Progress 10/01/23 to 09/30/24

Outputs
Target Audience:We proactively engaged with various stakeholders and participated in the College of Agriculture, Food, and Natural Resources Annual Field Day. Over the course of this two-day event, we organized an engaging session specifically for 4-H students and a second session catering to farmers, college students, extension agents, PVAMU faculty and staff, state and federal agencies, and private citizens. To further amplify our outreach, we shared these demonstrations through videos on social media, ensuring that our work reached a broader audience and sparked greater interest in our initiatives. Changes/Problems:We don't anticipate any significant changes to our plan moving forward. However, we need a no-cost extension to complete the originally proposed activities. Some delays have occurred due to the research compliance application process, which affected our timeline. We believe that with this extension, we can successfully achieve our objectives without altering our approach. There are no special or additional reporting requirements specified in the award Terms and Conditions that would impact our current strategy. What opportunities for training and professional development has the project provided?We trained the participants on using different climate-smart procedures and devices during the field day and field demonstrations. Team members demonstrated through hands-on approaches the following procedures: i) the use of carbon dioxide and greenhouse gases monitoring, ii) soil moisture monitoring, iii) monitoring plan chlorophyll level and health, and iv) the use of drones and different remotely controlled cameras. How have the results been disseminated to communities of interest?We used the outreachevents we organized to effectively train participants on various climate-smart procedures and devices. During the field day and demonstrations, our team provided hands-on training in critical areas, including monitoring carbon dioxide and greenhouse gases, soil moisture assessment, plant chlorophyll level, health monitoring, and the operation of drones and various remotely controlled cameras. These interactive sessions allowed participants to engage directly with the technologies and practices that can enhance climate resilience in their agricultural efforts. What do you plan to do during the next reporting period to accomplish the goals?During the next reporting period, we plan to continue most of our successful activities from last year, including training participants on climate-smart procedures and devices. Additionally, we will place a stronger emphasis on outreach efforts to engage a broader audience. We aim to publish some of our findings in peer-reviewed journals to share our results and insights with the scientific community. This dual focus on outreach and dissemination will help us achieve our goals more effectively.

Impacts
What was accomplished under these goals? Task 1.2: Faculty will develop modules to improve undergraduate computing education through enhanced courses. In year one, sample modules were developed. In year two, these modules were delivered in embedded courses. In year three, modules were continued in more classes, including large enrollment courses with students from different colleges and majors. Task 1.3: Undergraduate students develop RLOs. Students developed RLOs or videos about Ag Smart technologies in Years 1 & 2. The quality was not professional for broad distribution. The PI Team thus created three short videos on the SmartAg topics being addressed in the modules. These will be posted on an outward-facing website and YouTube channel. Task 2.1 and Task 3.1: E-Extension: A resource webpage is being developed to facilitate digital interactive communications and provide various resources to support the dissemination of Agricultural technology for youth, students, and active professionals. This website will include the modules and videos and a link to the YouTube Channel. Task 2.3: Continuing education for agricultural producers. There was an AgField Day in April 2024 with various Smart Agriculture demonstrations for producers. Educational interventions in formal classrooms and non-formal contexts such as extension, advisory, and outreach programs can increase marginalized students' and stakeholders' access to climate change knowledge and innovations. Task 3.4: The project continues to develop outlets for current and relevant knowledge through FANH university faculty who teach content related to smart agriculture and problem-based learning. These will also be included on the outward-facing website. Task 2.2 or Task 4.5: Youth participating in GetSmartAg day. Youth participated in "Ag Day on the Hill" at Prairie View A&M University. In total, 23 students participated in the event. After the activity, 100% of the youth indicated that they were more aware of careers in STEM/Agriculture because of their participation. Youth were asked if they were more interested in pursuing a career in STEM/Agriculture, and 65% indicated yes, with another 30% indicating some interest. Lastly, students were asked if learning about other agricultural technologies like the ones they saw on the Day on the Hill was of interest to them on a scale from 1-10. The average for the students was 7.1, with many expressing interest in learning more. One youth said, "It's nice to see that we can work with more than just soil and crops," while others wanted to learn more. Task 4.1 and 4.6: Student assessment of learning gains. We implemented a retrospective post-pre-evaluation design to assess students' CSA knowledge and career aspirations upon participating in a water sustainability seminar by implementing CSA innovations. Based on the targeted seminar intervention, the data indicated that Latinx and Asian students increased their knowledge by >55% and shared testimonials regarding their elevated interest in pursuing CSA careers post-graduation. Latinx and Asian students reported higher mean scores than white students. Shared testimonials on their elevated interest in pursuing CSA careers post-graduation included, "This lecture opened up options that I didn't know were available, such as jobs regarding AI application in agriculture." Another stated, "It makes me want to pursue a career in precision agriculture."

