Individual Fellow Initiatives
Peer Mentor Leadership Project
Cohort: 2021
Fellow: Gwendolyn Stovall
UT CNS Freshman Research Initiative (FRI) peer mentors are a critical component of FRI success! FRI peer mentors, many serving as student teachers, guide undergraduate students in scientific research activities. For many, that includes leading meetings, providing student feedback, creatively solving problems and helping students connect the dots, honing interpersonal social skills, effectively communicating, and more – all 21st Century skills (Trilling and Fadel, 2009).
Making New Scientists: Supporting the Training of Incoming Science Majors
Cohort: 2021
Fellow: Ruth Shear
Traditional science degree programs concentrate primarily on content and are not known for preparing their graduates with other skills needed for scientific careers.
Valuing Humanities Education at the University of Texas
Cohort: 2019
Fellow: Julia Mickenberg
For some time now the humanities have been “in crisis,” but the crisis is becoming acute: majors in nearly all humanities fields have been sharply declining, enrollments are down, hiring of tenure-track faculty is down, and, at some colleges and universities across the United States, whole departments are being eliminated. Here at the University of Texas, majors that are growing seem to be ones that promise a literal return on investment (invest money in a degree and get that money back, in the form of a well-paying job upon graduation) or at least suggest an obvious and practical use.
Strategic Course Redesign Focused on Professional Skills
Cohort: 2018
Fellow: Kristin Patterson
The goal of this project is to shift the focus of a set of introductory courses, that are heavy in disciplinary content, in order to make space for greater emphasis on professional skills, such as information literacy, quantitative reasoning, communication, and others. The main challenge in accomplishing the goal is that the particular courses involved have high-enrollment—2300 undergraduates enroll in each course each year and they are taught by a team of 13 faculty. Because many faculty teach the courses, it is difficult to standardize the curriculum and the expectations across sections.
Data Analysis Tools: Integrating Computational and Statistical Techniques in the Environmental Engineering Curriculum
Cohort: 2018
Fellow: Paola Passalacqua
The goal of this project is to train the next generation of environmental engineers in computing and statistical techniques to solve big data problems. Current undergraduate students in the Department of Civil, Architectural and Environmental Engineering have little to no exposure to computational and statistical methods for data analysis (e.g., big data collected from sensor networks). I proposed to integrate computational techniques in several courses throughout the Environmental Engineering Degree.