engineering statics studentswhen solving TMCT items while blindfolded. The three main categories of strategies that wereused by these participants include analytical, holistic and mixed strategies. Holistic strategiestended to be the most successful in solving TMCT items. However, high scoring participantstended to be ones who utilized a variety of strategies, often to double check answers. Thesefindings provide a foundation for understanding how sighted students approach spatial tasks innon-visual formats and can inform the development of future spatial interventions.Future WorkFuture work will include expanding the sample size and recruiting students from otherdisciplines to participate in the project. Differences in how BLV versus sighted
experiences for undergraduates (REU) program,” Mentor. Tutoring Partnersh. Learn., vol. 31, no. 1, pp. 103–121, Jan. 2023, doi: 10.1080/13611267.2023.2164988.[7] M. C. Linn, E. Palmer, A. Baranger, E. Gerard, and E. Stone, “Undergraduate research experiences: Impacts and opportunities,” Science, vol. 347, no. 6222, p. 1261757, Feb. 2015, doi: 10.1126/science.1261757.[8] S. Howitt and A. Wilson, “Scaffolded Reflection as a Tool for Surfacing Complex Learning in Undergraduate Research Projects,” CUR Q., vol. 36, no. 4, pp. 33–38, May 2016, doi: 10.18833/curq/36/4/8.[9] C. Rodgers, “Defining Reflection: Another Look at John Dewey and Reflective Thinking,” Teach. Coll. Rec., vol. 104, no. 4, pp. 842–866, 2002.[10] D
my continuing in engineering. The professional relationships (including with your instructors, if applicable) I have made during my studies within engineering at [post-secondary institution] have been 56% 29% important factors for my continuing in engineering.3.4 Comparison with Previous Survey ResultsAlthough our earlier work was intended as a pilot to better hone the instrument, data wascollected and analysed as part of that project [6]. As most questions provided in this seconditeration of the survey were the same, the responses from each group can be compared forconsistency.For example, both iterations included the question: In general, would you say your mentalhealth (such as feeling anxious, depressed, or irritable) is
bring diverse perspectives to challenge and refine my interpretations.Third, I will use robust qualitative methods, including member checking to ensureparticipants validate their contributions. By combining these approaches, I aim touphold the integrity and credibility of my work while remaining critically aware ofmy own positionality.Nadia, the second author, is my PhD advisor and identifies as a queer, neurodivergentwoman. They are an advisor of Prism, an LGBTQIA+ student club and are a part ofthe ASEE Virtual Community of Practice focused on LGBTQIA+ students, faculty,and staff. They are serving as a critical friend on this project and are helping provideanother perspective to research design, analysis, and interpretation.Proposed
deconstructed the question using the Population, Concept, and Context (PCC)framework, a widely used approach in systematic literature reviews [7]. The PCC guidelines for this review arePopulation – engineering educators and students; Concept – utilization of generative models (e.g., GenerativeAI, ChatGPT, GPT); Context – formal and informal engineering education settings.3.2. Identifying Relevant StudiesThe search strategy is structured into concept lines, following the approach outlined in [8] for scopingreviews, which is designed to identify and include articles, conference papers, and gray literature relevant tothe research question. For the scope of our project, we define this as an "Aspect": An aspect is an element ordimension of the research
supplement the more challenging first-year courses like Calculus and Physics, monthly social learning communities, progress reports,community volunteer activities, and program coaching [7].This project was reviewed by the Gonzaga IRB received exempt status under 45 CFR 46.101(b). 9References[1] Jones, Sharon; Caitlin Cairncross; Tammy Vandergrift; and Julie Kalnin. “Persistence of Students Who Begin Engineering Programs in Precalculus.” ASEE Advances in Engineering Education, Volume 9, Issue 4. 2021.[2] Tougaw, Doug. “Welcome Changes? The Choice is Ours.” ASEE Prism, Volume 33, Issue 1, Fall 2023.[3] Burtner, J., "The Use of Discriminant Analysis to Investigate the
could not make pre-settimes or who did not feel comfortable giving feedback in a social space. The video-chat formattook around 30 minutes to complete due to the round robin method and the online survey formattook around eight minutes.Additional future data collection methods and data points to be used include guided reflectionjournals (BASE Level II thru IV) and student developed and led community projects (BASELevel III and BASE Expert).All surveys are conducted with the use of QuestionPro software, with the surveys set toaccessibility settings in terms of font size, color, background color, and more. Additionally, allsurveys can be accessed and answered on computers, phones, and tablets, with the ability to usetext to speech functions and
