A major goal of biomedical engineering is the development of novel and innovative medical technology that advances and improves healthcare outcomes. An important component of medical device design is the ability to identify the clinical needs of patients and healthcare providers and to apply engineering solutions to meet these needs. Our biomedical engineering department has developed a clinical and industry immersion course, which exposes students to the environment in which physicians and patients practice and engages students in this needs identification process. Through these experiences, students have the opportunity to interact with physicians, healthcare providers, and current biomedical engineers. To further refine students’ understanding of a user-centered approach to needs finding, we have incorporated a Human-Centered Design module at the beginning of this clinical immersion course. To examine the efficacy of this approach, this study aimed to determine the impact of this Human Centered Design module on students' perspectives regarding user feedback and the design process during product development. The first round of data was collected through an online Qualtrics survey sent out to the students enrolled in the Clinical Observations course. This survey collected feedback that quantified students' confidence levels throughout different parts of the engineering design process, and their understanding of the Human Centered Design module presented in class. Both quantitative (Five-point Likert-scale) and qualitative (open-response) data were analyzed. Additionally, an assignment was administered to assess students’ understanding of human-centered design concepts. Both self-reported and external assessments provided insights on how this module changed students' understanding of different aspects of the clinical design research process. Students reported moderately high levels of agreement with statements regarding the modules impact on their understanding of user needs (Mean, M=3.62), and that this helped them develop empathy for users and their unique perspectives (M=3.68). Students also agreed that this module was a valuable addition to the course (M=3.79), and felt that it provided them with practical tools and techniques for conducting user research and gathering insights (M=3.66). Students also reported that this module inspired them to incorporate human centered design in their future biomedical engineering work (M=3.79). This study is currently in-progress, with plans to increase sample size and conduct thorough data analysis in future work. Data collected after students participate in the clinical experiences will provide more insights into the ability of students to apply this concept as they begin drafting ideas for their course design project and the impact it has on the design process.

Authored by
Lauren Edmunds (University of Arkansas), Dr. Mostafa Elsaadany (University of Arkansas), and Timothy J. Muldoon (University of Arkansas)

Virtual reality (VR) laboratories offer a promising alternative to physical labs, particularly for developing laboratory techniques and enhancing hands-on education. However, most existing research has primarily focused on assessing VR labs' effectiveness in teaching specific concepts and skills. A recent review identified a significant gap in understanding students' learning experiences in VR labs through a theoretical lens. Most prior studies often concentrate on design outcomes and neglect how learning in VR labs shapes student experiences.
This qualitative study explores students' experiences in VR laboratories through the lens of experiential learning theory (ELT). The ELT defines learning as the “transformation of experience,” making it a well-suited theory for investigating students' experiences in VR laboratory environments for learning. By adopting a theory-driven approach, we address the lack of studies that evaluate VR lab learning experiences through experiential learning framework. Our research question is: "What are students’ experiences when using VR labs for learning?"
The study is based on students' experiences in 5 VR laboratories in a biomedical engineering course. We conducted and analyzed semi-structured interviews of 6 students to gain insights into students' experiences in VR labs. The interview protocol was based on Kolb’s experiential learning cycle. We employed a hybrid analysis approach, beginning with deductive analysis based on Kolb’s cycle, followed by inductive analysis to uncover additional experiences beyond the theoretical framework. This analytical approach allowed us to better understand students' experiences without limiting our findings to predefined categories.
Preliminary analysis reveals that students’ experiences in VR labs do not follow Kolb's cycle in a linear sequence. Instead, they exhibit a fluid movement across different stages of the cycle. Although VR laboratories are designed to facilitate experiential learning, students reported the virtual experience to be lacking in reflective opportunities. Rather than isolating VR labs as standalone experiences, students described them as integrated with classroom sessions to create a more holistic learning environment. These findings suggest that the design of VR lab experiences should go beyond simple implementation and consider pedagogical integration. Future work will propose a framework for experiential learning in VR labs and best practices for effective VR-based education.

Authored by
Deborah Moyaki (University of Georgia), Dr. Nathaniel Hunsu (University of Georgia), Dr. Dominik May (University of Wuppertal), and Dr. Cheryl T Gomillion (University of Georgia)

Proficiency in signals and systems is essential to a biomedical engineer’s (BME) education, as many key technologies in healthcare—such as medical imaging, diagnostic instrumentation, wearable health monitors, and electronic health record systems—depend on digital signal processing. BME students typically find signals and systems courses difficult because they require an intuitive understanding of calculus, differential equations, circuit analysis, and principles of human physiology. In addition, signals and systems courses require application of mathematical formulas to model and analyze signals as well as cognitive flexibility in switching between time and frequency domains.

In traditional electrical engineering-oriented signals and systems courses, concepts are presented from the perspective of mathematical modeling of systems, where the signals being investigated are primarily periodic and predictable. Such math-focused approaches can deprive students of the critical connections they could be making between theoretical concepts and human physiology. Our course emphasizes the development of fundamental skills that enable students to observe and identify key features of physiological signals, supporting visualization, modeling, and analysis without requiring extensive mathematical derivations. Students apply core principles of digital signal processing to analyze and interpret their own physiological data—such as heart rate, blood pressure, respiration, and muscle activation—which are inherently less predictable and not strictly periodic. This practical, pattern-seeking approach is what we refer to as the “Signal Detective Mindset.”

This paper has two primary objectives: (1) to describe the Signal Detective approach as a pedagogical tool and (2) to evaluate the effectiveness of the Signal Detective approach in enhancing students’ understanding and application of core signal processing concepts.
While the signal detective approach has been previously implemented in the course, it had not undergone formal evaluation until now. Quantitative and qualitative analysis of the data collected shows that the signal detective approach was effective. Students not only demonstrated measurable skill in signal identification but also articulated how the signal detective method improved their understanding and confidence level in tackling other signals and systems.

Students also thought the method helped clarify concepts they had learned in prior coursework as well as signals and data they encountered in their jobs (co-op positions). While the approach prioritizes applied analysis over theoretical mathematical rigor, students appear to appreciate this tradeoff - recognizing that developing intuitive, structured ways of engaging with signals is a critical step in mastering the more abstract dimensions of signal processing. This signal detective mindset offers a unique educational opportunity because it enables students to make connections between the underlying concepts and how their own bodies function.

