As artificial intelligence becomes more prevalent in educational settings, its use has expanded beyond students to professors, with both groups incorporating AI tools like chatbots into their daily routines. Recent data from an AI firm reveals intriguing insights into how educators utilize this technology worldwide.
AI Adoption Among Professors
Georgia State University professor Sue Kasun has turned to Gemini, an AI model developed by Google, for assistance in brainstorming new course assignments. Kasun notes, “There were, like, suggestions of offering different choices, like having students generate an image, having students write a poem.” The course in question focuses on integrating culture and identity into language education for immigrant youth. Despite her creativity, Kasun acknowledges the time constraints educators face.
Data Insights from Anthropic
Drew Bent, who leads education research at AI company Anthropic, reveals that education is a significant use case for their AI chatbot, Claude. Bent explains, “When we looked into the data late last year, we saw that of all the ways people were using Claude, education made up two out of the top four use cases.” The analysis, based on 74,000 interactions over 11 days, highlights professors’ use of AI for curriculum development and academic research. Additionally, AI aids in automating administrative tasks such as email drafting and budget creation.
Concerns and Criticisms
While AI is used for a variety of tasks, grading student work represented about 7% of the analyzed conversations. Bent notes, “It wasn’t the top use case. But it was one of the use cases where, when educators use AI for grading, they often automate a lot of it away, and they have AI do significant parts of the grading.” However, Marc Watkins from the University of Mississippi expresses concern about using AI in grading, worrying it could weaken professor-student relationships and higher education’s value. He warns of a “nightmare scenario” where students and teachers rely solely on AI for writing and grading papers, questioning the purpose of education in such a scenario.
Future Implications
Professor Kasun shares this unease about using AI for grading but finds AI beneficial for other educational purposes. She calls for more institutional support and guidance on effectively integrating AI into academia, stating, “We are here, sort of alone in the forest, fending for ourselves.” Bent argues for partnerships between tech companies and educational institutions while maintaining that “us as a tech company telling educators what to do or what not to do is not the right way.” Both Bent and educators agree that current decisions on AI use in education will have long-lasting effects on students.
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