part of a larger study that aimsto understand the strategies, approaches, and experiences of women engineers who have taken acareer break and returned to the workforce.MethodsIn this section, we detail the process we took to analyze podcast data for our project. Sincecompleting the analysis, a paper outlining a seven-step methodology for utilizing podcast data inqualitative research has been published by Kulkov et al. [11]. We will utilize Kulkov et al’sframework as a point of comparison, highlighting both alignments and divergences between ourapproach and the published methodology. Our podcast methodology features three main steps:Podcast and Episode Selection, Ethical Consideration, and Data Collection and Analysis. Thesesteps are
work.Previous Work Practical laboratory experiences including engineering labs and projects represent essentialelements of learning [1], [2]. As part of intensive laboratory experiences, robots have had alongstanding positive impact on education of students at all levels. Small, wheeled, programablemobile robots like LEGO Mindstorm series have been used as motivational tools to attract studentsto STEM fields in general [3], as well as to help students (and teachers) learn how to program [4]- [6]. However, at the practical level of industrial robot programming, the use of industrialmanipulators for teaching programming robotic tasks was often the only option. Expensivehardware, proprietary software, and required safety measures made programming of
available for regular consultation.10. helps me use my time effectively to work towards timely and successful completion of my research project.11. is willing to receive my suggestions on research direction.12. is supportive through my academic difficulties.13. is supportive through any personal difficulties.14. refers me to appropriate student support services and organizations.15. ensures that I have the appropriate training (e.g., with using equipment, tools, instruments, or software) to conduct my work.16. helps me to develop my future career in my chosen field of study.Research Group ExperienceThe variable is based on the average responses to 5 questions (N = 148, Cronbach’s alpha = .685)1. I can ask another student from my research
students to participate in a 4-year Integrated DesignSequence, where student teams participate in engineering design projects every Spring semester,at a minimum. There is an associated Integrated Design course for each year of study. Additionalproject-based courses are required in the Fall semester for freshmen, as an introduction tomechanical engineering, and for seniors, as the first semester of a 2-semester senior designproject.Course embedded strategies for encouraging students to pass the FE Exam are summarized inTable 1. Phase 1 includes course elements that have existed prior to AY23-24, representing thebaseline level of professional licensure discussion in required courses. Other required courseswill be phasing in at least one quiz with FE
before segueing into the construction of several classificationmodels for mental health metric prediction. This will be followed by the evaluation of our modelsin Section 4 before we conclude our work in Section 5. We will then finish with our planned futurework to improve our project in Section 6.2 Related WorksMachine learning and its applications within the field of mental health is currently a popular topicin research, with many works revolving around integration into diagnosis frameworks [9]. Crisisintervention is a large part of the field as well, with recent work showing that machine learninghas been valuable in clinical practice for caseload management and ameliorating risk [10]. Currentwork in the field of mental health with applied
Paper ID #49113Adaptive Learning in Higher Education: A Knowledge Tracing and ExplainableAI ApproachNandan Reddy Muthangi, University of Toledo Nandan Reddy Muthangi is a senior-year Computer Science and Engineering student at the University of Toledo, where he currently serves as the President of the Association for Computing Machinery (ACM) Student Chapter. He is actively involved in research and development across multiple interdisciplinary domains. Nandan works as a Research Assistant in the LONG and the Cyber-Physical Human Systems (CPHS) Lab, where his contributions span projects involving autonomous drone navigation
victimization, intimate partner violence, stalking,bullying, microaggressions, and discrimination compared to cisgender students [13]. This callsfor action not only within the field of engineering but also across broader educational sectors.When schools implemented strategies to reduce harassment, TGNC youth reported strongerconnections with school personnel, which were in turn associated with increased feelings ofsafety [14].Future PlanOur subsequent work involves integrating data from the project spanning 2020 to 2023. Thisapproach aims to expand the sample size of minority student groups, facilitating more robustquantitative statistical analyses. Additionally, examining student performance across multipleyears will allow for a more comprehensive
