The ASEE Faculty Teaching Excellence Task Force has just completed its NSF IUSE ICT Capacity Building grant and started its next NSF grant (IUSE ICT Level 1). Both grants support the building of a recognition framework for engineering and engineering technology (EET) faculty in the US for their efforts and achievements in professional development (PD) as it relates to teaching.

Various arguments can and have been made about the need for EET faculty to receive training in how to teach. Such arguments are more than a century old and have continued to more recent calls. Indeed, the changing nature of the job responsibilities of a professor requires skill set (e.g., identifying mental health challenges of students) that were not considered in previous generations.

To promote the recognition of EET faculty PD in teaching, ASEE charged a task force with developing a plan to achieve such an outcome. The first step in this plan was to engage various diverse ASEE constituencies on the value of such a recognition system, as well as barriers to implementation. Such efforts were supported by a grant from the NSF IUSE ICT Capacity Building program. One of the key outcomes from this work, which was completed in August 2024, was a three-level recognition framework: (1) Registered Engineering Educator, (2) Certified Engineering Educator, and (3) Leading Engineering Education.

The first level, Registered Engineering Educator, is focused on the acquisition (through training) of key competencies. Such draft competencies were identified through literature investigation, focus groups, and surveys. The second level, Certified Engineering Educator, is focused on the implementation of some of the competencies learned during the previous level. The third level, Leading Engineering Educator, looks to recognize individuals who are improving engineering education outside of their own classroom.

The next stage of the larger project, which was recently funded via an NSF IUSE ICT Level 1 grant, will pilot the Registered Engineering Educator level at eight diverse partner institutions, aided by 24 additional partner institutions that serve as an Evaluation Team. Centers for Teaching and Learning at the partner institutions, plus nationally recognized content providers (e.g., NETI), will provide most of the content as EET faculty at the pilot institutions work towards achieving the requirements of the Registered Engineering Educator level.

Research for this grant will begin with how individuals are recruited to participate in faculty development programs and how they make their PD selections. Additionally, we explore items associated with value, access, and barriers to PD (both perceived and actual) for faculty, plus how this might vary by institution type. Finally, we explore how conversations and practices might change as a result of participation in PD.

Authored by
Dr. Donald P. Visco Jr. (The University of Akron), Dr. Jenna P. Carpenter (Campbell University), Dr. Elizabeth Litzler (University of Washington), Dr. Douglas Bohl (Clarkson University), Dr. Charles Henderson (Western Michigan University ), Dr. Alan Cheville (Bucknell University), and Dr. Rae Jing Han (University of Washington)

Need: Attrition is a significant issue for STEM undergraduate majors: on average 49% of students transfer to another major or leave college completely by their 8th year of study, with even greater rates for STEM majors who are under-represented minorities or women. Barring financial barriers to retention, the most significant drivers of attrition are reported to be difficulty in adjusting to academic and life needs and resolving educational and occupational goals, and feelings of isolation. We posit that the former impediments are closely related to ineffective Self-Regulation of Learning (SRL), since SRL addresses an individual’s behaviors and strategies as an independent and reflective learner, and their motivation to sustain effort when challenged. We posit that the latter impediment is closely related to a lack of sense of belonging (SOB), since SOB addresses an individual’s cognition, affects, and behavior around their perceived legitimacy as a member of a community who is included, involved, valued, and accepted. Further, it documented that many students enter college with ineffective SRL, and that under-represented students like minorities and females have fewer relatable peers and so are more at risk of having a low sense of belonging in college.
So, can retention be improved by systematically training students in effective SRL strategies?

This NSF IUSE project draws upon published research of educational psychology social-cognitive frameworks around SOB (Strayhorn, 2019) and SRL (Zimmerman, 2000 and 2002), and the findings of a prior NSF-funded study and a pilot study, to uniquely develop and refine an intervention that synergistically interweaves the learning of STEM topics with developing effective SRL and building SOB.

Project: This 3-year IUSE:HER Level 1 project is completing its first year. In the first year, 80 sophomore civil engineering students received training in SRL to improve their metacognitive knowledge, awareness, and experience, and develop personalized and adaptable strategies for building effective SRL. Key findings include student perception of the importance and helpfulness of the intervention, and statistics regarding uptake of SRL, SRL effectiveness, SOB, and performance in major courses taken alongside the intervention.

Broader impacts: This project creatively incorporates evidence-based advances in educational psychology and education into undergraduate STEM education and lays the groundwork for significant institutional improvement in associates and baccalaureate STEM programs by offering a replicable, transferable, and adaptable design.

National Academies of Sciences, Engineering, and Medicine. (2016). Barriers and Opportunities for 2-Year and 4-Year STEM Degrees (S. Malcom & M. Feder, Eds.). National Academies Press. http://dx.doi.org/10.17226/21739
National Academies of Sciences, Engineering, and Medicine. (2021). Addressing Diversity, Equity, Inclusion, and Anti-Racism in 21st Century STEMM Organizations (L. Scherer, Ed.). National Academies Press. http://dx.doi.org/10.17226/26294
Strayhorn, T. L. (2019). College Students' Sense of Belonging: A Key to Educational Success for All Students (2nd ed.). Routledge: New York, NY.
Zimmerman, B. J. (2000). Self-Efficacy: An Essential Motive to Learn. Contemporary Educational Psychology, 1, 82–91. https://doi.org/10.1006/ceps.1999.1016
Zimmerman, B. J. (2002). Becoming a self-regulated learner: An overview. Theory into Practice, 42(2), 64–70. https://doi.org/10.1207/s15430421tip4102_2.

Authored by
Dr. Ann (Beth) Wittig (City College of New York at City University of New York (CUNY) )

This Research Experiences for Undergraduates (REU) program supports active research participation by community college (CC) students with a focus on Smart Engineering, including: Artificial Intelligence/Machine Learning, Smart Health, Smart Materials, and Smart Infrastructure. The program is offered as 10-week non-residential summer research experience for local community college students. The program also features high-quality interactions of students with faculty and/or other research mentors, access to appropriate facilities and professional development opportunities, an opportunity to tap the nation's diverse student talent pool, and broaden participation in science and engineering. Th participating CC students are also introduced to and encouraged to transfer to 4-year college education to enhance their future employment and increase participation of the underreported in STEM education.

This extended abstract presents the results from a retrospective pre-post exit survey by the grant external evaluator of participants in the xxx University Pathways REU in engineering, as funded by the National Science Foundation. This project supports regional community college students at xx University for summer work in engineering research, placing the participants in research labs working on cutting edge problems in AI/machine learning, smart infrastructures, smart materials, and smart health.

The evaluation research questions include:

• To what extent was the project successful at engendering growth across the four target constructs?
• What aspects of the summer experience are reported as being most beneficial?
• What do participating students say about their summer experience more generally?
• How do the 2024 cohort’s results compare with those of the previous two cohorts?

The key findings include:

• The REU exit pre-post surveys again showed consistently positive results across the intended outcomes with moderate to large effect sizes.
• The importance of conducting research under the guidance of a faculty mentor was viewed by the students as essential to the summer’s experience.
• The 2024 REU group expressed a strong association between gains in self-confidence, understanding of engineering and a commitment to continue in engineering.
• The 2024 evaluation findings are generally consistent with those of the previous two years, with the 2024 group reporting the most positive effects of participation among the three cohorts.

If accepted, the extended abstract will delve into the details of the survey questions, statistical sampling and methods, and the statistical results analysis.

Authored by
Dr. Ibrahim F. Zeid (Northeastern University) and Mrs. Claire Duggan (Northeastern University)

The Sketchtivity project explores the teaching of freehand sketching using an intelligent tutoring software in engineering design education through providing individualized feedback on sketching fundamentals and 2-point perspective techniques. Project findings indicate that Sketchtivity enhances spatial visualization skills, creativity, and student confidence, with measurable improvements observed in as little as 3-5 weeks across 4 university implementations. The research has raised further questions regarding the specific sketching knowledge and skills engineers need to learn to optimize visual communication and engineering education. One study aims to begin to address these questions by investigating the role of sketch styles in influencing engineer preferences and perceptions of creativity and functionality in sketched product ideas. This study and future research on sketching instruction will use surveys to evaluate perceived characteristics including preferences, highlighting the importance of examining the distinctions between ranking and rating scales as tools for assessing these perceptions.
A comparative study was conducted across two graduate level mechanical engineering courses to assess the validity of rating versus ranking scale methods in evaluating sketch preferences. Participants evaluated 10 products across 3 categories (spacecrafts, chairs, and toasters) presented in varying line styles including single line, variable thickness, feathered and heavily feathered line work. One course completed a ranking based survey while the other completed a rating-based survey. The analysis compared the two data sets to determine whether ranking or rating scales better capture aggregate preferences in design sketch assessments. The results indicate that ranking and rating scales reveal similar mean preferences, with a clear favorability towards the single line style especially for more complex engineering products indicating that the clean, single line style typically seen in industrial design should be taught to engineers. Ranking scales demonstrated greater differentiation between sketch styles, while rating scales showed more compressed responses, with participants often assigning equivalent scores to multiple sketches. The study suggests that while both methods are valid for engineering design education contexts, ratings may be more suitable when finer distinctions between preferences are sought, whereas ranking is more effective for gauging general trends. This work informs best practices in survey design for engineering education research and for future work, emphasizing the importance of selecting scale types based on study objectives. The findings contribute to a broader understanding of how sketching styles influence engineering design perception and provide insights into instructional strategies for developing effective sketching skills among engineering students.

Authored by
Shiho Nakamura (Georgia Institute of Technology) and Dr. Julie S Linsey (Georgia Institute of Technology)

As the Industry 4.0 revolution reshapes manufacturing, design, and engineering processes, the role of mechanical engineers is expanding beyond traditional boundaries. Since mechanical systems are increasingly interconnected with digital technologies, training the next-generation mechanical engineers in Internet-of Things (IoT) programming and software engineering methodology is critical for meeting industry demands. However, these critical skills are often missing in traditional mechanical engineering curriculum. To address this challenge, we have modernized our curriculum by integrating IoT technologies and software engineering concepts in a new course. Specifically, we couple project-based learning and Agile methods, which represent the best practices in the IoT industry, to provide mechanical engineering students with a highly practical, hands-on learning experiences. In this paper, we present details of the Agile method component of the new course.

Authored by
Dr. Xinghui Zhao (Washington State University), Prof. Hakan Gurocak (Washington State University-Vancouver), and Dr. Kristin Lesseig (Affiliation unknown)

Engaging teams of computing students, working over one or more terms to develop software systems that contribute or improve some aspect of their local community is a valuable high-impact educational practice [1-3]. However, this form of community-based service learning can be an intimidating practice to implement [4,5]. This NSF IUSE-sponsored project, Scaffolded Projects for the Social Good (SPSG), introduces a framework for a software studio approach designed to seamlessly integrate service learning into the computing curricula [6,7]. SPSG offers a low-adoption threshold solution for educators, providing a comprehensive toolkit to guide the process of selecting appropriate projects, and providing structure for all deliverables that fosters collaboration between students and community organizations, from the point of initial contact through project hand off. The project focuses on creating a flexible, easy-to-adopt framework that allows instructors to easily embed externally sourced community-based service learning projects into their courses. The ultimate goal is to leverage this high-impact educational practice to promote the development of professional dispositions and technical skills among students while working on real-world projects that serve non-profit and community organizations.

