While many rural students grow up surrounded by agriculture, few have opportunities to learn how data and artificial intelligence are shaping the future of the industry.

Dr. Tugce Aldemir, an assistant professor in the Department of Teaching, Learning and Culture at Texas A&M University, wants to change that. Supported by a National Science Foundation CAREER award, Aldemir is creating an AI-guided agriculture STEM (Ag-STEM) learning model that will help rural middle school students use data, technology and scientific inquiry to address the agricultural challenges affecting their own communities.

“Many students understand the land, weather, water and agriculture because of where they grow up,” said Aldemir. “They just don’t always realize that knowledge is part of science.”

The five-year project will place students in the role of researchers and problem solvers. Working in teams, they will build and troubleshoot low-cost environmental sensors, collect and analyze data related to soil, water and air quality, investigate challenges to sustainability and develop recommendations based on the evidence they collect.

Connecting STEM Learning to Real-World Challenges

Modern agriculture increasingly relies on data analytics, automation and AI. From monitoring soil moisture and crop health to optimizing the use of irrigation and fertilizer, farmers rely on technologies that help improve efficiency and conserve resources.

Aldemir’s project seeks to bridge the gap between what students experience in their communities and the technologies driving one of Texas’ most important industries.

Participating students will take on roles such as soil scientist, agronomist and plant pathologist. As they collect data and test ideas, they will learn computational thinking skills such as identifying patterns, troubleshooting problems, evaluating evidence and making informed decisions.

The goal is not necessarily to turn every student into a computer programmer, but more to help them become a confident, critical and data-informed problem solver,” said Aldemir.

Caldwell Junior High teacher Danielle Hicks was instrumental in the early work of this project. (Photo courtesy: Caldwell ISD)

Using AI as a Tool for Thinking

A key feature of the project is a classroom-safe AI peer mentor that helps guide students through the exploration process. Unlike traditional AI tools that are mostly designed to provide answers, the system is intended to support student thinking through questions, prompts and feedback that encourage reflection and problem-solving.

The approach builds on years of prior work supported through internal grants from the College of Education and Human Development. Working alongside teachers in Caldwell and Brenham junior high schools, Aldemir and her collaborators explored how AI could support student thinking, rather than replace it.

This interdisciplinary effort involved Aldemir’s Collaborative Human-AI Learning Ecologies for STEM+ (CoHALE) laboratory, along with Dr. Ali Bicer of Teaching, Learning and Culture, Dr. Donggil Song of the Texas A&M College of Engineering, Dr. Ram L. Ray from Prairie View A&M University and Dr. Yasmin Kafai from the University of Pennsylvania.

Building Confidence Through Discovery

The early classroom experiences of the project have already revealed the potential impact of this approach. In one classroom activity, students encountered impossible moisture readings from sensors they assembled. Instead of immediately seeking help, they worked together to troubleshoot the problem, trace the issue to faulty wiring and successfully collect new data.

Aldemir has also seen students who never viewed themselves as “science kids” emerge as leaders while explaining findings to their classmates.

Supporting Rural Communities

The project reflects a broader effort to ensure rural students can fully participate in an economy increasingly shaped by technology and data. While many students already have firsthand knowledge of agriculture, Aldemir believes those experiences can serve as powerful foundations for STEM learning and future careers.

This research is also rooted in strong partnerships with rural educators. Teachers have played a central role in co-designing lessons, refining activities and ensuring the learning experiences fit the realities of rural classrooms. Among those partners is Caldwell Junior High agriculture teacher Danielle Hicks, whose classroom helped inform some of the project’s earliest pilot work.

One participating teacher also began using the same sensor technology introduced through the project on her own farm after seeing its potential for making better decisions in agriculture.

Aldemir is proud of being able to conduct this research with the help of the NSF CAREER program, which is the foundation’s most prestigious award for early-career faculty. Ultimately, she says success will ultimately be measured by the opportunities created for students.

“I want students to see that the knowledge they already have is valuable,” said Aldemir. “They can use that knowledge along with data and technology to solve problems and make a difference in their own communities.”

For media inquiries, contact Ruben Hidalgo.