An Innovative Approach to Facilitating Interdisciplinary Collaboration among STEM and Public Health Students in Biomedical AI and Clinical Translational Research

Abstract

Introduction.

Research internships, designed to enhance students’ scientific knowledge, research skills, and confidence, typically focus on a single science, technology, engineering, and mathematics (STEM) discipline and miss the opportunity to facilitate the development of interdisciplinary collaboration skills crucial for translational research.

Methods.

As part of the Human BioMolecular Atlas Program (HuBMAP), we piloted a 5-day spring break research internship with two tracks: technology (targeting STEM students) and policy (targeting public health students). The program, attended by 21 participants and conducted synchronously via Zoom, included interactive virtual sessions, hands-on activities using digital tools, small-group discussions, and reflection assignments, with students collaborating and drawing upon their diverse perspectives to generate hypotheses, solve problems, and practice disseminating scientific findings through abstracts and posters.

Results.

The internship was well-received, with17 of 21 participants completing a self-assessment of academic and research abilities before and after the internship, and 18 completing a post-program satisfaction survey. Participants reported increased research self-efficacy and high satisfaction with the program overall, topics addressed, opportunities for peer interaction, program length, and value for academic development. Students' free-text responses highlighted the value of interdisciplinary collaboration.

Conclusion.

This innovative pilot program and its promising outcomes emphasize the benefits of early interdisciplinary collaboration in students’ research careers and provide initial evidence for the effectiveness of a cohort-based research internship for engineering and public health students. We intend to continue developing and refining the curriculum and plan to offer an open-access version accessible for instructors at other institutions.

Introduction

Artificial intelligence and machine learning (AI/ML) are rapidly growing areas of biomedical research. Challenges addressed by AI/ML research span across traditional disciplines and require effective collaboration and contributions of large teams of researchers with diverse perspectives. Similarly, computational biology techniques advance rapidly, which calls for the need to develop educational programs that promote bioinformatics skills and data analysis.¹ At the same time, as the body of biomedical knowledge grows, training programs recognize the need to expose students to interdisciplinary learning and experiences.² Incorporating public health perspectives is especially important to ensure that innovations promote equity and population health by addressing real-world challenges that benefit diverse populations. One such initiative is the Human BioMolecular Atlas Program (HuBMAP), a consortium funded to support tissue mapping, technology development for image, various omics, and non-image data analytics and visualization, and demonstration sites that span 42 institutions and over 300 investigators in four countries.³ Aims addressed by the HuBMAP consortium require the effective collaboration of biology, engineering, clinical science, ethics, and public health and policy scholars. The overarching goal of HuBMAP is to produce an atlas of the human body at single-cell resolution.³ Public health perspectives are critical to ensure that the AI/ML-based tools and processes used in its development align with principles of fairness, equity, and accessibility, and that they are representative of the U.S. population, by advocating for the inclusion of data from diverse samples. This helps to prevent biases that can exacerbate existing inequalities and a lack of explainability, which are long-standing issues in the AI/ML fields.^4,5 HuBMAP and other large-scale research consortia highlight the importance of interdisciplinary collaborations, underscoring the critical need to strengthen the student training pipeline by emphasizing experience in inter-disciplinary teamwork and translational research prior to workforce entry. These efforts should encourage and support partnerships among students and researchers from diverse disciplines, ensuring the next generation of scientists can thrive in and contribute to interdisciplinary, team-based research environments.^6,7

Research internships are proven programs that enhance students' scientific knowledge, research skills, and confidence.^8-11 Yet, these opportunities tend to focus predominantly on single science, technology, engineering, and mathematics (STEM) disciplines while failing to facilitate the development of interdisciplinary collaboration skills crucial for translational research endeavors. Innovative programs for trainees within STEM disciplines that have prioritized interdisciplinary collaboration show notable improvements in students’ communication, collaboration, critical thinking, and creative problem-solving skills.¹² Such promising outcomes emphasize the benefits of early interdisciplinary collaboration in students’ research careers. However, to our knowledge, few, if any, undergraduate research internship programs have been intentionally designed to bring together students from STEM fields and those from health policy and public health disciplines for the purpose of fostering interdisciplinary collaboration. In this paper, we describe a pilot research internship that was novel in both its structure and objectives: it provided undergraduate students with deliberate opportunities for interdisciplinary interaction and teamwork. Specifically, the program promoted collaboration between engineering and public health trainees on cell-level research projects. Our report demonstrates an innovative approach to training program design and provides initial evidence for the effectiveness of a cohort-based research internship that brings together engineering and public health trainees in the context of AI/ML biomedical research.

