Artificial intelligence can support student learning, but its impact depends on how the technology is designed and used. In a recent Hechinger Report article, Jing Liu, associate professor of education policy and director of the Center for Educational Data Science and Innovation, discusses two studies that reveal contrasting outcomes of AI in education. One found that AI-powered math practice was associated with improved outcomes for middle school students, while another found that an AI assistant adversely affected college students’ grades and engagement. Intentional about releasing the studies together, Liu’s findings underscore the importance of evaluating AI tools in real learning environments to fully understand their impacts.
The lesson isn’t that colleges should avoid AI, Liu says. It’s that even a carefully designed tool can have consequences beyond its intended use. And Maryland deserves credit for testing the assistant before a university-wide rollout and for making the troubling results public for the whole field to learn from.
