interactive approaches learned at the Stanfordd.school’s Teaching & Learning Studio. The stated learning objectives of the bootcamp are: ● Ability to formulate and test non-scientific hypotheses ● Ability to identify the broader impact of your research work ● Ability to apply these methods to grant writing, job search, and career development ● Develop an understanding of the NSF I-Corps program principlesAdditional objectives include networking skills development, personal reflection and actionplanning, and community building. The bootcamp is typically delivered in 3 half-day sessionsover a 3-day period, although a 2-day version has also been piloted. The advantage of holdingthe bootcamp over 3-days is that it provides additional time
along with. I like to think that I can work for anyone and with anyone after my time playing football at Mines.Students also identified ways that their peers’ FOK contributed to the success of the capstoneproject. One of the welding students both appreciated the potential for the robotic welder to maketheir work more efficient and came to see that “everyone sees things differently and everyonecan bring a good idea to the table.” An MME student emphasized commonality, writing,“Communication between engineers and technicians can be challenging but shouldn’t. We seemto have more in common with each other than not and are working towards common goals justfrom different points of view/contributions.” Another student similarly emphasized
the challengesof engaging students without the presence of teachers and peers to encourage, motivate, andsupport them [5]. While there is little research on effective pedagogies for engaging students inonline labs, a recent study suggests that providing support for students before and during thehands-on projects, clear instructions about the experiment and set-up, and pre-structuring of labactivities, lead to successful student engagement with the activity [6]. Moreover, an importantgoal of Discover UC San Diego is to build confidence and self-efficacy, especially infirst-generation high school students, for college success. As defined by [7], “self-efficacy refersto an individual’s subjective conviction in his or her capabilities to perform
are not permitted to seek anyadditional donated funding. An example project for a faculty-driven project is the“WhiteBoardBot” used in the first year of implementing this model. For this project, studentswere tasked with designing a robot that could automatically write and erase text on a whiteboardbased on user inputs. This project was selected because it meets the requirements for amechatronics engineering project. It requires a combination of mechanical, electrical, computerengineering, and control system design to solve a real-world challenge. Students must design andselect appropriate mechanical components, sensors, and actuators. The system also needed tocontain a user-friendly graphical user interface. Safey and professionalism were
scope, espe-cially in the final semester, many noted that the Capstone provided essential real-world experience.However, there were concerns about uneven workloads among team members, with some suggest-ing more structured peer evaluations to improve team dynamics.For continuous improvement, the survey highlighted the importance of integrating more technol-ogy, such as Building Information Modeling (BIM) and AI design tools, into the course. Somesurvey responses also suggested a two-semester sequence to allow more time for the design pro-cess and client feedback. Instructors recommended enhancing project management and collabora-tion tools to reflect industry practices better. Overall, the Capstone course was praised for bridgingthe gap between
Low-Resource Languages Visualization Tools Adaptive Learning Linguistics Evaluation Metrics Pre- and Post-Course Assessments Peer Review System Surveys and Interviews Social Sciences Figure 1: Framework for NLP Education: An Integrative Approach.3.2 Framework Design for NLP Education3.2.1 Objective:The initial phase involves developing an educational structure that balances theoretical knowledge withinteractive
Minnesota, Dulut ©American Society for Engineering Education, 2025 Experiences in Piloting a Program for Implementing High Impact Practices with Limited ResourcesAbstractIt is known that low-income, first-generation, and underrepresented students in engineering andcomputer science have rates of retention and graduation that lag behind their peers. A growingbody of research has identified a range of high-impact practices and exemplar programs thathave been successful in improving outcomes for these at-risk populations. Some areas that thesepractices seek to address include: financial need, academic preparation, sense of community,confidence, and professional identity. The challenge of
: last week of semester● Final Report: end of semester ● In year 2, 3 continuing and 11 new projects were awardedProgram DesignRationale Program feature ● In a similar, university-wide program ● Projects must be led by undergraduate open to “all”, faculty largely were students, graduate students, postdocs, awardees or staff ● Students, staff, and postdocs may not ● Proposal template, office hours, have proposal writing experience information session ● Equity in review process ● Scoring rubric shared with template ● Sufficient budget for events and student ● Budget
