Paper ID #48536WIP: College-Wide First Year SeminarBuilding the Foundation for CareerSuccessDr. Cheryl B. Schrader, Wright State University Cheryl B. Schrader retired as president and rejoined full-time professor ranks in Wright State’s Department of Electrical Engineering. Prior to Wright State she served as chancellor of Missouri University of Science and Technology and associate vice president for research and dean of engineering at Boise State University. Professor Schrader earned her BSEE degree from Valparaiso University and MSEE and Ph.D. degrees from the University of Notre Dame. Over her career she received
Paper ID #45986Panel on Environmental Engineers Solving Problems of Planetary HealthDr. Daniel B Oerther P.E., Missouri University of Science and Technology Professor Daniel B. Oerther, PhD, PE joined the faculty of the Missouri University of Science and Technology in 2010 as the John A. and Susan Mathes Chair of Civil Engineering after serving for ten years on the faculty of the University of Cincinnati where he was head of the Department of Civil and Environmental Engineering. Professor Oerther is internationally recognized for leadership of engineers, sanitarians, and nurses promoting the practice the sustainable
graduate students. She also works in the areas of teaming in engineering classrooms and creating instructional tools for engineering in various contexts and educational settings. She has expertise in mixed-methods research designs.Mr. Siddharthsinh B Jadeja, University at Buffalo, The State University of New York Siddharthsinh Jadeja is a passionate and driven engineering education graduate research student in the Department of Engineering Education at the University at Buffalo, deeply committed to enhancing engineering education through innovative, human-centric design approaches. With a strong foundation in engineering principles and a keen interest in educational methodologies, Siddharthsinh focuses on integrating design
aerospace engineering from the University of Michigan - Ann Arbor in April 2021; her thesis included both technical and educational research. She also holds an M.S.E. in aerospace engineering from the University of Michigan - Ann Arbor and a B.S.E. in civil engineering from Case Western Reserve University, both in the areas of structural engineering and solid mechanics.Kenya Z. Mejia, San Francisco State University Dr. Kenya Z. Mejia is an Assistant Professor of Mechanical Engineering at San Francisco State University. Her work focuses on diversity and inclusion in engineering education, particularly in engineering design education.Prof. Silvia Heubach, California State University, Los AngelesDr. Gustavo B Menezes
Paper ID #49429BOARD # 229: Capacity-Building for Change in an IUSE ICT Project: InstitutionalizingMini-ActivitiesDr. Amy B Chan Hilton, University of Southern Indiana Amy B. Chan Hilton, Ph.D. is the Director of the Center for Excellence in Teaching and Learning and a Professor of Engineering at the University of Southern Indiana (USI). Her interests include faculty and organizational development to support both faculty and student success, learning analytics, teaching innovations, and systems thinking and storytelling for institutional change.Shelly B. Blunt, University of Southern IndianaWilliam Elliott, University of
following criteria: a) The subject population includes military members, government civilians, and contractors. b) The researchers make a special effort to recruit subjects within or related to the cyber career field. c) The researchers may recruit people with cyber experience from non-DoD organizations based on availability. The recruitment locations are military organizations. The participants are recruited throughemail and in-person contact. Participants agree to be part of the experiment, and a meeting isarranged. The experiment occurs over Microsoft Teams, using Teams’ recording transcriptfeature for the interview. After the experiment begins, the protocol in Figure 2 is followed:Figure 2. Experiment protocol, showing the
requirements and usability. The Android app screen shown in the PCD creates a visual representation of the user actions explained in the UOF. FBD clearly explains how functionality will be divided between the Android app and the PCB and high-level technical solutions on how the system will interact with the cocoa bean bag. Most importantly, all three diagrams highlight the three core requirements of the project, which are a hand-held device, non-invasive operation, and an easy-to-use moisture meter. (b) In-class exercise: Following the case study discussions, this workshop includes a guided in-class exercise in which all teams are provided with a short list of example requirements and are asked to draw