Authored by
Dr. Uri Feldman (Wentworth Institute of Technology) and Dr. George D. Ricco (Miami University)

(Research Paper) Class attendance is one factor contributing to students’ success in undergraduate classes. Course instructors use attendance policies as classroom management tools to encourage students’ engagement and outline the procedure for absenteeism. They range from strict policies that penalize absent students to lax policies where attendance is encouraged but not enforced. However, these extremes are not suitable for every classroom situation, especially hands-on design and team-based engineering classes. At the same time, providing students with more flexibility often comes at a cost for faculty members and instructional teams who have to make decisions about missed classes and assignments. Understanding how flexible attendance policies affect students’ attendance behaviors and perceptions, and impact instructors’ workload is crucial for designing equitable classroom/attendance policies. This paper presents the impact of an innovative attendance policy on students’ attendance behavior and perceptions of autonomy in a third-year biomedical engineering class. We hope to address the following research questions: (1) Did students perceive the new attendance policy as equitable, why or why not? (2) Did students perceive the new attendance policy as agency-supporting, why or why not? We interviewed two students enrolled in a biomedical engineering seminar course to understand their perceptions of and experience with the innovative attendance policy. We found that students perceived the policy as relatively equitable and supported their agency. These results contribute to efforts to promote equitable engineering classroom cultures that are scalable and manageable for the course instructors.

Authored by
AraOluwa Adaramola (Cornell University), Alexandra Werth (Cornell University), and Dr. Campbell James McColley (Cornell University)

This manuscript describes a course project that guides each biomedical engineering (BME) student through the scripted teardown of an inexpensive medical device: a fingerclip pulse oximeter. Supporting objectives are to increase a student’s experience with the physical resources required to complete such a task, coupled with an improved awareness of the documentation needed to properly archive the process. The project addresses medical device user manuals, product priority dates, accuracy assessment, clinical device studies, regulation, component design, and manufacturing. Students also address ethical implications of teardowns, including the dissemination of the resulting device information. Pre/post-project surveys help to assess student self-perceptions of learning, and summative learning assessments based on topical rubrics are underway. To date, the month-long project has been utilized with 48 students enrolled in three offerings of a three-credit, senior-level, one-semester BME 575 – Clinical Systems Engineering course at Kansas State University as a means to introduce students to medical device development issues that they may not otherwise consider prior to employment.

Authored by
Dr. Steve Warren Ph.D. (Kansas State University) and Dr. Charles Carlson (Kansas State University)

This work in progress describes the curriculum revision in the Biomedical Engineering (BME) program at a mid-sized, private university. The goal of this revision is to increase student competency by emphasizing industry relevant skills as well as design, while increasing student engagement through improved flexibility, and engagement with real world problems.

Input from faculty, students, and the BME Industrial Advisory Board indicated that the original curriculum had less flexibility and career readiness than was desired. In the original curriculum, students select between four subject-matter tracks (mechanical, electrical, tissue/biomaterials, and premed) with different required courses. Beyond these tracks, each student selects two technical electives. Both the tracks and limited electives constrain students’ choices – especially those that change their career goals midway through the program. Design-based courses were limited to one freshman course and the final semesters of the program (Biodesign and a yearlong capstone project.)

Work on the revision began in Fall of 2019 through multiple committees as well as several faculty retreats. This process focused on identifying key skills, tools, and course content that are essential to all BME disciplines. The original curriculum and new curriculum were also benchmarked against nine peer institutions. The revision was approved in November 2022 with the first cohort of students starting in the Fall of 2023.

The first significant revision to the curriculum is the integration of engineering design throughout all semesters with basic design and entrepreneurship being introduced in the first year, followed by yearlong, 3-credit design projects in the 2nd and 3rd year, culminating a yearlong, 6-credit capstone project. This continuous exposure to design principles and practices is intended to develop students’ problem-solving skills, creativity, and provide real world context to the content covered in their other courses.

The revised curriculum also emphasizes the consistent use of industry-standard tools such as SolidWorks and MATLAB across various courses. By incorporating these tools into multiple aspects of the curriculum, we aim to build students’ proficiency and confidence in using them. This approach not only enhances their technical skills but also demonstrates the practical applications of these tools in solving real-world engineering problems. The consistent use of these tools helps students see the interconnectedness of their coursework and understand how the skills they develop can be applied in professional settings.

Finally, the curriculum replaces, combines, or eliminates several courses from the original tracks to create a unified core curriculum with five technical electives that can be taken throughout a student’s education. Thus, students can tailor their coursework to their interests and career goals.

Data on the student opinion of the revised curriculum as well as skill acquisition is ongoing, and preliminary results will be included in the final paper.

This is an observational study. The [Institution] IRB has determined that this study is exempt from review.

Authored by
Dr. Julian M Lippmann (University of Miami) and Mr. Jorge E Bohorquez (University of Miami)

Background: Engineering educators regard the ability to find, evaluate, and synthesize technical information as a core competency for engineering undergraduates [1], [2]. However, the content demands of STEM undergraduate curricula often limit the ability of instructors to teach students these skills [3]. Engineering librarians frequently partner with biomedical engineering (BME) educators to promote the development of these skills [4], but these partnerships are often limited to guest lectures within either first-year engineering programs or in senior design courses [5], [6], [7], [8], [9]. This bimodal implementation strategy suggests a gap in the middle years of the BME curriculum during which students may benefit from additional literacy training.

Purpose: This Work in Progress paper provides an update of a longitudinal assessment of BME students who have matriculated through a scaffolded information literacy training program. This assessment explores whether laboratory courses are an effective context for integrating information and data literacy into the undergraduate BME curricula.

Instructional Methods: Students at Vanderbilt University complete a required BME laboratory course as a sequential series of one credit courses in their sophomore (BME 2900W), junior (BME 3900W), and senior (BME 4901) years. To promote students' skill growth in the areas of information and data literacy, engineering librarians develop and deliver lectures in these courses that introduce students to specialized engineering information sources. These hands-on lectures teach students how to access technical resources efficiently and utilize them effectively. In BME 2900W, librarians demonstrate how to find methods papers, handbooks, and experimental protocols. In BME 3900W, students learned how to find review articles, patents, and engineering standards. In BME 4901W, librarians provide an overview of managing research data, including best practices for organizing files and designing machine-readable tabular data.

Methods: Beginning in the Spring 2022 semester, we initiated a longitudinal pre-test / post-test assessment of this program. Students completed pre-tests prior to the instructional intervention in BME 2900 to establish their baseline knowledge prior to the training program. Students completed the same pre-test prior to the BME 3900 intervention to assess skills gained and retained since the first intervention. Following the BME 4901 intervention, students completed a post-test to reassess skills gained and retained over the entire training sequence. The assessment instrument, which includes both multiple-choice and open response questions, is available on the Open Science Framework [10]. Student responses are collected via paper instruments and then saved in a spreadsheet with response identifiers, course information, and answers. This protocol was reviewed by the Vanderbilt University Institutional Review Board and was approved as a Quality Improvement project (IRB #232075).

The first portion of the assessment consists of a series of multiple-choice questions (Q3-Q12). We used Analysis of Variance (ANOVA) to compare the proportion of correct answers from each BME class (2900W, 3900W, 4901W). These were calculated using the stats package in R-4.3.1.

