Amin Alipour Awarded NSF Grant to Explore the Impact of AI in Computer Science Education

Computer scientist Amin Alipour is embarking on a mission to study how using artificial intelligence (AI) impacts computer science learning.

Alipour, an assistant professor in the University of Houston College of Natural Sciences and Mathematics, is the principal investigator of a new study involving UH computer science students. His research is funded by a $350,000 grant from the National Science Foundation.

Impacts of AI on Student Learning

AI has a substantial impact on everyday life; it’s the basis of technology that powers the iPhone’s “Siri” and guides self-driving cars. AI is also changing the realm of computer programming.

“New AI can automatically write computer programs from scratch,” said Alipour. “For years, only humans were capable of performing this task.” These AI systems may have a positive impact on workflow in the programming industry by making software development faster and easier. The same could also be true for computer programming assignments, which is why this technology could be attractive for computer science students.

Alipour previously developed techniques to evaluate the safety and improve transparency of AI and related systems in software engineering. This is his first study focused solely on the effects of these systems on student learning.

“We want to know when and how using AI would negatively impact the students’ learning by making them more confused or sloppy in their work,” said Alipour. For example, Alipour will be checking for a possible increase of software bugs in programs that students write.

Another negative outcome could be a student’s dependency on AI to complete assignments, rather than developing their own unique problem-solving skills to complete a task.

“Right now, the impacts of using these tools are unclear,” he said.

Providing a Support System for AI in Computer Science Education

Alipour wants to develop evidence-based frameworks to adapt these AI systems for computer science students. He plans to achieve this by looking more closely at computer science students and their interaction with these AI systems.

As part of his study, he also aims to incorporate engagement for mentors through professional development workshops and online classes related to computer science education research, along with assessment meetings with mentors. These activities will help reinforce learning and provide a solid foundation for solving issues related to adoption of AI tools in computing education.

“The results of the study will be a huge asset to computer science education and research because the computer science community will have access to lessons learned, challenges faced and products developed by our team,” said Alipour.

Collaborative Effort from Multiple Sources to Promote New Research in AI

Alipour’s study, which began in October, was selected for the grant based on NSF’s mission to promote the progress of science.

The project is supported by NSF’s EHR Core Research: Building Capacity in STEM Education Research program, which is designed to build investigators’ capacity to carry out high-quality STEM education research.

Alipour appreciates all the support he has received. Donna Stokes, NSM associate dean of undergraduate affairs and student success, and assistant professor of education Allison Master are serving as mentors for the study. He also created an advisory board for the study that includes representatives from North Carolina State University and the University of Illinois.

Additionally, Alipour collaborated with Giulia Toti of the University of British Columbia and Sruti Srinivasa of Microsoft Research in the development of the grant proposal.

“I had an outstanding group of colleagues who helped me shape and polish my application,” said Alipour. “It was definitely a team effort.”

- Chris Guillory, College of Natural Sciences and Mathematics