A Practical Guide for Mentoring Scientific Inquiry

Abstract

Science is a process of acquiring understanding, not just a collection of facts. The literature on teaching science emphasizes the importance of student research—teaching students to develop new knowledge, rather than solely assimilating facts. As student research becomes more widely integrated into curricula, there is an ongoing opportunity to develop and refine explicit techniques and tactics for facilitating authentic research by students. Here, we draw on our experience as instructors in the tropical biology field course at Dartmouth College to provide specific strategies and approaches that we have used to help students conceive and conduct original research projects. We organize our suggestions around the stages of the research process, from generating and refining questions, optimizing methods, and interpreting data, through presenting findings and placing research in a broader context. Although research skills often develop organically through immersion in research environments, it is our experience that explicit instruction can expedite the development of these critical skills.

Course‐based undergraduate research experiences in a remote setting: Two case studies documenting implementation and student perceptions

“…The final week of projects was focused on dissemination and communication of project findings, a critical component of inquiry‐based learning (Schamel & Ayres, 1992; Symes et al., 2015). Bio 301 culminated in an IP symposium, where each group presented a formal 6 min presentation followed by 3 min of questions from their peers.…”

“…Third, given the novel academic setting, projects may be reduced in scope (e.g., yield less data) from what might typically be feasible on campus in the same time. Here, we recommend calibrating expectations by emphasizing the importance of process and skill building rather than outcomes: combatting the perennial challenge in science education that obtaining “clean” data (e.g., low variance surrounding treatment means) or data that support hypotheses should be the primary outcomes by which the merits of the project are assessed (Symes et al., 2015). Finally, in the absence of regularly scheduled periods where students and faculty work in close proximity in a field or laboratory setting, creating meaningful student‐faculty interactions must be re‐imagined, yet prioritized.…”

“…A final silver lining of remote CUREs involves mentoring, a critical component to maximizing outcomes during CUREs (Linn et al., 2015), which can be achieved with modern tools such as virtual meeting software and learning management systems (Box 2). The ability to schedule virtual “face‐to‐face” meetings between whole classes, small groups and individual students and faculty provides a more than adequate setting for the exchange of ideas, sharing of experiences, and relationship building that are critical elements of mentoring (Symes et al., 2015). Likewise, other essential aims of CUREs, such as moving outside of textbook examples and participating in the scientific method (Windschitl et al., 2008), still remain possible in a remote setting.…”

Designing a Real-World Course for Environmental Studies Students: Entering a Social-Ecological System

“…Teaching through research fosters higher levels of student engagement than the typical classroom setting and facilitates the development of skills for problem solving (e.g., [22]). Further, an immersive field environment promotes deep learning [23]. Mogk and Goodwin [24] emphasize that, in the field, students make their own decisions about what is important and how to present that information, rather than receiving information filtered through an instructor.…”

A pilot study to define and identify future priorities intoAllocasuarina robustarecovery as part of a community program

“…A cornerstone of science is the generation of questions; this may involve creating or reaffirming known knowledge or applying an experimental design differently, none of which will lead to misinformation. Misinformation from experimental design occurs at the execution stage, affecting the results and data analysis (Newman, 2008;Symes et al, 2015).…”