Results: Student performance on the multiple-choice questions across the three-time series (2900 Pre-test, 3900 Pre-test, and 4901 Post-test) are reported in Supplementary Table 1. These questions assess students’ ability to correctly identify: 1) sources of information to consult when completing different tasks (Q3-Q7); 2) which library-licensed resources to utilize when searching for different types of technical literature documents (Q8-Q11); and 3) what type of document the acronym “IMRAD” applies to (Q12). Because these pre-tests and post-tests were administered on paper to students in attendance in lab, the sample size across sections shows some variation.

Figure 1 shows the proportion of correct responses divided by class, question, and topic.
The ANOVA results indicate a significant increase in the number of correct responses to all test questions within each successive course (Mean square = 4.0; F-statistic = 25.9; p-value<0.001). The ANOVA results for course and question interaction term indicated a significant difference for questions across courses (Mean square = 0.43; F-statistic = 2.74; p-value<0.001). Since Q1-Q7 each address resource types, Q8-11 address tool knowledge, and Q12 is on article structure, these questions were combined into the three categories for comparison: Resource, Tool, and Reading. ANOVA results with the proportion of correct responses for each independent variable are reported in Supplementary Table 2.

Figure 1: Proportion of correct responses for (A) all questions combined, (B) individual multiple-choice questions, and (C) topics covered by the questions (Resource: 1-7, Tool: 8-11, Reading: 12) for each BME class. The error bars show the standard error for each point.

Discussion: These results suggest that targeted information and data literacy instruction, offered within laboratory courses, can contribute to science process skill gains for BME students. Students who completed this training sequence showed statistically significant improvement in their ability to identify the best sources of evidence to use to answer technical questions, as well as the ability to identify library licensed resources that could provide access to each type of evidence (Figure 1A). Crucially, these findings also suggest that these skill gains can be sustained over time; students completing the post-test following the conclusion of BME 4901 still demonstrated statistically significant improvements over their baseline scores entering the training sequence. The major exception to this finding is that students across the program showed no improvement in their recognition of the acronym “IMRaD,” which may suggest that this mnemonic has limited utility or relevance for undergraduate students (Figure 1B).

There was a substantial improvement in the results between the 2900 and 3900 courses. The largest improvements were in Q10 and Q11 (Figure 1B), which assessed their ability to identify which library-licensed resource can be used to find experimental protocols and engineering handbooks (Cold Spring Harbor and AccessScience, respectively). This is likely because these were newer tools to the students, while Q8 and Q9 both related to Web of Science, which is a more popular platform.

These findings highlight the value of demonstrating specialized engineering information tools to students within a BME laboratory course. These tools provide uniquely useful information for students expected to draft laboratory reports that cite primary and secondary literature sources, yet early-career undergraduate engineering students are unlikely to learn about these specialized tools within an information literacy training session designed for first-year students. These improvements in performance were retained overtime, which suggests that for many BME students, a single instructional intervention with a librarian within a laboratory course can promote material information and data literacy skill gains.

Future Work: While these are promising findings, the multiple-choice questions in these tests do not measure how well students can use technical literature; rather, they test recognition of resource types, tools, and article structure. To supplement these multiple-choice questions, students were also presented with three open response questions (Q13-15) that asked them to share their understanding of academic citation practices, methods for reading scientific literature, and approaches to managing research data.

Analysis of these open response data is currently ongoing. These open response data will be qualitatively analyzed using grounded theory to inductively identify themes and sentiments within the data [11], [12]. This qualitative analysis may reveal changes over the course of the training program in student’s understanding of effective strategies for citing evidence, working with primary literature, and managing research data that are not observable within their responses to multiple-choice questions. Preliminary findings from this qualitative analysis will be shared via a Work in Progress poster at the Annual Meeting in June 2025.

Authored by
Mr. Alexander James Carroll (Vanderbilt University), Dr. Joshua Daniel Borycz (Vanderbilt University), Sheldon Salo (Vanderbilt University), and Prof. Amanda R. Lowery (Vanderbilt University)

Hands-on activities implemented in the classroom can be beneficial for students to reinforce their learning and concept retention [1]. In previous works, it has been demonstrated that high school students need guidance to learn new concepts in biomedical engineering courses, for example to help them navigate potential frustration during the learning processes [2]. For this reason, it is also important to carefully design hands-on activities to promote a positive interest and motivation in students to perform the activity and hence to learn from it [3] [4]. Teaching modules can be created to increase student learning in STEM concepts, using activities that students can enjoy while learning mathematical reasoning [5], suggesting that this can be used to promote conceptual learning and retention. Moreover, well-planned workshops can also help improve scientific skills, promoting a better understanding of STEM concepts [6]. This work hypothesizes that teaching modules that include hands-on activities can enhance concept retention in the BME field, by allowing students to learn and retain the concepts to later be able to apply them to a real-life application in BME.

Authored by
Yareni P Lara-Rodríguez (University of Puerto Rico, Mayagüez Campus) and Dr. Christopher Papadopoulos (University of Puerto Rico, Mayaguez Campus)

Health disparities are defined as preventable health differences among historically marginalized groups. There are a myriad of problems contributing to health disparities in the United States: economic factors, healthcare access, environmental factors, education, and poor quality of care. Engineering presents a solution to address health disparities by better training engineers to understand health disparities and creating engineering solutions to approach them. In biomedical engineering (BME), students learn how to apply engineering principles and methods to problems in the healthcare system. Therefore, to create a biomedical engineering workforce ready to solve modern-day problems, concepts of health disparities should be incorporated in undergraduate curricula.

The existing literature on health disparities in curricula predominantly focuses on disciplines such as public health, biology, medicine, and pharmacy. While literature has shown that BME departments and educators have incorporated health disparity concepts into undergraduate coursework at various institutions, there are few examples of how it is incorporated into the whole curriculum. Accreditation Board for Engineering and Technology (ABET) has updated their standards requiring departments to incorporate diversity, equity, and inclusion in biomedical engineering curriculum, creating an opportunity to address topics such as health disparities. Therefore, the engineering education research (EER) community needs to explore the extent to which health disparity concepts are incorporated in BME undergraduate programs.

The purpose of this exploratory study is to investigate how current undergraduate BME programs at varying institution types (i.e., R1, emerging research institution, HBCU, HSI) prepare students for addressing health disparities. This work is grounded by Lanier and colleagues’ (2022) “Ten Simple Rules in Biomedical Engineering to Improve Healthcare Equity” and Lattuca and Stark’s (2009) “Academic Plan in Sociocultural Context”. Additionally, this study utilizes a multiple-case study methodology with embedded units of analysis.

First, I will outline the literature and provide examples of specific educators and departments who have included health disparity concepts in their programs. Second, I will provide an in-depth discussion on the research design and methods guiding this study, specifically on the case institution selection and methods. Lastly, I will share the next steps of this project, which entail data analysis, findings, and dissemination of findings.

