When teaching AI, drop the coding and embrace machine learning

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When you think of artificial intelligence courses, you probably picture students writing code on a computer. But that’s not where educators should start, says Joseph South, chief learning officer of the International Society for Technology in Education.

Instead, teachers should help students approach decisions the way digital programming might — by working through information, finding patterns, and making a choice.

“At ISTE, we strongly believe that students need to learn how the digital world works,” said South. “These capabilities would be incomplete without an understanding of how these extremely powerful tools work.”

Computers and digital devices are as ubiquitous to today’s students as pencils and pens were to their grandparents. People usually call Siri to send a text message or allow Netflix to choose the next show to watch. Underlying these actions is artificial intelligence, or AI, which uses a system of data analysis and algorithms to help machines make decisions about what a “Star Wars” fan might want to watch based on the information available.

Experts believe that a crucial part of learning how AI technology works is that students should learn about machine learning and start doing it when they are young. As students grow older, the curriculum can then be expanded to include ethical issues such as B. AI bias or how data is collected and applied and who ultimately owns it.

Crucially, however, teachers need to understand the subject themselves in order to help students become fluent on their own.

Using machine learning to solve problems

As you teach students the basics of machine learning and how AI works, Michael Dalley, an associate professor and director of Center for Professional Development and Education Reform at the Warner School of Education at the University of Rochester, suggests that classes should learn how to apply a machine learning approach to problem solving.

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In other words, they should learn to think like a computer.

“We know there’s an explosion of big data,” Daley said. “It’s an awareness that we think people should learn in school because their data is shared everywhere. We want them to understand what big data is and how big data is processed.”

This interest is what prompted Daley to start EAGER, a two-year project funded by the National Science Foundation to help build machine learning in K-12 students.

Part of the project is a program that converts data into a visual representation, such as a pictogram of a face. For example, the program can reflect the abundance of beetles in a certain region by making certain facial features more or less prominent in a visual representation. Eyebrows can represent the air temperature in a certain area, while the nose on the figure can show humidity and the ears could represent the number of bugs. These characteristics change with the data: for example, eyebrows may be thicker and ears smaller.

Students can then visualize the data without getting lost in the numbers. You can also drag the pictograms on top of each other to view clusters, e.g. B. Compare the faces with thinner eyebrows representing regions of lower air temperature. Patterns then appear, indicating evidence that can help students create a hypothesis.

“We think this kind of questioning is a new kind of science,” Daley said.

Standards – and laws – are required

South said ISTE started thinking about the rise of AI about five years ago, with a focus on how to support teachers to educate students on the technology and related ethical issues surrounding design for machines.

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“We wanted students to participate in activities to help them understand how AI works and what the ethical issues are,” he said. “AI reflects human values ​​and prejudices, and we wanted to expand the number and type of students designing AI.”

ISTE was developed for this purpose a partnership with GM In 2017, it started teaching educators how to teach the subject. To date, more than 1,500 teachers have been trained to think about machine learning — and in turn, they’ve taught over 3 million students, South said.

The program is free and is being launched with high schools in California, Texas and Michigan that serve populations with high levels of poverty or have populations that have historically been underrepresented in STEM subjects.