Publications

• Type: Conference Papers and Presentations Status: Published Year Published: 2024 Citation: Brogan, G. S., Kirk-Bradely, N., Strong, R. Jr., Mohtar, R., Dooley, K., & Fares, A. Ahmed, A. A., Awal, R., Ampim, P., & Moore, J. (2024, April 15-17). Utilize AI in climate-smart agriculture curriculum to improve underrepresented students motivation toward climate-smart agriculture (CSA) careers. [Poster Presentation]. 2024 AI in Agriculture and Natural Resources Conference, College Station, Texas, United States.
• Type: Conference Papers and Presentations Status: Published Year Published: 2023 Citation: Strong, R. Jr., Brogan, G. S., Mohtar, R., Dooley, K., & Fares, A. (2024, June 26-28). Advancing climate smart educational access for marginalized students: A retrospective post-then-pre design to assess nationally funded instructional interventions. [Paper Presentation]. Development Studies Association annual meeting, London, England. https://www.devstud.org.uk/conference/conference-2024/programme/#14882
• Type: Conference Papers and Presentations Status: Published Year Published: 2024 Citation: Josh Dotson, Ali Fares et al. Machine Learning-Powered Aerial System for Monitoring Crop Water and Nutrient Stress. ARD Meeting, Nashville, TN, 2024.
• Type: Conference Papers and Presentations Status: Published Year Published: 2024 Citation: Strong, R. Jr., Brogan, G. S., Mohtar, R., Dooley, K., & Fares, A. (2024, February 9). Targeted educational interventions to improve underrepresented students' motivation toward climate-smart agriculture careers. [Poster Presentation]. Data-Driven Intelligent Agricultural Systems Symposium. College Station, Texas, United States.

Progress 10/01/22 to 09/30/23

Outputs
Target Audience:Students from k-12, undergraduates, and graduates. Also, professionals working in the agricultural sectors. State and federal agencies and the general public. Changes/Problems: Nothing Reported What opportunities for training and professional development has the project provided?We anticipate an average of 50 students per class with each producing one RLO (150 total). In our first launch, we reached64college students, and43videos were produced. We will be repeating these three courses and adding more courses in year 3. We will be reviewing the videos to select those to post on the project website and YouTube Channel. These RLOs will be showcased for the youth and agriculturalists through Extension and other programs. BAEN 642 (Water-Energy-Food Nexus: Toward Sustainable Resource Management) and had 10 students participating in a sustainable water module. 17% (n = 7, 70%) of students from the pre to the post-assessment collected increased knowledge in the course topic. 40% of the students reported being interested in a career related to smart agriculture. 35% of students reported enhanced interest in working on smart agriculture projects. Student group's responses in the 2 courses offered the project team revised strategies and solutions in developing, implementing, and evaluating year 2's reusable learning objects (RLOs). The project team is developing those strategies and solutions now for implementation and evaluation in the fall of '23 and spring of '24. Get AgSmart Day PVAMU organized the 2023 Ag. Field Day on April 28-29. Day one day for school groups (127 youth attendees and 28 adults) including breakout sessions on how agricultural technology is used to improve the climate, and virtual reality with an aerial view of campus. Day 2 was for agriculturalists/farmers in the area (12 youth and 183 adult attendees). It included climate smart ag. practices and benefits and building skills in smart ag. technologies. There was also a field demonstration on climate-smart and AI in ag., carbon sequestration, and soil health on July 14 (see a link to the video and photos below of the events).https://twitter.com/ripendra/status/1679909925105946625?s=20). How have the results been disseminated to communities of interest?Results were disseminated in the following outreach activities: PVAMU Ag Field day, April 2023 https://twitter.com/ripendra/status/1652387261240029185?s=20 https://twitter.com/ripendra/status/1652012899563388930?s=20 GetAgSmart High School Students Visit https://twitter.com/ripendra/status/1669916104498589696?s=20 GetAgSmart UT-Austin Graduate Students Raising Technology and Predictive Analytics for Sustainable Ag. https://twitter.com/ripendra/status/1669908409536184321?s=20 GetAgSmart Field Demonstration https://youtu.be/P4LKRRsDO2U Field Demonstration at PVAMU Research Farm - YouTube January 2023 GetAgSmart Workshop https://youtu.be/dvbDbcuVzgM What do you plan to do during the next reporting period to accomplish the goals? Shift from a reusable learning object to a GetAgSmart Video Use YouTube and other video platforms to reach youth rather than website Ensure the videos are of high quality, engaging, and understandable for the broader public Have a workshop with faculty who implemented modules to determine improvements and assist new faculty/courses for year 3 Develop consistent pre/post tests and knowledge tests for future implementation Use a standard course assignment and rubric for future class video assignments Post exemplar videos to use for outreach in year 3 Recruit students as youth mentors for future events Plan outreach activities/dissemination and measures of outcomes for year 3