The findings of this study will provide a deeper understanding of how BME academic programs incorporate health disparities in their curricula, providing a baseline for how institutions incorporate health disparity topics relevant to BME. As a product of this work, a set of criteria will be developed for BME programs to assess if their curriculum effectively incorporates health disparities. By incorporating health disparities in biomedical engineering curriculum, the BME education community can aid in developing engineers who are socially conscious and driven to make an impact in society.

Authored by
Dr. Julia Machele Brisbane (Coulter Department of Biomedical Engineering at Georgia Tech and Emory University)

The ability to monitor and assess one’s own knowledge and skills plays a pivotal role in learning (1). Several have previously described the beneficial effect of this type of metacognitive tool through interventions such as exam wrappers, reflections and self-surveys (1-3). Unfortunately, bioengineering curricula do not give students sufficient practice developing these tools. For many students, it can be easy to fall into the trap of implementing ineffective learning strategies repeatedly without changes in outcome. A self-evaluation can be an obstacle for many students (4).

Allowing students to make errors and then reflect on why these occurred has been shown to positively impact learning (5). By articulating the “whys” and “hows” of errors and finding gaps in thought processes and/or incorrect learnings, students can refine their understanding of course content. In this study, we hypothesize that the use of metacognitive tools such as exam error classification and progress planning in a sophomore level core curriculum physiology course will lead to more deep/strategic learning and engagement (as opposed to superficial/apathetic learning engagement). Furthermore, the evolution of perceived student strengths and weaknesses and clarity of action plans can be informative in assessing the depth of reflection and ability to self-correct.

A pilot version of this study was completed last spring in a sophomore level bioengineering systems physiology course of 41 students. The metacognitive error classification and reflection extra credit assignment was completed after exams 1 and 2 with students providing detail on their study plan, how the plan evolved, its benefits and whether they found the act of reflection of error types and strategies beneficial towards their exam performance. Forty students completed the assignment after exam 1 and 37 fully completed it after exam 2. The majority of the students (22% strongly agree/59% agree) found the assignment to be beneficial in their exam performance (16% neutral, 3% disagree). Survey results revealed that students that improved their exam scores from exam 1 to exam 2 focused on lapses in learning during their studying, adapting their studying plan for a more effective use of time. Students overall reported struggles with test-taking, following through with plans and time constraints as common obstacles in performing well on exams. Finally, many students clearly articulated the effect of changes in their plan and strengths they observed in their own performance and understanding.

Development of a metacognition skillset has the potential to improve course-specific performance for students and impact the overall student experience. Furthermore, the error classification and reflection survey data can also help the instructor better communicate and assess the course material.

1. National Research Council. 2001.
2. Perry. 2018.
3. Stanton. 2021.
4. Zhao et al. 2014.
5. Saenz. 2019.

Authored by
Dr. Sabia Zehra Abidi (Rice University)

To fully embed engineers as clinicians into the clinical flow, it is important to prepare students with an engineering mindset to solve medical problems. Furthermore, to ensure effective translation of medical technologies, students need to be trained with product design classes with clear connection to regulatory science. Preparing medical professionals through a program where engineering and medicine curricula are blended into a cohesive whole would enable the imparting of skills to diagnose symptoms and treat patients simultaneously with the engineering know-how to invent and translate new technologies. In addition, curricular efficiencies will shorten total study duration to seven years, thereby reducing debt burden.

The "Physician Innovator Training Program (PITP)" within the University of California Irvine (UCI) School of Medicine and School of Engineering was designed and piloted in 2023 to introduce first and second year medical students to engineering topics with the goal of developing the next generation of physician innovators. To introduce students to innovation and engineering, the program developed a two-year elective course, "Foundations of Innovation & Engineering", that focused on the four main themes of the PITP as it relates to medicine: Identification, Ideation, Innovation, and Implementation. After taking the first part of their elective course, students are then asked to apply to PITP to continue the elective and participate in the UCI biomedical engineering undergraduate senior capstone program as project mentors. The 9-month capstone mentorship program allows them to work directly with engineering students, physician and engineering faculty, as well as industry representatives, to develop real-world novel solutions in healthcare. Upon completion of the elective and undergraduate capstone, PITP participants are then required to develop a multi-year capstone project that they present during their MS4 year. Lastly, they are encouraged to participate in the UCI Biomedical Engineering Masters of Engineering (MEng) program in between their third and fourth years of medical school, to further their engineering professional development.

The two-part elective of the PITP was designed to provide students with the core principles of innovation and foster an innovative mindset to identify unmet clinical needs, develop the tools to meet those needs, and take their solutions from IP to eventual IPO. The course leveraged the expertise of physicians and engineers actively involved in innovation at UCI. Each session began with a focused didactic component, followed by case-based discussions using examples of real clinical challenges and the solutions created. For some sessions in the Ideation theme, students performed hands-on training using tools such as Arduino, ChatGPT, and CAD. Given that this was the first offering of the course, student participation records, an IRB exempt approved feedback survey, and an application to participate in the full PITP was developed and analyzed to assess student interest and improve future offerings of the course as well as subsequent portions of the program.

In the first year offering of the elective course, a total of 37 students participated in the course in which they attended 8 engineering and innovation related seminars to prepare them for the technical and entrepreneurial requirements for innovation. Survey and attendance record results found that students were able to participate in almost all of the seminars offered, and students found them to be useful introductions to the current tools and technologies that exist. They also requested further short assignments prior to the seminars to help them connect what they learn to clinical settings to improve future offerings of the course. In addition, the participants were asked to apply to the PITP to take the second part of the elective as well as act as mentors in the undergraduate biomedical engineering senior capstone course to develop their own multi-year capstone project. Seventeen of these students applied for the PITP to continue the elective and participate in the senior capstone course, as well as the multi-year capstone project as part of the program. Five students were accepted as the first cohort to participate in the full PITP. Additionally, 8 of the applicants expressed an interest in performing the MEng program in between their MS3 and MS4 years regardless of entry. Survey results, attendance records, and application responses indicate that the program is highly desired by the medical students, although there were concerns with time and commitment responsibilities given the extensive training required for the program during medical school. The preliminary findings of this pilot program suggest that integration with the BME capstone program and elective courses that focus on innovation and engineering can be integrated within medical school curricula to train the next generation of physician innovators.

Authored by
Prof. Christine E King (University of California, Irvine), Prof. Elliot E Hui (Affiliation unknown), Yama Akbari (University of California, Irvine), and Dr. Warren Wiechmann (University of California, Irvine, School of Medicine)

The development of technical writing skills plays a major role in any engineer’s training. The act of organizing thoughts in a written format helps students solidify concepts covered in the classroom and may continue the learning process as students uncover areas they did not fully understand previously. Additionally, strong communication skills are highly sought after by employers. Despite this, many traditional engineering courses that employ technical writing assignments fail to give students the space to reflect upon and improve their writing. Furthermore, students are often dissuaded from further engaging in the writing process due to time constraints and lack of grading incentives. The repercussions are two-fold: (1) students may not view technical writing as a critical skill worth improving, compared to other technical skills, and (2) students may develop an adversarial relationship with writing assignment due to relatively subjective evaluation. We posit that allowing students to resubmit assignments to improve their grade addresses these repercussions and improves self-efficacy, while reducing anxiety.

