Research Teams & Topics

Mentors and students – one-on-one or in a team? Predetermined or student-inspired topics?

The traditional model of mentorship has a direct link between one mentor and one student, with knowledge transfer flowing one direction, toward the student. The topic is chosen by the mentor, and the mentee provides the work to complete projects. But are there other ways of arranging this relationship? Let’s take a look…

How we did it:

In ARC-Learn, we re-envisioned the mentor-mentee relationship. Instead of a one-on-one relationship, we expanded the idea to include a research team. ARC-Learn research teams were made up of 1-3 mentors, and 2-5 students. Students had the opportunity to learn from more than one mentor as well as their student colleagues, and mentors on the team supported each other and received feedback from a range of students. These teams then worked together to support the development of individual research questions within that topic, and supported each other at every step along the way, including finding data, analyzing data, interpreting results and sharing results.

We tried out two different models for team formation:

Student-driven: Formation of research teams was largely student-driven for Cohort 1. Students came up with ideas for polar related research topics and grouped themselves into research pods. Mentors joined in the groups they felt they could best support. However, this process took a long time, and some individuals were disappointed when their mentors did not have the specific subject matter expertise to support their chosen project. Mentors also struggled with their role, as they did not necessarily have as deep subject matter expertise in their students’ projects as they would have liked. Cohort 1 Research Topics
Mentor & student-driven: As a shift for Cohort 2, we workshopped proposed themes with our mentors, and formed mentor teams around topics they felt confident they could support. Students then self-selected into groups based on the established topics. This was a much faster and less stressful process for students and mentors alike, though some students and mentors still experienced the same mismatch in subject matter interest and expertise. Cohort 2 Research Topics

Overall, our program focused on polar research, which is a timely topic that captured student interest. However, the pool of mentors is quite limited within this specific field, and the type of research they do often requires extensive field work in remote locations, meaning many mentors were absent for long periods. Polar scientists tend to focus on the natural and physical sciences, limiting the types of projects we could support (especially for students interested in social science).

Considerations for your program:

There is no law that says the time-honored tradition of mentor-mentee relationship is the only way to learn from those with more experience. Consider a team approach to allow students the opportunity to learn from each other as well as from multiple mentors and give students a strong sense of ownership over their project.

One challenge we faced using this model is that students can sometimes get a bit lost with multiple mentors and teammates. Make sure each student has one mentor who can track their progress and help them with the program, even if they are working with more than one mentor.

It’s important to allow students the autonomy to pick their own research question. It gives them ownership over the project and really helps them to understand the research process. However, if their research question cannot be supported by the mentors or the data available, this can be very frustrating for everyone involved. In addition, some students expressed disappointment that they were unable to directly collaborate with their research team members, and would have preferred to work on the same research question to gain these team research skills.

This type of long duration, inclusive mentorship program would probably work best within a research field containing a lot of potential mentors. Consider broadening the topic to draw from a wider pool of mentors (example: “oceanography” would have more mentors available than “polar sciences”). However, avoid framing your topic so broadly that you build expectations for something you can’t provide (example: “oceanography” describes physical and natural sciences, while “ocean sciences” could include social sciences and engineering which you may not have mentors to support).

ARC-Learn students located their own data sets to answer their research questions. Unusable data taught them about the true stop-and-start nature of scientific inquiry. However, for some of them, it ended up being a source of frustration that lasted throughout the program. Consider asking mentors to find several large data sets for students in their research team to use, if they choose to. This way, mentors will be equipped to support students in data cleaning and help students scope their research questions (as mentors would have a better sense of types of research questions that could be asked of the data). Students could also have the option of driving their own research question and finding their own data.