Education Programs: Humanities Connections Planning Grants

Period of Performance

5/1/2018 - 11/30/2019

Funding Totals

$35,000.00 (approved)
$32,464.44 (awarded)

Digital Humanities, Data Science, and Digital Justice Minor at Xavier University of Louisiana

FAIN: AKA-260563-18

Xavier University of Louisiana (New Orleans, LA 70125-1056)
Kim Vaz-Deville (Project Director: October 2017 to March 2021)

The design of an undergraduate minor in humanities, data science, and digital justice.

The aim of the Xavier University of Louisiana’s College of Arts and Sciences’ planning grant proposal is to design an undergraduate minor in the area of Humanities, Data Science and Digital Justice. The minor will teach students the humanistic tools of critique, appreciation, and engagement, with the by-product of providing skills development in digital platforms that are used in businesses. This planning grant will facilitate faculty training in strategic platforms that align with business technologies but also offer the opportunity to transmit and teach humanities’ habits of mind and heart that align with our undergraduate core curriculum. In addition to course development, faculty and staff training, and student engagement and outreach, the courses and minor proposal will be submitted for University approval toward the end of the planning year.

Media Coverage

Xavier University launches digital humanities minor (Media Coverage)
Publication: New Orleans City Business
Date: 9/3/2020

Associated Products

Introduction to Digital Humanities (Course or Curricular Material)
Title: Introduction to Digital Humanities
Author: Kim Vaz-Deville
Abstract: This course introduces students to the field of digital humanities. Through course activities, students will gain awareness of how the tools, technologies and methods are used in both academia and the business world. Ultimately, students will become critical and reflective users of a range of digital tools, technologies and methods used by business, industry and academia to explore issues and solve problems by understanding that all technologies are complex, socially situated, and political. The course will consist of a combination of lecture, guest speakers, lab (1.5 hours classroom; 1.5 hours of lab). (3)
Year: 2020
Primary URL:
Audience: Undergraduate

Ethics at the End of Life (Course or Curricular Material)
Title: Ethics at the End of Life
Author: James Dunson
Abstract: In this course, students will be asked to consider their own research interests in light of the goals and values of patients. End-of-life issues accomplish this task uniquely, because our ability to manage symptoms has far outpaced our ability to cure disease. How should we regard the wishes of patients who are chronically sick, slowly losing cognitive function, or even terminally ill? If the confrontation with one’s own mortality is, to a large degree, a personal issue, then how should we understand patient pain and suffering? While it is true that end-of life issues raise significant questions about the purpose and limits of scientific research, they also introduce equally important questions about what we can claim ethically about someone else’s confrontation with mortality. For this reason, students will be challenged to move beyond both dogmatic scientific claims and abstract ethical arguments. They will also be tasked with learning some digital tools (e.g. Wordpress, Omeka, or Tableau) that they can use to present and publish their semester-long research projects in a database of student work on Bioethics. This includes becoming proficient in the ethics of digital publishing and in strategies for developing a scholarly portfolio. (3)
Year: 2020
Primary URL:
Audience: Undergraduate

Explorations in Data Science for Humanities (Course or Curricular Material)
Title: Explorations in Data Science for Humanities
Author: Nawa Raj Porhkl
Abstract: This application focused course will present basic data organization, data cleaning, data management, visualization and statistical modeling in digital humanities. This course lies at the intersection of fundamental programming skills, data visualization, data cleaning and statistical modeling in R and Excel environment. Furthermore, data cleaning is exercised using Excel and rest of the components of the course are handled on R platform. Students will identify appropriate statistical methods for the data or problems and conduct their own analysis using real datasets. This is a hands-on, project-based course to enable students to develop skills and to solve interdisciplinary problems.
Year: 2020
Primary URL:
Audience: Undergraduate