The SPSG framework was piloted in four courses at two institutions, involving 21 student teams during the Fall 2023 and Spring 2024 semesters. These teams, consisting of juniors and seniors, engaged in projects supporting community-based and commercial clients, with the majority working on non-profit initiatives, all using the SPSG framework. To assess the impact of these experiences on students, pre- and post-surveys with a longitudinal component were used to gather data on students’ skill development and professional growth.

Key deliverables from the project include the SPSG Structure Guide, Instructor Guide, Code Management Guide, Project Feasibility Evaluation Rubric, Mentor Guide, and several questionnaires for clients. These resources are designed to streamline the project implementation process for instructors, guiding them through each phase of project planning and execution while encouraging collaboration between students, mentors, and clients. All materials are available on the project’s website, providing open access to any educator interested in adopting the framework.

In the upcoming year, the framework will be further refined and adapted to new educational contexts to broaden its applicability, including the involvement of community partners in socially valuable student projects that don't necessarily lead to a fully deployable software artifact. As survey data is analyzed, adjustments will be made to improve the SPSG framework and its associated tools, enhancing its value to instructors and students alike in engineering education programs.

Authored by
Dr. Chad A. Williams (Central Connecticut State University), Dr. Stan Kurkovsky (Central Connecticut State University), Nathan Sommer (Xavier University), and Prof. Mikey Goldweber (Denison University)

This paper describes the design and development of a Web-based Data Science Learning Platform (DSLP) aimed at making hands-on data science learning accessible to non-computing majors with little or no programming background. The platform works as middleware between users such as students or instructors, and data science libraries (in Python or R), creating an accessible lab environment. It allows students to focus on the high-level workflow of processing and analyzing data, offering varying levels of coding support to accommodate diverse programming skills. Additionally, this paper briefly presents some sample hands-on exercises of using the DSLP to analyze data and interpret the analysis results.

Authored by
Dr. Xumin Liu (Rochester Institute of Technology)

Research in nontraditional engineering students (NTES) generally focused on their demographics, the challenges they faced, their deficiencies, and methods to improve the outcomes of NTES in engineering programs. None of the existing studies in NTES are asset-based and focus on their strengths such as their lived experiences, or leveraging their strengths to increase engaged student learning for all students. The objective of this study is to identify the characteristics of NTES lived experience that can be incorporated into engineering classrooms to increase engagement for all students. Through interviews with NTES and thematic analysis, the attributes of NTES’ past experience that were of interest to traditional engineering students in their engineering courses and classrooms were identified. Results show that NTES professional skills (networking and problem-identification), and the application of their work experience into technical lecture content were more frequently discussed when they collaborated with traditional engineering students. Future work for this project will include validating the lived experience of the NTES with the traditional students, and creating in-class cooperative learning activities that utilize NTES lived experience.

Authored by
Dr. Ean H Ng (Oregon State University), Dr. Ganapathy S Natarajan (University of Wisconsin - Platteville), and Ingrid Scheel (Oregon State University)

The addition of generative artificial intelligence (AI) algorithms to the traditional engineering design process, e.g., generative design (GD) and large language model (LLM) assisted design, significantly shifts the role, cognition, and behavior of the human designer. The way the human explores the design space is the design task most affected by the generative AI-based paradigm shift. Traditional design (TD) characteristically requires the human designer to explore the design space by generating a range of ideas/potential solutions which might solve the goal(s), and then analyze their performance in the objective space. However, the GD process prompts designers to employ inverse thinking by computationally defining and scoping the objective space (e.g., materials and manufacturing constraints) for the AI-agent to explore and analyze all available options in the design space while optimizing towards (a) feasible solution(s) which are presented to the human designer for further selection and iteration. The inverse relationship of TD and GD requires the designer to think and behave in a unique manner for each paradigm. However, there is little research exploring Generative Design Thinking, i.e., the cognitive processes that underlie GD. There also lacks an available infrastructure for conducting and applying the results of educational research to determine best GD teaching practices and develop new teaching materials.

The goals of this joint-effort project (UT-Austin, UIUC, Oregon State University, University of Arkansas, and the Institute for Future Intelligence) are to address three research gaps: design cognition research to define GDT, education research to create/test materials for teaching GD/GDT, and technology development to support GD research. In design education, the development of curriculum to prepare next-generation students for effective industry use of generative AI requires a clear definition of GDT which describes the relevant cognitive processes and how to best teach them. In design research, this definition will aid the development of AI-agents for augmenting previously human-driven tasks, e.g., by providing inspiration during conceptual design to overcome fixation.

Project outcomes fall within these three gaps. First, a systematic review of literature on design thinking/design cognition topics (e.g., systems thinking, computational thinking, design creativity) is underway to define GDT by suggesting how these cognitive processes manifest during GD, how to best teach them, and to clarify the differences between GDT and other “design thinking” concepts. We have developed an Evolving Design Thinking (EDT) model to guide our review and represent how evolving technologies like generative AI drive the evolution of design thinking/cognition. Second, we have developed a text-based curriculum with CAD activities to teach basic GD principles. Student data (transcripts via think-aloud, design process and artifact data via a CAD platform) were gathered and used to refine the curriculum and explore students’ thought processes during GD. Third, software development includes the creation and continued support of Aladdin, a web-based open-source CAD/CAE platform which enables research and the creation of educational modules in renewable energy design contexts. Finally, project outcomes have been disseminated to collaborative academic (Lehigh University, Utah Tech, Hawaii Kapiolani Community College) and industrial partners (PTC Inc.) for broader impacts.

Authored by
John Zachary Clay (University of Texas at Austin), Dr. Molly H Goldstein (University of Illinois Urbana-Champaign), Dr. Charles Xie (Affiliation unknown), Dr. H. Onan Demirel (Oregon State University), and Dr. Zhenghui Sha (University of Texas at Austin)

Tutoring support is vital to eliminate knowledge gaps and achieve learning outcomes, while attaining instructional scalability to large class sizes common in STEM courses. However, determining which courses require additional tutoring support is challenging due to the lack of formal quantitative measurement tools, thus hindering the ideal provision of Teaching Assistant (TA) allocation. Herein, we develop a NetLogo framework for an Agent-Based Model (ABM) designed to simulate student progress and performance in a required Electrical and Computer Engineering (ECE) undergraduate course. It predicts and quantifies course outcomes under varying amounts of tutoring support via TA office hours. The ABM incorporates key parameters such as learners' attainment in previous semesters, grading schemata, and tutoring impact to predict the corresponding number of at-risk students. Meanwhile, the technical approach utilizes a NetLogo-based implementation of the ABM, which realizes a flexible, modular, and observable design.

The ABM is composed of three primary components: student agents which represent individual students along with their content proficiency, a course environment which encapsulates the grading scheme along with tutoring support parameters of the TAs available, and a feedback mechanism which enables the ABM to adjust its predictions based on the instructor's input. The technical results demonstrate that the ABM is capable of accurately predicting the number of students having significant risk of DFW, i.e. earning a course letter grade of D or F, or withdrawing (W). The results show that the ABM is robust and reliable in its predictions of DFW rate, whereas three out of four semester configurations analyzed indicated that the ABM’s predicted values bordered the 95% confidence interval. When measuring accuracy, test runs included course enrollment ranging from 70 to 121 students, commensurate with actual course delivery enrollments. The NetLogo model was parameterized towards attaining the worthy objective of lowering the DFW rate. Furthermore, to assist administrative decision making, it computes the monetary cost of tutoring per supported student. This new metric, known as Remediation Cost Per Supported Student (RCSS), delivers a quantitative measurement of cost-effectiveness for a course staffing configuration when considering the number of tutors paid and the number of students who received remediation. The model's performance is evaluated through a series of experimental scenarios, which involve varying student enrollment, grading schemes, and teaching assistant support levels using a dataset of previous course offerings.

Authored by
Mr. Paul Amoruso (University of Central Florida), Ivan Garibay (University of Central Florida), Dr. Joel Alejandro Mejia (University of Cincinnati), Dr. Laurie O Campbell (University of Central Florida), florencio Eloy Hernandez (Texas A&M University - Corpus Christi), and Dr. Ronald F. DeMara P.E. (University of Central Florida)

As generative AI becomes ubiquitous, writers must decide if, when, and how to incorporate generative AI into their writing process. Educators must sort through their role in preparing students to make these decisions in a quickly evolving technological landscape.

We created a writing tool that provides scaffolded use of a large language model as part of a research study on integrating generative AI into an upper division engineering writing and communication course. Drawing on decades of research on integrating digital tools into instruction and writing research, we discuss the framework that drove our initial design considerations.

We then describe data from the iterative design and piloting of our tool and related resources during our first year of implementation. Based on our work with instructors over the past year, we have identified some indications of what is emerging as best practices for both using generative AI productively in academic writing and for integrating generative AI into writing intensive-courses. With respect to writing with AI, a process in which students think first, use "good enough" prompting to initiate their AI interaction, then follow up asserting their own agency by iteratively directing the AI to provide modified output, carefully corroborate and interrogate the AI output for accuracy and bias, and finally reflect on the interaction and future uses of the AI. To create an AI-infused curriculum, we are learning that instructors focus on (and center) student learning objectives before analyzing their course to determine where the AI can appropriately play a role without offloading essential learning activities. Instructors then revise the activities and after enacting the revised curriculum, reflect on student learning to ensure all objectives are met. In some instances, instructors have after reflection decided that they need to reintroduce learning through revised activities. We end with suggestions for those implementing generative AI into other writing-intensive courses and an indication of our future direction.

Authored by
Dr. Tamara Powell Tate (University of California, Irvine), Beth Harnick-Shapiro (University of California, Irvine), Mark Warschauer (University of California, Irvine), and Waverly Tseng (University of California, Irvine)

Quantum science and engineering will play a huge role in the 21st-century STEM workforce, as evidenced by national investments in quantum industries and the many interdisciplinary quantum information science and engineering (QISE) programs that have emerged in recent years. Science and engineering educators can play an important role in researching the best ways to prepare a thriving and diverse quantum workforce. Nuclear magnetic resonance (NMR) is one quantum technology that historically has had a multidisciplinary impact - having garnered five Nobel prizes across physics, chemistry, and medicine - and still serves as a crucial analytic and diagnostic tool in applied science and engineering industries. NMR uses the quantum mechanical properties of atomic nuclei in an external magnetic field to provide information about a sample’s chemical composition and structure. Magnetic resonance is used more broadly for manipulating quantum spins to encode information useful for biomedical imaging or quantum computation. Integrating NMR into the undergraduate science and engineering curriculum would help build the STEM workforce of the future, where a basic understanding of quantum physics will become a necessity in emerging 21st-century technologies.