The courses evaluated in this preliminary study were bioengineering laboratory courses where technical writing assignments comprise over 80% of the final grade and a resubmission policy was employed. This resubmission policy allowed students to resubmit writing assignments one additional time for up to 100% of the points back. To assess students’ self-efficacy and anxiety, a course survey was given at the start and end of the semester, where students evaluated statements related to self-efficacy and anxiety on a 5-point Likert scale. Pre- and post-course survey results were paired by individual student, anonymized, and filtered for completed surveys (n = 22). Using the Kruskal-Wallis test for ranked non-parametric data, the results were analyzed for any differences between pre- and post-course scores. These methods were reviewed and approved by an institutional review board.

Results indicate that assignment resubmission improved students’ self-efficacy and reduced anxiety. In assessing statements related to self-efficacy, such as “I am confident I understand topics [in this course]” and “I believe I can master skills [in this course]”, a significant positive difference was seen in the post-course scores (p < 0.001). A reduction in anxiety-related scores was found for low-complexity and high-complexity course-specific tasks (p < 0.001 and p = 0.003, respectively). Qualitative responses from students explicitly acknowledged the positive role the resubmission policy played in the quality of their work. Future steps include assessing more courses over a greater range of topics and levels, as well as evaluating the effect, if any, of resubmission on underrepresented groups in engineering to see if these policies improve classroom equity.

Authored by
Dr. James Long (Rice University)

The development of novel data analytics, machine learning, and artificial intelligence tools have reshaped biomedical engineering. Applications of machine learning (ML) and artificial intelligence (AI) in medical devices have resulted in FDA releasing action plans for regulating AI/ML-based Software as Medical Device (SaMD). Even in areas seemingly unrelated to ML, ML applications, such as image analyzers and text summarizers, have seeped into the daily routines of biomedical engineers. However, due to the relative opaqueness of ML algorithms, ML systems can demonstrate biased behaviors; these behaviors can be seen in both medical devices and general-purpose ML products such as ChatGPT. In fact, a sizable portion of the FDA AI/ML SaMD whitepaper illustrated the need for addressing biases in medical devices. For the next generation of biomedical engineers who will use and design ML-enabled systems, they will need to not only acquire ML literacy but also know how to address biases in ML systems. Sadly, curriculum for machine learning in biomedical engineering (BME) is already a rarity, let alone learning content for addressing bias in machine learning systems.

The BME department at UC Davis newly established a BME course, titled Machine Learning for Biomedical Engineers. To address the necessity of educating our biomedical engineers about bias in ML, we designed and implemented a one-week learning module about diversity, equity, and inclusion problems within the data collection process in ML products. The module ended with a hands-on exercise, where students were given a blind dataset to train a machine learning algorithm on, only to find that the trained machine learning algorithm associated career words with male and family words with female. Students were properly warned about the contents of the module before the instruction, especially before the hands-on module. A seven (7)-item short survey was issued to the students after the module was completed. The survey contained five (5) Likert-scale questions (1: strongly disagree; 6: strongly agree) on several aspects of diversity, equity, and inclusion issues in machine learning systems. The survey also contained two short-answer questions on the clearest and muddiest points covered in the module. The survey was conducted on paper and no demographic information was collected. To ensure anonymity, the instructor deferred the transcription and processing of the data to their research assistants that were not enrolled in the course. This work was designated as Non-Human Subject Research.

Nineteen (19) valid responses were collected out of 22 students who enrolled in the class in Spring 2024. Students reported good confidence on all Likert-scale measures, with the highest average confidence reported on providing equal opportunities of ML (5.28/6) and the lowest reported on ability to take actions to reduce bias in ML (4.74/6). Students reflected that tacking the “right” problems with ML and collecting data with equity in mind were the clearest points from the module; however, many students seek more clarity on how they could convince engineering teams to perform equitable ML, especially if the engineering team does not possess diversity or decides to accept societal bias in the data. We intend to further refine this module and disseminate this module through our platform for the broader educational community in BME.

Authored by
Dr. Xianglong Wang (University of California, Davis), Tiffany Marie Chan (University of California, Davis), and Angelika Aldea Tamura (University of California, Davis)

Many engineering core curriculum feature design education via senior design capstones, or “bookend” design experiences at the beginning and end of the engineering curriculum. This not only leaves design experiences in the critical middle years of engineering education largely unaddressed, but also misses out on the opportunity for development of critical engineering skills. We aim to tackle this gap in knowledge and practical experiences through a strategic course redesign to enhance metacognitive skills, employ empathetic engineering, and develop expert-like biomedical engineering design epistemologies. At the foundation of this work is a backwards design pedagogical approach to course curriculum development in which learning outcomes are the foundation and guide all class activities and content. BME 2081 is a 1-credit, third-year course of approximately 55 students which heavily features teamwork and reflective reasoning to better prepare students for senior design and the biomedical engineering workforce. Based on the theories of situated and experiential learning, this new course structure focuses on design scenarios that emulate the “real-world”, while providing sufficient scaffolding to coach students through the reflective process, allowing for abstract conceptualization. This work in progress paper presents the steps of the decision making process throughout the course redesign, as well as details of the course and results from the ideation processes, pilot testing with students over the summer, and the first iteration of the course in Fall 2024. The redesigned biomedical engineering course includes four modules that aim to introduce students to all steps of the biomedical design process through hands-on learning experiences. We present various course activities including rapid prototyping, reverse engineering (device dissection), data validation on real-world datasets, as well as regulatory standards and ethics case studies through role playing scenarios. For the purpose of this paper, we will be discussing initial results from a course artifact in Module 3. The goal of this work is to create a course which engages students in the collaborative design process while fostering reflective reasoning and empathy within biomedical engineering contexts.

