Teachers Turn to AI for Productivity, Reveals Stanford Study

A recent study from Stanford University highlights how teachers are increasingly relying on artificial intelligence (AI) tools to enhance their productivity. Researchers found that while many educators utilize AI, their focus tends to be more on tools that aid their teaching rather than on student-facing applications like chatbots. This finding comes amid a growing interest in understanding the practical applications of AI in education.

The study tracked the AI usage of approximately 9,000 U.S. teachers who began using the platform SchoolAI between August 1 and September 15, 2024. Over a span of 90 days, researchers analyzed usage logs instead of relying on self-reported data, which can often be unreliable. According to Chris Agnew, director of Stanford’s project, “We all know that humans are flawed at reporting our own behavior accurately.”

The analysis revealed that not all teachers used AI consistently. In fact, 16% of the educators logged in only once, while 43% were short-term users. Only 41% became regular users, accessing the platform between eight and 49 days out of the total 90. A mere 1% of participants, classified as “power users,” logged in for more than 50 days. Agnew noted that the adoption rates among teachers were slightly higher than typical software retention rates, which hover around 30% after three months.

The findings suggest that teachers are integrating AI into their workflows on an as-needed basis rather than making it a fixture of their daily routines. During the study, approximately one-third of the participants utilized the platform in a given week. The data also indicated variability in usage patterns; not only did the frequency of use differ among teachers, but so did their preferred tools. SchoolAI offers a variety of resources, including student-facing chatbots, lesson generators, grading aids, and teacher assistant chatbots.

Interestingly, lighter users often engaged more with student-facing chatbots, while those who used the platform more frequently gravitated towards tools designed for teacher support. Power users, in particular, spent over 80% of their time on productivity-enhancing features, largely bypassing student tools from the outset. Agnew described this trend as a reflection of a “human in the loop” approach to AI in education, where teachers can apply their expertise to AI-generated outputs to inform their teaching practices.

Moreover, the study uncovered patterns concerning when teachers prefer to use AI tools. Although one might expect that educators would turn to AI after hours for grading and lesson planning, the data revealed that most teachers accessed these tools during weekday mornings. While the research did not explore the reasons behind this timing, Agnew speculated that teachers might be using AI to brainstorm ideas or prepare materials before classes begin. “This is a partner for them in their teaching practice as they are orienting themselves to the school day,” he remarked.

The researchers acknowledge that tracking active days does not provide a complete measure of the impact of AI on teaching. Moving forward, the next phase of the study will delve deeper into the content of teacher-AI interactions and examine how students engage with the platform. This exploration may reveal distinct patterns in student usage that could further inform the integration of AI in educational settings.

As AI tools continue to evolve, understanding their real-world application in classrooms remains crucial for both educators and stakeholders in the education sector.