Impacts
What was accomplished under these goals? Objective 1 Task 1.1: Workshops to gather information and establish a knowledge base for technology basics related to smart agriculture. The team invited key stakeholders to a workshop on January 2023, on PVAMU that included 3 stakeholder groups: a) industry - agriculturists with technical expertise in precision agriculture, b) higher education - college students, faculty, and administrators, and c) extension - expertise in youth and youth development. Facilitators asked open-ended questions and recorded the discussion on emerging jobs in smart agriculture and the needed training. There was an emphasis on Climate Smart Agriculture jobs with technology and data-driven approaches. There were suggestions on holding summer workshops, camps, or even farm fitness boot camps to provide youth with an opportunity to connect with industry. Lastly, inviting farmers into classrooms to share their expertise could enhance interest in pursuing a career in precision agriculture. The college students shared how they started thinking about their career options at the end of middle school and going into high school. This is the key target age, and most students were unaware of career opportunities in agriculture prior. They believed that programs that catered towards innovation and technological advancements in agriculture could impact career pathways sooner. Knowing about types of careers in smart agriculture and seeing individuals that "are like them" would have been encouraging. University faculty and staff emphasized the need for specific skills youth and students might need to be successful in a STEM career. Some of the skills identified were focused on computer software (Excel, python, or other computer data analyses and apps) and being able to analyze and interpret big data. Other areas mentioned were effective communication and leadership. Youth extension personnel indicated that to gain rapport with the youth there is a need to use individuals who "look" like them in the videos. Utilizing other youth and students was mentioned as a way for youth to find a sense of belonging in these potential career fields. Schools could also incorporate specialized pipelines in Smart Ag or STEM from middle to high schools. Working with school staff, administration, and CTE educators will help these products go further and have a greater impact. The youth group also mentioned working with churches, local community groups, and organizations currently involved in the communities. Lastly, to gain young people's interest, the content must be culturally relevant. The most common words, technology, learning, university, and industry were used across all focus groups. The importance of providing technology that connected youth to the industry was discussed as a path forward. Helping youth understand what advancements were happening within agriculture and how they could be a part of it, and providing spaces for learning such as youth programs, technology hubs, internships, or secondary education. These learning opportunities could lead to future classes and hands-on experiences at the university level. Stakeholders shared how the education and experiences provided to youth during their time at a university would enable them to be successful within the agriculture industry using AgSmart technologies. The event was video recorded and added to our YouTube channel: https://www.youtube.com/watch?v=dvbDbcuVzgM&t=2s Task 1.2: Faculty will develop modules to improve undergraduate computing education through enhanced courses. The team delivered modules embedded into the material on the fundamental properties of AI systems and hands-on experiences with smart agriculture in three courses (Water-Energy-Food Nexus, Unit Operation for Bio and Ag. Engr., and Information Resources Management). Students developed reusable learning objects as a course assignment. Based upon the stakeholder feedback, we shifted the assignment to be more of a Project Pitch with the project being to create a video about smart agriculture technology. Task 1.3: Undergraduate students develop RLOs. We anticipate an average of 50 students per class with each producing one RLO (150 total). In our first launch, we reached 64 college students, and 43 videos were produced. We will be repeating these three courses and adding more courses in year 3. We will be reviewing the videos to select those to post on the project website and YouTube Channel. These RLOs will be showcased for the youth and agriculturalists through Extension and other programs. BAEN 642 (Water-Energy-Food Nexus: Toward Sustainable Resource Management) and had 10 students participating in a sustainable water module. 17% (n = 7, 70%) of students from the pre to post-assessment collected increased knowledge of the course topic. 40% of the students reported being interested in a career related to smart agriculture. 35% of students reported enhanced interest in working on smart agriculture projects. Student group's responses in the 2 courses offered the project team revised strategies and solutions in developing, implementing, and evaluating year 2's reusable learning objects (RLOs). The project team is developing those strategies and solutions now for implementation and evaluation in the fall of '23 and spring of '24. Objective 2 Task 2.2: Get AgSmart Day PVAMU organized the 2023 Ag. Field Day on April 28-29. Day one day for school groups (127 youth attendees and 28 adults) including breakout sessions on how agricultural technology is used to improve the climate, and virtual reality with an aerial view of campus. Day 2 was for agriculturalists/farmers in the area (12 youth and 183 adult attendees). It included climate smart ag. practices and benefits and building skills in smart ag. technologies. There was also a field demonstration on climate-smart and AI in ag., carbon sequestration, and soil health on July 14 (see a link to the video and photos below of the events). https://twitter.com/ripendra/status/1679909925105946625?s=20). Task 4.1: Pre-posttest for undergraduates enrolled in courses with SMART technology curriculum. Two courses were taught in smart agriculture technologies, 1 at PVAMU (CINS 5301) and 1 at TAMU (BAEN 642). CINS 5301 had an IoT module and 23 students completed the pre/post evaluations. 78% (n = 18, 78.26%) of students reported an increase in knowledge of IoT applications to AG. 77% of students reported "agree to strongly agree" with a future interest in working on IoT projects. 91 of the students indicated an interest in pursuing careers in IoT technologies. Of the 14 males in the course, 12 were African Americans and of the 9 females in the course, 8 were African Americans and one was Asian.

