Magee joins GSLIS faculty

Magee_web.jpg?itok=4ovjWPzS GSLIS is pleased to announce that Rachel Magee will join the faculty this fall.

Magee’s research focuses on how young people engage with technology, and considers their social relationships and values as important factors in their technology use. She is also interested in developing technologies, strategies, and techniques to better support teens’ information access and use.

“Rachel is a wonderful addition to our top-ranked faculty in youth services. She is bringing new approaches to understanding youth’s experiences with digital spaces and media, and in particular, how they transition between different modes of online communication. We are delighted that she is joining us,” said GSLIS Dean Allen Renear.

Before embarking on her doctoral studies, Magee served as a teen and reference services librarian at the County of Los Angeles Public Library for three years. Magee is now looking forward to bringing that experience to the classroom. “I’m very excited to teach people who will be going out into the field and working directly with youth, drawing from my own experiences as a teen services librarian and my research,” she said.

“I was attracted to GSLIS for a number of reasons, first and foremost being the dynamic people,” she continued. “The faculty and students here are working on important problems. The school is at the forefront of innovative research and education, and has long recognized the importance of supporting and advocating for youth. I think this is a great environment to think big and I'm so excited for the opportunity to join this community.” 

Magee holds degrees in English and in radio, television, and film from the University of Texas at Austin, a master’s degree in information resources and library science from the University of Arizona, and is now completing her PhD in information studies at Drexel University.

Tags:
Updated on
Backto the news archive

Related News

Trainor receives the Karen Wold Level the Learning Field Award

Senior Lecturer Kevin Trainor has been selected by the Division of Disability Resources and Educational Services (DRES) to receive the 2024 Karen Wold Level the Learning Field Award. This award honors exemplary members of faculty and staff for advocating and/or implementing instructional strategies, technologies, and disability-related accommodations that afford students with disabilities equal access to academic resources and curricula. 

Kevin Trainor

Seo coauthors chapter on data science and accessibility

Assistant Professor JooYoung Seo and Mine Dogucu, professor of statistics in the Donald Bren School of Information and Computer Sciences at the University of California Irvine, have coauthored a chapter in the new book Teaching Accessible Computing. The goal of the book, which is edited by Alannah Oleson, Amy J. Ko and Richard Ladner, is to help educators feel confident in introducing topics related to disability and accessible computing and integrating accessibility into their courses.

JooYoung Seo

iSchool instructors ranked as excellent

Fifty-five iSchool instructors were named in the University's List of Teachers Ranked as Excellent for Fall 2023. The rankings are released every semester, and results are based on the Instructor and Course Evaluation System (ICES) questionnaire forms maintained by Measurement and Evaluation in the Center for Innovation in Teaching and Learning. 

iSchool Building

ConnectED: Tech for All podcast launched by Community Data Clinic

The Community Data Clinic (CDC), a mixed methods data studies and interdisciplinary community research lab led by Associate Professor Anita Say Chan, has released the first episode of its new podcast, ConnectED: Tech for All. Community partners on the podcast include the Housing Authority of Champaign County, Champaign-Urbana Public Health District, Project Success of Vermilion County, and Cunningham Township Supervisor’s Office.

Community Data Clinic podcast logo

New study shows LLMs respond differently based on user’s motivation

A new study conducted by PhD student Michelle Bak and Assistant Professor Jessie Chin, which was recently published in the Journal of the American Medical Informatics Association (JAMIA), reveals how large language models (LLMs) respond to different motivational states. In their evaluation of three LLM-based generative conversational agents (GAs)—ChatGPT, Google Bard, and Llama 2—the researchers found that while GAs are able to identify users' motivation states and provide relevant information when individuals have established goals, they are less likely to provide guidance when the users are hesitant or ambivalent about changing their behavior.