Materials and Methods

Structure and content

As a part of the HuBMAP program, the author team piloted a spring break research internship comprising two tracks, a technology track and a policy track. The former targeted students from STEM disciplines and focused on AI in digital imaging, biology, engineering, and quantitative health. The latter was designed for public health students, emphasizing AI policy and ethics, data governance, and open science. The two-track structure was designed to provide slightly different emphases based on students’ academic backgrounds and prior research experience. While the overall structure of the program was shared, each track engaged in a distinct hands-on session on Day 2. Technology track students participated in a cell annotation activity, while policy track students focused on data extraction and screening for a literature review. Students then completed individualized lab notes based on their respective activities.

The pilot program, housed within the Computational Microscopy Imaging Laboratory at the University of Florida, was conducted over five days in March 2024 and delivered in a synchronous remote format via Zoom, with approximately 25 total contact hours. The schedule included interactive sessions, lectures, hands-on activities, and practical tasks conducted in a virtual setting, as well as small-group discussions and reflection assignments (see Appendix A for curriculum details).

Throughout the internship, students in the technology and policy tracks were encouraged to collaborate, sharing different perspectives and drawing from their diverse experiences to generate hypotheses and solve problems. For example, students analyzed the HuBMAP public data on the demographics of HuBMAP organ donors, followed by discussions on the biological and ethical implications of the representativeness of an organ donor pool to the U.S. or world populations. Additionally, students developed policy briefs articulating their perspectives on the significance of HuBMAP and similar programs for translational research discoveries and training of the next generation of scholars.

One example of how the program engaged students in a hands-on activity within a remote, synchronous Zoom set-up was the cell annotation activity, in which students received a tutorial on how to use Seeden Viewer,¹³ a cell annotation software, from a post-doctoral associate. Students then worked in small groups utilizing the Zoom break-out rooms feature to conduct their cell annotations. This collaborative activity was designed to help students develop technical skills in cellular identification and classification. The hands-on experience with specialized digital pathology software allowed students to apply theory to practice using a tool that is both research-oriented and industry-relevant. Through guided annotation exercises, the activity aimed to expose students to the balance of technical skills, biological understanding, and methodological rigor involved in biomedical AI research.

Students also collaborated in small interdisciplinary groups to develop research posters, which they were encouraged but not required to present at the institutional undergraduate research symposium. Students were provided with suggested topics for their posters but were also encouraged to refine these ideas or to generate their own research questions. To support the gradual development of posters throughout this short research experience, students were encouraged to maintain digital lab notes on a collaborative Google Drive, which they could refer to while developing their research ideas. Participants presented five posters at the University of Florida 2024 Undergraduate Spring Research Symposium. These activities provided students with the opportunity to devise a plan to address a research question and to disseminate and communicate scientific findings in plain language. While our team did not include lay members, students were instructed to write their abstracts and posters in language accessible to non-expert audiences. Students received a presentation on Day 5 on how to write effective abstracts. In this session, students were guided on the importance of scientific communication as a means of distilling technical information into ideas and messages that are understandable by laypeople, thus bridging the gap between scientists and the public. The students received guidance on using simple, concise, and active language, and emphasis was placed on conveying one idea per sentence.

Participant recruitment

The pilot experience was advertised to University of Florida undergraduate students in the Department of Biomedical Engineering and undergraduate students enrolled in the Bachelor of Public Health program via an email announcement containing a promotional flyer. The experience was also promoted to undergraduate students studying Health Informatics. Participants were required to complete an online application form administered through Qualtrics, indicating which track they were applying for (technology or policy track) in addition to providing details about their class standing, major, grade point average, their resume, and a personal statement outlining their background, interest in participating in the experience, and their career goals. All participants were required to be U.S. citizens or permanent residents, and all participants received a $300 stipend.

