Improving Teaching and Learning

The development of increasingly powerful computational resources has made computational competencies new core forms of literacy that should be formed as part of basic education across all STEM fields.

The current proposal envisions developing alternative pedagogical materials for the “Measuring Racial Inequality” course, written in plain language and accessible to students from social sciences/humanities and underserved communities and families.

The primary goal of this project is to enhance student engagement and participation in the learning environment, especially those who have may have been marginalized by conventional approaches to teaching. This project aims to support, encourage, and train faculty to incorporate compassionate pedagogy (CP) and experiential learning (EL) into their teaching, with the goal of promoting student connection and faculty creativity.

Within social work curriculum, the topic of disability is either explicitly absent or medicalized.  The lack of a rich understanding of disability as a cultural experience that intersects with other cultural experiences is concerning given our ethical guidelines of cultural competence and equity.  Additionally, not only are students excluded via this omission, but so are faculty, staff, and social workers working in the field.  Approximately a quarter of the population identifies as having a disability, yet our curriculum barely acknowledges their experiences.

The Computer Science department provides CS classes to the whole university via our Computer Science "Elements" program. The Elements sequence can be started by any student in any major with no prerequisites; later Elements courses only have prerequisites from earlier Elements courses. Some students choose to take just 1 or 2 CS classes in order to learn some programming, and others choose to take 18 hours in order to earn the Elements of Computing Certificate. The CS Elements program serves a very diverse population of students, in terms of backgrounds, majors, and goals.

Each year I attend Teaching Discovery Days and Texas Teach-Up and leave motivated to try new teaching practices. The majority of the practices I observe during Texas Teach-Up, hear about at conferences, or read about in the literature need substantial adaptations to work in my large classes. Figuring out how to make new practices work well and remain manageable sometimes seems insurmountable. Discussions with others who teach large courses often provide insights and ideas, but in any given department at UT there may be just one or just a few professors who teach these large class sizes.

Student evaluations of teaching (SETs) are one of the official means to gauge the performance and effectiveness of an instructor at higher-education institutions. They are often used for promotion/tenure decisions as well as to guide faculty into becoming effective instructors. But the question is whether, as currently implemented at UT Austin, SETs are reliable indicators of (a) effective teaching, and (b) long-lasting, impactful learning?

Our project seeks to revitalize the syllabus document as a tool of inclusion. We are interested in making visible the “hidden curriculum” with which students often struggle. The syllabus language, grading and attendance policies, communication and assignment fulfillment methods, course calendar flexibility, course material formats – these can all contribute to developing personal accountability and investment in community.

Biology continues to be seen as a field for science-interested, but math-disinterested students. However, due to the surge in data use in all biology careers, and the focus in research on sequence data, there is a strong need for data skill development in biology degree programs. Math anxiety poses a specific challenge for biology education. A suggestion to overcome this, is an early introduction to data skills in the two-course sequence of Introductory Biology.
 

The primary goal of this community-based service project is to provide experiential learning opportunities for undergraduates interested in statistics and data sciences while supporting the broader Austin-area community. Coordinating with local organizations, students enrolled in some of our SDS courses are gaining hands-on experience in data analysis while exploring authentic contexts. This innovative and collaborative effort provides a community-based model that allows students and local organizations to co-develop and answer real-world research questions.