Publications

• Type: Other Status: Published Year Published: 2023 Citation: Texas A&M Prairie View sponsored Agricultural Field Days for exhibitors, youth, and farmers on April 28-29, 2023. https://twitter.com/ripendra/status/1679909925105946625?s=20 https://youtu.be/P4LKRRsDO2U

Progress 10/01/21 to 09/30/22

Outputs
Target Audience:Middle to high school students, undergraduate and graduate students, landowners/managers, farmers, and ranchers, researchers from federal and state agencies. Changes/Problems:We had delayswith the grant sub-contracts going through compliance, and thus the Co-PIs at Texas A&M University didnot receive grant funding on time as planned. What opportunities for training and professional development has the project provided? Nothing Reported How have the results been disseminated to communities of interest? Nothing Reported What do you plan to do during the next reporting period to accomplish the goals?We will continue working on the objectives and activities of the project by developing and implementing accessible Reusable Learning Objects (RLOs) using agricultural smart technologies (modeling, sensing, virtual and augmented realities, and big data analytics) in food and agricultural systems. Furthermore, through informal learning, we will engage underserved youth, undergraduate students, and current agricultural professionals in smart agricultural technology. The team will establish a multigenerational community of practice (CoP) to strengthen human and social capital within diverse communities for the project's sustainability over time. Also, we will assess the performance of the learning modules and informal learning in providing students and professionals with the skills needed to succeed in smart agriculture practice. This includes employment and improved interest in the technology within food, agricultural, natural resources, and human (FANH) sciences careers.This project will recruit, engage, train, and mentor underrepresented youth and undergraduate students and active agricultural professionals through a multigenerational learning community to ignite the interest of minority and underrepresented students in agriculture disciplines. Members of the project team are experienced in mentoring and working with youth, students, and active agricultural professionals in formal and informal settings. They also have strong teaching, research, and outreach programs in smart agriculture. ?