Authored by
Rachel Bocian (Cornell University), Alexandra Werth (Cornell University), and Dr. Campbell James McColley (Cornell University)

As students more frequently engage with the virtual world, it becomes increasingly important for instructors to understand how students are using online resources and artificial intelligence (AI) to learn course materials. Identifying how students use online resources and AI is especially critical for the field of biomedical engineering (BME), whose multidisciplinary scope may require students to use online resources not necessarily created for BME audiences or contexts. In this study, we will identify BME students’ current use of online resources and AI by surveying BME students and instructors about how online resources and AI are being used to enhance learning in BME courses. Here, we define “online resources” as any webpage, simulation, video, news article, peer-reviewed manuscript, forum, or other interactive tool accessed through the internet that enhances student learning.
Students enrolled in nine different BME courses at [institution name] will be invited to participate in our study during the last week of classes of the Fall 2024 semester. Courses will include lecture-based courses, lab-based courses, and project-based courses. Courses will include students from multiple years in the degree program. After consenting to participate, students will complete online surveys through Qualtrics. Survey questions are focused on 1) assessing students’ perceptions on the efficacy of instructor-provided online resources on student learning, 2) asking students to reflect on what types of online resources students use to learn course contents outside of the classroom and how frequently students use these online resources, 3) what specific online resources students use, such as specific websites, and 4) how students use AI as they learn the course material. Additionally, the instructors of record for the nine courses will be invited to participate in our study. Instructors will complete a separate Qualtrics survey, which focuses on identifying 1) what online resources instructors provide to students to support student learning of course material, 2) how effective instructors perceive instructor-provided online resources to be in supporting student learning, and 3) how instructors perceive students using AI for learning. Demographic information will be collected from all surveyed participants to identify any additional correlations between participants and survey results.
From the collected data, our goal is to identify common themes about how students use online resources and AI based on 1) student year in the degree program, 2) course topic, and 3) course type. By correlating this data with what online resources students are using in their respective courses, our results will help instructors realize how they can better integrate or design online resources for their courses. Additionally, by comparing the survey data from the students about instructor-provided online resources with the instructors’ survey responses, we will clarify possible disparities that may exist between instructors’ perceived effectiveness of these resources and students’ reported effectiveness these resources demonstrate in supporting student learning. Further, our aim is to help instructors identify ways in which AI may be more readily applied in their courses to support responsible student use of AI in a manner that trains students to be industry-ready in their understanding and application of AI. Combined, our results will highlight opportunities for instructors to enhance the learning of BME students through application of effective online resources in their courses.

Authored by
Dr. Alex Nelson Frickenstein (University of Oklahoma)

In this work-in-progress, we describe our efforts to better understand how to support student learning in the biomedical engineering (BME) major, in which course content is often presented through visual communication such as lecture slides with mostly images or equations. Specifically, we want to learn how to support students as they take notes in courses where material is presented primarily in a visual modality, but students have access primarily to text-based tools to take notes (e.g., writing/drawing with pen and paper or typing text on a laptop). We asked whether there is an equity gap for students without access to devices such as iPads, which allow students to both draw and write text by hand using a stylus.

We are concerned about how diversity, equity, and inclusion (DEI) may be negatively impacted by any differences in student ability to: (1) take notes effectively or (2) afford note-taking devices such as iPads. Any disparity in note-taking ability among groups of students is likely to decrease achievement or engagement, as note-taking is essential for learning and remembering course material as well as being engaged during class.

Students report that many courses required for BME such as chemistry, biology, math, and physics, involve visual-only lecture slides to present important information, and that instructors often prefer to verbally explain the visuals in greater detail rather than annotating the visuals with text. As a result, most lecture slides include only visual depictions such as photos, graphs, figures, and equations. Students report that when a short text description is included on the slide, it may not make sense without proper context, which is provided only verbally (if at all). More detailed information, such as how the visual representations connect to key concepts of the course, is mentioned verbally.

Our department is concerned that the advantage for students who can afford or otherwise have access to electronic devices, and iPads specifically, creates an equity gap that widens the disparity already experienced by underrepresented students, especially in large introductory courses, which is where many underrepresented students who planned to major in engineering decide to leave the major. We note that BME programs may be particularly susceptible to losing students in prerequisite coursework, as students must take prerequisite courses in all the typical pre-engineering areas such as math and physics, in addition to extensive coursework in chemistry and biology.

Students perceive that the visual-heavy lecture presentation method works better for students who use iPads because they can simply download the slides before class and then add text or visual annotations in real-time with the instructor. We wondered whether our department should consider providing iPads (or helping students find resources to afford iPads). Before taking on such an initiative, however, we wanted to learn more through a formal survey.

In this paper, we share the preliminary results of a survey of 66 undergraduate students, including upper-division students already in our major and lower-division pre-major students who are currently enrolled in an introductory course. Students report the advantages of being able to download visual-heavy slides before lecture and then annotate during class. Furthermore, students report that some electronic devices are better than others for annotating visual information. For example, students report that using a stylus on a device such as an iPad is a more efficient way to annotate visuals than typing text with a laptop or phone because with a stylus or touch-screen students can draw images, hand-write text or images, or type text.

For students using pen and paper, the fast-paced delivery of information and expectation to quickly draw out the diagrams, structures, and equations (that a student with an iPad would already have downloaded) can lead to challenges in keeping up in the lecture and spending more time copying down information rather than understanding concepts. According to our survey results, most students who do not use iPads or electronic devices to take notes report that using electronic devices is cost-prohibitive. Most, but not all, students report that they would use an iPad for taking notes if it was provided free of charge.

In conclusion, ensuring that all students have equitable access to learning resources is essential to create inclusive learning environments. Our survey results help us identify accessibility concerns in note-taking for lecture content composed primarily of visual communication. We discuss possible solutions to these problems, in addition to other student insights in note-taking that are of general interest to engineering educators, to promote a more equitable learning environments.

Authored by
Dianne Grayce Hendricks (University of California, Santa Cruz) and Aditi Bhat (Affiliation unknown)

Biomedical Quality Engineers (QEs) ensure that medical devices are safe, reliable, and consistent. Over 40% of entry-level biomedical engineering (BME) jobs are QE positions, and 70% require QE-related skills. However, most BME undergraduates are unaware of careers in QE, and many current QEs learned about the field after they entered the job market. BME students have low outcome expectations for QE careers and higher outcome expectations for research and development (R&D) positions. This study tests whether increasing awareness of QE and R&D careers improves outcome expectations for either type of engineering career. Accurate career expectations are necessary in order for students to make informed decisions about QE or R&D career pathways.

This project builds on our qualitative study of the experiences of current Quality Engineers, which found that they were unaware of Quality Engineering as a career for BMEs when they were undergraduates. Similar to our previous work, we use qualitative methods based on Social Cognitive Career Theory (SCCT) to discover pivotal points in the participants’ learning experiences. Specifically, we will identify areas where BME curricula did not provide undergraduates with QE-related learning experiences and how exposure to QE concepts changes student perceptions of QE careers. Our project partners with a master’s degree in medical product development. This program provides coursework on quality systems, regulatory management, and other QE principles and it enrolls recently graduated BME students. We collected focus group data from students as they started in this program and are in the process of interviewing them now that they’ve completed the program. In both the focus groups and interviews, we inquire about their prior and current views on QE as a career path. We will use SCCT-based a priori codes as well as open coding of the transcripts to test the intervention suggested by our previous research — that introducing students to Quality Engineering through coursework will increase their interests and outcome expectations regarding the career path.

This qualitative research project will inform the design of BME curricula to create a balanced awareness of both QE and R&D career pathways so students can pursue careers that match their interests, goals, and outcome expectations.

