Creating College-High School Partnerships to Assess the Prevalence of Antibiotic-Resistant Microbes in the Environment

Project No.
PI Name
Carol Bascom-Slack
Yale University


Abstract 1

Creating College-High School Partnerships to Assess the Prevalence of Antibiotic-Resistant Microbes in the Environment

Presentation Type
Carol Bascom-Slack, Yale University


Many reports indicate the need for infusing more authentic research into the undergraduate curriculum. There have also been recommendations to encourage partnerships to diversify pathways to STEM careers. The PARE (Prevalence of Antibiotic-Resistance in the Environment) program addresses both of these needs.


This project aims to improve STEM education in a transformative way by providing a low cost, low time commitment gateway opportunity for instructors to transition out of a traditional laboratory style of instruction into an authentic research-based course. At the same time, partnerships are created between undergraduate and high school students (and their instructors) to generate a database of antibiotic-resistant microbe levels at environmental sites all around the country. This aggregate data set can be used for analyses by students to answer questions of interest to the broader scientific community.


Currently there are no systematic surveillance methods for reporting levels of antibiotic resistant microbes at environmental sites, yet we know that environmental exposure to antibiotics is high in certain areas. Students use systematic sampling and reporting methods prescribed in instructional materials developed for the program. The techniques, level of expertise required, and cost to implement are within reach of instructors at a diversity of institution types including high school, community college and doctoral-granting institutions. The project takes only one or two class periods, making it easy to place into an existing curriculum, yet there are multiple opportunities for expansion of the project. Social media provides an opportunity for instructors to share ideas and to troubleshoot, creating a community of researcher-instructors.


Detailed implementation materials have been developed for instructors and for students. Instructor feedback guided revision of the first iteration of materials. A data-entry site compiles data from each participating student. A social media site allows instructors to communicate results and ideas. First-year undergraduate instructors attend the American Society of Microbiology Conference of Undergraduate Educators together, providing an opportunity for professional development, program feedback and collaboration. Aggregate research data should allow students and researchers to identify antibiotic-resistance hotspots, to determine how far resistance levels extend beyond a hotspot, and to learn how these levels change over time. Student assessment should indicate whether the program is having a positive impact on student learning or behavior.

Broader Impacts

Currently, the project has been disseminated to over 60 instructors and approximately 500 students participated in the first year with over 1,000 expected to participate this academic year. Students experience authentic research, but the greater impact may be on the institutions if instructors continue to implement in subsequent years and if they choose to expand the program beyond what is prescribed. One of the most reported comments by high school students is how much they enjoyed interaction with college-level students. Given the fact that we target high schools serving underrepresented minorities or economically disadvantaged youth, we hope that (and are assessing whether) these interactions will have a positive impact on studentsï¾’ desire to apply to college.

Unexpected Challenges

Student-collected data are used to accumulate a database of information useful for the greater scientific community. The rate of error by students was initially underestimated and the commitment of participating instructors to identify and correct errors was overestimated. The student-error problem was addressed by altering our protocols. Previously, students worked individually, but now they work in teams such that individuals from each team 1) perform experimental methods on same sample (identify methods errors) 2) perform calculations on same set of results (identify calculation errors) and 3) enter the results into the database (identify entry errors). Commitment by instructors was addressed through individual phone calls stressing the importance of reliable data. A field in database was added for instructors to 'sign off' on review of their students' submissions.


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