Evaluation methodology

A retrospective pre-then-post design was used to evaluate the outcomes of the program.¹⁴ At the end of the pilot program, all participants were invited to complete a post-program evaluation survey, administered anonymously via Qualtrics, which included a self-assessment questionnaire and a satisfaction survey. The complete post-program evaluation survey is provided in Appendix B.

The satisfaction survey aimed to assess participants’ overall experience of the internship and gather feedback on areas of improvement. Students were asked to rate their level of satisfaction with the program across 5 domains: overall satisfaction with the program, topics addressed in the experience, opportunity to interact with peers, length of the program, and value for academic development. Response options ranged from 1 (extremely dissatisfied) to 5 (extremely satisfied). Students were also asked to provide free-text responses regarding the ways in which, if any, peer collaboration enhanced their research experience and to suggest improvements for future iterations of the program.

For the self-assessment, we employed a cross-sectional survey to administer a retrospective pre-post questionnaire that used a 17-item scale adapted from the Entering Research Learning Assessment instrument.¹⁵ Items on the scale included research skills, interpersonal skills, researcher identity, inclusivity, and professional development skills. For each item, students were asked to indicate their abilities on a Likert-type scale of 1-5, from 1 representing “no ability” to 5 representing “great ability” both before and after the program. The complete list of the 17 items in the self-assessment survey can be found in Appendix B, Block 2. A Wilcoxon Signed-Rank Matched Pairs test was performed to assess the difference in the mean student scores for the before and after questions. Analyses were conducted in SAS version 9.4 (SAS Institute Inc., Cary, NC), and figures were generated in R version 4.4.0 (R Foundation for Statistical Computing) within RStudio version 2025.05.0 (Posit Software). All p-values were two-sided, with p < 0.05 considered statistically significant.

Results

The pilot spring break research internship involved 21 undergraduate students majoring in biomedical engineering, electrical engineering, and public health. Of these, 13 students participated in the technology track and 8 in the policy track. Of the 21 students invited to complete the anonymous post-program evaluation survey, 18 submitted responses. Due to item-level nonresponse, not all questions received complete answers. Demographic data are based on 17-18 participants, depending on the variable. Program feedback was analyzed for all 18 respondents who submitted responses to the question asking students to rate their level of satisfaction across five domains. Data for the before and after self-assessment questions were available for 17 participants.

The 17-item scale used in the self-assessment survey (Appendix B. Block 2) showed high internal consistency, with Cronbach’s α = 0.94 for the “before” questions and α = 0.95 for the “after” questions. Based on students’ responses, the Wilcoxon Signed-Rank Matched Pairs S statistic indicated a statistically significant improvement in mean scores, with an S statistic of 54, and p = 0.0009. The mean self-assessment score across all items increased from 3.56 (SD = 0.75) before the program to 4.19 (SD = 0.53) after the program. The distribution of student self-assessment ratings for each of the 17 items before and after participating in the experience, as assessed using a pre-post design, is presented in Figure 1. The proportion of students who rated their ability as 5 (“great ability”) increased across all items. Notable gains were observed in areas such as Item 3 (ability to work in the research environment comfortably), which was rated as 5 by 18.8% of students before the program and 50% after, and Item 8 (ability to make a case for a research question based on the literature), which increased from 6.2% before to 31.2% after.

Figure 1. Percentage distribution of students’ self-rated research abilities before and after participation in the CIMAP Spring Research Experience assessed using a retrospective pre-post design.

This figure shows the percentage distribution of responses to the 17-item scale adapted from the Entering Research Learning Assessment instrument completed by students (n = 17) at the end of the CIMAP Spring Research Experience. Using a retrospective pre-post design, students rated their perceived research abilities before and after the experience on a 5-point Likert-type scale, where 1 = No ability, 2 = A little ability, 3 = Moderate ability, 4 = Good ability, and 5 = Great ability. The 17 items were as follows:

1. Communicate the context, methods, and results of your research.

2. Tailor your research communications for different audiences (e.g., general public, disciplinary conference).

3. Work in the research environment comfortably.

4. Ask questions to clarify your understanding of your research project.

5. Practice regular and open communication with your research mentor.

6. Practice regular and open communication with your research team members.

7. Use the tools, materials, and equipment needed to conduct research.

8. Make a case for your research question based on the literature.

9. Identify forms of unethical practices or research misconduct.

10. Think of yourself as a scientist/researcher.

11. Feel like you belong in research.

12. Work independently on your research project.

13. Determine the next steps in your research project.

14. Understand how others might experience research differently based on their identity (e.g., race, socioeconomic status, first-generation status).