aboutone month collaborating with one or two team members to further develop their thoughts on EJIin a team project. Thanks to its OpenRoads module, this course is assigned to a classroom withcomputers. Students are given about fifteen minutes at the end of the two case study lectures tosearch online, develop their short essay outlines, and ask any questions they may have. This firstEJI assignment is promptly graded and returned to students, offering plenty of time andnecessary feedback for students to work on their team projects. Students are encouraged tocollaborate with peers they know and are interested in similar topics. After teams are officiallyconfirmed, students work outside class while the course moves on to highway geometric designand
Internet of Things, and engineering education. She has published in several peer-reviewed conferences and journals and has been a program committee member at several conferences. ©American Society for Engineering Education, 2025 Active Learning and Specifications Grading for Undergraduate Algorithms and Data Structures coursesAbstractAlgorithms and Data Structures are core concepts taught in all computing undergraduateprograms. It is important to ensure that student activities in the class lay the foundation andprepare them for future courses and career. In addition, assessment should allow for students todevelop a growth mindset. The course may benefit with a grading system can be
Polytechnic Institute Tanisha Gupta is currently pursuing a Bachelor of Science degree in Biomedical Engineering at Worcester Polytechnic Institute (WPI). She has worked on several projects, including her Interactive Qualifying Project in collaboration with Heidelberg Instruments Nano AG, which focused on demystifying nanofabrication and developing educational materials for beginners in nanoscience. On campus, Tanisha serves as Vice President of WPI’s chapter of the Society of Women Engineers, is a Global Ambassador for the Global Experience Office and works as a Peer Learning Assistant for Introduction to Biomechanics.Dr. Emine Cagin, Heidelberg Instruments Nano AG Dr. Emine Cagin is the CTO of Heidelberg Instruments Nano
programs to help CUNY faculty better understand the expectations of funding agencies and write more competitive proposals. Her intensive NSF CAREER and Grants 101 bootcamps, which are open to CUNY faculty across all its colleges, have supported 21 NSF CAREER awards, and prepared over 150 faculty to submit and win awards. Linda was part of the planning committee and a presenter for NSF’s Engineering CAREER workshops for 3 years and organized a CUNY-wide Convergence Workshop in 2018 as well as Broader Impacts presentations. Linda has a PhD in Educational Psychology from the University of Illinois at Urbana-Champaign; her postdoc, through the University of Arizona, focused on art and technoscience collaborations. She
chose to group themby careers, such as Data Analyst, Biostatistician, and Environmental Consultant – and they canalso be broken down into sub-competencies. Additionally, each competency or sub-competencycan have different levels of achievement. For example, a Communication competency could bepart of an Interpersonal Skills category (in a program where other categories might includeLeadership Skills and Analytical Skills) and have sub-competencies for Listening, Presenting,and Writing that all have levels of expertise such as Beginner, Intermediate, and Master. Thisflexibility allows for units to customize the student experience to best fit their objectives.Because the development of professional competencies can take place in the classroom as
mechanical engineering (n=57) and industrialdesign (n=16) major programs at The Ohio State University participated in the activity.Research Method: Ideation EquationStudents were instructed to bring a full sheet of paper with their name on it and a writing utensil.Students were seated around a large conference room, each student with a chair and ample tablespace. Once seated, students were instructed that they would have 60 seconds to write down asmany solutions as they could think of to an “equation” that would be written on a whiteboard.The equation was (circle) + (square) = “?” (e.g. Fig. 1). Fig. 1. Ideation equation prompt represented on a participant page.Students were given a verbal half-way warning, and a 10-second warning
], looked at engineering project-work aimed at improving language skills,combining engineering students in the UK with peers in Gaza, an area which is facingdaunting politico-humanitarian challenges. This research looks again at issues relating to thelanguage of learning and teaching in the UK and Gaza, but this time focuses specifically onthe experiences of female engineering faculty. A ‘Story Circles’ methodology [2] wasadopted, in combination with follow-up focus groups. In these safe spaces, practicessurrounding the use of English in engineering were explored, allowing academics to compareapproaches and experiences. Though the study has been interrupted by the current war,results to date suggest that there are many more similarities than
