What Does Data Tell Us About AI in K-12 Education
Authors: Yerin Seung; info@ciddl.org
Generative AI is no longer a “future of education” conversation. It is already shaping lesson planning, language support, and student feedback in schools across the country. During a recent CIDDL Office Hour, evaluator Cheryl Lemke shared statewide survey data from Utah’s Digital Teaching and Learning (DTL) program. With more than 7,500 teachers, 700 school leaders, and 100 district leaders responding, the findings give us a rare, large-scale glimpse into how AI is actually being used and what still keeps educators up at night.
Utah’s Bold Steps in AI Education
Utah has taken bold, system-level steps to support AI integration in education. In a move that is rare among state education agencies, the Utah State Board of Education has created a new position, AI Director, to lead its efforts. The state also proactively negotiated licensing for AI tools, including MagicSchool AI and SchoolAI, ensuring that their use is secure, private, and tailored to district needs. These tools operate within closed systems that protect student data while offering powerful opportunities for personalization and instructional support.
What the Data Say: AI’s Growing Role
Recent survey data highlight how AI is currently being used. Teachers report applying AI to tasks such as generating lesson plans, designing assignments, creating rubrics, and improving content. At the same time, students most often use AI for brainstorming, generating step-by-step solutions to problems, and receiving writing feedback. Interestingly, a gap was observed between how students and teachers reported student use of AI, suggesting a potential discrepancy in teacher awareness or visibility into students' digital behaviors.
Real-World Classroom Examples
Teachers also provided powerful real-world examples of how they are using AI in their practice. In an elementary classroom, a teacher used an AI chatbot to translate questions and responses for an English learner, offering not only linguistic support but a personal touch by using the student’s name in their native language. In a middle school English class, students utilized a genre-specific chatbot to explore horror short stories and analyze literary elements, including pacing and foreshadowing. In science, one teacher guided students through the design of sustainable water systems using AI-generated support, followed by student-led accuracy checks to reinforce critical thinking. These examples illustrate how AI, when thoughtfully integrated, can enhance access, deepen learning, and increase engagement.
Challenges and Cautions
However, these opportunities are accompanied by challenges. Teachers and administrators cited concerns such as the time required to learn new tools, fears of plagiarism, and overreliance, which can potentially lead to cognitive decline, a lack of clear policies, and ethical concerns around privacy and misinformation. Even in a forward-thinking state like Utah, not all educators are eager to embrace AI, underscoring the need for responsive professional development that addresses both enthusiasm and hesitation.
Teacher Preparation: Bridging the Divide
One of the most important takeaways for teacher preparation is the growing divide between districts and states that are integrating AI and those that are not. This digital divide is not just technological but also pedagogical. Teacher educators must stay informed about developments in K-12 environments to prepare future teachers adequately. Candidates need opportunities to examine how AI is used in schools, critically evaluate tools, and design instructional experiences that maintain students’ agency and support higher-order thinking. As we move forward, the CIDDL team will continue supporting educators and leaders in navigating this evolving landscape.
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