Source: UNIVERSITY OF TENNESSEE submitted to NRP
INTEGRATION OF ARTIFICIAL INTELLIGENCE IN FOOD ENGINEERING EDUCATION TO TRAIN FUTURE WORKFORCE
Sponsoring Institution
National Institute of Food and Agriculture
Project Status
ACTIVE
Funding Source
Reporting Frequency
Annual
Accession No.
1031624
Grant No.
2024-70003-41454
Cumulative Award Amt.
$149,998.00
Proposal No.
2023-05512
Multistate No.
(N/A)
Project Start Date
Mar 1, 2024
Project End Date
Feb 28, 2027
Grant Year
2024
Program Code
[ER]- Higher Ed Challenge
Recipient Organization
UNIVERSITY OF TENNESSEE
2621 MORGAN CIR
KNOXVILLE,TN 37996-4540
Performing Department
(N/A)
Non Technical Summary
Traditional engineering education in lecture-focused classrooms fails to adequately educate food science students to meet the demands of rapidly evolving processing innovation in the food industry. The accelerated development of new food processing technologies outpaces faculty abilities to incorporate up-to-date technology and knowledge into already compacted food engineering courses. The emerging natural language processing-based artificial intelligence (AI) technology (e.g., ChatGPT) may offer an innovative solution while presenting challenges for higher education due to the potential misuse of AI tools that can lead to ethical issues and stifle critical thinking development. This project seeks to develop an AI-integrated pedagogy to transform passive lecture-based classrooms into high-engagement, active learning experiences that prepare students to think critically, innovate, and transition smoothly into the workforce. Through simulated future work environments, students will assume different roles related to AI, including consultees, coworkers, and supervisors. The AI-supported roleplay will help students develop skills in adapting new concepts from AI, solving engineering problems with AI, and assigning tasks to AI. The series of active learning strategies will enhance students' mastery of engineering concepts in food science and develop workforce readiness skills such as lifelong learning, critical thinking, problem-solving, communication, teamwork, ethics, and professionalism. This project will prepare students for future technological challenges and opportunities by understanding the limitations and potential uses of AI tools. Successful completion of this project will result in a novel pedagogy, validated curricula, and extensive training documents for the innovative integration of AI into agricultural and food science programs nationwide.
Animal Health Component
(N/A)
Research Effort Categories
Basic
(N/A)
Applied
(N/A)
Developmental
(N/A)
Classification

Knowledge Area (KA)Subject of Investigation (SOI)Field of Science (FOS)Percent
50150102020100%
Knowledge Area
501 - New and Improved Food Processing Technologies;

Subject Of Investigation
5010 - Food;

Field Of Science
2020 - Engineering;
Goals / Objectives
This project seeks to develop innovative AI-integrated pedagogy for implementation across three levels of food science courses to advance food engineering education.
Project Methods
The AI-supported pedagogy will be designed and implemented in three existing courses at different levels - FDSC 100 Science of Foods, FDSC 341 Food Engineering, and FDSC 490 Food Product Development. The roleplay activities and instructional materials will be specifically designed for the three courses considering the student's academic background (major, progress), course contents, and expected learning outcomes. The AI-supported curricula, instructional materials, and training materials will be developed and disseminated for broader adoption. A comprehensive, utilization-focused evaluation will be performed.

Progress 03/01/24 to 02/28/25

Outputs
Target Audience:Undergraduate students and instructors in food science. Changes/Problems: Nothing Reported What opportunities for training and professional development has the project provided?One graduate student and one undergraduate student are involved in the project on the course redesign. The students better understand AI technology during the course redesign process and experience the usefulness and limitations of AI tools. How have the results been disseminated to communities of interest?We are in the early stage of the project for data collection. There is no result dissemination yet. What do you plan to do during the next reporting period to accomplish the goals?In year 2, we expect to complete the course redesign of FDSC 341/541 Food Engineering and have full implementation in fall 2025. We will implement the AI-supported strategy in the other two courses, FDSC 100 Introduction to Food Science and FDSC 490 Food Product Development. Student surveys and focus groups will be conducted. We will further refine the course materials and implementation plans.

Impacts
What was accomplished under these goals? Our year 1 project was kicked off in March 2024 by confirming the project responsibilities of investigators/instructors. We worked with the project evaluator in developing evaluation protocols with focus group and survey questions developed and IRB approved. Our major activity focused on developing an AI-supported roleplay learning strategy, creating instructional materials for the major food engineering course FDSC 341/541 Food Engineering, and introducing AI application examples in the FDSC 490 Food Product Development course. We have identified learning objectives that can be achieved through the AI-supported learning strategy and that might help students to be successful in working in an environment with rapid technology upgrades, including: (1) Enhance knowledge acquisition and understanding of new engineering concepts through interaction with AI as a consultant; (2) Develop critical thinking and problem-solving skills through peer critique of solutions with AI; (3) Improve design skills and innovation and demonstrate leadership and communication skills through supervision and review of AI-generated products; (4) Encourage collaboration and teamwork among students through AI-assisted learning experiences. To support these AI-related learning objectives, we focused on redesigning the Heat Transfer Module in the food engineering course with the following activities performed: We identified ChatGPT as the major implementation AI tool for this course. By importing the book chapters into ChatGPT, we developed a custom AI tutor that the FDSC 341 Food Engineering students can specifically use. We revised the Heat Transfer module lecture slides to be self-guided learning materials and addeddetailed explanations of engineering concepts, definitions, and application examples. We also added example AI prompts that students can use to consult AI to acquire knowledge about engineering concepts and applications. We modified some example problems as AI-guided examples. By showing the AI solutions, we allowed the students to critique the AI solutions for problem-solving and critical thinking development. We tested this so-far modified heat transfer module in the 2024 fall semester food engineering course. We also conducted a student survey and focus group to collect students' feedback on the revised teaching activities. Based on students' feedback, we are further refining the heat transfer module materials and revising the other three modules of the food engineering course. In addition to the revision mentioned above, we are developing more practice problems with AI solutions for critiques. We are also developing three team projects that will allow the students to work as a team and use AI tools as assistants to solve comprehensive design problems. This new activity will support our identified learning objectives 3 and 4. In addition to the major activity focused on the FDSC 341/541 Food Engineering course, we demonstrated the potential use of AI tools in the FDSC 490 Food Product Development class to inspire the students in their capstone project. During students' updates on their product development, they have been actively using AI tools (e.g., ChatGPT) to prepare food recipes. This course is still ongoing.

Publications