We have received an NSF-IUSE grant and established an interdisciplinary and cross-institutional team to develop, assess, and disseminate modular lab-based materials that help integrate NMR across the undergraduate science and engineering curriculum. Along with our team’s expertise in research-based science educational pedagogies such as investigative science learning environment, process-oriented guided inquiry learning, and peer-led team learning - our materials also draw from the recent education research findings of the course-based undergraduate research experience model. Over the past three years, these materials have been developed and tested at both Sarah Lawrence College and the City College of New York and reviewed by an advisory board of NMR and science education specialists. Our materials have been designed to: (1) make use of current pedagogical best practices for an engaged and inclusive science learning environment, (2) provide students with class-based undergraduate laboratory experiences that introduce research skills and emulate experimental research in a lab, and (3) be easily adapted and adopted for use in a wide array of educational environments and courses in the science curriculum. We have evaluated these objectives through surveys, focus group interviews with students and instructors, and analysis of video recordings of different classroom implementations of the modules. Our research shows that students using our modules not only successfully master the content, they also: (1) spend over four times as much time sense-making using our modules as in a traditional lecture course, (2) demonstrate positive scientific identity shifts, and (3) make statistically significant gains in learning attitudes about science and self-assessed research skills. We see the integration of these modules into the undergraduate curriculum as a positive step towards the larger goal of expanding the pool of quantum-literate workers needed for the 21st-century STEM workforce.

Authored by
Dr. Merideth Frey (Sarah Lawrence College), Dr. Dedra Demaree (Blue Ridge School), David Gosser (Affiliation unknown), and Colin David Abernethy (Affiliation unknown)

Learning is a lifelong process exercised within and beyond the classroom, and a vital skill in almost all technical professions. Engineers, in particular, are impacted by rapidly evolving technologies and practices that require continuous learning and adaptation long after their training and the initial transition into their professional careers. However, despite the critical role of learning in their academic success and profession, engineering students experience academically rigorous and challenging courses with minimal emphasis or conscious focus on learning strategies that power effective learning.
Often-used learning strategies such as rereading, highlighting, repetition, and memorization are intuitive for many students, yet do not facilitate the higher-order thinking required to solve difficult engineering problems and understand concepts. As a result, weak learning strategies are an important factor in why students often initially struggle in their courses to reach the level of concept mastery and the ability to synthesize, apply, and evaluate problems using engineering principles; and why they may continue to struggle as lifelong learners. The consequences of ineffective learning are already transcending in students’ academic careers: slowing their curricular progress and affecting their ability to adjust to university life, build self-regulatory skills, and gain a sense of control over their learning experiences.
These challenges stem from the fact that the engineering curriculum has traditionally emphasized teaching content and material while assuming that students can manage their own learning. Integrating self-regulated learning skills into the engineering curriculum holds great potential to promote students’ learning skills and growth mindset. The aim of this NSF IUSE-funded project is to develop, implement, and evaluate course-integrated self-regulated learning skills training interventions.
One challenge of such interventions is to have a thorough understanding of how engineering students are learning, and what learning strategies and learning behaviors they most engage with, so we can develop a targeted intervention to promote engagement of effective learning strategies/ behaviors and move away from ineffective learning strategies and behaviors. Although there is a range of literature that developed surveys and empirical studies to understand various components of students’ self-regulated learning skills, such as motivation, learning strategies inventory, metacognition, and growth mindset, there is no single survey and study that covers all these aspects. In addition, the majority of the empirical studies about learning strategies' utility were conducted in psychology, math, physics, and biology classes, with limited data on engineering students. Thus, as the first step of our project, we developed a complete set of survey questions to understand all three dimensions of students’ self-regulated learning (growth mindset, cognitive strategies, metacognition), with some questions adapted from existing validated surveys, and some newly developed questions. Using the convenience sampling method, in a pilot study, the surveys were sent to 831 engineering students in five mechanical and electrical engineering courses, which were taught by the four instructors who are NSF project team members. In this paper, we demonstrate the survey results with a general descriptive analysis for the general students' sample, as well as for various demographics groups, such as gender, first-generation college students, transfer students, and other underrepresented groups.

Authored by
Dr. Huihui Qi (University of California, San Diego), Celeste Pilegard (University of California, San Diego), Dr. Minju Kim (University of California, San Diego), Dr. Saharnaz Baghdadchi (University of California, San Diego), Prof. Curt Schurgers (University of California, San Diego), Dr. Alex M. Phan (University of California, San Diego), and Dr. Marko Lubarda (University of California, San Diego)

The University of X's Freshman Year Innovator Experience (FYIE) program, hosted at a Minority Serving Institution (MSI), seeks to improve the first-year experience for new students by nurturing essential academic success skills. Specifically tailored to freshman mechanical engineering students, the program aims to equip them with self-transformation skills to navigate through the amplified academic and professional obstacles brought about by the COVID-19 pandemic. Participants of FYIE engage in two concurrent courses: Introduction to Engineering (Course A) and Learning Frameworks (Course B). In Course A, students undertake a 6-week engineering design project, while in Course B, they work on a 6-week academic career path project. Throughout these simultaneous projects, time-bound interventions highlight the similarities between the engineering design process and the academic career pathways project. The main goal is for students to recognize that the design thinking skills acquired in the engineering design process can be applied to resolve their academic career challenges. The FYIE program was initiated as a pilot in the spring semester of 2023, with instructors from Course A and B introducing the parallel projects. The implementation has continued through the fall 2023, spring 2024, and ongoing fall 2024 semesters, introducing improvements at every iteration, with adjustments made to the parallel projects and the identification of intervention points for self-transformation through analogy. The creators of the program will present the outcomes from the pilot implementations and address the obstacles and future work. This proposed endeavor is aligned with the continuous mission of the College of Engineering and Computer Science (CECS) at the University of X, which includes: 1) increasing the number of STEM degrees granted to Hispanics, 2) promoting the participation of women in STEM-related fields, and 3) enhancing persistence and self-confidence in STEM fields amidst the challenges posed by COVID-19. The project is supported by the NSF award 2225247.

Authored by
Dr. Noe Vargas Hernandez (The University of Texas Rio Grande Valley), Dr. Javier A. Ortega (Affiliation unknown), Dr. Arturo A Fuentes (The University of Texas Rio Grande Valley), Dr. Eleazar Marquez (The University of Texas Rio Grande Valley), and Dr. Pierre Lu (The University of Texas Rio Grande Valley)

This NSF-funded Division of Undergraduate Education (DUE) Improving Undergraduate STEM Education (IUSE) project aims to integrate sociotechnical issues into Introduction to Circuits, typically the first course in electrical engineering (EE) for undergraduate students. To prepare graduates for the real-world problems, which are interdisciplinary and involve complex social impacts, instructors must help students address the sociotechnical nature of engineering. However, many engineering instructors are unsure how to do this. In this project, we aim to make it easier for them by developing sociotechnical modules with detailed teaching guides for the Introduction to Circuits course, each connecting fundamental circuits topics to larger social issues. In year 2, we implemented our first two modules at different institutions, developed and administered a survey assessing students’ perceptions about sociotechnical issues in engineering, recruited and facilitated a cohort of graduate students from across the USA to develop more modules, and presented our work at several international venues.

Authored by
Dr. Susan M Lord (University of San Diego) and Dr. Cynthia J. Finelli (University of Michigan)

The National Science Foundation (NSF) award (2206952) establishes a new Research Experiences for Teachers (RET) site, enhancing their knowledge and skills in advanced manufacturing/robotics at Bowling Green State University (BGSU). The primary objective of this project is to play a transformational role in preparing future leaders in advanced manufacturing by instilling advanced manufacturing/robotics research experience within STEM educators through six-week summer workshops dedicated to hands-on research projects/experiences. In these workshops, participants engaged with highly qualified researchers using cutting edge robotics technology and augmented by industry access. The research projects focused on contemporary advanced manufacturing topics including modern sensors and actuators, advanced robot programming, CNC programming, CAD/CAM, 3D printing, and e-factory. At the end, participating educators translated their research experiences and knowledge into classroom practice. As part of this research experience, participating educators developed working robots/models, instructional modules, and course materials that they used in their classrooms and share with other educators at their institutions.
The project cements the partnership among BGSU, local high schools, and community colleges to address the common need of producing STEM graduates in advanced manufacturing area. BGSU RET site provided research experience to 28 regional high school and community college educators during 2023-2024. During the 6-week summer workshops, these 28 educators conducted advanced manufacturing research at BGSU eFactory lab and developed curriculum modules for their students. After completion of the summer workshop, many of these educators implemented their curriculum modules at their respective institutions. They will continue to implement these modules in the future and create a sustained wave of awareness among future students in the U.S. manufacturing heartland.

Authored by
Dr. Md B. Sarder (Bowling Green State University)

This paper examines the impact of a National Science Foundation Scholarships in Science, Technology, Engineering, and Mathematics (NSF S-STEM) Program at a large, Minority-Serving institution in the western U.S. Despite growing efforts to diversify STEM fields, underrepresented minority (URM) students continue to face significant challenges in persistence and success. This scholarship program addresses these challenges by providing financial support, faculty and peer mentorship, and skills development opportunities to academically talented and low-income URM STEM students. This study evaluates how participation in the program enhances key noncognitive skills, such as students' sense of belonging, leadership and collaboration skills, and science identity, which are critical to STEM persistence. Using both survey and university-based data among the 47 participating scholars, results reveal that program participants report strong levels of sense of belonging, high efficacy in leadership and collaboration skills, and strong science/math identities. Additionally, compared to university rates, scholarship students showed above-average retention and graduation rates, with the majority pursuing graduate studies or careers in STEM. These findings highlight the importance of comprehensive support programs that integrate financial aid, mentorship, and professional development to promote persistence and success among URM students in STEM fields.

Authored by
Dr. Jen-Mei Chang (California State University, Long Beach), Dr. Jelena Trajkovic (California State University Long Beach), and Dr. Gino Galvez (California State University, Long Beach)

Design thinking in scientific modeling emphasizes creativity, collaboration, and iteration, making it highly beneficial in education. It encourages deep engagement with scientific concepts, enhancing critical thinking and problem-solving skills. As Inkinen et al. (2020) noted, model development is a fundamental scientific practice that aids students in understanding complex phenomena by providing explanations and facilitating predictions about the natural world. This approach fosters an active learning environment where abstract concepts become more accessible (Citrohn & Svensson, 2020).

The iterative nature of design thinking allows for continuous refinement of models through feedback and evaluation. Mentzer et al. (2015) highlight that models can be visual, graphical, or mathematical, essential in engineering design processes. This flexibility helps students explore multiple solutions, deepening their understanding of scientific principles. Emphasizing feasibility and evaluation encourages students to assess their models critically, ensuring they are both theoretically sound and practically applicable.

