
Encourages deep understanding and curiosity.
Makes learning feel effortless and fun.
A true gem in the academic community.
I’m grateful for how you challenged us to think critically while still being supportive. Your teaching style helped me grow so much
Linda Rutherford serves as Assistant Professor of Practice in the Department of Computer Science within the College of AI, Cyber and Computing at the University of Texas at San Antonio. She holds the Kay and Steve Robbins Faculty Teaching Fellowship Award in Computer Science. Rutherford joined the UTSA faculty in 2019, beginning as a part-time lecturer and later transitioning to a full-time role. A retired U.S. Air Force veteran with 20 years of service, she possesses a broad background in technology applications and business development, which informs her instructional approach. Her academic credentials include a Master of Science in Information Technology/Cyber Security earned from UTSA in 2017, a Master of Military Operational Art and Science from the Air Force Air Command and Staff College in 2000, a Master of Arts in Computer Resource and Information Management from Webster University in 1995, and a Bachelor of Science in Management Information Systems from the University of Nevada.
Rutherford's teaching centers on data analysis and visual computer programming. She leads CS 1173: Data Analysis and Visualization, a highly enrolled course serving over 400 students each year and ranking among the most popular in the computer science curriculum. In addition to her classroom responsibilities, she acts as Faculty Champion for Computer Science under UTSA's Academic Innovation program, supporting pedagogical advancements across the institution. Rutherford contributes to faculty development by authoring practical teaching tips published on university resources, including guidance on utilizing Canvas Development Shells—private sandbox courses for experimenting with content, tools like Padlet and ChatGPT, and assignment redesign without impacting live classes—and strategies for efficient grading using Canvas's Apply Filters tool to manage ungraded, late, or resubmitted work. These resources assist colleagues in streamlining course preparation and end-of-semester tasks. Her office is located in NPB 3.316.

Photo by Brett Jordan on Unsplash
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