Teachers-in-training and their university educators feel ill-equipped to integrate generative artificial intelligence into classrooms, a recent survey reveals. The findings highlight a critical need for institutions to provide clear guidelines and professional development opportunities for faculty.
Educators Seek Guidance on AI Integration
A significant majority of both aspiring teachers and their professors report receiving no training on how to use generative AI in educational settings.
As artificial intelligence rapidly becomes a fixture in society, a new survey indicates that both future educators and the professors training them feel unprepared to adopt this technology in their classrooms. The crucial takeaway is that while students are eager to learn about AI and teachers want to teach it, institutions are currently lacking the necessary support systems.
Priya Panday-Shukla, an instructional designer at WSU Global Campus, authored the paper in Teaching and Teaching Education. She emphasizes that faculty, despite being subject matter experts, require institutional backing to understand AI’s capabilities, limitations, and ethical considerations. This foundational knowledge is essential for educators to make informed decisions about whether or not to incorporate AI tools into their courses.
“The whole point is that if faculty have that information, they will be able to make an informed decision: ‘OK, this is what I teach, this is what I do, and maybe I could use it for this or for that—or maybe I should not use it,’” Panday-Shukla explained.
Key Insight: Students are asking to learn more about AI, and teachers are asking to learn more about AI, but the support structure is currently lacking, according to Panday-Shukla.
Panday-Shukla surveyed 52 pre-service teachers and 21 teacher educators in early 2024. The pre-service teachers had an average age of 20, with most graduating in 2025. The teacher educators averaged 54 years old and had extensive university teaching experience. Follow-up interviews were also conducted.
While attitudes toward generative AI varied, a substantial portion of both groups reported no training in implementing AI in their classrooms. Specifically, 48 of the 52 students hadn’t used AI in their current classes and received no training on its use in teaching. Similarly, 18 of the 21 professors surveyed were not using AI and had not received training.
Panday-Shukla suggests that a lack of familiarity with AI might cause some professors to avoid it, which she argues does a disservice to students entering a workforce increasingly shaped by this technology. One estimate suggests that up to 30% of current work hours could be automated within five years, necessitating career shifts for millions.
To address this gap, Panday-Shukla developed a workshop for educators. This workshop offers a framework for considering AI integration. Building on K-12 AI matrices, she created a system with four graduated levels of AI use in classrooms, from outright prohibition to mandatory use. This framework aims to help educators establish transparency and provide clear guidance to students regarding AI assistance for assignments and necessary usage protocols.
Panday-Shukla stresses that AI is not a substitute for original research, writing, or academic rigor. “When you need to verify information, you still do it the old way,” she stated. “You check it one source at a time, one piece of information at a time. It’s no different from that.”
Her own paper exemplifies transparent AI use. She acknowledges in her publication that she used Google Gemini to review passages for clarity and readability, treating the suggestions as options rather than direct solutions. Such declarations are becoming a standard requirement in academic journals.
“It’s just another tool that requires thoughtful integration, and therefore, we have to learn how to use it properly,” she concluded.