University of Waterloo in Canada. His background is primarily in biomechanics, tribology, mechanical design, materials and Systems Design. He is a former Vice President of R&D and Distinguished Engineering Fellow from DePuy Synthes, Johnson and Johnson where he worked for over 28 years both in the USA and the United Kingdom. Throughout his career Dan has architected multigenerational product platforms, lead projects, built strategy and delivered multiple medical device innovations from research and concept through to the market. He is an inventor with 30+ patents and an author on some 50+ publications. ©American Society for Engineering Education, 2025 When to Start Taking Social
interviews with two past participants—one in a tenure-track position and the other ina teaching-track role—offered deeper insights into the program’s long-term impact. Both faculty membersemphasized the lasting professional relationships formed through the program, which later led tocollaborative research projects, grant awards, and teaching initiatives. They also highlighted the value ofmentorship in identifying campus resources and navigating professional development opportunities.Although their use of the five-year career plan differed—one revising it annually as part of their reviewprocess, and the other using it briefly after program completion—both reflected positively on the process.Their experiences affirm that the program’s benefits extend
? (i.e., why did you do it this way? How would you have responded if xyz happened instead today?) 8. What class content was particularly interesting/engaging? 9. Other comments or questions.References [1] Resources for teaching evaluation guides. https://tinyurl.com/5ah3ehc3, 2021. Accessed on June 3, 2024. [2] American Sociological Association. Statement on student evaluations of teaching. www. asanet.org/studentevaluations, 2020. Accessed on February 9, 2025. [3] T. C. Andrews, P. Brickman, E. L. Dolan, and P. P. Lemons. Every tool in the toolbox: Pursuing multilevel institutional change in the DeLTA project. Change: The Magazine of Higher Learning, 53(2):25–32, 2021. [4] O. R. Arag´ on, E. S. Pietri, and B. A. Powell
reflect assumptions that may narrow participation and reinforce disciplinary and institutional silos. This limits engagement from a broad range of contributors, including working professionals, educators, students, and people with systemic or per- sonal restrictions. By broadening participation and intentionally fostering cross-sector and interdisciplinary connections, AI conferences can help unlock more innovation. We advocate for clearer framing that supports the demystification of AI and a wider under- standing of its implications to society. This can increase fit-to-purpose for conference attendees and improve on the projects and collaborations that may arise from attending a conference that’s well suited to
begin their PhD training and is a hallmark of our commitment to our early engagementstrategy.During Impact Week, we collaborate with key partners across the university to jump start studentsuccess in each of the Impact Training key areas. We collaborate with our university’s Center forScience Communication Research to build elements of storytelling in science communication.We also partner with our Lundquist College of Business to infuse innovation andentrepreneurship training, with a focus on assessing societal needs and understanding keyconcepts such as market pull vs technology push [9]. We translate these fundamental conceptstowards the process of designing research projects that can lead to transformative discoveriesthat have high potential
Paper ID #46853Work In Progress: Mentorship Matters—Shaping the Professional Pathwaysof Biological Engineering StudentsMrs. Leslie Bartsch Massey, University of Arkansas Leslie Massey is an advanced instructor in the First-Year Engineering Program (FEP) at the University of Arkansas, holding a BS in Biological Engineering and an MS in Environmental Engineering. She previously worked as a project manager at the Arkansas Water Resources Center before returning to teaching full-time in 2013. Currently, she teaches various courses in the FEP, including Introduction to Engineering I and II, and coordinates the First-Year Honors
Paper ID #45333Work-Life-Fit in the Structural Engineering IndustryDr. Rachel Mosier, Oklahoma State University Dr. Rachel Mosier is an Associate Professor at Oklahoma State University, with a background in structural engineering and project management. Dr. Mosier has received regional and international teaching awards through the Associated Schools of Construction.Erin Conaway ©American Society for Engineering Education, 2025 Work-Life-Fit in the Structural Engineering IndustryAbstractDiversity in the Architecture, Engineering, and Construction (AEC) industry has long been afocus and a topic
-bearing project. 3D printing andwaterjet cutting were performed in the university makerspace. Table 2. Cost of components and manufacturing. Qty Cost Total Component ($) ($) Central steel shaft 1 7.52 7.52 Nylon sample material 1 0.77 0.77 Material for internal structure 4 1.51 6.04 Handle housing 4 1.25 5.00 Fasteners 8 0.43 3.44 Retaining pin 2 4.30 8.60 Microcontroller board 1 8.95 8.95 Amplifier 3 8.16 24.48 Strain gauge