. 2024, doi: 10.3390/architecture4040046.[26] H. Zhang and R. Zhang, “Generative artificial intelligence (AI) in built environment design and planning – A state-of-the-art review,” Progress in Engineering Science, vol. 2, no. 1, p. 100040, Mar. 2025, doi: 10.1016/j.pes.2024.100040.[27] L. Sela, R. B. Sowby, E. Salomons, and M. Housh, “Making waves: The potential of generative AI in water utility operations.,” Water Res., vol. 272, p. 122935, Dec. 2024, doi: 10.1016/j.watres.2024.122935.[28] Y. Wu, M. Xu, and S. Liu, “Generative artificial intelligence: A new engine for advancing environmental science and engineering.,” Environ. Sci. Technol., vol. 58, no. 40, pp. 17524–17528, Oct. 2024, doi: 10.1021
what they discovered about the course content and course structureby creating their systems picture.For each section in the paper, students are generally penalized for missing required discussionitems, lacking depth in required discussions (minor penalty), or discussions that do notadequately address the project requirements (major penalty). For assessment purposes, theCategory and Influence sections are tied to course sub-outcome C02.a: Identify strategies usedby successful students through generating a “toolkit” of skills to enhance learning. The FutureWork section is tied to course sub-outcome C01.b: Explain reasoning behind interest inengineering as a major and develop long-terms goals as an engineering professional. TheSummary section is
students expressed thatindicate their development of understanding JEDI principles: (a) Diversity and Inclusion: Integration of DiversePerspectives; (b) Equity, Justice, and Accessibility; and (c) Community-Centric Approach, although the evidencealso suggests that not all students fluently apply these ideas in a problem-solving context. Overall, the resultssuggest that the 1-credit seminar is effective to build essential literacy of JEDI, which will be instrumental in futurework in sustainability engineering and design.1. IntroductionJustice, Equity, Diversity, and Inclusion (JEDI) are recognized as core components of educationin sustainability. JEDI are essential principles of the UN Sustainable Development Goals(SDG’s) (United Nations 2015) and
asked to participate inthree components: a) an Electronic Survey, (b) an Interview (up to 75 minutes), and (c) anOptional member-checking interview (i.e., upcoming following the data analysis phase).Recruitment activities were dynamic and responsive as the study progressed and included (a)leveraging personal and professional networks, (b) obtaining faculty participant referrals, (c)electronic advertising in various venues (i.e., ASEE division listservs, faculty developmentconsulting groups), and (d) direct outreach to individual departments and faculty members.These activities resulted in a final sample of 36 faculty representing a range of contextual factors,including coming from 15 states, representing 18 institutions, various institutional
. 6 Method search Participants Year 1 (2022) Year 2 (2023) Year 3 (2024) N = 518 N = 253 N = 214 A B C Ø College of Engineering Alumni Offices sent emails to engineering graduates from their institution in 2014 or later Ø Snowball sampling Ø
Divisions (CED, WIED, DEED, MIND, ERM, LEES, etc.), Society of WomenEngineers (SWE), National Society for Black Engineers (NSBE), National Society forProfessional Engineers (NSPE), Professional Engineers societies, etc.Figure 2 shows an actual Wake Forest Engineering faculty ad from fall 2018. The content ofthis faculty ad shows vision, values, and inclusion. The ad has some elements that one would nottypically see in a faculty ad, including (a) departmental values upfront and visibly clear, (b) asection describing our uniqueness and a vision of the kind of engineering program we arelaunching, (c) a section describing a vision of who we want. The ask for the candidates alsodemonstrate inclusion and an invitation to align with the vision and values
expectations about career paths and future roles in engineering aftercollege graduation.Purpose of the Study Given the necessity to have effective intervention programs such as Summer Bridge thatpromote URM participation in the STEM field, the study addresses the following researchquestion: 1) Does participation in the summer bridge program significantly increase a) self-efficacy, b) math outcome expectations, c) goal orientation, d) feeling of inclusion, e) knowledge of MSU and the engineering industry, and f) career success expectations among students? The current study hypothesized that participation in the SBP will positively influencestudents' self-efficacy levels, math outcome expectations, goal orientation, feeling of
Paper ID #45288Bridging Educational Equity Gaps: A Systematic Review of AI-Driven andNew Technologies for Students Living with Disabilities in STEM EducationKevin Zhongyang Shao, University of Washington Zhongyang (Kevin) Shao is currently a first-year Ph.D. student in Electrical and Computer Engineering (ECE) at the University of Washington, Seattle (UW). His research focuses on human-computer interaction and STEM education, particularly in developing user-centered, inclusive, and responsible AI technologies to enhance the accessibility and personalize learning for post-secondary STEM students. His current work