Authored by
Ms. Deepthi Suresh (University of Michigan), Prof. Paul Jensen (University of Michigan), and Prof. Jan P. Stegemann (University of Michigan)

Modern-day engineering classes have found it challenging to keep students engaged the whole time, which has become a focal point since the pandemic. The necessary changes in pedagogical methods during the pandemic have burdened the students. Online classes, not having the college experience, and reduction of one-to-one interaction with faculty, are aspects of an engineering class that could impact the outcomes of a course as well as the department. Given the hands-on experience as a student, particularly in the field of Biomedical Engineering, that is essential for developing their skill to make them ready for their career, the last few years have warranted instructors to innovate pedagogy.
In the past couple of years, at our university, we began employing active learning methods in the Biomedical Engineering classes to tackle the challenges that we faced during the pandemic. As part of these changes, we included a component of education research to study the effectiveness of active learning in the classroom. Our team had the opportunity to interact with students one-on-one, which opened our eyes to a very important issue the students were feeling. The changes we made during the pandemic, and since, impacted students in a way that some of them pointed out feeling like being subjects of experimentation. That made us introspect our processes and made us realize we need to first understand the audience, in this case, our students, before we can assess how they are learning.
This study aims to contribute to the existing literature by employing Maslow's Hierarchy of Needs as a framework to explore the needs and experiences of Senior Biomedical Engineering students (graduating in 2024 and 2025). The study was administered to the students enrolled in two separate senior-level courses in the BME department, one in Fall and one in Spring. The study aimed to study in parallel the same research question (1) at the course level and (2) as a department at the end of four years of undergraduate enrollment. By examining the five categories of needs - physiological, safety, love and belonging, esteem, and self-actualization - we sought to understand whether our students' basic needs are being met if they feel safe and supported within the department if they have opportunities for growth and development, and if they feel empowered to pursue their goals.
Using a mixed-methods approach, we administered a quantitative survey to Senior BME students, asking them to score each category of need based on their experiences. We also conducted semi-structured interviews with a subset of participants to gather more in-depth insights into their perspectives and challenges.
The primary research questions we pursued during the study included
1. What is the level of satisfaction among Senior Biomedical Engineering students in terms of their safety, physiological, belonging, self-esteem, and self-actualization needs?
2. How did each course individually in the course sessions meet or fail to meet these needs, as perceived by the students?
3. How effective are departmental policies and practices in promoting a sense of community and inclusivity among students, as perceived by senior students?
4. Can targeted interventions aimed at improving student engagement and motivation (e.g., more group work, peer feedback) also improve feelings of safety and belonging among BME students?
5. Can understanding these needs inform departmental decisions about course design, faculty training, or student support services to improve overall student success?
This is a work in progress which we aim to continue till Spring 2025, but preliminary results so far from the survey and semi-structured interviews have indicated significant progress needs to be made in meeting specific needs such as physiological needs (breaks during long sessions, the ability for lecture schedules to allow for lunch, etc), esteem needs (better interaction with course faculty), and self-actualization needs (career related guidance and opportunities). As far as the safety and belonging needs are concerned the student responses indicate the department policies allow the students to express themselves, and that for the individual courses, the instructors play a significant role in addressing these needs.
The findings from this study have the potential to inform pedagogical changes, departmental policies, and student support services that prioritize student-centered learning and promote a more inclusive and supportive learning environment. The results can also be used to develop targeted interventions aimed at addressing specific needs or challenges identified by students.

Authored by
Dr. Viswajith Siruvallur Vasudevan (Cornell University) and Prof. Jonathan T. Butcher (Cornell University)

In this work-in-progress, we describe the design and implementation of the first four offerings of a novel, project-based molecular biology experimentation and design lab course. A key feature of the course is participatory design, which can be defined as the process of involving end-users in all steps of the engineering design process. We used participatory design in two ways: (1) the instructor co-created the course with two senior undergraduate students, and (2) students enrolled in the course were involved in decisions at every step of the project.

This project-based lab course lab course is the third in a series of three molecular biology lab courses required by our BME major, and most students take the labs in their second or third year. As this lab series is often the first exposure students have to BME courses in our department, it is especially important to make all students feel welcome and give them tools for future success.

We leveraged student involvement in the design and implementation of the course to make the course accessible and relevant to students. The course curriculum was co-designed with two undergraduate students in iGEM, who designed the lab project based on some of their iGEM work. In addition to providing much-appreciated expertise in the topic and valuable troubleshooting skills, the iGEM students added useful insights to the instructor and made the class more accessible and enjoyable for students.

The 10-week lab project involves a molecular biology process known as “clonetegration,” or the one-step cloning and integration of a plasmid carrying a cloning module and integration module. We use a plasmid carrying the fluorophore mcherry for the initial step of integration by a viral integrase enzyme at a known attachment site in the E. coli genome. After integrating the entire plasmid into the genome, we flip out the integration module (including the integrase enzyme and antibiotic resistance) using the pE-FLP plasmid, so that only the cloning module including our gene of interest remain integrated in the genome. We confirm successful integration and flip-out steps with colony PCR.

Recent studies have shown that project-based courses and participatory design experiences are particularly effective at engaging women and other students from underrepresented groups in engineering. In addition, a major benefit of participatory design is providing students with a real-world lab experience in a safe and supportive environment that will prepare students for success in capstone and other future BME research opportunities.

The following are examples of how we facilitate participatory design by students enrolled in the course:
(1) We provide resources and ask students to write their own protocol before lab, instead of providing a step-by-step protocol or “cookie cutter” instructions.
(2) Students execute the project with only minimal supplies provided. Students make bacterial growth media, buffers, and their own chemicompetent cells.
(3) In each lab, we discuss factors to consider when designing experiments and students decide how to proceed. Students make design decisions such as which E. coli strain to use with specific plasmids.
(4) Students design experimental controls and design PCR primers.
(5) Students complete lab quizzes collaboratively, and we review answers as a class. We provide students with guiding questions for troubleshooting experiments.

In conclusion, in this paper we describe the design and implementation of a project-based molecular lab course that is focused on participatory design by students. Course assessment includes instructor observations, informal feedback from students, and end-of-course student surveys. Access to all course materials will be provided.

Authored by
Dianne Grayce Hendricks (University of California, Santa Cruz), David James Kelaita (University of Colorado Boulder), and Tanya Ivanov (University of California, Los Angeles)

Undergraduate engineering students often struggle when presented with complex course projects that require critical thinking and integration of knowledge from past classes. In our junior level bioimaging course, we observed that students found it difficult to approach projects that demanded the application of coding skills learned in previous courses to solve image processing and analysis problems. This issue often leads to last-minute efforts and undue stress, which prevents students from truly understanding course material and gaining deeper insights into its content. To address this challenge, we introduce a scaffolded approach aimed at promoting self-directed learning and building productive work habits to help students solve large problems.

