I have mentored NSF funded REU students through a math bio program.
My collaborators described our experience in a paper, Using a Summer REU to Help Develop the Next Generation of Mathematical Ecologists.
Here's my answers to questions given my experiences mentoring over 3 summers over the past 7 years:
In general, what does success look like in an undergraduate research project?
For the students, learning about research through doing research.
I have had students discover they want to go to grad school.
I have also had students learn they do not want to go to grad school.
Both outcomes are successes because they positively shaped the students' lives.
An added bonus is that I have had 2 student first-authored papers from their projects.
However, the mentorship was my greatest personal success.
The timespan is relatively short (6-8 weeks), and I'll have to learn and apply my knowledge quickly. So what does success mean?
Plan out a schedule before you start.
We treated our REU like a mini-biology master's program for 10 weeks.
- We spend about 2 weeks in a coding and math/stats/biology boot camp. This ensures all students have the skills they need.
- We then gave the students a focused project, usually in groups of 2-3.
For some students, the project would take all summer.
But, they would have something to present at future meetings.
These projects could be simple questions we had about data or existing models.
Or, they might be recreating an existing paper.
We selected projects given our (the mentors' interests) that also naturally lent themselves to bigger questions.
For stronger students, these projects would springboard into bigger questions they would discover on their own.
- We would spend the last 2 weeks winding down. The students would create a poster of their work. This gives them something to share at their home university. We also would send students to a national meeting to present after the REU. Also, we would do a de-brief with the student.
Throughout the REU, we would have guest speakers talk about the softer sides of science and research.
For example, we have regular speakers on careers in science and also people talking about how they got their jobs.
We also ensured our REU students' research was impactful and novel because we applied the models to new systems used by managers.
For example, we would have the students work on problems US Fish and Wildlife Service biologists could use the results from for their management.
Thus, even if the math and statistics were not new, the biological application were novel and impactful because agency biologists could use the results for decision making.
How can I ensure that measurable achievements come out of such a project? What kinds of measurable achievements are there to aim for?
Look at the paper I shared.
My collaborators did formal pre- and post-REU assessments.
These allowed them to describe how they changed students likelihood for going to grad school and learned about science.