Exploring AI in Education: A Look at Its Impact on Student Learning
Artificial Intelligence (AI) is increasingly being integrated into educational settings, offering both opportunities and challenges. At Carnegie Mellon University (CMU), educators are experimenting with AI tools to understand their impact on student learning and skill development.
Data Science Education and AI
Fethiye Ozis, an associate teaching professor in civil and environmental engineering at CMU, tested AI tools like Perplexity and ChatGPT in her data science courses. Students in her class used air quality data from campus sensors to identify patterns and compare air quality between buildings. The vast amount of data collected posed challenges for students, prompting Ozis to explore AI’s potential in data processing, cleaning, and visualization.
Despite the small sample size, Ozis found no significant performance differences between students who used AI tools and those who didn’t. Interestingly, 44% of students opted out of using AI, citing confidence in their own skills and a critical evaluation of AI’s utility. This raises questions about the factors influencing students’ decisions to use AI and how educators can prepare them to make informed choices.
Incorporating AI in Business Communication
Emily DeJeu, an assistant teaching professor at CMU’s Tepper School of Business, focused on teaching business communication students to use Microsoft CoPilot effectively. She aimed to find productive use cases that enhance learning outcomes. After a year, DeJeu, with the help of the Eberly Center, assessed AI’s role in improving students’ writing and its perceived usefulness in workplace communication.
The findings indicated that while AI improved writing quality, it did not necessarily enhance underlying writing skills. DeJeu concluded that extensive AI instruction wasn’t necessary, but designing assignments that don’t favor AI use was crucial. She emphasized the importance of teaching ethical AI use, as students may lack this understanding.
AI’s Role in Peer Feedback
Alan Thomas Kohler, a senior lecturer in CMU’s Writing and Communication Program, explored AI’s potential in the peer review process. In his course for computer science majors, peer feedback is essential, and Kohler incorporated AI tools like Copilot to facilitate this.
Although initial research showed no significant benefits to learning or performance, Kohler remains interested in the various ways generative AI can be used to enhance student engagement without replacing essential learning processes.
Shaping the Future of Education with AI
These initiatives are part of broader efforts at CMU to integrate AI into education. As these AI projects continue, they have the potential to influence the university’s long-term strategies in education. As Lovett noted, these studies could lead to more informed decisions about AI applications in higher education, potentially transforming degree programs and assessment methods to ensure equitable student outcomes.
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