fit thedata well (Table 3). The coefficientof determination indicated themodel explained a considerablecourse grade variation for BLIstudents. This model identifiedsimilar patterns of significance asthe intervention model withsignificant direct effects between Figure 3. Construct relationships for interventionPSE and belonging, as well as PSE usefulness ratingand course grade (see Table 5, Figure 3). Like the intervention model, no direct or indirect effectslinked usefulness rating to course grade.Table 5. Utility model coefficients.Dependent Independent β B S.E. z p Direct EffectsPSE Useful 0.21 0.15 0.13 1.19 0.235 PSE 0.58
adopted technology, where all faculty responders do use the technology as well asthe majority of students. (a) Faculty and panelists usage of AI 28.57% 42.86% 28.57% Daily Weekly Monthly Rarely Never (b) Students usage of AI 2.78% 5.56% 13.89% 27.78% 50.00% Daily Weekly Monthly Rarely NeverFigure 1. Survey response on AI usage by (a) faculty and panelists (b) students.The wide adoption of AI, however, comes without being paired with proper training on how touse AI responsibly. Figure 2 depicts the percentage of the surveyed student
prepare thestudents for a STEM world.References[1] L. C. Cançado, R. L. Reisel, and M. D. Walker, Impacts of a Summer Bridge Program inEngineering on Student Retention and Graduation. Journal of Engineering Education, vol. 107, no. 1,pp. 30-40, 2018.[2] B. Louie, D. Knight, and J. Sullivan, “A drop-in tutoring program to support first-year engineering,”in 2011 ASEE Annual Conference & Exposition Proceedings, 2011, pp. 22.40.1–22.40.14. doi:10.18260/1-2--17322.[3] L. Redd, Institutional barriers affecting the academic and social development ofunderrepresented college students: Perspectives of administrators, University of Pittsburgh ETD,Jan. 30, 2019. [Online]. Available: http://d-scholarship.pitt.edu/35904/[4] D. Super et al., “Industry
deadline.Closing the Peer Evaluation LoopAfter each peer evaluation, the instructors analyze the ratings to assign individual grades. The ratingscale for all six questions is 1-5, with 5 corresponding to the top option (i.e., best performance). Foreach student, we average the ratings of their teammates for the six categories which gives us an overallpeer evaluation rating. Note that a student’s self-ratings are excluded. The result is an overall ratingof 1-5, with a rating of 3 being average. A rating of 3 equates to 85 points or a B on our scale.In addition, the instructors read all the comments to ensure they are professional and appropriate.Comments are edited as necessary. Once this step is complete, the evaluations are released back tothe students
& B. McMullin(eds.) Emerging issues in the practice of University Learning and Teaching, Dublin, All Ireland Society for Higher Education (AISHE).Escandell, S., & Chu, T. L. (2023). Implementing relatedness-supportive teaching strategies to promote learning in the college classroom. Teaching of Psychology, 50(4), 441-447.Hmelo-Silver, C. E. (2004). Problem-based learning: What and how do students learn?. Educational psychology review, 16, 235-266.Kolb, D. A. (2014). Experiential learning: Experience as the source of learning and development. FT press.Lattuca, L. R., Knight, D., & Bergom, I. (2013). Developing a measure of interdisciplinary competence. International journal of engineering education
. Joyce B. Main, Purdue University at West Lafayette (PWL) (COE) Joyce B. Main is Professor of Engineering Education at Purdue University. She received an Ed.M. in Administration, Planning, and Social Policy from the Harvard Graduate School of Education, and a Ph.D. in Learning, Teaching, and Social Policy from Cornell University. She is Co-Editor-in-Chief of the Journal of Engineering Education. ©American Society for Engineering Education, 2025 A focus on state-wide community college and technical college engineering transfer programs across California, Colorado, and GeorgiaIntroduction With college costs increasing faster than inflation over the last 20 years, some studentsface
report.Lab Activity 4: ToF Sensor Integration The goal of this task is to power your DC motors and servo motors based on the distance reading from your ToF sensor. 1. Restrict your sensor reading range between 0 and 100 cm. If a reading above 100 cm is detected, end the program and stop all motors and servos. 2. At 50 cm: a. Motor 1 is at 0% duty cycle b. Motor 2 is at 0% duty cycle c. Servo 1 is at 90 degrees d. Servo 2 is at 90 degrees 3. As the sensor readings get smaller than 50 cm: a. Motor 1 speeds up going CW b. Motor 2 speeds up going CCW c. At 0 cm, both motors are spinning at their maximum duty cycle for this activity (50%) d. Servo 1 decreases its angle e
Paper ID #49164Approaches for Efficiently Identifying and Characterizing Student Need Assessmentsin Two-Year CollegesDr. John Krupczak Jr, Hope College Professor of Engineering, Hope College, Holland, Michigan. Program Officer, NSF (2013-2016). Past Chair of the ASEE Technological Literacy Division; Past Chair of the ASEE Liberal Education Division; Senior Fellow CASEE, National Academy of Engineering (2008-2010).David R BrownDr. Amy B Chan Hilton, University of Southern Indiana Amy B. Chan Hilton, Ph.D. is the Director of the Center for Excellence in Teaching and Learning and a Professor of Engineering at the University of