Incorporating design thinking into science education enhances students' epistemic knowledge, which is their understanding of the nature and justification of scientific knowledge. Lee (2023) explains that experimentation and model development help students navigate scientific inquiry complexities, such as hypothesis formulation and data analysis. This process is vital for cultivating scientific literacy, empowering students to construct evidence-based arguments, and engaging in meaningful discussions. Argumentation within this framework enriches learning as students articulate reasoning and critique peers' models.

Research indicates that model-building demands critical thinking and creativity. Dauer et al. (2013) emphasize the need for genuine motivation beyond compliance with school tasks, suggesting modeling should connect molecular phenomena to broader concepts, reflecting students' understanding of scientific principles.

Selecting appropriate representations is crucial for effectively communicating scientific ideas. Peterson et al. (2021) discuss cognitive image functions that enhance comprehension through visual displays. Understanding these functions helps students articulate invisible aspects of phenomena, enriching explanations. Park et al.'s (2021) findings show that collaborative drawing activities facilitate the negotiation and refinement of visual representations.

The cognitive demands of modeling are significant as students navigate complex content and representation design. Minkley et al. (2018) note that developing representations simplify natural phenomena's complexity, requiring identifying relevant aspects and relationships akin to a design process considering functionality.

Teachers play a crucial role in supporting modeling practices. Baumfalk et al. (2018) stress the importance of creating environments for effective model construction and utilization, guiding students through iterative processes where they refine models based on feedback and evidence. Such support is essential for developing skills necessary for modeling as a practice rather than a task.

The project with preservice science teachers explored how they design models to explain phenomena. Pedagogical tools were developed to scaffold this process, with groups presenting models using meta-representations to explain occurrences while peer feedback enhanced feedback skills. Key findings included shifts in designs based on evidence or feedback across iterations, variations in initial designs, and an initial focus on objects rather than invisible components.

Authored by
Dr. Jaclyn K. Murray (Mercer University) and Alex St Louis (Mercer University)

The National Science Foundation (NSF) Research Experiences for Teachers (RET) program supports summer research experiences for K-14 educators to enhance their scientific disciplinary knowledge in engineering or computer science and translate their research experiences into classroom activities and curricula to broaden their students’ awareness of engineering education and career pathways.

In 2024 an RET site (funded by the NSF) launched at the University of Alabama with a common theme of technologies and applications of sensing systems for physiological and environmental monitoring. This theme was selected because knowledge of how to measure physical quantities of materials, devices, tissues, and the environment is critical to answering research questions across all engineering domains. This then leads to a strong alignment of projects with national and state goals of integrating engineering design and engineering design practices within the context of science content creation.

In the first iteration of our RET, 11 science and math teachers from middle schools in west Alabama participated in research and professional development workshops over 7-weeks. During each week teachers engaged in structured engineering, sensors/programming, and education/curriculum workshops in addition to their faculty directed research. The engineering workshops highlighted the different disciplines and career-paths across engineering and computer science. The sensors/programming workshops guided teachers through using the Arduino Uno platform to measure physical quantities (light, temperature, humidity, sound, and acceleration). The education/curriculum workshop guided teachers through linking their research to education standards and exploring resources available to help teach engineering content in their classrooms. At the end of the 7-weeks the program culminated in a poster symposium with teachers presenting the results of their research to faculty, engineering students, and other professionals on campus.

Based on focus group feedback collected at the end of the program, teachers enjoyed the challenge of learning to do a research project and learned skills they could bring into their classrooms to increase student engagement. However, they noted that more support during the summer to help them develop their curriculum would be useful and help them transition their research to their classrooms. This work will outline the lessons learned from running our site and workshops during Year 1 and outline the planned revisions for Year 2 to address teachers focus group feedback to improve their research experiences and transitioning their work to their classrooms. These lessons and details are expected to support other engineering educators who are planning to launch a RET site or are interesting in possible revisions for an existing site.

Authored by
Dr. Todd Freeborn (The University of Alabama), Erika Machan Steele (The University of Alabama), and Chris Smith Crawford (The University of Alabama)

This poster highlights the establishment of a Research Experiences for Undergraduates (REU) site at the University of South Alabama, dedicated to tackling the growing issue of microplastics in the Gulf Coast region through an interdisciplinary and hands-on approach. The primary objective of the program is to cultivate a positive and proactive mindset among undergraduate students regarding the detection, measurement, and remediation of microplastics, while simultaneously instilling sustainable engineering practices. The program aims to recruit 30 undergraduate students for a 10-week immersive experience at the University of South Alabama, where they will engage in collaborative research and experiential learning focused on microplastics. The intellectual framework of the program encompasses five key thrusts: (1) Understanding the degradation of plastics into microplastics and their impact on ecosystems, (2) Developing novel detection and measurement techniques for microplastics in various environmental contexts, (3) Designing and testing filters to mitigate microplastics in waterways, (4) Establishing systems to monitor microplastic pollution over time, and (5) Repurposing collected microplastics for alternative applications. Through this comprehensive approach, students will gain both fundamental research skills and practical experience, while working in teams to address real-world environmental challenges. In addition to research activities, the program emphasizes the development of essential skills such as ethics and responsible conduct in research, data collection and analysis, critical thinking, technical writing, and teamwork. Mentorship from faculty and peers will be central to the students’ growth, fostering frequent interactions that encourage creativity and innovation. The ultimate goal is to transform undergraduate students from passive learners into independent, collaborative researchers equipped to tackle complex environmental problems, with a focus on sustainable solutions for the future.

Authored by
Dr. Shenghua Wu (University of South Alabama), Prof. Jinhui Wang (University of South Alabama), and Melike Dizbay-Onat (University of South Alabama)

First offered in the summer of 2006, the NSF-funded AERIM Research Experience for Undergraduates (REU) program has now gone through four full 3-year funding cycles and has been offered a total of 12 different summers, with 1-2 year breaks in between. The focus of this REU program has long been on automotive and energy research, with strong ties to the automotive industry in Southeastern Michigan. A total of 122 students from 83 different colleges and universities have taken part in the program and have now progressed to different points of their academic and professional paths. One of the greatest successes of this REU has been its ability to attract a diverse group of undergraduate researchers, with groups historically underrepresented in engineering (particularly women) representing over two-thirds of the participants. The program is assessed each year using pre- and post-surveys, as well as focus group discussions in the past 3 years. The assessment and follow-up has also included periodic emails and surveys to gauge the outcomes of the program several years after students have completed the REU. Maintaining contact and tracking the career progressions of students after several years is no easy task, but one that has been made easier with the advent of professional social networking sites, such as LinkedIn. The goal of this paper is to report on some of the demographics and outcomes of this REU, as well as share some of the lessons learned, particularly since the advent of COVID-19.

Authored by
Dr. Laila Guessous (Oakland University) and Dan DelVescovo (Oakland University)

Abstract
In alignment with the mission of the National Science Foundation to advance scientific progress, enhance national health, prosperity, and welfare, and strengthen national defense, this Research Experiences for Undergraduates (REU) Site in Computational Sciences and Engineering provides a diverse group of students with exposure to various challenges in the field. Participants engage in solving these challenges through the application of methodologies derived from cybersecurity, data analytics, machine learning, process automation, structural engineering, and data-driven safety management. The program offers students direct, hands-on research experience that addresses significant societal issues. Such practical involvement not only enhances students' scientific problem-solving capabilities but also fosters an understanding of the scientific method as a tool for investigating technical challenges. Furthermore, this application of theory to real-world problems is instrumental in solidifying students' interest in STEM fields, which is crucial for improving retention and graduation rates at minority-serving institutions and providing upward mobility for students from underrepresented communities. Through comprehensive research activities, year-long faculty mentoring, and continued engagement via research presentations and publications, the program aims to significantly increase minority students' interest in STEM education. The opportunities provided through this initiative serve as foundational steps in cultivating undergraduate students into proficient scientists and researchers.

This paper presents a summary of the experiences and lessons learned from establishing the REU site, including the development of a dedicated website for promotion, student recruitment strategies, and the implementation of research and extracurricular activities. Additionally, it includes reflections on student projects and feedback. The insights gained from this initiative can serve as valuable guidance for similar future programs designed to engage students in undergraduate research.

Authored by
Dr. Vassilios Tzouanas (University of Houston-Downtown), Dr. Henry Clyde Foust (University of Houston - Downtown), Dvijesh J Shastri (University of Houston - Downtown), Emre Yilmaz (Affiliation unknown), and Mahmud Hasan (University of Houston - Downtown)

In Fall 2022, the Vertically Integrated Projects (VIP) learning model was launched at University of X (UofX), a public urban research university in the southeastern United States. Supported by an IUSE grant, this program is now in its third year, with 6 teams comprising 29 undergraduate participants. The VIP model involves active learning on faculty-led, team-based projects. Team members include first-year students through graduate students with one to three or more semesters of participating in VIP. The VIP model enables tiered mentoring, from faculty to graduate students, graduate students to undergraduates, and more senior to newer students [1]. The goals of UofX’s VIP program are to: (1) help build a more inclusive research culture; and (2) help students build STEM identity, as well as self-efficacy, mindset, and intentions to stay in engineering. The first goal was based on research about the positive impact of active learning and mentoring for recruiting and retaining women and other historically excluded groups in STEM [2]. The second goal builds on previous work on mentoring and community building on STEM Identity, while extending that work to related variables [3, 4]. The purpose of this paper is to report on the evaluation of the VIP program at UofX after two years.

This paper comprises three parts. In the first, we will discuss the challenges and opportunities in implementing the VIP model at the UofX from the perspective of the PIs. This section will focus on issues involving recruiting faculty mentors and recruiting and retaining diverse undergraduates into the VIP program. In the second, we will report results from focus groups conducted in the second year of the program with undergraduates, graduate student mentors, and faculty team leaders. This section will focus on motivations for joining VIP, perceived strengths and weaknesses of the program, and suggestions for improving the program. In the third, we will summarize our research findings to date and discuss issues related to conducting research in this context and how we have adapted some of our research strategies in response to certain challenges. We conclude with lessons learned as well as directions for moving forward.

References

[1] “The VIP model.” VIP Consortium. https://www.vip-consortium.org/content/vip-model (accessed Jan. 26, 2024).
[2] National Academies of Sciences, Engineering, and Medicine, Promising Practices for Addressing the Underrepresentation of Women in Science, Engineering, and Medicine: Opening Doors, Washington D.C., USA: The National Academies Press, 2020.
[3] S. Ivey and S. Parish, "Cultivating STEM Identity through the Peer Mentoring Relationship," in Navigating the Peer Mentoring Relationship: A Handbook for Women and Other Underrepresented Populations in STEM, K. Wade-James, A. Rockinson-Szapkiw, J. Wendt, Dubuque, IA, USA: Kendall Hunt, 2020, p. 316.
[4] C. O. Stewart, J. T. Campbell, T. Chase, M. Darbeheshti, K. Goodman, S. Hashemikamangar, M. Howland Cummings, S. S. Ivey, D. J. Russomanno & G. E. Simon, “Communicating Identity in the Urban STEM Collaboratory: Toward a Communication Theory of STEM identities,” International Journal of Science Education, Part B, vol. 13, no. 4, pp. 345-361, Oct. 2023, doi: 10.1080/21548455.2023.2179380.

