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
,well-being, and lives of graduate students. It can support us in interrupting harmful interpersonal practicesand modeling supportive practices.ApproachData was collected through two phases of exploratory semi-structured qualitative interviews with sevenparticipants under the University of Colorado Boulder IRB protocol 21-0217. The participants andmethods are fully discussed in Beardmore [6]. Participants included STEM graduate students whoself-identified as being disabled or having one or more disabilities. This paper does not present the resultsin ordinary prose, that is, writing that follows a basic grammatical structure organized into sentences andparagraphs [7]. Instead, it presents an amalgamation of the participants' paraphrased quotes
on crucial aspects of workplace interactions, helping to evaluateand enhance the participant’s overall communication abilities.The first section, Comfortability in Workplace Conversations, focuses on evaluating how comfortableparticipants are in different professional communication scenarios. Participants will be asked to reflecton their ability to engage in conversations with peers, whether discussing day-to-day work or addressingconflicts. For example, one prompt might ask, "How comfortable are you in addressing a colleague whena work-related issue arises?" Another question could focus on interactions with higher-ups, assessing theparticipant's ease in communicating with managers or supervisors. The goal is to gauge the
], 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
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
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
program is to prepare and support engineering faculty toprovide effective and meaningful mentorship to NHERI REU undergraduate researchers, whomany times are first-time researchers.As a hybrid program, the NHERI REU includes an in-person faculty research mentor, often anECO Committee member, and a virtual mentor, the ECO Education Specialist. While research isconducted at one of eleven (11) NHERI experimental or research facilities, all REU studentsmeet each week for virtual research meetings to prepare a research poster, presentation, and peer-reviewed paper on the research they conducted. Students also meet at least once a week for anindividual check-in meeting with the Education Specialist to ensure understanding, receivefeedback on writing
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
identities, definitions, interests, and civic engagement • Provides multiple ways for students to show their learningThe TPP students share the development of their lesson plan with classmates to get feedbackfrom their peers, and later share how the implementation of the CRT lesson went.By the end of the course, the pre-service teachers also write a positionality statement in additionto their teaching philosophy. Through course assignments, the Culturally Responsive TeachingPreparedness Survey (CRTPS) [17], and Noyce scholar interviews by our project evaluator, wehope to gain insight into how our TPP students develop to be equitable and inclusive STEMclassroom teachers.AcknowledgementsThis material is based upon work supported by the
agency and creativity during the transition process.Our Solution: PatchWe present Patch1 , a free and open-source online coding environment built to help novice learnersbridge the gap between Scratch and Python. Figure 1 shows Patch’s editor. Built on the ScratchVM [17], Patch integrates Pyodide [18], a library that enables web-based Python execution, toallow learners to write Python code that directly interacts with the Scratch game engine. Patch isbuilt to mirror many of the successful aspects of Scratch’s programming environment that aren’tseen in a traditional text-based programming environment. We describe below how Patchaddresses the key transition challenges: Figure 1. The editor of the Patch coding
laboratories, automotive, energy,aerospace, and NASA. In the comments section of the survey, many reflected on the impact of their REUexperience, describing it as “a wonderful program that opened many doors to my career”; “incrediblyimpactful… many opportunities in networking and career development have been especially beneficial tome”; “REU was honestly one of the best parts of my undergrad for so many reasons…growing up shy andunconfident, the position helped me build confidence, interact with peers from other schools and helped mefeel much more confident when applying for first jobs in my career…”; “Honestly, I had a wonderfulexperience in the program and I wouldn’t have even been interested in research if I didn’t do this program!I’m in the
the groundwork for future functionalities.We are currently working on the second prototype, which is anticipated to be completed by theend of Summer 2025.Learning Innovation Thrust. To identify key concepts in CPS, the learning thrust is based onthe work of Meyer and Land's conceptualization of threshold concepts. The theory of thresholdconcepts originated in the context of a research project on teaching and learning in undergraduateeducation across disciplines in the United Kingdom [11]. It was developed more fully throughMeyer and Land’s later writings [12–14], in which they articulated the defining characteristics ofthreshold concepts — particularly that they transform learners' thinking within a discipline andshape how learners identify
traditional and ESL. It may be argued that a stronger focus on semantic andphonemic fluency could support the more typical research and teaching on written and oralcommunication.Potential intersections between spatial and communication skillsSpatial abilities are typically strong in engineering students who succeed, in other words recentengineering graduates are more likely to have strong or excellent spatial skill abilities comparedto their non-engineering peers. One potential reason for the perceived lack of communicationability among engineering students may be related to their strong spatial ability, where studentsmay have a great depth of knowledge about a particular “product,” but find it difficult totransform this knowledge into writing that
post surveys. ● Student Reflections: Open-ended reflection data was collected from student assignments, online discussions, and individual reflections. A specific prompt was chosen for this study: "How did this course develop your perspectives of value creation? Consider the following as you write your answer: In what ways have you grappled with the notion of value (political, economic, social, technological, legal, and environmental impact) in this course/project? How would you handle a situation where improving technological advancement might increase societal costs? What value did this course create/generate for you?"Data AnalysisBoth quantitative and qualitative data were analyzed. The quantitative
environmental engineering students. Major year-over-year changes made – against which experiences and outcomes were measured – includedthe instructors reducing group sizes and increasing the number of external mentors involved inthe class, altering project deliverable targets, and implementing more frequent external mentormeetings; the instructors doubling the frequency of peer evaluations and time sheet gradedfeedback to students and also setting aside dedicated in-class time for external mentors to marketthemselves and their companies; and the instructors adding general contractors (GCs) as externalmentors to the course, supplementing the civil and environmental designed-focused mentors inthe course.Measured outcomes from the changes in the senior
students to reflect on their overall experience with the project. Open-ended questions invited students to share what they found the most enjoyable and most challenging part about the project. They were also asked to provide suggestions for improving the project in future iterations. This section included questions to gauge whether students would recommend the project to their peers and whether it motivated them to pursue a career in STEM. The feedback collected in this section was essential for understanding the project's impact on student satisfaction.Results and DiscussionEvaluation of Students’ Improvement in Modeling and Coding Skills The AI-assisted ODE modeling project was designed to assess and