15. Explore possible research career pathways.

16. Set research career goals.

17. Develop a plan to pursue a research career (determine the next step in your training).

Participants reported high satisfaction with the program overall, with a mean score of 4.28 (SD = 1.24) across all five domains. The mean student score for each specific domain was as follows: topics addressed: M = 4.11 (SD = 1.24), opportunities to interact with peers: M = 4.61 (SD = 0.76), program length: M = 4.33 (SD = 0.94), and value for academic development: M = 4.50 (SD = 0.83). The distribution of student satisfaction ratings is presented in Figure 2. Notably, the domain with the highest level of satisfaction was Domain 5: Opportunities to interact with peers, with 72% of respondents rating it a 5 (“extremely satisfied”). In contrast, Domain 2: Topics addressed received the lowest level of satisfaction, with 56% of respondents assigning it the highest rating.

Figure 2. Percentage distribution of student satisfaction ratings across program domains.

18 students rated five domains on a 5-point Likert-type scale from 1 (extremely dissatisfied) to 5 (extremely satisfied). Bars represent the percentage of respondents selecting each level of satisfaction.

Participants were also asked to respond to a free-text question regarding how collaborating with peers from different disciplines enhanced their experience (Appendix B. Block 2). Of the 18 survey respondents, 16 provided comments indicating that collaboration enhanced their research experience. One respondent indicated that collaboration did not enhance their experience, and another did not provide a response to the open-ended feedback items. Students highlighted the value of bringing STEM and public health students together, describing it as a valuable opportunity for collaboration and peer learning. They expressed that gaining insight from diverse perspectives enhanced their understanding of research, broadened their horizons, and illustrated how interdisciplinary collaboration could advance medicine. STEM students were noted for their technological expertise, while public health students contributed insights into the broader impact on population health. Students expressed a desire to continue working in interdisciplinary teams in the future, emphasizing the collaborative experience gained from the internship. Furthermore, they mentioned that the interdisciplinary collaboration helped them grasp the intersection between technical innovation and societal well-being, enabling them to explore innovative solutions to global health challenges together.

Regarding future directions, we asked students how we could improve the program for next year. Suggestions included making the experience longer to allow topics to be explored in greater depth, introducing a requirement to keep cameras on to encourage a sense of togetherness, introducing more tracks, including more foundational training on AI, incorporating more opportunities for group work, and fostering more discussion between participants from different tracks.

Discussion

As biomedical AI research continues to expand, there is a growing need to involve trainees in hands-on, interdisciplinary research. In our pilot program development, we adopted an innovative team science approach, providing meaningful opportunities for engineering and public health students to participate synchronously and remotely in hands-on tasks and activities in AI research, science policy, and program advocacy. A distinct contribution of our interdisciplinary research internship was its explicit aim to unite students from STEM and public health backgrounds and provide structured opportunities for them to collaborate across disciplines. Our program was guided by a thoughtfully designed curriculum that integrated opportunities for peer feedback and learning. While the overall schedule and assignments were largely shared between the engineering and public health students, the two-track design allowed us to align the experience with students’ academic backgrounds, and to ensure each group had the opportunity to take part in relevant hands-on activities, ensuring that students came away with tangible, discipline-relevant skills before transitioning into collaborative, interdisciplinary activities that formed the core of the shared experience. Initial findings from this pilot cohort are promising, showing significant perceived gains in students’ self-rated research abilities, as well as positive feedback on the value of interdisciplinary collaboration between STEM and public health students.