Authored by
Craig O. Stewart (University of Memphis), Dr. Chrysanthe Preza (The University of Memphis), and Dr. Stephanie S Ivey (The University of Memphis)

Purdue University established Freshman Engineering (now known as First-Year Engineering) in 1953, the first program in the U.S. to do so. Over the years, First-Year Engineering (FYE) programs have been established at several institutions, but not all, across the country. In the early 1990s, the National Science Foundation (NSF) provided funding for what were called the Engineering Education Coalitions. They funded a total of eight coalitions that involved more than 40 institutions of higher education over the period from 1990-2005. In addition, NSF created the Action Agenda program in the late 1990s aimed at individual institutions that wanted to adapt and adopt the findings from the existing Coalitions. A strong focus of the Coalitions was on introductory engineering courses, with the rationale that engineering was losing too many students through attrition, and we needed to pay more attention to the formative years. Nearly every Coalition created some version of an FYE program through this funding mechanism. The number of FYE programs across the nation has increased dramatically based on these investments, largely in response to curricular efforts aimed at retaining engineering students by providing them with meaningful career-oriented experiences early in their college educations.

Many of these first-year programs were called “common first-year engineering programs,” meaning that all students enrolled in the same courses at the same time. It is a one-size-fits-all, cookie-cutter approach to education. Despite the laudable goals espoused by most FYE programs, there has been an unintended consequence: curricular rigidity and inflexibility. Thus, students have little agency to shape their own pathway toward an engineering degree. Recently, a midwestern R1 institution obtained a grant from the NSF to develop the next generation of first-year programs: FYE2.0. The program we envision will provide students with essential skills, while at the same time providing them with opportunities for customization and flexibility in charting their own engineering journey. This paper outlines the logistical progress made in implementing FYE2.0 to date and discusses plans for the future.

Authored by
Dr. Sheryl A. Sorby (University of Cincinnati), Dr. Muhammad Asghar P.E. (University of Cincinnati), Dr. Gregory Warren Bucks (University of Cincinnati), Jeremy Michael Olivar Hill (University of Cincinnati), Dr. Jeff Kastner (University of Cincinnati), Prof. Teri J Murphy (University of Cincinnati), and Dr. David Reeping (University of Cincinnati)

Background
Soft robotics is a novel and emerging field of robotics. Unlike traditional robot mechanics, soft robotics uses flexible, compliant materials instead of rigid parts and linkages. This soft aspect of the robots has led to their increasing use in organic applications such as biomimicry, orthotic devices, and surgical robots. This field has seen rapid growth recently, which is only projected to continue as the field expands into new engineering settings. However, this rapid growth has led to a lack of up-to-date, accessible educational material surrounding soft robotics.

Overview
Our project, funded by the National Science Foundation Improving Undergraduate STEM Education program, takes place in the context of a modified version of capstone design experiences called engineering clinics at our institution. Clinics are offered to third- and fourth-year students, where they engage in multi-disciplinary, team-based projects in collaboration with faculty. In the soft robotics clinic, students are tasked with identifying and designing new soft robotics prototypes, developing modules that support student learning in connection with their prototypes, and sharing these results on a public-facing, freely accessible website. As students design the prototypes and modules, they work with faculty to identify courses or outreach programs where the modules could be implemented with the long-term goal of the project being an implementation of the learning modules in multiple courses and programs at our institution. In this manner, the project has the potential to impact the learning and interest in soft robotics of both the students designing the modules and the students participating in the modules once they are developed. By having projects made by students, for students, our goal is to benefit both through soft robotics. At the end of each semester, student module designers are asked to self-report their growth in soft robotics learning and interest and reflect on their experience in the clinic. Students participating as learners are also asked to respond to a post-module survey to gauge their learning and soft robotics interest in relation to their module participation.

Results
We have previously reported on the learning outcomes of students in the first semester of the clinic project. This project has since continued, engaging students in another two semesters of project work (Spring 2024 and Fall 2024) as well as summer work for two students (Summer 2024). The results of this paper will focus on the continued observation of learning patterns that emerged in the first semester of the project as well as new patterns that were noted. The effects on student growth from factors that differed in each subsequent semester will also be analyzed. This includes placing a greater emphasis on understanding the potential applications of projects in our engineering curriculum, changing team sizes, as well as other factors.

Conclusion
This work offers valuable insights into the continuation of a novel initiative to involve students in the design of educational modules and encapsulates the results of those modules being implemented.

Authored by
Joseph Richard Midiri (Rowan University), Dr. Cassandra Sue Ellen Jamison (Rowan University), Dr. Smitesh Bakrania (Rowan University), Prof. Wei Xue (Rowan University), and Dr. Mitja Trkov (Rowan University)

The NSF Research Experiences for Teachers (RET) Site in Manufacturing Simulation and Automation has recently completed its third year, continuing its mission to enhance STEM education for high school teachers and community college faculty. Hosted by the University of Louisville, the RET program offers an immersive, six-week research experience that equips educators with the latest advancements in manufacturing technology and pedagogical strategies. During this transformative program, participants engage in hands-on research projects focused on manufacturing simulation, automation, and integration of digital twins into manufacturing processes. Educators work in state-of-the-art laboratories alongside faculty and students, gaining practical insights into modern manufacturing practices and emerging technologies. Through collaborative workshops and interactive sessions, participants develop innovative curriculum modules that bridge the gap between theoretical knowledge and real-world applications, which enables them to effectively teach these concepts in their classrooms. The RET Site also features plant tours and guest lectures to provide educators with a comprehensive understanding of the manufacturing landscape and the skills needed for today’s workforce. As a result of their experiences, educators return to their institutions equipped with new teaching resources and a deeper understanding of the manufacturing industry, which results in a greater interest in STEM careers among their students. This program has made significant contributions to enhancing STEM engagement, building a robust educational pipeline, and strengthening the connection between academia and industry, ultimately preparing the next generation of innovators in advanced manufacturing.

Authored by
Dr. Faisal Aqlan (University of Louisville)

This paper highlights a key approach, specifically developing and adopting a comprehensive strategic plan, that was taken to support curriculum innovations and enable cultural change. Over the past four years, the School of Civil and Environmental Engineering at the Georgia Institute of Technology has worked systematically to change the undergraduate civil engineering and environmental engineering programs. The goals were to enhance early engagement in the major, strengthen professional identity development, improve retention in the program, and enhance engineering efficacy and professional skills development. A key feature of the process included adopting and institutionalizing these goals in the School’s strategic plan. The strategic plan was developed over an 18-month period and included engagement of numerous stakeholders, including faculty, students, staff, advisory boards, alumni, and industry partners. Throughout the planning process, the School aimed for a balance of alignment with the College and Institute’s strategic directions, and charting a unique path forward germane to the disciplinary and professional contexts within Civil and Environmental Engineering. The final plan encompasses three umbrella areas: Community, Student Experience, and Discovery & Service with themes, objectives, and initiatives in each area. The initiatives under the area of Student Experience are strongly aligned with the objectives of the NSF-funded Revolutionizing Engineering Departments (RED) grant, as well as a Kern Entrepreneurial Engineering Network (KEEN) grant from the Kern Family Foundation. These initiatives include developing new courses, adopting a new curriculum, and deploying innovative pedagogy to support the program goals listed above. In addition, initiatives in the area of Community target the associated cultural changes, including incentivizing professional development, enhancing inclusiveness, and improving the sense of belonging. The effect of integrating these initiatives in the comprehensive strategic plan was to gain wide “buy-in” from faculty and staff and to effectively formalize the program goals into the shared vision for the future of the School.

Authored by
Dr. Donald R. Webster (Georgia Institute of Technology), Dr. Adjo A Amekudzi-Kennedy (Georgia Institute of Technology), and Dr. Robert Benjamin Simon (Georgia Institute of Technology)

South Dakota Mines (SDM), a STEM-focused campus, is uniquely situated at the foothills of the Black Hills. The region is geologically rich with its abundant clays and shales. Within a ~50 mile radius one finds urban, forest, ranching and tribal lands. Consequently, the local high school student population is equally diverse, with a relatively high percentage of first-generation college, rural and Native American (Lakota) students. Douglas High School has a student population that represents this diversity. In this regard, SDM hosted a high school STEM teacher from Douglas High School through a NASA Research Experience for Teachers as part of a research internship. The teacher conducted research on ceramic glaze formulations using 100% local materials from the Black Hills. The teacher also successfully modified the formulations of local minerals to develop a ceramic coating (glaze) and will translate this understanding to her high school Chemistry classes. The translation will cover kinesthetic topics that include utilizing the potter’s wheel, kilns, and the Scanning Electron Microscope at SDM. Finally, the research findings, and translation to the curriculum will be mapped to meet the SD Department of Education Standards.

Authored by
Dr. Katrina Donovan (South Dakota School of Mines and Technology) and Dr. Jon J Kellar (South Dakota School of Mines and Technology)

Research experiences for undergraduates (REUs) are crucial in shaping academic and professional development. Engaging in research allows students to apply theoretical knowledge to real-world problems, fostering critical thinking, problem-solving, and analytical skills. Moreover, students benefit in many ways by living in the university dorms for 10 weeks, exploring a new university town, making new friends, and taking on new life experiences.

The purpose of this NSF Grantees Poster is to provide a holistic overview of undergraduate student researcher perceptions related to participating in an NSF REU Site program, titled “NSF REU Site: Growing Entrepreneurially-Minded Undergraduate Researchers with New Product Development in Applied Energy.” This REU integrated the strengths of academic applied research, including a solid theoretical foundation and rigorous scholarship, with key business practices such as real-world customer discovery and the creation of viable business models. The intention of the REU was to equip students with an entrepreneurial mindset, expanding their research toolbox and skillset.

At the end of the 10-week REU program, participants completed a final reflection responding to the following questions:
1. Entrepreneurial Mindset: The entrepreneurial mindset is defined as “the inclination to discover, evaluate, and exploit opportunities.” What are the 3 most important things you learned about an entrepreneurial mindset (or entrepreneurship) by participating in the REU program?
2. Research Skills: Identify the top three research skills gained while participating in the REU program.
3. Advisor Research Lab: What did you like about working with your advisor? What opportunities for improvement can you recommend?
4. Connect to Real World: What skills did you learn that are important for engineers conducting research in the real world? Please consider both professional skills (e.g., communication, collaboration, etc…) and context specific skills (e.g., topic area).

Thematic analysis was conducted on the reflections using NVivo. Findings and lessons learned are provided.

