The next phase of computer science education: incorporating AI

As AI increasingly becomes part of people’s everyday lives, educators are thinking about how to teach their students about the developing technology.

So is the Computer Science Teachers Association (CSTA): The org announced earlier this week a $1.6 million commitment to revamp CSTA K-12 Computer Science Standards to align with new technology such as artificial intelligence.

Jamie Payton, professor and chair of the Computer and Information Sciences Department at Temple University, presented on the topic’s importance as part of a Computer Science Education Week event held on Wednesday about AI’s impact on K-12 education. The event was hosted by CS4Philly, an organization focused on equity and access to computer science education for Philadelphia youth.

AI builds on computer science foundations, such as computational thinking, algorithmic thinking, encoding, storing and manipulating data.

“Now we need to layer on this piece about AI, but especially with the focus on thinking about the social impact of AI, thinking about the potential bias that can be amplified from human-collected datasets that can influence decision making that’s supported by AI-enabled systems,” she said.

Increasing capacity

One of the challenges educators face when teaching computer science and AI is capacity, Payton said. Educators want all students to have equitable access to computer science and AI opportunities, but there aren’t enough teachers available to teach the subject.

In 2022, Code.org reported that 53% of high schools in the United States offer computer science courses, and nearly 88% of high school students in Pennsylvania attend a school that offers a computer science course. However, Payton noted, only a small percentage of students are actually enrolled in these courses and are exposed to foundational concepts and AI education.

The education system needs to work together to provide equal opportunities and support teachers as they teach computer science.

AI can also be used to address inequities in education. AI-enabled learning systems often provide hints when a student needs help with a question, but Payton said educators want to advance those learning systems so they align with teacher practices. (MentoMind is developing a similar tool.)

“We’re also looking at developing skills that underlie learning,” Payton said. “And specifically we’re looking at trying to increase persistence, academic resilience and collaboration.”

Tools like this can help students deal with larger social issues they are facing and be a “way to close some of those equity gaps in educational outcomes for K-8 students,” she added.

What to do next?

Next steps include continuing to work with teachers who are already teaching computer science, and working with teachers who teach other subjects to get them certified in computer science. (The School District of Philadelphia previously received PAsmart grants from the Pennsylvania Department of Education to offer computer science training through Code.org courses for K-12 teachers.)

It’s too complicated for teachers to have to think separately about teaching specialized versions of computer science, foundational computer science, cybersecurity, AI and more, Payton said.

Instead, the best approach would be to integrate all those topics into a common training programs for teachers, common curricula that are more accessible for schools, and working with orgs such as CSTA to accomplish those goals.