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Research Data Services

The DataLab Projects

DATALAB PROJECT DESCRIPTIONS – SPRING 2024

Emily Balda and Dr. Amy Joh are examining constructs of culture, ethnicity, and race (CER). The goal of the study is to investigate college students’ own understanding of the concepts of culture, race, and ethnicity. College students will provide their own definition of CER through a web-based survey with both open- and close-ended questions. College students will also provide information about their background and ethnic-racial identity, which have been shown in the past to be related to CER. Data will be collected through Qualtrics and analyzed with Excel and SPSS. The findings from this study will provide a clearer understanding of how research participants view and use the concepts of CER.

Sarah Leitao and Dr. Nicole Hansen are answering this research question: What is the impact and effectiveness of the implementation of Pennsylvania’s Disability Inclusive Curriculum Pilot program on student learning outcomes, program implementation, stakeholder satisfaction, and organizational impact? We will be working together to co-code three-year action plans that each participating school/district has developed. Additionally, we will analyze and code environmental scans submitted by each school that describe the extent to which people with disabilities are represented and included in in curriculum, the school environment, the school student body, and school communication. We will use Atlas.TI to code the data.

Arabella Moen and Dr. Jennifer Itzkowitz are updating a previous project of Dr. Itzkowitz. They will be  will replicate an existing study to see if the results have changed since the initial study was done in 2013. They are using STATA to analyze their data. 

Margaret Grimm and Dr. Luye Li are examine the factors that influences public trust in the police and American courts, opinions on police fair treatments, confidence in the U.S. Supreme Courts and assess the trend over the years of public opinion in the U.S. criminal justice system. 

Ariana Coletta and Dr. Michelle D'Abundo are doing a mixed-method project involves qualitative analysis of responses focused on self-care from US frontline workers during the COVID-19 pandemic. We will focus on comparing manual coding to AI coding for a subset of the data. 

Maryam Attalla and Dr. Shajina Anand will be developing and implementing a data-driven system that predicts water and fertilizer requirements for agricultural practices in New Jersey. By integrating weather and soil condition predictions with machine learning models, the project aims to empower farmers to make informed decisions regarding irrigation and fertilization. This methodology facilitates the efficient allocation of resources, minimizes water consumption, and allows for precise fertilizer application. Consequently, it results in enhanced crop yields, cost savings, and reduced environmental effects.

Victor Carrillo and Dr. Tinachun Chu will be building workflow in Rstudio for sequence data in AWS Lightsail. They also will be teaching Dr. Chu's BioInformatics class how to use AWS Lightsail for research. 

Oliwia Kempinski and Dr. Hongfei Tang will be creating the The Intelligent Learner Guiding System (ILGS). ILGS is an online platform that will provide a comprehensive and interactive learning experience for individuals seeking to enhance their knowledge. The ILGS will utilize a hierarchical structure of webpages, each dedicated to a specific knowledge point, to build a comprehensive knowledge tree in each subject, such as Finance. Users will be able to navigate through the tree, exploring topics of interest and gaining a deeper understanding of concepts.