Impacts
What was accomplished under these goals? The project's first year was focused on planning and preparation for implementation. We spent a significant amount of time preparing and securing the approval of the Institutional Review Board. Given the wide range of ages engaged with this project (4-H youth from 8 years old to adult farmers wanting to learn new technologies to improve their agricultural efficiencies), we needed to consider the appropriateness of data collection, recruitment, and consent. We created a verbal script for recruitment, a child assent form, a parent consent form, and an adult consent form. The child's consent was the most difficult to gain approval due to the reading level for an 8-year-old. This delayed the agency funding and our ability to execute the project earlier in the year. We developed a pre and post-questionnaire for youth to determine their interest in agriculture, technology, and career pathways in agriculture. Additionally, we created a pre and post-questionnaire for adults related to using reusable learning objects (RLO) in each construct area (modeling, sensing, virtual reality, augmented reality, and big data analytics). The adult questionnaire also seeks information about informal learning within technologically mediated modules to improve knowledge, skills, and interest in future employment in food, agriculture, natural resources, and human sciences careers. We also asked about which smart agriculture materials they used and for them to describe their learning in the workshop. For faculty, we will track the number of students enrolled in their courses to align the development of undergraduate student projects (RLO development) to be used in broader audiences to expose youth, agriculturalists, and the public. Now that we have these items approved, we can develop the workshop and modules indicated in our Year-One Objectives. Our logic chart for year one was focused on objectives 1.1 and 1.2. Task 1.1: Workshops to gather information and establish a knowledge base for technology basics related to smart agriculture. The student and stakeholder input will be used to develop key learning objectives for faculty development. We organized the stakeholder's workshop in January 2023. We will report on that next year. Task 1.2: Faculty will develop modules to improve undergraduate computing education through enhanced courses and research opportunities. These innovative AI learning modules will be integrated into existing courses to include project-based learning. We have created three sample modulesandused them during the 2022fall in undergraduate Agricultural Systems Management/Agricultural Engineering courses. One module: Informing Technology Choices and Tradeoffs Analysis, is focused on water production technologies and how to use a technology scorecard. The scorecard lets students think critically to quantify synergies and tradeoffs between technology choices. Challenges and Opportunities are presented by the Water, Energy, Food Nexus Research Group. This is tied to Sustainable Development Goals 6 (Clean Water and Sanitation) and 7 (Affordable and Clean Energy). Global themes will be presented with demands worldwide for desalination plants. Students are presented with renewable energy scenarios and cost-benefit analyses. The scorecard includes (a) resource requirements, (b) economic aspects, (c) environmental impact, (d) human capacity requirements, (e) technical requirements and robustness, and (f) social-cultural criteria. The students are also asked to engage in discussion about tradeoff analysis. The second module: Introduction to the Internet of Things (IoT),was designed to introduce how data is collected from sensors and other advanced embedded systems like machine-to-machine and Smart World services. A variety of domains are included, with a focus on precision agriculture. Students will be taken through a smart home scenario with a summary of IoT characteristics, advantages, and disadvantages. Smart agriculture sensors, process automation, cost management, waste reduction, and enhanced product quality and volumes serve as the context for the student project and laboratory experiments to develop an IoT camera system and control an IoT Light Emitting Diode (LED) using Raspberry Pi. The third module, Big Data Analytics in Post-Harvest Processing, was designed to introduce how big data is needed for programming systemsduring and after harvest. The learning objectives included translating knowledge, skills, and insights from computer programming to post-harvest engineering and determining how big data analytics are used in programming for food and feed commodities post-harvest. Students will be given real-world scenarios to solve programming problems related to this field. While the focus is on writing code to process big data, there will also be a conversation on the lack of availability of data post-harvest can lead to other issues. These modules will serve as the framework for the development of other undergraduate enhancement materials and the creation of a student RLOs assignment. Students will develop AgSmart solutions to address complex problems and demonstrate interesting technology tools such as modeling, sensing, virtual reality, augmented reality, and big data analytics that can be presented to a broader audience to increase interest in STEM career pathways for underserved populations. The key personnel on the grant project have been meeting regularly over Zoom. Our official kick off was on May 5. We also met June 1, 15, 27, July 13, 27, August 10, 24, and September 7.

Publications