), Developing a Culturally Adaptive Pathway to Success: Implementation Progress and Project Findings Paper presented at 2020 ASEE Virtual Annual Conference Content Access, Virtual Online . 10.18260/1-2--34412[12] Wigfield, A. (1994). Expectancy-value theory of achievement motivation: A development perspective. Educational Psychologist, 6(1), 49–78.[13] Wigfield, A., & Eccles, J. S. (2000). Expectancy-Value Theory of Achievement Motivation. Contemporary Educational Psychology, 25(1), 68–81. https://doi.org/10.1006/ceps.1999.1015[14] Moreno MA, Goniu N, Moreno PS, Diekema D. Ethics of social media research: common concerns and practical considerations. Cyberpsychol Behav Soc Netw. 2013 Sep;16(9):708-13. doi
included memes having a direct reference to any aspect of school (bothrelated and unrelated to engineering). Codes within this category included course components(e.g., assignments, exams, projects, and studying), course content (e.g., content specific toengineering courses, professors), and student lifestyle (i.e., aspects of student life related to thetechnical and social characteristics of their engineering program). The Work category includedmemes that provided commentary on or related to students’ perceptions of life after graduationand in the workforce. This category included codes related to students’ anticipated and specificcareer paths (e.g., referring to a specific engineering discipline or industry) and work lifestyle(i.e., social and
Paper ID #47777Work-In-Progress: The Intersection of Neurodivergent Identity, Creativity,and Innovation among Engineering StudentsDr. Azadeh Bolhari, University of Colorado Boulder Dr. Bolhari is a professor of environmental engineering in the Department of Civil, Environmental, and Architectural Engineering (CEAE) at the University of Colorado Boulder. She specializes in teaching the fate and transport of contaminants as well as capstone design projects. Dr. Bolhari is passionate about community-based participatory action research. Her research interests lie at the intersection of engineering and social science, focusing
Lab- Based Biomaterials CourseIntroduction and MotivationTechnical communication focuses on conveying scientific information in a clear and conciseway. It is therefore a learning goal in high-level engineering courses as a preparatory skill for thework force. Accordingly, instructors use a myriad of communication tools such as final projects,lab reports, and poster pitches as deliverables in their courses [1]. These approaches not only testrecall, understanding, and application of course material, but also help students analyze andevaluate data and/or primary literature [2]. Indeed, ABET guidelines require that BiomedicalEngineering curricula must include “Making measurements on and interpreting data from
immersive VR experience [4]. This project aims to address this gap by integrating CTML principles into our fully immersive VR design, thereby creating a robust educational tool that promotes meaningful learning experiences for a diverse array of students.Moreover, a 2023 study by Huang et al. [9] on immersive VR in science learning suggests thatgenerative processing - the cognitive load necessary for deep learning - is enhanced in VR butmay not always translate into muscle memory or procedural expertise. Thus, an optimalsemiconductor training approach would involve initial VR instruction, followed by physicallaboratory work to ensure students can perform delicate tasks such as wafer handling andphotolithography.Semiconductor Fabrication in a
contribute to future efforts that enhance computerscience education for K-12 students.6 AcknowledgmentsThis project is supported by the National Science Foundation (NSF) under Grant No. 2311746.Any opinions, findings, and conclusions or recommendations expressed in this material are thoseof the author(s) and do not necessarily reflect the views of the NSF. We thank Vicky Sedgwick forher support in collecting and tagging the state standards and her contributions to our analyses, the10 state and regional education officials who participated in interviews about their state standardswriting process, and Monica M. McGill for supportive leadership throughout the process.References [1] Betul Ekiz-Kiran and Sevgi Aydin-Gunbatar. Analysis of Engineering
-efficient computing. ©American Society for Engineering Education, 2025 Toward a Fair and Unbiased Debugging Evaluation InstrumentIntroductionDebugging skills are critical to the semiconductor industry, as deficiencies can incur significantcosts. The unpredictable nature of debugging tasks has earned it the nickname “The ScheduleKiller” [1] with some electronics engineers spending up to 44% of their time on debugging [2].Despite the critical economic importance of this million-dollar question [3], undergraduate ECEcurricula often omit hardware debugging skills [4], [5]. Instead, it is left to develop indirectlythrough design projects and labs. To help fill this gap, we are developing a circuit debuggingcurriculum
Tools Professional Outcomes 4. In-Depth Competence 12. Multi-Disciplinary Teamwork 5. Risk, Reliability, and Uncertainty 13. Professional and Ethical 6. Problem Formulation and Responsibility Conceptual Analysis 14. Effective Communication 7. Creative Design 15. Lifelong Learning 8. Sustainability 16. Project Management 9. Multi-Media Breadth and Interactions 17. Decision Making Frameworks 10. Societal Impact 18. Leadership 11. Contemporary and Global IssuesThe EEBOK2 is the