Progress 09/01/24 to 08/31/25

Outputs
Target Audience:The target audience for this reporting period consisted of 18 secondary students from San Marcos, Texas, and nearby rural communities who have limited access to STEM enrichment and smart agriculture technologies. The program engaged these students to increase awareness of STEM opportunities and encourage interest in pursuing higher education pathways in agriculture and advanced technology. A secondary audience included four post-secondary students at Texas State University who contributed to mentoring and research activities in smart agriculture, gaining experience in leadership, collaboration, and applied technology. This audience focus aligns with the project's goal of expanding participation and preparedness among underrepresented students in the region. Changes/Problems:During the reporting period, there were no problems with the original project approach. However, the project received supplemental funding to enhance the WAM-SA program by integrating advanced AI-focused training, hands-on activities, and data-driven smart agriculture projects. This enhancement represents a planned expansion rather than a change in the original approach. The supplemental funding allows the program to double the number of secondary student participants and increase postsecondary mentor involvement, while also developing open-access digital learning resources for AI in precision agriculture. These enhancements will strengthen experiential learning in drones, sensors, data analytics, and AI, and broaden the program's outreach and impact without altering the core objectives of the original project. No special or additional reporting requirements have been imposed beyond those in the award Terms and Conditions. What opportunities for training and professional development has the project provided?The project offered significant training and professional development for both secondary and postsecondary participants. Secondary students completed structured technical training in smart agriculture technologies, including drone operation and remote sensing, soil and environmental sensing, CAD modeling, 3D printing, data analytics, and introductory AI tools. They also participated in professional development modules focused on communication, résumé preparation, mock interviews, and technical presentations. Postsecondary mentors advanced their professional skills through leadership training, instructional experience, and direct facilitation of student teams during labs and project activities. These combined experiences strengthened technical proficiency, communication, and overall career readiness for all participants. How have the results been disseminated to communities of interest?The project engaged in several outreach activities to disseminate program information and expand awareness among communities traditionally underrepresented in STEM and agriculture. Texas State undergraduate students serving as student teachers in local high school agriculture programs introduced the WAM-SA internship in their classrooms, reaching secondary students who may not typically be exposed to emerging technologies in agriculture. Outreach was further supported through parent and community networks, where program flyers were shared to broaden visibility and encourage participation among families unfamiliar with STEM enrichment opportunities. Faculty also distributed informational materials during Bobcat Days, allowing direct engagement with visiting high school students, families, and educators. These interactions provided an opportunity to discuss the program structure, internship activities, and the broader importance of smart agriculture technologies. Collectively, these outreach pathways enhanced public understanding of STEM applications in agriculture and increased community awareness of experiential learning opportunities available through the program. Dissemination efforts will continue as the project advances, with updated materials incorporated into future recruitment and public engagement activities What do you plan to do during the next reporting period to accomplish the goals? During the next reporting period, the project will launch additional WAM-SA internship cohorts and expand the curriculum with new AI-focused training modules, hands-on activities, and data-driven smart agriculture projects supported by the recent supplemental funding. This funding will allow the program to double participation among both secondary and postsecondary students. Planned efforts include refining drone-based sensing modules, strengthening sensor-instrumentation and data analytics activities, and enhancing leadership and communication training to support professional skill development. The near-peer mentorship structure will be further optimized to improve collaborative learning and individualized guidance. The team will also improve tracking of participant outcomes and broaden outreach through university communication channels, STEM engagement events, and targeted community partnerships.

Impacts
What was accomplished under these goals? Goal 1: During the reporting period, the project successfully launched the first two cohorts of the WAM-SA internship program, providing a total of eight weeks of structured experiential learning for secondary students from women and minority groups. Key accomplishments aligned with Goal 1 include: (1) Experiential learning and hands-on experiences: A total of 18 secondary students in two cohorts completed the four-week internship program, receiving hands-on training in smart agriculture technologies, including drone-based remote sensing, soil and environmental sensing, data analytics, and introductory AI tools. Students also delivered technical presentations demonstrating their understanding of STEM applications in modern agriculture and the use of emerging technologies to monitor and analyze agricultural systems. (2) Outreach to secondary schools: Student-led visits and recruitment efforts engaged additional students and schools, laying the groundwork for participation in future cohorts and raising awareness of STEM opportunities in smart agriculture. (3) Financial support for underrepresented students: Scholarships were awarded to a senior high school student who participated in the program and subsequently enrolled at Texas State University in the Department of Agriculture, as well as to postsecondary mentors to support their continued STEM education. Goal 2: The program implemented a series of professional and social development activities designed to build leadership and interpersonal skills among secondary student participants. Students attended workshops on communication skills, résumé writing, and mock interviews to enhance both interpersonal and professional competencies. They engaged in group meetings and collaborative technical projects, including working with sensors, flying drones, and performing data analysis tasks, which offered practical opportunities to develop collaboration, problem-solving, and leadership abilities while applying smart agriculture tools and methods. Additionally, students participated in peer feedback sessions and reflective discussions, reinforcing critical thinking, communication skills, and self-assessment throughout the program Goal 3: The project successfully implemented a near-peer mentorship structure in which four undergraduate students served as mentors for secondary participants. These postsecondary mentors guided students through technical modules, hands-on experiments, and project activities while facilitating collaborative learning and supporting professional skill development. By modeling leadership behaviors and providing individualized guidance, the mentors established a structured framework that promoted both leadership and mentorship among secondary and postsecondary participants, reinforcing engagement and skill-building across all levels of the program. Summary of External Evaluation: An external evaluation conducted by Dr. Merritt Drewery in Year 1 assessed both high school participants and college student mentors in the Smart Agriculture Program. High school students demonstrated increased confidence and competencies in science and engineering, particularly in applied skills such as AI, drones, using sensors to collect data, and data analysis, and showed a shift from general interest to concrete career orientation. College mentors reported growth in leadership, communication, and adaptability when teaching younger students. Focus groups and reflection exercises highlighted the value of hands-on learning, mentorship, peer collaboration, and exposure to college environments. These evaluation results validate the program accomplishments under Goals 1-3 and provide actionable guidance for continuous improvement.

Publications