Performing Department
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Non Technical Summary
Our project tackles a pressing issue in agriculture, which is the need for a skilled workforce adept at harnessing the power of data. In today's agribusiness landscape, the data revolution is transforming how we manage crops, make decisions, and ensure food security. This project addresses the shortage of experts in agricultural management and economics, which is vital for sustaining our farms, communities, and the environment. To do this, we will establish a cutting-edge "Agribusiness and Data Analytics" Master of Science program at North Dakota State University. We will train a diverse group of students, including underrepresented minorities, in agribusiness theory and data analytics. These students will engage in real-world research projects, gain practical experience, and interact with industry professionals. Through workshops, seminars, and outreach, we aim to share our findings with the broader agricultural community. Our ultimate goal is to graduate highly skilled individuals who will enhance decision-making in agriculture, improve profitability for farmers, and help build sustainable and resilient farming practices. By filling this knowledge gap, we strive to benefit not only the agricultural industry but also society at large, promoting economic growth, community well-being, and environmentally responsible practices.
Animal Health Component
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Research Effort Categories
Basic
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Applied
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Developmental
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Goals / Objectives
Project Goal Statement:The major goal of this project is to establish and implement a highly interdisciplinary Master of Science (MS) program in "Agribusiness and Data Analytics" at North Dakota State University, with the primary objective of training seven USDA National Needs Fellows (NNF) to address the Targeted Expertise Shortage Area of "Agricultural Management and Economics." This initiative aims to equip these fellows with the knowledge and skills to harness the data revolution and contribute to the USDA mission under discipline code M, "Agricultural Marketing and Management."Project Objectives:Develop and Launch the "Agribusiness and Data Analytics" MS Program:The project will focus on creating a comprehensive curriculum tailored to the specific needs of the agribusiness industry in the realm of data analytics. It will entail establishing the necessary infrastructure, including faculty recruitment, facility development, and resource allocation. Additionally, it will encompass securing the essential regulatory approvals and accreditation to ensure the program's successful launch.Recruit and Train Seven USDA National Needs Fellows:The project's second objective is identifying and selecting seven qualified NNF candidates from underrepresented groups. These individuals will undergo comprehensive training that includes exposure to agribusiness theory, practice, and proficiency in data science concepts and methods. The project will strive to create an inclusive and diverse learning environment that fosters collaboration and shared research.Professional Development and Experiential Learning:To enhance the fellows' professional development, the project will provide opportunities for engagement in experiential learning through practical research projects. It will facilitate interactions between the fellows and prospective employers, enriching their skill sets and expanding their networks. Continuous assessments and follow-ups will be conducted to monitor the progress and development of each fellow.Knowledge Generation and Dissemination:The project will encourage the generation of new knowledge within the field, specifically focusing on data science applied to agribusiness education. It will actively support the programmatic development of the "Agribusiness and Data Analytics" track and ensure the dissemination of program outcomes and research findings to the academic community and the public, employing various channels such as publications, conferences, and outreach initiatives.Alumni Impact:One of the final objectives is to track the career trajectories and impact of the seven fellows in academia, industry, and government. By showcasing the accomplishments and contributions of program alumni, this objective aims to highlight the program's success and its role in addressing the expertise shortage in agribusiness. This, in turn, will serve as a testament to the effectiveness of the program in preparing experts for critical roles within the field.By accomplishing these objectives, this project aims to fill a critical gap in agribusiness education, empower underrepresented groups in the field, and contribute to the USDA's mission by providing experts well-versed in data analytics for agriculture and food production.
Project Methods
Project Method Description:This project will employ a multi-faceted approach to deliver science-based knowledge to the target audience and facilitate a transformation in knowledge, actions, and conditions. The methods are designed to offer a rigorous and comprehensive educational experience to the USDA National Needs Fellows (NNF) and other students, as well as to disseminate research findings to the broader community. The methods include formal instruction, experiential learning, research, and outreach activities.Efforts to Cause Change in Knowledge, Actions, and Conditions:Formal Instruction:The project will offer formal classroom instruction and laboratory experiences to NNFs and students enrolled in the "Agribusiness and Data Analytics" MS program. The curriculum will cover agribusiness theory, data science, and practical applications, enabling participants to gain comprehensive knowledge.Experiential Learning:To change actions and behaviors, the project will provide experiential learning opportunities through research projects. Fellows will engage in hands-on research, applying their knowledge to real-world situations in collaboration with industry partners and stakeholders.Workshops and Seminars:Workshops and seminars will engage students in critical discussions and enable them to interact with industry professionals. These events will facilitate a change in knowledge and actions by exposing students to cutting-edge developments in agribusiness and data analytics.Extension and Outreach:The project will actively disseminate knowledge through extension and outreach activities. Research findings, data-driven practices, and innovative methodologies will be shared with agricultural communities and the public, contributing to a change in conditions within the agricultural sector.Evaluation:To assess the success and impact of the project, a comprehensive evaluation plan will be implemented, encompassing various types of evaluation studies and data collection methods. Key milestones and measurable or quantitative indicators of success will be closely monitored and analyzed:Formal Education Evaluation:Regular assessments, exams, and performance evaluations will track the progress and learning outcomes of NNFs and students. Success will be measured through grade improvements, certifications earned, and demonstrated proficiency.Experiential Learning Assessment:Research projects and internships will be evaluated based on the quality of research conducted, publications, and the extent of real-world impact, such as improved agricultural practices and decision-making.Workshop and Seminar Feedback:Feedback from students and participants in workshops and seminars will be collected to gauge the change in knowledge, actions, and perspectives following these events.Extension and Outreach Impact:The impact of extension and outreach activities will be assessed by measuring the reach and engagement with the broader agricultural community. Quantitative data, such as the number of attendees, inquiries, and participation in new practices, will be collected.Publication and Research Impact:The success of the project's publications and research contributions will be evaluated by tracking the number of citations, publication downloads, and real-world applications of the research findings.Diversity and Inclusion Metrics:The project will monitor the diversity and inclusion of participants and assess changes in the demographic composition of the agribusiness workforce over time.The evaluation plan will relate these milestones and indicators of success to the expected project outcomes and accomplishments. Regular data collection and analysis will ensure that the project remains on track and that its objectives are met, ultimately leading to a significant change in knowledge, actions, and conditions within the target audience and the broader agricultural community.