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Food insecurity among college students causes a significant threat to academic success and overall well-being. According to the National Postsecondary Student Aid Study, more than 4 million students were food insecure during the 2019-2020 school year. While university food pantries work tirelessly to solve this issue, many students remain unaware of these resources or are hesitant to use them. It is important to understand how students perceive and engage with campus food pantries compared to popular campus dining options to improve outreach and reduce food insecurity. While surveys and focus groups can be useful, they may not fully capture the subconscious drivers of decision-making. This study leveraged both survey responses and eye-tracking data to investigate student preferences between a local college food pantry and prominent on-campus food options. Participants viewed 13 paired image scenarios, and Areas of Interest (AOIs) were defined to collect eye-tracking metrics: Time to First Fixation, Total Fixation Duration, and Fixation Count. An Extreme Gradient Boosting (XGBoost) model identified key eye-tracking metrics, using student’s reported food option choices for cross-validation. Results revealed that Fixation Duration was the strongest predictor, suggesting that prolonged visual attention correlated with preference. Additionally, students leaned toward the food pantry for convenience to receive shelf-stable snacks but opted for alternatives when seeking prepared meals. This research supports the development of more effective food assistance strategies that prioritize student needs and behaviors.
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Inventory Control at a University Food Pantry Using an MVC Software Pattern and Data Visualization
University food pantries have been opened on-campus to reduce food insecurity among students. However, they are relatively self-governed and receive a limited amount of support. This study aims to resolve the inventory management issue at university food pantries using the combination of the Model-View-Controller (MVC) software pattern and data visualization. As a result, a foundation is established to predict the food choices of clients and to manage food waste effectively. The benefits of visualization on decision making through the use of a resourceful inventory system are outlined. The focus of this research is on university pantries, in particular, the Aggie Source Food Pantry at North Carolina Agricultural & Technical State University. A sample of 50 clients' food choices was acquired from picklists for June and July of 2019. The inventory tracking system implemented is a client-server mobile application used for data collection. Data visualization was applied to evaluate the food donations and distributions. Students preferred essential foods (e.g., pasta, canned vegetables), over unhealthy foods (e.g., Pop-Tarts, cookies). The data consisted of 338 pounds of distributed food and almost 2,473 pounds of donations. Data was simplified into comprehensive visual diagrams. The MVC structure established a program interface that grouped application functions and managed data objects. The solution allowed the staff to understand pantry status and the trends in production. It is anticipated that the prototype will be implemented in the daily activities of the pantry.
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- Award ID(s):
- 1735258
- PAR ID:
- 10293365
- Date Published:
- Journal Name:
- Inventory Control at a University Food Pantry Using an MVC Software Pattern and Data Visualization
- Page Range / eLocation ID:
- 1 to 7
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript
- Conference Paper:
- https://doi.org/10.1109/SoutheastCon45413.2021.9401894