Our findings align with previous research demonstrating the benefits of small group activities and collaborative learning approaches. For example, Ortiz Martín et al. reported that a hands-on, active-based learning approach in a Computer Science practical lesson for undergraduate Biology students was associated with high student satisfaction, with most students finding it useful for acquiring and consolidating subject knowledge.¹ Schmidt et al. found that a small group active learning exercise involving interprofessional groups of health professions students improved their ability to apply scientific concepts to clinical problems, develop clinical reasoning skills, and engage in teamwork.² Similarly, Valentijn et al. implemented an innovative, challenge-based interdisciplinary concept in undergraduate biomedicine and medicine programs, in which students collaborated with patients, physicians, and scientists to design research proposals addressing clinical problems. This approach was associated with improvements in communication, critical thinking, collaboration, and problem-solving skills.¹² Our approach builds on the findings of these prior programs, introducing a novel component in our intentional design to bring together students from STEM and public health disciplines for interdisciplinary collaboration. While some existing programs, such as the Summer Public Health Scholars Program hosted by Columbia University Irving Medical Center,¹⁶ do offer students exposure to both public health and biomedical science topics, they are typically designed to provide individual-level exposure to a broad range of topics, rather than to intentionally foster interdisciplinary collaboration between students from different academic disciplines. Our program was thus innovative in its design to bring engineering and public health students together and provide structured opportunities for interdisciplinary teamwork. The evaluation of this pilot program demonstrates that such interdisciplinary internship experiences are not only feasible but also well-received by participants. Students reported that collaborating with peers from different disciplines and learning from their perspectives was one of the most exciting and valuable aspects of the research experience.

We framed our work within the context of existing evidence on promoting academic advancement and entry into research for undergraduate students.^8-11 Our evaluation indicates that participation in a research internship promoted students’ sense of belonging in research and positively influenced their self-efficacy regarding future research activities. We intend to continue developing and refining the one-week internship curriculum, as trainees expressed appreciation for exposure to various activities but suggested a desire for more time dedicated to working with project-related data. Data for short training experiences will need to be carefully evaluated for feasibility and counterbalanced against the trainees' technical abilities and existing skills. In preparation for next year’s spring break research internship, we plan to involve undergraduate students from target majors in the design and testing of the curriculum and activities. Furthermore, to expand and sustain our interdisciplinary spring break research internship as a blueprint for other programs, we plan to develop an open-access online curriculum accessible to instructors and research leads at other institutions.

This study is limited by the small sample size of the cohort, the application to a single institution, and our original focus on a specific NIH-funded program. First, the small sample size in this pilot study may limit the statistical power and generalizability of the findings. However, the fact that we observed statistically significant improvement between the pre- and post-program self-assessment questions suggests that the program had a meaningful impact, even with a small cohort and a relatively short program duration of 5 days. The findings support the feasibility and potential value of this program model in the greater scheme of developing short-term research internships for undergraduate students aimed at enhancing research skills, researcher identity, confidence, and a sense of belonging, and in fostering interdisciplinary collaboration across academic disciplines. Previous studies have also highlighted the value of short-term internships, with Tanner et al. noting that changes in students’ sense of belonging in the scientific field can increase within the first three weeks of a research experience.¹⁷ Future iterations involving larger cohorts will be important to validate and build upon these preliminary findings. Second, the use of a retrospective pre-post design, in which students rated their research abilities before and after the program at the same time point, may result in recall bias or response-shift bias. Third, while the generalizability of this approach is limited to one program, the feedback from the trainees signals the openness and need for more interdisciplinary and transdisciplinary training activities and hands-on experiences to be offered and integrated within training programs. Finally, we did not formally assess the quality of the poster presentations or directly evaluate the quality of interdisciplinary interactions using objective measures such as standardized rubrics. As such, our conclusions regarding the quality and impact of these interdisciplinary collaborations is based on students’ qualitative feedback provided in the post-program evaluation survey, which may be subject to self-report or social desirability bias. Although we did not formally assess the outcomes of the student interactions, all activities were conducted under the guidance of faculty and PhD student mentors. These supervisors provided real-time feedback and support during the collaborative process using the break-out room feature on Zoom, which helped ensure that the students’ discussions and conclusions were conceptually appropriate.

