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CUREs for Research

Why CUREs for Research?

Although many faculty members choose to teach CUREs for pedagogical reasons or for other professional and personal reasons, faculty members also choose to teach CUREs primarily to accomplish research goals. This is possible because CUREs are often connected with a faculty member's ongoing research program and they allow for expansion of some element of the research program by providing:

  • More minds and hands to work on the research - students often generate new ideas that don't occur to experts in the field and can generate new research directions. Furthermore, projects that require collecting and analyzing large datasets can get done faster;
  • Opportunities to explore a larger variable space - students can work in parallel on a common system or experimental set-up, taking on responsibility for their own sample, treatment, or experimental variable while contributing to a larger dataset or analysis; and
  • Lower risk avenues to pursue new research directions - if the research goes as planned, great! If not, then students have learned something along the way and no one's dissertation was on the line.

Conducting Research with Students

Two main research issues often arise in CUREs: data quality and authorship. Each of these is discussed separately below.

Data Quality

Faculty members who are starting a CURE often ask, how can we ensure the scientific quality of the work when students are just learning themselves and there are many of them enrolled in a course who may do work of varying quality? How to ensure the quality of the data will depend on the types of data being generated. Here are strategies that have been used to improve the quality and consistency of students' work and the resulting data:

  • Set up "performance checks" where all students have to pass a certain performance standard (e.g., pipetting with a certain level of accuracy) before they are allowed to move to the next step of the research. Students can each be assigned a "checker" role for a skill they have mastered to divide the workload of checking performance of all students in the CURE.
  • Design replicates into the CURE so that several students or groups of students are doing the same experiment or research task and can compare results. This strategy not only helps to increase sample sizes, it can be used as a teachable moment for discussing the value of replicates as well as the potential sources of error and how error can be reduced.
  • Allow students to iterate, or repeat aspects of their work in order to practice and become more proficient at the techniques or skills they are using and to gain confidence in the quality of the data. If the data look similar over multiple iterations, this improves the sample size and also ensures the trustworthiness of the data. Iteration takes time; be sure to leave some unscheduled time for this or be flexible in scheduling to allow for the unpredictability of research.

Authorship

Because CURE students are working on research that could ultimately lead to publications or other scholarly products (e.g., database entries, conference posters or presentations), the question often arises whether all students in the CURE should be co-authors. There is no single answer to this question. Rather, CURE leaders need to consider the following:

  • What counts for authorship in the discipline of the CURE?
  • What counts for authorship in the venue or product where the work will be shared? (e.g., conference presentation, technical report, database entry, primary literature)
  • What are the norms of authorship order in the discipline of the CURE?
  • What are the ways authorship order could or should be decided?
  • How or when should authorship and authorship order be revisited as progress is made in the research?
  • What processes should be put in place to make sure authorship is equitable and appropriate in terms of both scholarly and ethical standards?

Also see CURE as Pedagogy