Search
Close this search box.

AFRO 498 Race, Gender and Information Communication Technology

 

New course offering this Fall in the Department of African-American Studies for those interested in digital media, communications, technology and information studies!

AFRO 498 • Tuesday • 2:00 PM – 4:50 PM

Instructor: Noble, Safiya U. (snoble@illinois.edu)

Credit: 4 hours

Course: Race, Gender and Information Communication Technology 

Description: The portrayal of African-Americans with respect to technology has typically been predicated on a "deficit model," placing African-Americans on the "wrong side" of technological innovation, despite their engagements in and contributions to the design, manufacture, production, consumption and disposal of information communication technologies. These narratives stem from the a series of intersecting practices that are technological, commercial, ideological, and discursive, including narratives of the "digital divide". In this course, we will go beyond issues of computer and Internet access to look at race and representation in digital technologies, with additional focus on intersections of gender and class. We will use a critical media studies approach to examine how information technologies affect, and are affected by race, class and gender.

CRN: 60705 (Graduate) 

or 

60704 (Undergraduate Juniors and Seniors with permission of instructor – contact Safiya U. Noble atsnoble@illinois.edu

 

Share:

More Posts

Mark Moran Defends Dissertation

Doctoral Candidate Mark Moran successfully defended his dissertation, “STAKEHOLDER REPRESENTATION IN THE CEO’S LETTER TO SHAREHOLDERS” on December 8th and will graduate May 2024. Program

Thierry Guigma Defends Dissertation

Doctoral Candidate Thierry Guigma successfully defended his dissertation, “PLACE OF TWITTER AND GOOGLE SEARCH DATA IN DISEASE OUTBREAK MONITORING AND FORECASTING: CASE OF THE COVID-19

Sam Walkow Defends Dissertation

Doctoral Candidate Sam Walkow successfully defended her dissertation, “USING DATA STORIES TO UNDERSTAND SPACIAL MENTAL MODELS OF DATA IN NATURAL SCIENCE DOMAINS: CHARACTERIZING TECHNICAL AND