This work-in-progress research is being conducted at Texas A&M University university within the department of biomedical engineering. The teaching practice is being applied to coding projects in a bioimaging course where students were tasked with image processing problems designed to expose our students to active areas of research, image analysis, and to recognize the problems and shortcomings associated with the project. Specifically, the topics of the projects were utilizing medical imaging data for masking/pre-processing of the lungs, automated cell counting from histology slides, calculating ejection fraction from lung CT scans, and co-registration of image data from two imaging modalities. The projects were originally designed to each be completed within a two-week deadline. To enable this short turnaround time, the deliverables of each project report were designed so that the students would first familiarize themselves with the initial code (if provided) and data, research the topic, apply techniques from the literature, recognize shortcomings of the techniques, and provide a metric for the result with any relevant statistics and conclusions. The intent was not for the students to fully solve the problem within the two-week period. Rather, students’ abilities to approach large problems through applying their coding and statistics skills from prior classes, researching relevant coding tools, and discussing what could be done to improve shortcomings if given more time were the intended points of evaluation.

Through the first rollout of these projects, both instructors observed that students appeared to flounder with the size of the project, and as a result, they procrastinated working on the project until only a day or two before it was due. Initial check-ins regarding progress were met with little student enthusiasm or understanding. Much to the dismay of the instructors, initial polling of students about time spent on the projects was also far greater than desired, even with the delay in starting. This, along with the level of detail in the reports, indicated that students were not being productive and/or effectively utilizing their resources. Utilization of the first five minutes of each of the six class periods to discuss the “pain points” appeared to benefit the few who had started on the remaining projects, but this didn’t appear to improve early student involvement on the project for the bulk of the class. The use of a scaffolded approach with an initial deliverable three days into the last project by one of the classes resulted in better student engagement during the “pain points” discussions.

In the next iteration of the course three main modifications to the projects will include:
1. More scaffolded support designed to help students reduce each problem into tasks and progress steadily through the earlier projects
2. Student self-tracking of time spent on each project and short reflection about productivity
3. Maintenance of a Google Doc documenting their progress and for ease in reporting

The first two projects will be divided into several deliverables that feature corresponding learning modules. These modules will explore self-directed learning concepts, such as resource utilization, effective question-asking, trouble-shooting, and productive work. The final two projects will not have the learning modules but will require the reporting of time spent and shared documentation. Students will take pre- and post-course surveys about their confidence in approaching complex problems and effectively utilizing their time.

The goal is to create more independent learners with growth mindsets, giving them the skills and confidence needed to tackle complex coding challenges. By practicing these skills in the first projects, students are expected to gain confidence, continue these practices on the final projects with less instructor-provided support, identify practices that contribute to productive work, and self-reinforce time management practices. The surveys will be utilized to assess student confidence in approaching large problems in image processing and their reflections will further drive the development of the learning modules for the first two projects for future iterations.

Authored by
Dr. Travis Carrell (Texas A&M University) and Anne-Marie Ginn-Hedman (Texas A&M University)

INTRODUCTION: The increasing aging population and focus on preventative medicine have led to a growing demand for physical therapy and wearable technology [1]. The wearables market, projected to grow from $28.2 billion in 2021 to $66.9 billion by 2030 [2], includes technology that facilitates physical therapy exercises at home, leading to better health outcomes for compliant patients. This industry is poised to incorporate advanced technologies, necessitating support from biomedical engineering. Biomedical engineers are uniquely positioned to develop innovative solutions at the intersection of science and medicine. To equip them with the necessary skills, it is crucial to provide opportunities for hands-on learning during their undergraduate education. This paper presents a newly developed three-course medical device design series (Course 1, Course 2, Course 3) aimed at training biomedical engineering students through progressively complex projects addressing unmet needs in physical therapy. The courses employ the educational concept of scaffolding, offering extensive guidance initially and gradually transferring responsibility to the students.
COURSE SEQUENCE STRUCTURE: Course 1 introduces the fundamentals of medical device design, focusing on physical rehabilitation and assistive devices through prescriptive lectures, homework, and labs. Students undertake four projects, culminating in the development of a prototype for a client with a recent surgery. Course 2 is an intermediate course emphasizing electro-mechanical design and advanced prototyping skills. Students complete three projects, including reverse engineering a musculoskeletal joint and developing solutions for joint-related problems, with guidance from physical therapy students. Course 3 focuses on advanced prototyping and manufacturing techniques, with projects addressing specific physical therapy needs. Students complete two projects, one individually and one as part of a team, involving interviews with physical therapists, clinicians, and patients to develop solutions for various conditions.
PRELIMINARY RESULTS AND CONCLUSIONS: The effectiveness of these courses is assessed through surveys conducted before, during, and after each course. Preliminary results from Course 2 indicate positive student feedback, with 87% reporting a high or moderate positive impact from educational videos and materials produced by physical therapy students. Additionally, 100% of students valued Project 1, and 67% highly valued the final project. Anecdotal evidence from alumni suggests that the courses prepare students to make immediate contributions to projects and provide valuable information critical to success in the medical device industry. Future work will focus on collecting and analyzing more data to support these findings. Preliminary findings are encouraging, highlighting the benefits of this approach in teaching medical device design and fostering strong interdisciplinary collaboration.

Authored by
Prof. Colleen Louise Bringman (The University of Iowa) and Amy L Kimball (The University of Iowa)

Biomedical engineering is a growing field that plays a key role in addressing challenges in healthcare by creating innovative technologies and solutions, meaning it is critical to ensure that graduates are best prepared for the challenges they may encounter in a professional environment once they have graduated. The transition from developing a strong foundation of conceptual understanding during undergraduate education to applying knowledge to real-world scenarios, particularly upon entering the workforce or pursuing higher education, has been an ongoing concern in the field of biomedical engineering. That said, this work- in- progress (WIP) seeks to understand how students engage in problem-solving by assessing the current role of metacognitive skills. Metacognition entails a person's self-awareness of how they approach thinking and has been identified as a crucial skill set for engineering students to develop while pursuing their education. Metacognitive skills are divided into two primary categories metacognitive knowledge and metacognitive regulation, each consisting of three subcategories (declarative knowledge, procedural knowledge, and conditional knowledge; planning, monitoring, and evaluating respectively). Development of both primary categories is encouraged for student success. Methods to evaluate metacognition for this WIP include qualitative assessments (in-person interviews) of 10% of an undergraduate tissue mechanics course, before the incorporation of pedagogical interventions that will take place in future work. Future directions of this research would entail continued observations of how students use metacognition to approach engineering problems and the incorporation of instructor-guided in-person and digital pedagogical interventions that encourage further development of metacognitive skills. Thus, exploring the relationship between metacognition, conceptual understanding, and student approach to problem solving. This will be accomplished through an increase in the number of participants, a comparison of academic performance through quizzes administered to the class following pedagogical interventions to those from previous years, and additional qualitative assessments (in-person interviews and surveys).

Authored by
Victoria Rose Garza (The University of Texas at San Antonio), Dr. Joel Alejandro Mejia (University of Cincinnati), and Dr. Teja Guda (The University of Texas at San Antonio)