Authored by
Dr. Lisa Bosman (Purdue University) and Rhea Dutta (Affiliation unknown)

This brief summarizes the first two years of participants’ data from a National Science Foundation (NSF) Research Experiences for Teachers (RET) project on Chip Design (Chip-RET). Semiconductor workforce development has become a national priority due to microchips’ importance to our supply chain security, national defense, and technological leadership. K-14 teachers play a pivotal role in exciting, motivating, and preparing students to join various microelectronics-related career pathways. To meet such requirements, K-14 STEM teachers need to receive the necessary training on the subject matter. Our institution proposed the Chip-RET, the first RET program in the US that focused exclusively on integrated circuit design and K-14 semiconductor education. To evaluate the effectiveness of such training, we further developed a custom semiconductor knowledge and literacy test (SKLT), whose content and interpretation have been validated by semiconductor industry experts.
Our data reveals that the Year One cohort of ten teachers demonstrated an increase in their mean percentage of correct responses to the SKLT test, from 39% to 65% pre- and post-RET. A follow-up Wilcoxon Rank-Sum Test underscored the significance of this difference, with a W-value of 3 and a p-value less than 0.001. Moreover, a repeat measure of the SKLT test nine months after the Chip-RET training (post-9 months) showed a mean percentage of correct response of 55%, suggesting that participants were able to retain much of their knowledge gained nearly one year after the training. A Wilcoxon Rank-Sum Test from pre- to post-9 months showed a W-value of 12 and a p-value of 0.007, further confirming the gain despite some loss of knowledge over the nine-month period.
Finally, the Year Two cohort of another ten teachers also showed an increase from 48% to 69% pre- and post-RET. The post-9 months data is not yet available and will be collected.

Authored by
Haniye Mehraban (Oklahoma State University), Dr. Jennifer Dawn Cribbs (Oklahoma State University), Erin Dyke (Oklahoma State University), Dr. James Stine (Oklahoma State University), and Dr. John Hu (Oklahoma State University)

Experiential learning fosters engagement, deepens understanding, and enhances practical problem-solving skills in STEM education (Beier, 2019; Kolb, 1984; NAE, 2005). The [PROJECT] at [INSTITUTION] creates data science learning opportunities for undergraduates with diverse academic backgrounds and exposes them to the practical applications of data science within interdisciplinary contexts. Unlike traditional data science academic programs for students already interested in the field, [PROJECT] seeks to train a future workforce where data science skills are needed as a core attribute of most career paths. Two interventions created for students include 1) data science modules developed for and deployed in introductory STEM and social science courses, and 2) experiential learning opportunities in data science through internal and external internships that allow students to apply data science concepts to real-world projects.

This paper focuses on the latter component of the project. We use a qualitative case study approach to explore the personal and professional growth of four students—each serving in distinct roles during their internship. Through our analysis, we identify key themes related to personal and academic growth. Key findings include the significant enhancement of the interns’ abilities in teamwork, organizational skills, and leadership, as well as a marked increase in confidence in data analytics and data visualization. For example, interns who initially had moderate confidence in data-related work reported substantial improvement by the program's end, with their career goals in data science becoming clearer. Interns also highlight the program's effectiveness in providing networking opportunities and a sense of community, which were instrumental in shaping their professional development.

The program’s approach to integrating data science into broader fields demonstrates its potential as a model for interdisciplinary education. Experiential learning opportunities bridge the gap between theoretical knowledge and practical application. The research highlights the importance of such initiatives in fostering comprehensive skill development and confidence in STEM students and equips students—regardless of their primary discipline— with the skills needed for the modern workforce. This research is supported by the NSF IUSE program under [GRANT NUMBER].

References

Kolb, D. A. (1984). Experiential learning: Experience as the source of learning and development. Englewood Cliffs, NJ: Prentice Hall.

National Academy of Engineering. (2005). Educating the Engineer of 2020: Adapting Engineering Education to the New Century. Washington, DC: The National Academies Press. https://doi.org/10.17226/11338.

Beier M.E., Kim M.H., Saterbak A., Leautaud V., Bishnoi S., & Gilberto J.M. (2019). The effect of authentic project-based learning on attitudes and career aspirations in STEM. Journal of Research in Science Teaching. 56 (1), 3–23. https://doi.org/10.1002/tea.21465

Authored by
Prof. Petra Bonfert-Taylor (Dartmouth College), Dr. Laura E. Ray (Dartmouth College), and Scott Pauls (Dartmouth College)

We are facing a wide range of grand challenges across the world, such as the continuous increase of energy demand, more frequent extreme weather disasters, and uncertainties associated with climate change. Wind energy, an affordable renewable resource—achieving costs as low as $0.04 per kilowatt-hour in a growing number of regions (Gielen et al., 2019; Wiser et al., 2008)—holds great potential to meet rising energy demands, mitigate the causes of climate change, and contribute to a cleaner, sustainable, and domestic energy generation portfolio. To fully realize the potential of wind energy, we must address research challenges arising from the complex, coupled phenomena that span spatial and temporal scales relevant to both wind energy and the broader power system. This necessitates a diverse, talented pool of future scientists and engineers in wind energy research and industries to tackle these issues. Despite the national and global demand for wind energy research and development (Veers et al., 2019), many undergraduate students of non-R1 universities lack opportunities to participate in active wind energy research. To tap the nation’s diverse student talent pool and broaden participation in science and engineering, there is a critical need to provide these students access to wind energy research early in their career and motivate them to pursue graduate education or research-oriented jobs in the wind energy sector.

The Great Lakes Wind Energy Challenges (GLWind) REU site funded by the NSF Division of Engineering Education and Centers (EEC), co-hosted by CSU and CWRU in Cleveland, Ohio, has supported nine undergraduate students in a ten-week intensive summer research program during 2023 and 2024 (Years 1 and 2). The REU student cohort actively engaged in ongoing wind energy research within existing learning and research communities at CSU and CWRU. They attended weekly seminars on the latest wind energy research and professional development, visited utility-scale wind turbines on the CWRU campus, and presented their research posters at the Summer Intersection Symposium and professional conferences beyond the program. REU students had enjoyed the rich diverse culture and historical landmarks of Cleveland. Annual program evaluations via surveys and focus group interviews were carried out to inform PIs and faculty about potential improvements and ensure continuous program enhancement. The GLWind REU program focused on recruiting women, underrepresented minorities, and students from community colleges, liberal arts colleges, and non-R1 universities without established research programs in engineering. In the summer 2023, 56% of participants were from non-R1 universities, and 67% belonged to underrepresented minority groups (UMG) in STEM. In the summer 2024, 67% of participants were from non-R1 universities, and 44% were UMG. The educational outcome aims at a diverse group of talented US students who are motivated and prepared to apply the research and communication skills developed in the REU program to succeed in broader STEM fields, and a structured, personalized mentoring mechanism for undergraduate students that will be disseminated to a larger engineering community via the ASEE conference.

Authored by
Dr. Wei Zhang (Texas Tech University) and Prof. Xiong Yu (Affiliation unknown)

This paper describes the experiences and outcomes of undergraduates enrolled in the new Women in Science & Engineering (WISE) Honors’ curriculum, supported by NSF DUE #2012339. Employers consistently rate communication skills and teamwork as critical in the candidate selection process (NACE, 2023) and look for problem solving skills and group projects on resumes (Grey, 2024). To address these needs, we focus on two courses designed to prepare future leaders of the STEM workforce: Service Learning in STEM and Women’s Leadership in STEM. These courses were developed through a unique partnership involving the WISE Program (academic affairs), and Career Center (student affairs), that connects students with real world projects through the Career Center’s community partnerships, and with industry leaders through the Industry Connections Program. Class sizes are small, with 20-35 students per section, to ensure that students have every opportunity to have a voice in class, and be open about their overall experience as women in STEM. Research has shown that such [science] meritocracy myths cause declines in self-esteem, increases in dropout rates, and substantial psycho-logical costs, such as self-blame and imposter syndrome” (Graves et al., 2022, p.5).

In addition to continuous feedback loops in classes, formal assessment was collected through course surveys and focus groups each semester, leading to adjustments to course readings, assignments, and in-class activities. Being in the fourth year of the program, we have integrated lessons learned from the students’ experiences and honed two highly valued courses which provide: active engagement with content, solutions-oriented class discussions, practice having difficult conversations, vision board design, connections to industry and alumni mentors, deconstruction of their experiences working with community partners and/or student organization leadership roles, and significant self reflection. Strategies to overcome discriminatory or biased behavior, a framework for having difficult conversations, language to help them articulate their leadership vision, philosophy, and skills, and a support network of peers and alumni mentors from industry equips students with the skills and confidence they need to thrive in their future career as STEM leaders.

A limitation of the project is the challenge of gathering post-graduate outcomes. To address this, long-term plans include implementation of more targeted alumni outreach strategies, maintenance of updated contact information, leveraging social media, and collaborations with alumni career services. We will also explore existing partnerships with industry and use surveys to collect long-term career data from alumni.

References:

Georgetown University Center on Education and the Workforce, Workplace basics: The competencies employers want, 2020. https://cew.georgetown.edu/cew-reports/competencies/

Graves Jr, J. L., Kearney, M., Barabino, G., & Malcom, S. (2022). Inequality in science and the case for a new agenda. Proceedings of the National Academy of Sciences, 119(10), e2117831119.

Gray, K. (2024, January 16). The key attributes employers are looking for on graduates’ resumes.
https://www.naceweb.org/talent-acquisition/candidate-selection/the-key-attributes-employers-are-looking-for-on-graduates-resumes#:~:text=Beyond%20these%20attributes%2C%20it%20is,candidates%20for%20a%20job%20opening.

NACE (2023, November). Job Outlook. Bethlehem, PA.

Authored by
Dr. Marianna Savoca (Stony Brook University), Dr. Monica Bugallo (Stony Brook University), Diana Voss (Stony Brook University), and Urszula Zalewski (Stony Brook University)

The goal of this project is to ensure the next generation of Civil and Environmental (CE) engineers are prepared to design, build, operate, monitor, and maintain the vast and complex civil infrastructure systems required for a sustainable & resilient society in the decades to come. This will be accomplished by developing a series of educational modules that will shift students’ focus from a siloed understanding of the traditional CE domains, towards a holistic and advanced Civil Infrastructure Systems and Analytics mindset and skillset. Specifically, the two objectives of this project are to: (1) develop a system-level thinking module that introduces the students to the core concepts of systems engineering followed by a series of analytic modules that provide students with a foundational understanding of the analytical mindsets required for 21st century CE Engineers, and (2) implement these modules across undergraduate CE engineering courses at Manhattan University to evaluate and assess the systemic changes in STEM educational outcomes that will result from the innovative modules developed for this project. We hypothesize that analytics-based system thinking can be infused into any existing undergraduate CE engineering curricula without requiring a complete redesign of these programs. Also, our assessment results resulted in new knowledge of the effectiveness and the transferability of our research, clearly demonstrating what works and what does not in undergraduate CE Engineering and STEM education.

