to education. Some AI tools exhibit bias. Even if it’s unintentional, a bias can amplify stereotypes about race and gender.
To guard against bias in data sets, organizations that develop and instruct AI models for education–or any field–should have diverse teams. They should rigorously test programs to identify potential bias and continually monitor the programs.
Is student privacy and security ensured?
AI programs should protect student security and privacy and follow all applicable laws.
Engaging with the program should produce improved outcomes and better support for students, including those who have been historically underserved. To give students the best learning experience possible, AI-powered software should be built on evidence-based research, as well as research on how the brain learns. It should be proven by research to measurably improve students’ learning, growth, and achievement.
It’s time that the use of AI in education evolves beyond mere efficiency and correctness. The true revolution is using AI to empower and elevate the minds of our students.
eSchool News