Notwithstanding the limitations, the program's success presented here created enthusiasm to expand the opportunities for interdisciplinary experiences to other trainees within the HuBMAP consortium as part of the consortium-wide 10-week summer program. We plan to develop and offer additional opportunities for students from different disciplines to participate in basic-to-population-level research activities. Specifically, we plan to implement a policy hackathon as an activity within a 10-week summer research experience to provide students from basic science, engineering, biology, and public health fields with an opportunity to deliberate on issues relating to data science policy, science advocacy, and open science.

Our pilot program also shows that spring break research internships can be successfully developed and delivered as synchronous online programs, indicating the significant potential to increase the participation of trainees not only from different disciplines but also from different institutions, thus enhancing the diversity of perspectives and institutions represented in such programs. For research team leads who are interested in replicating our innovation, we recommend beginning with identifying academic programs and groups of students who can be involved in research, identifying faculty leads with interdisciplinary research experience, mapping out the topics and flow of hands-on activities that can be conducted remotely, and setting up shared documents for reflections and notes to promote knowledge exchange and engagement. We recommend that spring break internships be planned for five days, including four days of hands-on research activities and a final fifth day focused on scientific communication (abstract or poster development) and evaluation. Lastly, our program provided funding to the trainees, and we encourage future programs to consider whether the allocation of funds can be made available to support trainees participating in the programs for students from underrepresented and low-income backgrounds.

Conclusions

Our report introduces a novel approach to training program design, with preliminary evidence supporting the effectiveness of a cohort-based research internship that brought together engineering and public health trainees within the context of AI/ML biomedical research. This innovative pilot program and its encouraging outcomes highlight the value of fostering interdisciplinary collaboration early in students’ research careers. Our next steps will be to further develop and refine the one-week internship curriculum, with plans to develop an open-access online curriculum that will be accessible to instructors at other institutions.

Table 1.

Characteristics of 2024 Spring Break Interns

Demographic	Per cent	N*
Sex
Male	35.3%	6
Female	64.7%	11
Race
White	38.9%	7
Black or African American	27.8%	5
Asian	27.8%	5
Other	5.6%	1
Ethnicity
Hispanic or Latino	29.4%	5
Not Hispanic or Latino	70.6%	12
Class standing
Sophomore	17.6%	3
Junior	35.3%	6
Senior	47.1%	8
Major
Biomedical Engineering	47.1%	8
Public Health	41.2%	7
Electrical Engineering	11.8%	2
Track followed
Technology	66.7%	12
Policy	33.3%	6
Highest level of parents’ education
High school or less	11.8%	2
Associate's degree	17.6%	3
College degree	47.1%	8
Advanced or professional degree (PhD, MD, etc.)	23.5%	4
Grew up in a rural area
Yes	17.6%	3
No	82.4%	14

^*Totals may not sum to 18 due to missing responses for some questions.

Appendices

Appendix A. 2024 Spring Break Research Internship Activities.

