1 of 2

CUREs - Design & Student Perceptions

Henna Kaur, Mina Negahban, Kenneth B. Kaplan, Ph.D.

Molecular and Cellular Biology, University of California, Davis 95616

Abstract

Course based undergraduate research experiences (CUREs) ideally expose students to five dimensions of scientific research: scientific practices, the process of discovery, the impact of the research, the need for experimental iteration, and the importance of collaboration (Auchincloss et al., 2014). However, it is unclear whether the design of lab-based activities and the perceived experiences of students reliably reflect these dimensions. To begin to address this issue, we created a dimension map of 53 CURE proposals that were generated in a workshop for international undergraduate instructors. In a second approach, we collaborated with the First Year Seminar team at UC Davis to survey students about how their CURE experiences impacted their perceptions of the learning outcomes associated with the specific CURE -dimensions. In the first part of our work, we found that instructors’ proposals emphasized scientific practices and the importance of the research over other CURE dimensions. We are in the process of gathering data from students and we will present our findings in the future. We hope to shed light on the gaps between lab-course planning and the perceived learning outcomes described in the CURE dimensions.

Course-based undergraduate research experiences (CUREs) are lab-based courses, in which students address relevant issues in biology by designing experiments in pursuit of novel findings. They differ from traditional lab courses by requiring the inclusion of five main dimensions in their design: scientific practices, discovery, iteration, collaboration, and broader relevance (i.e., impact) (Auchincloss et al., 2014). CUREs aim to increase undergraduate engagement with research in hopes of increasing retention rates in STEM majors and students’ sense of belonging in the greater scientific community (Bangera & Brownell, 2014, Eagan et al., 2013, Pender et al., 2010). CUREs can help increase this number by making research accessible to a more diverse population of undergraduates early in their academic careers, including groups that fall into the non-traditional students' category (Hurst-Kennedy et al., 2020).

Unlike more traditionally designed lab courses that focus on techniques, CUREs represent a particular challenge in design and delivery to ensure the experience reinforces all five dimensions in students from diverse backgrounds and with widely varying experiences. Obvious limitations include that students may not have sufficient guidance or space to reflect on the learning objectives embodied in the CURE dimensions. Similarly, instructors may overly focus on technique and not have the proper training to recognize or incorporate the full range of dimensions associated with CURE design, since this type of research-intensive course is new to many (Bangera & Brownell, 2014). In order for CUREs to have the most meaningful impact on students, it is vital that the effectiveness of CURE design and student learning outcomes are carefully assessed. The purpose of this study is to analyze how CURE design and student perceptions map onto CURE dimensions in order to create a more efficient framework for designing CUREs.

Table I:

Background

Results

STUDENT PERCEPTIONS

Future Experiments

Conclusion

Acknowledgements

Survey Approach

CURE Design Mapping

In 2021, the Genetics Society of America hosted the “Bridging Research and Education Workshop”, in which a group of international, college-level instructors designed CURE type modules using experimental model systems. We used these proposals (n=53), to evaluate how well they aligned with the complete set of published CURE dimensions. This approach allowed us to test the hypothesis that initial design of lab modules typically fail to fully address the learning objectives linked to the complete set of CURE dimensions. Our goal is to use this study to improve CURE design by highlighting the more commonly ignored CURE dimensions.

An example of the specific process of mapping descriptors to learning objectives that support a CURE dimension is as follows: we mapped descriptors involving hypothesis and experimental design, quantitative reasoning, oral, written or visual communication assignments onto learning objectives related to the scientific method and scientific communication, which support the “Scientific Practices” CURE dimension. Within experimental design, mention of reproducibility of tests or repeat of published experiments would support the “iterative” CURE dimension. Similar mapping was used for the other CURE dimensions.

