Innovations in Undergraduate Research Training Through Multisite Collaborative Programming: American Heart Association Summer Undergraduate Research Experience Syndicate

Abstract

Background To support diversity in biomedical science, the American Heart Association launched the Supporting Undergraduate Research Experiences for undergraduate students from underrepresented backgrounds to provide mentorship and high-level exposure at 5 leading medical institutions. Here we describe the initial formation of the partnership and the alteration made in response to the program to accommodate COVID-19 safety precautions. Methods and Results We outline how programming shifted from local, in-person programming in the summer of 2019 to a collaborative, mainly virtual curriculum in 2020 using students' self-reported before and after surveys from both 2019 (n=33) and 2020 (n=42). Students from both in-person (2019) and virtual programs (2020) self-reported significant gains in scientific proficiency. A qualitative-directed content analysis of student open-response questions was performed. Students reported extensive benefits from the 2020 virtual training, including Personal Gains, Research Skills, Thinking and Working Like a Scientist, and Attitudes and Behaviors. Notedly, we observed increases in the Attitudes and Behaviors category. We outline the pros and cons of in-person and virtual programming and make recommendations moving forward in a postpandemic world with hybrid work and learning systems. Conclusions Our effort informs the development of future undergraduate research training programs, significantly maximizing a hybrid training modality. The American Heart Association Supporting Undergraduate Research Experiences serves as a model for building multi-institutional partnerships and providing research experiences that overcome institutional barriers and support students' interests, commitment, and ability to persist in science, technology, engineering, and math fields.

Keywords: American Heart Association (AHA); Supporting Undergraduate Research Experiences (SURE); multi‐institutional programming; online; training; undergraduate; virtual.

Figure 1. Shifting from local programming to collaborative curriculum.

A, Overview of 2019 common and site‐specific programming. In 2019, each institution ran the summer undergraduate program locally and all provided mentored independent research projects. Other elements included journal clubs, professional development seminars, biotechnology company site visits, and other training and professional development opportunities. B, Overview of 2020 shared and unique programming with a collaborative curriculum that leveraged each institution’s successful previous programming. Although all programs retained an independent research component and local social activities, a substantial amount of programming was shared across institutions and therefore available to all students across the sites. Collaborative programming was coordinated by the American Heart Association. GRE indicates Graduate Record Examinations; and VSSA,Vanderbilt Summer Science Academy.

Figure 2. Self‐reported gains in students’ proficiency and confidence in research.

A, Upper panel: 2019 self‐reported presurvey and postsurvey proficiency of students as averaged across 13 questions (N=12 students). Lower panel: 2020 self‐reported presurvey and postsurvey confidence of students as averaged across 33 questions (N=30 students). B, Upper panel: 2019 difference in postsurvey and presurvey proficiencies for individual questions, averaged across students. Questions are divided into 5 thematic categories. Lower panel, right: 2020 difference in postsurvey and presurvey confidence for individual questions, averaged across students. Questions are divided into 6 thematic categories. Avg. indicates average.

Figure 3. Directed content analysis of open‐ended responses based on Undergraduate Research Student Self‐Assessment survey themes.

Scatter plots are shown for all 3 coders counts, with the bar graph indicating the mean. The error bars indicate the standard deviation from the mean. A, For the primary code, the average number of codes for Personal Gains, Thinking and Working Like a Scientist, Skills, and Attitudes and Behaviors was 18, 15, 23, and 39, respectively. B, The averages for secondary codes were 20, 8, 5, and 10. C, When both the primary and secondary codes are combined, the averages are 38, 24, 28, and 50. A Kruskal‐Wallis test was performed, followed by Dunn's multiple comparison test. Overall, there was no significant difference between the number of codes for each theme generated by the primary (P=0.15) codes. However, there was a significant difference in the secondary codes (P=0.008). Personal Gains codes responses were significantly more as compared with Skills codes (P=0.03). When the codes were combined, there was no significant difference (P=0.10). D, Representative quotes for each theme, including primary and secondary themes, are shown. A indicates Attitudes; N/A, not applicable; P, Personal Gains; PI, Principal Investigator; S, Skills; and T, Thinking and Working Like a Scientist.

Figure 4. Directed content analysis of open‐ended responses with virtual relevance.

During the review process, quotes that were related to the virtual nature of the program were flagged. Overall, this represented 34 of the 198 comments. We evaluated the codes associated with these 34 comments. Shown are scatter plots for all 3 coders counts with the bar graph indicating the mean. The error bars indicate the standard deviation from the mean. A, For the primary code, the average number of codes for Personal Gains, Thinking and Working Like a Scientist, Skills, and Attitudes and Behaviors was 1, 1, 8, and 12, respectively. B, The averages for secondary codes were 6, 2, 0, and 2. C, When both the primary and secondary codes are combined, the averages were 7, 3, 8, and 14. A Kruskal‐Wallis test was performed, followed by Dunn's multiple comparison test. There was a significant difference for the primary codes (P=0.0043). However, there was no difference between the theme of the code following the multiple comparison corrections. For the secondary codes, there was also a significant difference (P=0.0164). Personal Gains codes responses were significantly more as compared with Skills codes (P=0.0340). When the primary and secondary codes were combined, there was still a significant difference (P=0.0153). Coding for comments that corresponded to Attitudes and Behaviors was significantly greater than the number of codes corresponding to Thinking and Working Like a Scientist. D, Representative quotes for each theme, including primary and secondary themes, are shown. A indicates Attitudes and Behaviors; AHA, American Heart Association; CVI, Cerebral Visual Impairment; N/A, Not applicable; P, Personal Gains; S, Skills; and T, Thinking and Working Like a Scientist.