Session	Topics covered and key learning objectives	Description of curriculum and source
Day 1
Morning Session	Orientation and team introductions Overview of HuBMAP Strategic team science	We welcomed the cohort and provided an overview of the internship goals and content. We introduced facilitators and their roles. We welcomed a guest speaker from the National Institute of Health (NIH) to deliver a lecture on the HuBMAP program. The session on team science covered strategies for team science and collaboration. Students were encouraged to consider whether they had been part of a research team, had ever been involved in interdisciplinary, multidisciplinary, or transdisciplinary research, and could differentiate between these terms. Students were also encouraged to reflect on positive and negative experiences of collaboration.
Afternoon Session	Kidney anatomy and physiology Ethics and AI	Students received a lecture covering the basics of kidney anatomy and physiology, including key definitions/terminology, an overview of nephrons as the functional unit of the kidney, filtration at the glomerulus, renal vasculature, and an introduction to kidney diseases such as Chronic Kidney Disease, End Stage Renal Disease, Diabetic nephropathy, and Nephrotic Syndrome. We welcomed an assistant professor from the Department of Health Services Research, Management & Policy at the University of Florida who delivered a lecture on topics and current issues relating to AI in public health and policy and ethical issues relating to using AI in public health.
Guided readings and assignments	U.S. Government Accountability Office. Artificial Intelligence in Health Care Benefits and Challenges of Machine Learning Technologies for Medical Diagnostics.(2022). Available at https://www.gao.gov/assets/gao-22-104629.pdf Jain, Sanjay, et al. Advances and prospects for the Human BioMolecular Atlas Program (HuBMAP). Nature cell biology 25.8 (2023): 1089-1100. Pain, E. How to keep a lab notebook ∣ Science ∣ AAAS. September 3, 2019. Sedeen Viewer by Pathcore software. https://pathcore.com/sedeen/. (Technology track students only). Clarke, Z.A., Andrews, T.S., Atif, J. et al. Tutorial: guidelines for annotating single-cell transcriptomic maps using automated and manual methods ∣ Nature Protocols 16, 2749–2764 (2021). https://doi.org/10.1038/s41596-021-00534-0. Technology track students only. University of Florida library guide overview of Covidence (Policy track students only).
Day 2
Morning Session	Technology track: Cell annotation Policy track: Dissemination and collaboration data extraction	Students on the technology track received a tutorial on how to carry out cell annotation using Sedeen Viewer by Pathcore and then participated remotely and synchronously in a hands-on activity working in small groups in break-out rooms to annotate cells utilizing the software. The accuracy of their annotations was evaluated, and some of the students later presented this data in a research poster. Policy track students participated in a data extraction and screening activity using Covidence to conduct a systematic literature review for data dissemination and collaboration articles.
Afternoon Session	Small group work Lab notes	Students used a shared Google document to record lab notes documenting the activities they completed today and what they had learned.
Guided readings and assignments	Gichoya JW, Banerjee I, Bhimireddy AR, et al. AI recognition of patient race in medical imaging: a modelling study - PubMed (nih.gov). Lancet Digit Health. 2022;4(6):e406-e414. doi:10.1016/S2589-7500(22)00063-2 Jewett C. Doctors Wrestle With A.I. in Patient Care, Citing Lax Rules - The New York Times (nytimes.com). October 30, 2023. HuBMAP. External data sharing policy – HuBMAP Consortium. August 3, 2020.
Day 3
Morning Session	Policy brief describing the HuBMAP program and contribution of HuBMAP to human health research	Students received a didactic session on policy briefs and the importance of communicating scientific findings through plain language. Students wrote a policy brief describing the HuBMAP program, the significance of HuBMAP for human health, and the need for regulatory and policy action related to technology evaluation, data access, and collaboration.
Afternoon Session	Ethics Case Development	Students worked in small groups to develop an ethics case. This involved gathering data from the HuBMAP website to obtain information about the current profile of the HuBMAP donors, identifying shortfalls of the donor pool, and coming up with computational and public health arguments and cautions for organ donation for research.
Guided readings and assignments	Students were provided with instructions for the Fusion Usability Study. 2024 CIMAP Spring Experience: Daily Schedule - Google Docs.
Day 4
Morning Session	FUSION usability study	Both tracks participated in a Usability study for “Functional Unit State Identification for WSI” (FUSION), a new software developed by the Computational Microscopy Imaging Laboratory (CIMAP) at the University of Florida. Fusion is an AI-driven visualization software integrating molecular and structural-omics for biological discovery and precision medicine. Improving the usability of software such as Fusion to help realize its potential applications in research and clinical medicine is essential to translational science. During the usability study, students recorded their screens as they completed a tutorial on how to use the Fusion software and then answered questions about the features of kidney cells seen on slides that they examined using the Fusion software. More information about the Fusion software can be found here: http://fusion.hubmapconsortium.org/
Afternoon Session	Student-led use case interviews	Using break-out rooms on Zoom, students worked in pairs to interview each other about the usability and educational applications of Fusion, including what did and didn’t function well with the software, features that could be improved or added, suggested changes, and specific cases where they would find Fusion useful.
Guided readings and assignments	Students were asked to review the application form for the 2024 Spring Undergraduate Research Symposium (google.com).
Day 5
Morning Session	Introduction to writing academic abstracts	Students received a presentation on how to write effective abstracts. Possible topics for a research poster were suggested to students, although students were also encouraged to crefine these topics further or to formulate their own research questions based on their interests and the content covered during the program. Using Zoom break-out rooms, students worked in small groups on their abstracts.
Afternoon Session	Group work on posters Abstract submission Program evaluation	Following on from the morning session, students continued to work in small groups to finish their abstracts and work on creating their research posters. We reconvened in the main group to assist students with submitting their abstracts for the 2024 UF Spring Undergraduate Research Symposium. At the end of the internship, the link to the post-program evaluation survey was distributed, and students were encouraged to complete it and offer their feedback on the program.
Guided readings and assignments	N/A

Appendix B. Survey instrument

2024 Computational Microscopy Imaging (CIMAP) Spring Evaluation Survey

Please rate your level of satisfaction with the 2024 CIMAP Spring Research Experience.

