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Teachers feel most productive when they use AI for teaching strategies

Teachers turn to artificial intelligence for help with a variety of tasks. New research reveals which ones − and how − AI can help teachers with the most.

Saving time is not a given for teachers who rely on artificial intelligence. skynesher/E+ via Getty Images

Teachers can use generative AI in a variety of ways. They may use it to develop lesson plans and quizzes. Or teachers may rely on a generative AI tool, such as ChatGPT, for insight on how to teach a concept more effectively.

In our new research, only the teachers doing both of those things reported feeling that they were getting more done. They also told us that their teaching was more effective with AI.

Over the course of the 2023-2024 school year, we followed 24 teachers at K-12 schools throughout the United States as they wrestled with whether and how to use generative AI for their work. We gave them a standard training session on generative AI in the fall of 2023. We then conducted multiple observations, interviews and surveys throughout the year.

We found that teachers felt more productive and effective with generative AI when they turned to it for advice. The standard methods to teach to state standards that work for one student, or in one school year, might not work as well in another. Teachers may get stuck and need to try a different approach. Generative AI, it turns out, can be a source of ideas for those alternative approaches.

While many focus on the productivity benefits of how generative AI can help teachers make quizzes or activities faster, our study points to something different. Teachers feel more productive and effective when their students are learning, and generative AI seems to help some teachers get new ideas about how to advance student learning.

Why it matters

K-12 teaching requires creativity, particularly when it comes to tasks such as lesson plans or how to integrate technology into the classroom. Teachers are under pressure to work quickly, however, because they have so many things to do, such as prepare teaching materials, meet with parents and grade students’ schoolwork. Teachers do not have enough time each day to do all of the work that they need to.

We know that such pressure often makes creativity difficult. This can make teachers feel stuck. Some people, in particular AI experts, view generative AI as a solution to this problem; generative AI is always on call, it works quickly, and it never tires.

However, this view assumes that teachers will know how to use generative AI effectively to get the solutions they are seeking. Our research reveals that for many teachers, the time it takes to get a satisfactory output from the technology – and revise it to fit their needs – is no shorter than the time it would take to create the materials from scratch on their own. This is why using generative AI to create materials is not enough to get more done.

By understanding how teachers can effectively use generative AI for advice, schools can make more informed decisions about how to invest in AI for their teachers and how to support teachers in using these new tools. Further, this feeds back to the scientists creating AI tools, who can make better decisions about how to design these systems.

What still isn’t known

Many teachers face roadblocks that prevent them from seeing the benefits of generative AI tools such as ChatGPT. These benefits include being able to create better materials faster. The teachers we talked to, however, were all new users of the technology. Teachers who are more familiar with ways to prompt generative AI – we call them “power users” – might have other ways of interacting with the technology that we did not see. We also do not yet know exactly why some teachers move from being new users to proficient users but others do not.

The Research Brief is a short take on interesting academic work.

Some of the teachers involved with the initial case study were known to the authors before the start of the case.

Some of the teachers involved with the initial case study were known to the authors before the start of the case.

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