The Freshman Research Initiative
The integration of cutting-edge research with education both engages scientists and is critical to improving American competitiveness in science. The University of Texas at Austin has developed an innovative, groundbreaking, faculty-initiated program to tap the considerable resources of the research university — energy, ideas, expertise, mentorship, and facilities — to create a generation of science-minded innovators through undergraduate research.
The Freshman Research Initiative (FRI) is transforming the undergraduate teaching model by turning a student’s traditional trajectory on its head, placing first-year students into advanced research labs at the beginning of their educational experience rather than at the end. They connect with faculty. They are embraced by the community of their small research cohort. They work on real-world problems.
In short, they are inspired.
Started in 2005, FRI is a two-year-long program that begins during a student’s first year by placing them in one of more than 30 faculty-led “Research Streams” working on real world applications. Each year, freshmen are recruited into an intensive set of degree-program courses that incorporate critical thinking, interaction with faculty, hands-on experimentation, data interpretation, student presentation, publication and peer mentoring. The model incorporates cutting-edge faculty research amenable to large-scale freshman training and experimentation, after which students are experienced in a broad range of techniques and all aspects of research from conceptualization through execution and presentation.
Originally developed in biology and chemistry, the FRI program has been running and expanding for seven years and now involves projects in biology, chemistry, biochemistry, physics, astronomy, mathematics and computer science. In the past seven years, more than 3,000 new UT Austin students have participated, and the program now serves over 700 first-year students each year in the College of Natural Sciences, more than 33% of the incoming college class.
FRI is not a select honors program. There are no prerequisites, and it is unique in its ability to attract and empower students who are traditionally underrepresented in the sciences. Partially due to the fact that FRI courses replace traditional lab courses, making participation less daunting for many students, undergraduate research and the doors it opens have become available to students who have traditionally not participated. For example: approximately one-third of students entering the program are first generation college students, more than one third are underrepresented ethnicities, one quarter have low test scores and one-quarter have high financial need.
Students are challenged to ask their own questions within the context of a larger science problem and to produce relevant results, and they are provided the techniques and mentorship to rise to this challenge. Grit, resilience, tolerance for short-term failure, determination, passion and problem solving skills matter more within FRI than high school statistics, test scores or even previous courses. FRI levels the playing field for science students and is producing young scientists with new perspectives to help solve global challenges.
And clearly, FRI works: 35% more students graduate overall with a science or math degree if they participated in FRI, and the program more than doubles the graduation rate for Hispanic students in science, technology and math. FRI students have higher GPAs and get more scholarships compared with other students in the College of Natural Sciences. Additionally, these students are true contributors to the scientific conversation. Since 2005, 143 FRI students have co-authored peer-reviewed papers on their research.
The DIY Disease Diagnostics Team
This year a new Research Stream is being pioneered by three faculty members here at UT Austin: CSSB Associate Director Andrew Ellington (Molecular Biosciences), Peter Stone (Computer Science) and Pradeep Ravikumar (Computer Science). Each of these faculty members is outstanding in their own fields, but have come together to share their expertise with one another and with new students in the novel “DIY Disease Diagnostics Stream.” In this stream, freshmen will be challenged to develop an interdisciplinary skill set that would be daunting even to an experienced clinician (which is precisely why they need to be challenged now, before they are experienced clinicians). They will be trained in molecular methodologies that will allow them to develop self-test diagnostics, will gain a basic understanding of laboratory robotics, will interface with computer scientists who will help automate the delivery of diagnostics, and will create their own social networks for assessing the context and impact of their diagnostic assays.
- Advances in analytical chemistry, molecular engineering, biomarker discovery, and materials science have come together to begin a new age in diagnostics development. Whereas previously many medical tests were run in clinical labs or settings, point-of-care diagnostics can now be crafted for individual use. Much as home pregnancy tests altered the social landscape during the 1970s, home HIV tests are similarly providing a new means for consumers to empower themselves in medical decision-making. Similar tests for tuberculosis and other diseases will increasingly transform the interactions between clinicians and patients in resource-poor settings.
- In parallel, there have been revolutions in computer science that will further transform the delivery of health care. Not only is laboratory automation changing the nature of how we do science, but the increasing automation of society now mandates that we even begin to think about the robotic driver in the next lane. How will similar advances impact how we think about who our health care provider is, and how we interact with them? Is it possible that the diagnostics made possible by better-living through chemistry will now be administered by a robot?
- Finally, we continue to ride the wave of productivity and globalization released by the Internet. We now are intimately involved in the lives of individuals we’ve never met in person, and can crowd-source new data and new insights at a magnitude that was previously unimaginable. The aggregation of patient data will alter everything from the questions on a physical to the actuarial tables that determine insurance rates. Clinical trials will increasingly be carried out in a distributed fashion, with the results compared virtually. How will the glut of data that is being churned out every day by sequencing engines, and the coming glut of diagnostics data that will result from these sequencing insights, be handled not just by the medical profession, but by the consumers whom the data most directly impacts?
Making the Stream Possible
This Stream is only possible because of a generous gift from Bob and Cathy O’Rear, the involvement of the Gates Foundation, and UT Austin’s College of Natural Science, which is dedicated to providing the necessary research equipment, supplies, teaching assistants, mentors and student fellowships for this Stream.