After mapping descriptors to learning objectives and CURE dimensions, we found that the “Scientific Practices” and “Broadly relevant important work” were most commonly reflected in the proposals. In contrast, the “Iteration” and “Collaboration” dimensions were least reflected in the proposals. Table 2 shows the percentages of proposals that mapped to each CURE dimension using the high stringency approach. We conclude that, at least in this group of lab module proposals meant to be CURE-centric, proposals reliably failed to reflect at least one and often more than one CURE dimension (>90% missed two or more dimensions). Figure 1 indicates that the majority of proposals (34%) only met 3 dimensions. CUREs are specifically defined to include all five dimensions: “we propose that it is the integration of all five dimensions that makes a learning experience a CURE.” (Auchincloss et al., 2014). Our findings led us to hypothesize that students in CUREs would more frequently fail to identify the learning outcomes and associated CURE dimensions of collaboration and iterative experimental approaches with their experiences in the CURE.

To address how students perceive the kinds of learning outcomes that support CURE dimensions, we collaborated with the Associate Director of Curricular Development, Kate Andrup Stephensen, to create survey questions for students in the First-Year Seminar (FYS) CUREs. These survey questions were designed to assess student perceptions on whether their CURE experiences supported the learning objectives described in Table 1. Examples of the survey questions generated in collaboration with the curricular development team are shown in Figure 2 below. In total, students were asked to answer 38 questions that were divided among the learning outcomes that we connected to the CURE dimensions, as listed in the figure. The questions we contributed to the survey focused mostly on Iteration in the course, as it was the least achieved CURE dimension based on our thematic mapping results. Unfortunately, due to a low student response rate, we were not able to analyze the student response data.

Fig. 1: This figure shows the percent of proposals (n=53) we evaluated to meet 0-5 CURE dimensions using the learning objectives mapped in table 1

Fig. 2: This figure identifies examples of survey questions that were sent out to students in the FYS classes. White stars indicate questions that we generated, while the other questions were created by Kate and her team.

Kate Andrup Stephensen- Associate Director of Curricular Development, UC Davis

*Due to insufficient data collection (3 student responses), no results were generated from the survey.

A major challenge in assessing student perceptions is student participation. A goal for future studies will be to tie student participation to a reward system within the FYS CURE offerings to ensure robust response rates. A major long-term goal of this inquiry is to track changes in student perceptions before and after their CURE experience as well as their future academic and professional outcomes, and increasing student response rates is critical in achieving this.

While the majority of CURE proposals by college-level instructors meet the Scientific Practices and Important Work dimensions, most of them failed to include Iteration or collaboration in their design. This analysis likely identifies CURE dimensions that are more challenging for research-trained faculty to incorporate into their lab designs. It also identifies areas that future workshops on CURE design should emphasize. The next challenge is to identify how CURE design correlates with students’ perceptions of the proposed learning objectives. CUREs can be very powerful tools to increase retention and a sense of belonging in STEM fields, but require careful attention to design and an ability to assess how well design connects to learning outcomes.

Dimension	Learning Objective Indicators
Scientific Practices	References to the scientific method, hypothesis formulation, and/or experimental design
Discovery	Formation of open-ended questions and the identification of a “gap” in the field’s understanding of a biological question
Broadly relevant or important Work:	Proposals that tied in questions outside the immediate field of biology being explored in the lab, including but not limited to issues surrounding diversity, scientific ethics, health and disease and how the impact of this work would be communicated to a larger audience.
Collaboration	Inclusion of group projects such as papers, and posters in addition to group question formation, data collection, discussion, and outside group consultation.
Iteration	Proposed repetition of experiments, data collection and challenges to reproduce already published data or conduct follow-up experiments.

Approach

Using the 53 CURE proposals generated from the workshop, we evaluated them for inclusion of CURE dimension specific learning objectives (see Table I) using first a low followed by a high stringency mapping approach.

This stepwise analysis allowed us to identify common language used to describe course learning objectives and then to develop a more precise system to match these descriptors to CURE dimensions. In table 1, the five CURE dimensions are matched to their corresponding learning objective that we developed in our analysis.

Dimension	% of Proposals that met dimension
Scientific Practices	67.9
Discovery	57.2
Important Work	62.3
Collaboration	41.5
Iteration	9.4

Table 2:

1 of 2

2 of 2