Program Description
Program Philosophy
The MRS REU program is designed to engage students with the scientific process at all levels. Program participants have the opportunity to:
- Apply the scientific method to modern research questions in ecology, evolutionary biology, and behavior.
- Develop experimental design skills and gain experience with acquiring data.
- Learn rigorous data analysis techniques and statistical techniques.
- Present the results of independent research in front of faculty and peers.
The multiple skills acquired as a result of this process make REU program participants competitive applicants for graduate school and stronger candidates for jobs in biological research.
Program Design
Ther core component of the MRS REU program that facilitates the learning objectives stated above:
- All students develop an independent research project under the guidance of a faculty mentor. Faculty mentors have committed their time and expertise to the program, and are dedicated to helping students succeed throughout the development, execution, data analysis, and presentation phases of independent projects.
- Seminars and workshops will provide students exposure to the ongoing research at the MRS, describe local environmental issues (e.g. nitrogen deposition, climate change, fire), facilitate science communication, and assist students with the next step in their science training (graduate school)
Timeline
The first week of the MRS REU program is a critical period devoted to working in groups of 2–3 on three small–scale research projects. These projects allow students to get to know each other in an informal, collaborative setting. Â鶹ÒùÔº also get a chance to design and execute experiments, analyze data using statistical techniques, and present findings in front of their peers.
Weeks 2—9 are spent working intensively with faculty mentors developing, designing, and executing students' independent research projects, with instructional seminars and social events scattered in the mix
Week 10 is typically allocated to data analysis (graphical and statistical), and assembling an oral presentation that will be delivered to an audience of faculty mentors and peers.