Arizona State University Transforms Programming Education for AI Era

Artificial intelligence is reshaping the landscape of numerous professions, and software development stands at the forefront of this transformation. At Arizona State University (ASU), educators are rethinking how to equip students with the necessary programming skills in an environment increasingly influenced by AI. Faculty members in the School of Computing and Augmented Intelligence, part of the Ira A. Fulton Schools of Engineering, are pioneering new teaching methods in response to these challenges.

Erik Trickel, an assistant teaching professor at the Fulton Schools, has taken the lead in revamping the foundational course, CSE 240 Introduction to Programming Languages. Trickel acknowledges the shortcomings of traditional lectures, where students often disengaged and missed essential concepts. “Computer science isn’t something you can half-get,” he states. “You need to be able to sit down and not only write the code but also know why it works.” His goal is to foster a learning environment that emphasizes deep understanding and engagement.

Innovative Teaching Methods

With the support of instructional innovation coaches Stefani Jenkins and Jonathan Baek, Trickel has transformed the course structure from a conventional lecture format to a hybrid, flipped classroom model. This new approach focuses on collaboration and active problem-solving. Instead of passively listening to lectures, students work in small groups to tackle programming challenges, with trained staff members or teaching assistants ensuring that every participant engages in the discussion.

A cornerstone of this innovative learning model is its mastery-based grading system. Students must complete live programming challenges in a proctored setting, and they can attempt these challenges as many times as necessary until they succeed. “There’s no way to fake it,” Trickel emphasizes. “You can’t just memorize answers or copy code from online. You have to demonstrate the skill.” Weekly testing sessions provide students with opportunities to retry challenges, allowing them to refine their approach and deepen their understanding.

This structure has led to a cultural shift in the classroom. Trickel notes, “Struggle isn’t failure anymore. It’s just part of the process.”

Collaboration and Community Building

For many students, this collaborative, mastery-driven learning environment has proven transformative. Chelsea Allyson Angeles, a computer science student focusing on cybersecurity, explains, “Working in our groups is really helpful. We all have different backgrounds and ways of approaching problems. When you are thinking alone, you have no access to other perspectives.” She acknowledges the value of learning from peers, despite the usefulness of generative AI. “AI has a lot of knowledge, but it’s not always offered in a way that’s as accessible as learning from another person.”

Similarly, Mahin Patel, a sophomore in computer science, highlights the importance of social connections formed in the course. “The class really makes learning fun. I’ve met people I know I’ll stay in contact with even after it ends.” Darya Riazati, a junior in computer science, connects the course structure to real-world software development practices, noting, “Working in these kinds of groups better prepares us for what’s out there.”

The course also fosters a mentorship culture, encouraging past students to return as teaching assistants. Sriharsha Silasagaram, a sophomore who previously took the class, eagerly accepted the opportunity to help others. “The class was one of my favorites,” he says. “I wanted to come back and offer the same support I received to other students.” Trickel aims to create a cycle of learning where teaching reinforces understanding. “The best way to solidify your own knowledge is to teach it,” he explains.

Jenkins underscores the importance of training student leaders to facilitate group collaboration effectively. “We really wanted these student leaders to feel well-supported to run these groups,” she states. This preparation includes not only subject matter expertise but also skills in fostering group dynamics.

As the course evolves, it remains focused on equipping students with critical thinking, collaboration, and problem-solving skills. These competencies are increasingly vital in a world where AI tools are ubiquitous. Trickel maintains that while generative AI can serve as a valuable support resource, students must develop their coding and debugging abilities. “If you let AI do the thinking for you, you’re not actually learning,” he asserts. “We want our graduates to be the ones guiding technology, not the other way around.”

The philosophy behind the revamped CSE 240 course reflects a broader vision across the Fulton Schools and ASU. As technology continues to advance rapidly, computer science education must also adapt. By integrating collaboration, persistence, and human mentorship with modern technological tools, CSE 240 provides a glimpse into the future of programming education. “Students leave this class knowing they can do it,” Trickel concludes. “And that confidence will carry them through their careers in an AI-driven world.”