Cooper is Professor and Associate Head for Graduate Programs in the Department of Physics at the University of Illinois at Urbana-Champaign. He received his B.S. in Physics from the University of Virginia in 1982, his Ph.D. in Physics from the University of Illinois in 1988, and he was a postdoctoral research associate at AT&T Bell Laboratories from 1988-1990. His research interests include optical spectroscopic studies of novel magnetic and superconducting materials at high pressures, high magnetic fields, and low temperatures. Since 2013, he has co-taught (with Celia Elliott) a graduate-level technical writing course each spring to physics and engineering graduate students.Dr. Lynford Goddard, University of Illinois
-evaluated bystudents within their teams throughout the course, a process tracked through weekly billable hoursubmissions detailing time allocation across project components. The final grade was determinedby a final report (100 points), a final presentation/testing component (50 points), and thesubmission of a final peer evaluation and cumulative billable hours.The final report aimed to guide the reader through the problem-solving process the group used tocreate the final project. This report evaluation was based on effective communication, reportcomposition and presentation (title page, table of contents, figures and tables, formatting, andgrammar) and on course objectives. Reports had to clearly define design criteria, projectdevelopment
, researchassistance, automated grading, writing coach, make lesson plans, help to make progressreports, also helping the teachers how to teach a subject [76], [77], [78]. Although GenAI is apowerful technology in education, it still needs to be used with extra caution to ensure usingit safely and responsibly. For example, in [70], the article discusses the application ofArtificial Intelligence in online learning and distance education, based on a systematic reviewof empirical studies. The application of AI in these settings has been shown to enhance thelearning experience by personalizing the content, facilitating peer interaction, and providingreal-time feedback. Nevertheless, it also warns of the ethical and legal implications ofwidespread AI use in
engineering seminar, facilitated bytheir Academic Advisor and an Engineering Peer Mentor. These seminars provide generalinformation on the transition to college, study skills, co-curricular opportunities, and provide anoverview of the various engineering fields. This seminar is a group advising experience thatprovides weekly contact with advisors and peer mentors. Advising is about so much more thanregistration for classes and is designed to assist first-year and continuing student advisees, todevelop and implement plans for achieving educational and vocational goals so that students maybe directed and successful in their second college year and beyond.Academic Advisors in the First-Year Engineering Program are full-time professionals withgraduate
in the first year of an engineering curriculum reinforcestheir foundational nature. As first-year students enter university with a wide range ofbackgrounds, it can be difficult to create an immersive and engaging introductory experience thatreinforces these foundational skills without relying on a deeper understanding of technicalmaterial. In fact, for some students, introductory projects with roots in highly technical materialmay be alienating, damaging to student confidence, and ultimately detrimental to measures ofacademic success and degree persistence. It has been shown that student confidence in their ownacademic ability is affected by self and peer performance [1],[2] and the first year of a student’suniversity experience impacts
class time and the high number of students make it challenging to thoroughlydiscuss each group’s methods and provide detailed, positive feedback.Furthermore, over the years, we have observed that many students struggle to embraceconstructive criticism during class presentations. A significant number hesitate to engage inmeaningful discussions to address the feedback provided by their peers or the instructor. As aresult, numerous issues related to their projects remain unresolved, negatively affecting theirapproach to the prototyping phase.To address these challenges, we have developed an AI-based tool, called Capstone GuideChatbot (CAPCHAT). In the next two sections, we first review existing AI tools and baseline
were transcribed and then analyzed usingthematic analysis.The results of this study provide insights into students’ perceptions on ClearMind with respect toTAM’s core constructs: perceived usefulness, perceived ease of use, and social influence. Theparticipants found ClearMind both useful and easy to use, and were willing to continue using itand recommending it to their peers. They also identified some opportunities for improvementsuch as fostering positive emotions and better organizing the content.Our user study results imply that ClearMind is an accessible yet helpful mental health resourcefor students. This highlights ClearMind’s potential for broader adoption. Future work involves alarge-scale quantitative study to assess ClearMind’s
as phasechange, phase transition temperature, crystallization, and ice nucleation, in existing universitycourses. We educated a diverse group of students and exposed them to state-of-the-art techniquesearly in their academic careers to consider pursuing a STEM career and higher education. Asoutreach, we also trained graduate students, as well as students from an adjacent communitycollege (CC). The developed curricular activities provided students with experience inexperimentation, data analysis, and technical writing. Based on the ABET assessment of learningoutcomes, we assessed our goals to educate students on 1) using multidisciplinary science,engineering, and mathematical skills to evaluate and address complex issues emergent in