Authored by
Christina Cercone (Manhattan College), Medya Fathi (Manhattan University), Matthew Volovski (Manhattan College), and Dr. JUNESEOK LEE (Manhattan University)

Earth Trek is a mixed reality educational game that aims to enrich geotechnical engineering education through gamified learning. The game is designed for undergraduate geotechnical engineering students as part of the Multiphysics-Enriched Mixed reality for Geotechnical Engineering (MERGE) platform. It combines virtual reality technology with experimentation, field exploration, and engineering design through a series of mini-games based on standard lab assignments. These enable students to learn key concepts in geotechnical engineering in a virtual environment. Students can access various testing tools (e.g. thermal conductivity measurements and direct shear tests) through the game missions. They can also conduct parametric studies in the virtual laboratory to understand soil properties under different geological conditions. Students can also perform parametric studies in a virtual lab to understand the efficiency of heat transfer in geothermal piles. The game allows students to intuitively grasp complex theoretical concepts and practical operations through visualization and simulation tools. By completing the game's tasks, students can earn points and update the appearance of their characters, increasing their motivation to learn. Implemented across multiple institutions, Earth Trek not only improves students' laboratory skills and geotechnical knowledge, but also integrates smart city design concepts and develops their metacognitive and problem-solving skills. Beyond classroom teaching, the game supports self-paced learning, promoting lifelong education and preparing students for careers in geotechnical engineering.

Authored by
LuoBin Cui (Rowan University), Dr. Ying Tang (Rowan University), and Mr. Chenchen Huang (Rowan University)

Peer mentoring programs have become common on college campuses. Frequently, peer mentors are hired to work in writing centers or math learning centers to tutor students on learning. Peer mentors have also been integrated into courses such as with the Learning Assistant (Barrasso & Spilios, 2021) and supplemental instruction (Dawson et al., 2014) programs. It is common for university-based makerspaces to hire students to be peer mentors who can help those coming into the space accomplish their goals.

Unique to our program is hiring peer mentors (who are engineering majors) to support engineering students enrolled in a first-year design course taking place in a makerspace classroom. The course is structured to meet once a week for two hours. The typical course has 40 students and is led by a single instructor who is a member of the university engineering faculty. Thus, the student-to-faculty ratio in the space is 49 to 1. In the course, students work in small groups (usually four students) as they engage in assignments designed to help increase their knowledge of engineering. Some of the activities are scripted (e.g., circuit building), while others require the students to design and prototype a product following general guidelines. Thus, the students learn about engineering through design, prototyping, testing, refining, rebuilding, and retesting.

Given the high level of student engagement in activities in the course that they may not be familiar with (e.g., building prototype circuits using breadboards, using power tools), there is a need for additional learning support beyond what a single instructor can provide. Thus, the college hires a cadre of peer mentors (also undergraduate engineering students) to work with the students in the courses and support students in the makerspace classroom during open lab hours. The integration of peer mentors into the course has been taking place for several years. We are working with 15 undergraduate engineering majors this semester, preparing them to be peer mentors and researching how their mentoring experiences are influencing their professional development.

We recognize the potential for mentoring to benefit the mentors (Smith & Nadelson, 2016). However, there is a gap in the research detailing how peer mentors working with students in makerspace classrooms in undergraduate engineering may enhance their perceptions and knowledge of themselves as both professionals and engineers. To address this gap, we are gathering data from the peer mentors using both surveys and semi-structured interviews. Our survey contains ten free response items designed to elicit the thoughts of the peer mentors about how mentoring other students in the first-year design course taking place in the makerspace has influenced their knowledge and perceptions of themselves as developing into engineers.

We also developed our interview protocol to gather the narrative of the peer mentors to empirically document their lived experiences as mentors and the impact their mentoring experiences have on their professional and engineering identity development (Nadelson et al., 2017; Villanueva & Nadelson, 2017).

In our final report, we will detail the specific activities of peer mentors and how these activities enhanced their understanding of engineering, their thoughts about being a professional engineer, and their engineering and professional identities.

References

Barrasso, A. P., & Spilios, K. E. (2021). A scoping review of literature assessing the impact of the learning assistant model. International Journal of STEM Education, 8, 1-18.

Dawson, P., van der Meer, J., Skalicky, J., & Cowley, K. (2014). On the effectiveness of supplemental instruction: A systematic review of supplemental instruction and peer-assisted study sessions literature between 2001 and 2010. Review of educational research, 84(4), 609-639.

Nadelson, L. S., McGuire, S. P., Davis, K. A., Farid, A., Hardy, K. K., Hsu, Y. C., ... & Wang, S. (2017). Am I a STEM professional? Documenting STEM student professional identity development. Studies in Higher Education, 42(4), 701-720.

Smith, J., & Nadelson, L. (2016). Learning for you and learning for me: Mentoring as professional development for mentor teachers. Mentoring & Tutoring: Partnership in Learning, 24(1), 59-72.

Villanueva, I., & Nadelson, L. (2017). Are we preparing our students to become engineers of the future or the past. International Journal of Engineering Education, 33(2), 639-652.

Authored by
Dr. Louis S. Nadelson (University of Central Arkansas) and Dr. Pamela L Dickrell (University of Florida)

Engineering students taking dynamics, vibrations, and control theory courses struggle to acquire a deep understanding of complex engineering concepts due to their highly mathematical nature, lack of prior knowledge, limitations of large lectures, limited resources preventing the use of commercially available lab equipment, and lack of innovative teaching tools that could be utilized to enhance learning.
Hands-on experiences are especially crucial for engineering students to help them bridge the gap between theory and application. However, commercially available laboratory equipment utilized in the mechanical vibrations and control labs are bulky and expensive. Further, one may question issues of accessibility and equity for students. The inability to work at their own pace, repeat experiments later, and develop adequate knowledge and experience from troubleshooting the equipment and resolving problems is lacking with these turnkey solutions.
Since the pandemic, digital learning tools have become necessary complements, not just accessories, to support student engagement and learning. They offer advantages to increase student learning that traditional laboratory environments cannot, including increased accessibility for students with mobility impairments. Although some open-source virtual labs are available for science courses, there are limited available virtual labs for undergraduate engineering courses, including vibrations and control theory courses.
In our previous NSF IUSE Level I project (Award #2002350), we developed seven vibrations and one control lab equipment that are low-cost and 3D-Printed along with their learning activities. Learning activities for each tool use a modified POGIL (Process Oriented Guided Inquiry Learning) approach grounded in constructivist theory. They include an orientation to why content was important to learn, clear learning objectives, performance criteria for the learning process, exploratory prerequisite questions to activate prior knowledge, instructions for working with the devices, final critical thinking questions. Additionally, in a separate project, we developed open-source virtual labs for mechanical vibrations, control theory, and associated laboratories to support student learning of vibrations and controls concepts.
In our current NSF IUSE Level II project, we are developing additional learning experiences for students that leverage multiple representations of knowledge by combining (1) hands-on and (2) virtual simulation lab or demonstration experiences with (3) AI support embedded within a robust (4) process-oriented learning activity. These elements of the learning experience create complete learning packages that will advance student learning, enhance accessibility by increasing hands-on and virtual simulation learning experiences, and provide an affordable alternative to lab equipment. This work aims to broaden the impact on learning vibrations and controls across a diverse set of learners and learning contexts at multiple institutions.
The project has produced three new learning experiences based on new lab equipment designs and one prior design is adapted as a new classroom exercise, along with their virtual labs. The adapted design is being used in a Fall 2024 course, and the other devices are being tested for usability in multiple settings at two institutions. Data for these implementations is currently being collected. Results will address the impact on students' perceived capabilities as learners and engineers and on the achievement of intended outcomes.

Authored by
Dr. Ayse Tekes (Kennesaw State University), Dr. Tris Utschig (Kennesaw State University), and Coskun Tekes (Affiliation unknown)

Despite efforts to cast STEM fields in a more inclusive light, engineering and computer science are still perceived as ill-fitting and exclusionary by women and people of color. Another common misconception is that STEM content is too abstract to be relevant to everyday life. These perceptions affect efforts to ensure the involvement of underrepresented groups in STEM and efforts to shift the sometimes-exclusionary cultures of STEM workplaces and universities. In this work, we recast the paradigm of a robotics course into a more inclusive space by showcasing the value of interdisciplinary collaboration in engineering as well as highlighting both the value of engineering in crafting and of crafting in engineering by teaching robotics topics through a craft that has alternately been coded as masculine or feminine depending on time period and culture: weaving.

We developed an undergraduate introduction to robotics course that explores the connection of weaving and engineering through the rich engineering history of looms, the physical properties of cloth, incorporating electronics into cloth through e-textiles, and building robotic looms. Weaving patterns can be represented mathematically through the binary, matrix-like nature of the pattern, allowing the physical properties (feel and drapability) to be analyzed geometrically through an understanding of properties connected to engineering (yarn tension, weight, and interlacement structure). Furthermore, to create high-quality, complex cloth, weavers follow a process that mirrors the engineering design process. Weavers' desire to create more complex patterns and the industry's desire to mass produce these products has led not only to advancements in processes but also to multiple engineering innovations. For example, the development of modern automation was driven by the introduction of punch cards to program the first Jacquard looms which led to modern-day computers.

The course was supported by the use of RoboLoom, an open-source, educational, Jacquard loom kit, to bridge the gap between weaving and engineering in the classroom. This course was taught in the Spring of 2024 to 17 students from mayors ranging from art to computer science. Students were randomly distributed in interdisciplinary groups that were balanced by area of expertise. In these groups, students completed in-class interdisciplinary assignments and final projects. We conducted surveys and observations throughout the course to understand students’ experiences and how their attitudes toward math, weaving, engineering, and collaborative learning changed. Additionally, we conducted interviews to give students an opportunity to reflect and expand upon their attitudes and how they changed through the course experience. Finally, students reflected on each assignment in the course on how they used engineering or creative skills, how well the assignment worked for them, and how it could be improved. We received generally positive feedback from students who, in conclusion, valued learning interdisciplinary skills. In this work, we present our curriculum, findings, as well as reflections and recommendations for the design of this and other interdisciplinary engineering curricula. This material is based upon work supported by the National Science Foundation Division of Undergraduate Education.

Authored by
Samantha Speer (Carnegie Mellon University), Dr. Melisa Orta Martinez (Carnegie Mellon University), Dr. Kylie Peppler (University of California, Irvine), Olivia Robinson (Carnegie Mellon University), Dr. Joey Huang (North Carolina State University), Nickolina Yankova (Affiliation unknown), and Santiago Ojeda-Ramirez (University of California, Irvine)

The biotechnology and pharmaceutical industries are increasingly reliant on a workforce pipeline of graduates possessing the skills needed to quantitatively describe complex systems to predict functional outcomes relevant to healthy physiological function and to disease states. These skills will be essential for not only identifying novel drug targets and ascertaining the etiology of complex diseases such as cancer and heart disease, but also for achieving truly personalized medical diagnostics, therapies, and surgical approaches toward treating these diseases. Moreover, inherent biological complexity and high-throughput measurement approaches lead to massive “big data” sets, often with thousands of heterogeneous values. This complexity requires data science tools such as data-driven modeling and machine learning to appropriately integrate heterogeneous data. Thus, it is imperative to train a diverse new generation of scientists in the concepts and practice of multi-scale systems bioengineering and biomedical data sciences (BDS) research.