1. Overall satisfaction with the program

2. Topics addressed in the experience

3. Opportunity to interact with peers

4. Length of the program

5. Value for academic development

1 = “Extremely dissatisfied”

5 = “Extremely satisfied”

Block 1. Demographics

• What track did you follow?

• Technology

• Policy

• What is your major?

• What is your academic standing?

• Freshman

• Sophomore

• Junior

• Senior

• Master’s student

• Other (Please specify)

• What is your gender?

  • Male
  • Female
  • Other
  • Prefer not to say
• What is your race? Select all that apply

  • American Indian or Alaska Native
  • Asian
  • Black or African American
  • Native Hawaiian or Pacific Islander
  • White
  • Other (Please specify)
• Are you Hispanic, Latino/a, or Spanish origin?

  • Yes
  • No
• What is your parents' highest level of education?

  • High school or less
  • Associate’s degree
  • College degree
  • Advanced or professional degree (PhD, MD, etc.)
  • Other
• Did you grow up in a rural area?

  • No
  • Yes

Block 2. Program Outcomes

• BEFORE your CIMAP Spring Research Experience, indicate your ability to ….

  1. Communicate the context, methods, and results of your research.
  2. Tailor your research communications for different audiences (e.g., general public, disciplinary conference).
  3. Work in the research environment comfortably.
  4. Ask questions to clarify your understanding of your research project.
  5. Practice regular and open communication with your research mentor.
  6. Practice regular and open communication with your research team members.
  7. Use the tools, materials, and equipment needed to conduct research.
  8. Make a case for your research question based on the literature.
  9. Identify forms of unethical practices or research misconduct.
  10. Think of yourself as a scientist/researcher.
  11. Feel like you belong in research.
  12. Work independently on your research project.
  13. Determine the next steps in your research project.
  14. Understand how others might experience research differently based on their identity (e.g., race, socioeconomic status, first-generation status).
  15. Explore possible research career pathways.
  16. Set research career goals.
  17. Develop a plan to pursue a research career (determine the next step in your training).

All items on a scale

1 = “No ability”

2 = “A little ability”

3 = “Moderate ability”

4 = “Good ability”

5 = “Great ability”

• AS A RESULT OF participating in the CIMAP Spring Research Experience, indicate your ability to…

  1. Communicate the context, methods, and results of your research.
  2. Tailor your research communications for different audiences (e.g., general public, disciplinary conference).
  3. Work in the research environment comfortably.
  4. Ask questions to clarify your understanding of your research project.
  5. Practice regular and open communication with your research mentor.
  6. Practice regular and open communication with your research team members.
  7. Use the tools, materials, and equipment needed to conduct research.
  8. Make a case for your research question based on the literature.
  9. Identify forms of unethical practices or research misconduct.
  10. Think of yourself as a scientist/researcher.
  11. Feel like you belong in research.
  12. Work independently on your research project.
  13. Determine the next steps in your research project.
  14. Understand how others might experience research differently based on their identity (e.g., race, socioeconomic status, first-generation status).
  15. Explore possible research career pathways.
  16. Set research career goals.
  17. Develop a plan to pursue a research career (determine the next step in your training).

All items on a scale

1 = “No ability”

2 = “A little ability”

3 = “Moderate ability”

4 = “Good ability”

5 = “Great ability”

• This is the first year we brought engineering and public health majors together. In what ways, if any, has collaboration with peers enhanced your research experience?

• We plan to offer a research experience next year. What can we do to ensure that this experience is improved?

Data availability:

The data for this study are available from the authors upon reasonable request.