Paper ID #46968BOARD # 405: NSF HBCU-UP: STEM Academy for Research and Entrepreneurshipat the University of Arkansas at Pine BluffDr. Walter C. Lee, Virginia Polytechnic Institute and State University Dr. Walter Lee is an associate professor in the Department of Engineering Education and the director for research at the Center for the Enhancement of Engineering Diversity (CEED), both at Virginia Tech.Dr. David B Knight, Virginia Polytechnic Institute and State University David Knight is a Professor in the Department of Engineering Education at Virginia Tech and also serves as Chief of Strategy in the College of Engineering
Michigan’s Center for Engineering Diversity and Outreach, a postdoc in Mechanical Engineering at UT Austin, and the director of and research associate in the Center for Equity in Engineering at UT Austin. Her engineering education research interests include servingness in engineering; assets-based teaching and learning; natural language processing and generative AI as qualitative research methods; and graduate education, faculty hiring and retention, and career pathways.Dr. David B Knight, Virginia Polytechnic Institute and State University David Knight is a Professor in the Department of Engineering Education at Virginia Tech and also serves as Chief of Strategy in the College of Engineering and Special Assistant to the
Paper ID #46039Enabling Successful Transitions to Higher Education for Students with DisabilitiesSeth Vuletich, Colorado School of Mines Seth Vuletich is the Scholarly Communications Librarian the Colorado School of Mines. Seth provides specialized support to graduate students through all stages of the research lifecycle. Prior to entering the field of librarianship, Seth was a professional woodworker and earned a bachelor’s degree in geology from the University of Colorado, Boulder. Seth earned his Master’s in Library and Information Science from the University of Denver in 2021.Brianna B Buljung, Colorado School of
. Schmeckpeper taught at a land-grant college, the University of Idaho, and worked as an engineer in design offices and at construction sites.Dr. Ashley Ater Kranov, Washington State University Dr. Ashley Ater Kranov is an adjunct associate professor in the School of Electrical Engineering and Computer Science at Washington State University.Dr. Michael B. Kelley P.E., Norwich University B.S.C.E., 1974, Norwich University M.S.C.E., 1976, (Environmental Engineering), Purdue University P.E., Commonwealth of Virginia, 1979 to present. Ph.D., 1996, (Environmental Engineering), Rensselaer Polytechnic Institute Colonel, US Army (Retired) O ©American Society for Engineering Education, 2025 Norwich
changes in their short-term and long-term goals. The schedule ofsurveys for UPSILON specifically is included in Appendix B at the end of this work in progresspaper.Considerations Throughout the Evaluation ProcessThe considerations represented in this work in progress were the first time in multiple years thatthe scale, types, and coordination of assessment has been revisited in a more intentional way –especially post-shutdowns of 2020-2022. In revisiting the evaluation of the summer campsseveral key considerations were central to ensuring the effectiveness and accuracy of theassessments. We present the below categories that were essential in exploring: What changes andconsiderations are needed for documentation, data, and collection to capture
, goals, and student needs. Some ofthe advising models documented in the literature include the following: (a) learning-centeredadvising approach (focused on connecting purpose of education with curriculum and degree),(b) engagement approach (focused on relationship building between student and advisor), (c)developmental advising approach (focused on student development and growth), (d)prescriptive academic advising approach (focused on checklists towards degree completion), (e)proactive advising approach (focused on students initiating advising meetings and advisorstacking those identified as at academic risk), (f) appreciative advising approach (focused oncreating positive interactions to support growth and academic planning), (g) flipped
number, modelnumber, manufacture date, etc. Refer to Appendices A.1 and A.2 for representative images.Device Accuracy Assessment. Each student performs a CMS50NA accuracy assessment, usinga Masimo MightySat® fingerclip pulse oximeter as a reference. They acquire at least 25 time-aligned measurement pairs (e.g., index and middle fingers) using the two devices. The studentcaptures images of (a) the devices while worn, with active displays, and (b) a wider view of thetesting area. Using Microsoft Excel, the student determines absolute and relative pulse rates andSpO2 errors for all the data pairs. They then calculate various statistical parameters, including anRMS value for absolute error for the overall data set, consistent with the ISO