, including classroom settings,educator perceptions, and peer interactions [5]. Particularly relevant to this study and thedevelopment of STEM identity, Carlone and Johnson developed a model of science identitybased on the experiences of undergraduate female students of color [3]. Focusing on 15 womenof varying racial and ethnic identities at a small university, Carlone & Johnson conductedinterviews with participants about their experiences in science spaces, leaning heavily on therecognition component of science identity. As a result, Carlone and Johnson indicated threecomponents of internalized science identity: performance, recognition, and competence.Competence involves demonstrating skill and ability, performance pertains to speaking
accommodations, and others were very different. Both groups faced difficultyconversing with instructors and getting critical needs met, like access to recorded lectures.Students also witnessed and experienced ableism regularly [8], which often discouraged themfrom asking for support, a finding that was similarly supported by Goodwin [9]. Someaccommodations frequently failed, like the peer note-taker accommodation, which preventedregistered disabled students from utilizing resources that the university agreed they need tosucceed. This supported the data that there is a measurably lower chance of disabled engineeringstudents using their accommodations compared to their non-STEM peers [10]. Students withoutaccommodations had to decide which supports were
mentoringinteraction systems: • Microsystems: Direct, person-to-person interactions, such as those between graduate students and their peers, faculty, staff, and family. • Mesosystems: Interactions between different microsystems, like departments and colleges, which can either support or conflict with each other. • Ecosystems: Networks that influence development at a broader level, such as Graduate Schools, governing boards, and communities. • Macrosystems: Larger societal factors, including historical, political, and economic influences. When considering race, gender, and other social factors, research shows that many STEMmentoring programs in academia operate from a deficit-based perspective [19]-[25]. McGee
format on material that was easily brokenClassroom Patterns of Collaboration 3down into topics, in this case, cognitive biases. Students prepared by reading about their choiceof cognitive biases and reflecting on quotes from different perspectives about autonomousweapons. On the white board I drew a grid with classroom tables clustered into pods as locationsand two time slots of about 15 minutes. In my case, all of the groups met in the same classroom,however when more spaces are available, it helps people hear their own group better to be inseparate spaces. With one student, I walked him through announcing his topic and writing it onthe grid. Then, with patience and giving
consisting of process engineers to upper management and from multinationalcompanies to start up companies. This allowed the “instructors” to determine which KSA’s to focuson in the course. IntroductionMainstream graduate STEM education programs are traditionally designed to train students foracademic careers as they focus on knowledge and skills related to laboratory research practices,writing technical journal papers, and presenting results at conferences to academic peers. Thismethod of education has value in preparing students for academic careers but falls short in Proceedings of the 2025 ASEE Gulf-Southwest Annual Conference The University of Texas at
diversity, equity, and inclusion in the STEM fields through innovative, evidence-based strategies and is driven by a commitment to enhancing equity in all learning and working spaces. Lara has a diverse professional background that spans non-profit, legal, and educational sectors. She served as the Director of Development & Training at The Arc New London County, where she led grant writing efforts, cultivated community partnerships, and provided technology training. Her earlier roles include working as a Paralegal Advocate at the Connecticut Legal Rights Project, offering legal services to individuals with mental illness, and as Program Director at Literacy Volunteers of Greater New Haven, where she managed
degree programs, and STEMinar-specific surveys. Thecollected data highlighted key outcomes in student confidence, academic support, and programsatisfaction. Results from the 2023-2024 academic year’s first-year scholars indicate high levelsof confidence, support, and a strong sense of belonging within the program. Over 80% ofstudents reported feeling confident in speaking up in class and collaborating with peers fromdiverse backgrounds. Although some students faced challenges in forming friendships andseeking advice on class-related issues, nearly 90% felt well-supported by both faculty and peers.Satisfaction with mentoring remained strong, with 64% of students expressing high satisfactionin the spring semester and 80% satisfied with the program