At the University of Virginia, we developed an NSF-funded REU Site in Multi-Scale Systems Bioengineering and BDS (NSF #1560282 & #1950374) that has supported 81 students engaging in research projects for the past eight years (2017-2024). These students were recruited out of a total of 1,375 applicants, with participants drawn from 54 colleges and universities. Two summers (2020 & 2021) the program was run as a virtual REU due to institutional constraints on visiting researchers due to the pandemic. The REU students were matched to a mentor based on a combination of student interest in specific sub-areas of systems bioengineering research and mentor availability each summer. Most research projects relied primarily on previously developed methods and tools and typically involved application to biological data and generation of testable hypotheses. The specific research projects included a wide variety of topics in the field, ranging anywhere from molecular scale biophysics models to cell-scale signaling models, biomedical data science analysis of genetic data, tissue-level biomechanics models, and image analysis algorithms for quantifying cell distribution in tissue-engineered constructs. The participants took part in an introductory bootcamp on the fundamentals of systems modeling and had multiple opportunities to present their research progress throughout the summer to experts in the field. They also received professional development training on research ethics, technical communication, and launching careers in systems bioengineering. We analyzed participant demographics, outcomes in presenting or publishing their work, career outcomes, and survey data from each summer’s cohort.

The 81 REU participants came from 54 colleges and universities and represented 24 different majors, with 47% of them biomedical engineering (BME) majors; 68% were from groups traditionally underrepresented in STEM, 32% were first-generation students; 58% were women; and 41% attended non-R1 institutions; 67% presented their work at national meetings, and nine have become co-authors on ten papers. Of the 60 who have since graduated, 85% are either in graduate school or in STEM industry positions. Post-REU surveys of participants revealed that 98% of respondents rated their overall experience with the REU as either “very satisfied” or “satisfied” (average 4.72 on a Likert scale). Evaluations of specific program objectives and mentoring were similarly high. Regarding impact on long-term goals, nearly 75% said that the REU increased their interest in STEM and encouraged them to pursue further education towards a research or academic career, while 45% said the program helped solidify interest specifically in systems bioengineering.

From a programmatic standpoint, we have several recommendations: Our large number of applications suggest that the specific research area is important, and if well-presented to possible applicants can be a highly motivating selling point. Our experience during the pandemic was that a virtual REU can lead to positive research outcomes, although cohort bonding and the experience of working in a lab are diminished. One challenge of a one-size-fits-all bootcamp is appropriately accommodating the needs of the varied research topics. Some projects require coding, but others do not since they use established software tools; some require model development, others data science. We are continually iterating to find the optimal balance of instruction in topics that support every student in the program.

Authored by
Dr. Timothy E. Allen (University of Virginia)

The Resilient and Sustainable Infrastructure Systems in Smart Cities (RSISSC) REU Site grant was developed to bring a cohort of students to a large R-1 university to expose students to the critical role of civil engineers in serving society. Students participated in hands-on interdisciplinary research with faculty teams exploring innovations for Smart Cities, including new image analysis tools, sustainable materials analysis, technologies for quantifying indoor air quality and remediating water pollution, decision analysis tools, and strategies for autonomous navigation. Associated cohort programming helped students to build basic research skills (e.g. literature searches, data analysis, ethics considerations), to develop their career paths with emphasis on the preparation process for graduate studies, and to expose students to real-world applications of ‘smart’ technologies for resilient and sustainable infrastructure. The design of these enhancing activities was guided by the REU Site project evaluation framework that posits that guided immersive research experiences have measurable impacts on shifting students’ vision of career choices and that expanded personal networks, in this case through relationships with other researchers, are influential in converting student goals to actions. Evaluation assessments used a combination of surveys and interviews, personalized to the survey results.

The Resilient and Sustainable Infrastructure Systems in Smart Cities REU Site grant has met project goals in each of two years that the project has been active (2023, 2024). Evaluations findings from the first year informed adjustments to the program structure and organization for the second year. Across the two cohorts, the project engaged 20 undergraduate students (17 were not currently enrolled at the university) from a variety of majors to work on research questions in the fields of civil, environmental and geodetic engineering. Students were able to see relevance to Smart City innovations of their backgrounds in microbiology, biochemistry, physics, mechanical engineering, computer science, architecture and urban planning, and civil engineering. The student cohort diversity increased across the program years with the 2024 cohort having gender parity, one student from a Historically Black College and University, and two students from Puerto Rico. Students reported the most frequent skills they practiced throughout the program to be communication skills, creative problem-solving, professional and ethical responsibilities, shared leadership, and business and management principles (listed from most to least frequent). Students also developed social capital related to career exploration and the research process through the relationships developed with their graduate student mentors, faculty advisors and the program leadership. Overall, student participants reported positive program experiences, pride in the work results they showcased in a closing college-wide poster session, and greater clarity in their future academic and career plans.

Authored by
Dr. Allison Mackay (The Ohio State University), Prof. Jieun Hur P.E. (The Ohio State University), Dr. Julie P Martin (University of Georgia), and Mrs. Jennifer Brown (Clemson University)

Our project uses an ecological belonging intervention that requires one class session to implement and has been shown to eliminate equity gaps in student outcomes in introductory STEM courses. We describe disparate impacts on outcomes as equity gaps because they exist not from any deficit of the students themselves but rather due to systemic issues of marginalization. Our NSF IUSE: EDU Program, Institutional, and Community Transformation track grant brings this intervention into engineering where during the grant period we have implemented the intervention at three strategically chosen universities in both first- and second-year engineering courses. The intervention focuses on common challenges faced by students in engineering and is introduced by instructors early in the semester. Our research has demonstrated that the intervention is effective during the first year in supporting belonging for Black, Latiné, and Indigenous (BLI) students and in reducing equity gaps in academic performance during a first-year programming course. Our research has also demonstrated that BLI students who receive the intervention have improved help-seeking behaviors and are more likely to be retained in engineering into the second college year and that women students who receive the intervention may have more positive self-efficacy.

Our project is comprehensive in the development and delivery of the ecological belonging intervention and in the study of its effects. We use focus groups to understand challenges engineering students face in their courses and in different institutional contexts to contextualize the intervention specifically to each course in which it is delivered. We also provide instructor onboarding and training to deliver the intervention which includes an overview of the theoretical frameworks that undergird the intervention and how those theoretical properties are actualized and delivered during the intervention. These efforts along with the rest of our training are aimed at increasing implementation fidelity as we hypothesize that the intervention is most effective when fidelity is high. Our work is guided by a theory-of-action that is the backbone of the project’s research activities and iterative processes of improvement. We use a synergistic mixture of qualitative and quantitative methods to study both student and faculty outcomes.

To expand on understanding the impacts of the intervention on students, we have recently begun to examine how students experience the intervention, if they remember it, what they remember about it, and what they feel they gained from it. In this paper, we provide an overview of our findings in this area using data collected from surveys of two first-year engineering programming courses at two study institutions and focus groups and interviews with students at the third institution where the intervention is being implemented within second-year courses in specific engineering majors. We will also report on our continued research on the efficacy of the intervention on student outcomes. In their totality, the results of this work can provide actionable strategies for reducing equity gaps in students' degree attainment and achievement in engineering.

Authored by
Dr. Linda DeAngelo (University of Pittsburgh), Dr. Allison Godwin (Cornell University), Mr. Matthew Bahnson (Purdue University at West Lafayette (COE)), Dr. Danielle V. Lewis (University at Buffalo ), Prof. Natascha Trellinger Buswell (University of California, Irvine), Erica McGreevy (University of Pittsburgh), Dr. Christian D Schunn (University of Pittsburgh), Eric Trevor McChesney (University of Pittsburgh), Blayne D. Stone (University of Pittsburgh), Liwei Chen (University of Pittsburgh), Carlie Laton Cooper M.Ed. (University of Georgia), Spencer Currie (University of California, Irvine), Charlie Díaz (University of Pittsburgh), Gerard Dorvè-Lewis (University of Pittsburgh), Rachel Kelly Forster (University of Pittsburgh), Kevin Jay Kaufman-Ortiz (Purdue University/Cornell University), Melissa Lepe (University of California, Irvine), and Kelly Tatone (University of Pittsburgh)

Evidence-Based Instructional Practices (EBIPs) are pedagogical approaches grounded in research that enhance student learning, engagement, and retention. These methods, such as active learning, problem-based learning, and peer instruction, have been shown to improve both short- and long-term learning outcomes, particularly in fields like engineering, where students often face complex, abstract concepts and large class sizes. EBIPs help bridge the gap between theoretical knowledge and real-world application, fostering critical thinking and problem-solving skills that are essential in engineering education. Despite their known benefits, many engineering faculty struggle to implement EBIPs due to limited training, time constraints, and a lack of discipline-specific resources.

This NSF-funded project seeks to increase the adoption of EBIPs in undergraduate engineering courses by identifying and addressing the specific contextual barriers and affordances that faculty face during implementation. Faculty often report challenges such as insufficient time for curriculum redesign, a lack of professional development opportunities, and institutional cultures that prioritize research over teaching innovation. To address these challenges, the project focuses on three key activities: (1) investigating the decision-making processes and contextual challenges faculty encounter when implementing EBIPs; (2) co-developing course materials and curriculum to align with EBIP strategies; and (3) creating research-informed resources to support EBIP-based course development.

This project engages faculty from over 40 institutions, including R1 universities, undergraduate-focused colleges, minority-serving institutions, and two-year colleges. By capturing faculty experiences across this diverse range of educational environments, the project aims to develop scalable, adaptable strategies for EBIP implementation. Faculty participants are paired with experienced mentors who provide ongoing, tailored support to address discipline-specific challenges. These mentors assist in curriculum redesign, pedagogical guidance, and troubleshooting barriers, facilitating a deeper understanding of how EBIPs can be integrated effectively.

In this poster, we present key findings from the project, focusing on the contextual barriers faculty encounter during the decision-making process of implementing EBIPs, and the strategies used to overcome these challenges. Case study examples from the participating institutions illustrate both the struggles and successes faculty experience under the scaffolded guidance of a faculty mentor. These case studies offer a window into the process of curriculum transformation, highlighting practical approaches to integrating EBIPs and providing rich, detailed descriptions of the change process.

Authored by
Dr. Maya Menon (New Jersey Institute of Technology), Stephanie Adams (Oregon State University), Dr. Prateek Shekhar (New Jersey Institute of Technology), Dr. Shane A. Brown P.E. (Oregon State University), and Jeff Knowles (Oregon State University)