from multiple donors to the University of Florida'sHerbert Wertheim College of Engineering's Foundation to support the GGEE programs as part ofthe EQuIPD project at the University of Florida. The research team would like to thank the leadingdonor to the program, Arnie Goldberg, for their support and appreciation toward creating STEMopportunities across Florida. The team would also like to thank Bud and Kim Deffebach, whosponsor programs in Brevard County, Florida. The researchers would like to thank their co-authors,program management, and research teams for their assistance and support throughout the summerprograms and research study. The researchers would also like to thank the student participants forparticipating in the summer program and
20 7-Nov 11 Pumps Ch. 13 21 9-Nov 11 Pumps Ch. 13 22 14-Nov 12 Forces Due to Fluids in Motion Ch. 16 23 16-Nov 12 Forces Due to Fluids in Motion Ch. 16 24 28-Nov 13 External Flow - Drag Ch. 17 25 30-Nov 13 External Flow - Lift Ch. 17 26 5-Dec 14 CFD / Project Ch. 9 27 7-Dec 14 Review n/aFigure 1. Sign-up sheet for student lectures overlaid on the course scheduleThe presentation is part of the first assignment, “HW0”, which is worth 12.5 points the same as anormal homework assignment. The presentation
served as a Teaching Assistant Professor at McMaster University from 2020 to 2022, where he played an integral role in curriculum development for materials science education within a project-based learning initiative. His outstanding contributions to materials science education and pedagogy practice were recognized and he was honoured to receive the ASEE - New Materials Educator Award in 2023. Since joining UVic in 2022, as the principal investigator (PI) of the Hybrid 3D lab, Dr. Yu has focused on the research goals of systematically investigating the mechanics of heterogeneous architected metamaterials and demonstrating their strong potential to solve engineering design challenges in a wide range of sectors
follow Buck et al. [20] here for its focus on higher education.to level 3 was partly based on literature showing that scaffolding is important, especially forfirst-year students; but also because the activity was time-constrained and had specific learningobjectives (unlike, for example, an open research project that may last weeks or months). Thechallenge in providing open inquiry is to meet the learning objectives while not explicitlyinstructing students on what to do.3 MethodThis section describes the activity that was newly implemented in 2019, and delivered over sevenyears, to introduce more inquiry into the activity and increase student engagement and learning.The constraints imposed were to keep the following constant: • Learning
DallasSami Melhem, Texas A&M University Sami Melhem is an undergraduate student pursuing a Bachelor of Science in Computer Science at Texas A&M University, where he is also planned to enroll in a concurrent Master of Science program in Computer Science. Sami serves as an undergraduate research assistant in the department of Mechanical Engineering under the guidance of Dr. Srinivasa. His research interests include the simulation of manufacturing processes including robotic sheet forming and magnetic polishing, and the development of AI-driven educational tools. Beyond academics, Sami is deeply involved in the Aggie Data Science Club, where he serves as Projects Officer, overseeing and mentoring multiple student
, “Continuous improvement in education: A toolkit for schools and districts.” Institute of Education Sciences, 2021.[4] L. Lazzell and M. Yatchmeneff, “2017-2019 UAA Alaska Native ANSEP LSAMP University Success research project final report,” Anchorage, AK, 2019.[5] M. Yatchmeneff, “A qualitative study of motivation in Alaska Native Science & Engineering Program (ANSEP) Precollege students,” Purdue University, 2015.[6] M. Yatchmeneff and M. Calhoun, “Exploring engineering identity in a common introduction to engineering course to improve retention,” 2017.[7] M. Yatchmeneff, “A qualitative study of motivation in Alaska Native Science & Engineering Program (ANSEP) precollege students,” 2015, [Online
B.Tech. in Building Structure from the Federal University of Technology, Akure, Nigeria. Michael has extensive professional experience managing large-scale heavy construction and fac¸ade projects, including high-rise and industrial developments across West Africa, having held key roles in the field. His research interests include the integration of digital tools in construction education, resilient building design, and asset management in civil infrastructure. He is passionate about bridging academic knowledge with real-world application and is committed to developing innovative, cost-effective, and sustainable construction solutions.Tolulope Abiri, Morgan State University Tolulope Abiri is a graduate student in Civil
for reported motivations and ten sub-codesfor reported barriers. Themes, grouped sub-code names, and descriptions are presented in Tables2a and 2b along with number of responses with each code and the Fleiss 𝜅 for the three coders.Table 2a: Codes counted for the perceived goals and benefits to attending office hours, out of 106 responses Theme Sub-code Description: Students attended office hours Count Fleiss’ 𝜅 because they… Academic Assignment- …need to receive assistance on homework, project, 57 0.99 focused or other assignment Study Unspecified …have a desire to solidify
context-specificalterations to content assessments and tailored experience questions, this assessment framework can beadapted to evaluate tools for teaching in broader engineering contexts. As personalized educationbecomes more prevalent, assessment methodologies such as the framework proposed here will increase invalue.LimitationsThe initial study design for project AREEA was to have eligible participants be separated into threeseparate groups. In addition to the two groups mentioned in the Experimental Plan, we intended to have athird group test a 2D version of the HAILs in a computer lab setting. This group would be a control forGBL, as they would not experience augmented reality but only game-based learning. Unfortunately, dueto time
that may connect to a student's academicengagement and performance such as number of units completed in previous semester, gradesfrom previous semester, and tuition fee payment status with an accuracy of 85.9% for thepredictions on the test data: 94.5% correctly on the prediction of non-dropouts and 67.9%correctly on the prediction of dropouts. Furthermore, the same set of data was processed by theMulti-Output Classifier neural network resulting in accuracy scores ranging from 83.5% to94.2% for the five target variables, providing valuable insights to educators for advocatingtailored support for at-risk students.IntroductionMultiple research projects have shown the effectiveness of using early warning for supporting at-risk students in
students. Strategies to provide additional support for these studentswere proposed. While this study was carried out with data from only one Chemical EngineeringDepartment at one university, it presents information that will very likely apply to otheruniversities and engineering degree programs.References[1] P. Bransberger, C. Falkenstern and P. Lane, “Knocking at the college door: projections ofhigh school graduates, Western Interstate Commission for Higher Education (WICHE), 2020.[2] A. Dorn, “More teens are skipping college; here’s what they’re doing instead,” NewsNationNow, April 29, 2024.[3] C.R. Bego, J.L. Hieb and P.A. Ralston, “Barriers and bottlenecks in engineering mathematics:math completion predicts persistence to graduation,” 2019
) metallurgy, CAD made. I’ve always been projects. focused more on the aesthetics of crochet more than how it can impact the material properties of a fabric. It introduced me to the potential that
review of the course curriculumshowed that vector topics were indeed covered in the physics course. Yet the findings here showthat a significant proportion of students were not able to demonstrate the most basic of theseskills post-Physics. The investigative team has been involved in an ongoing curriculumimprovement project to seek ways to address this deficiency. On the other hand, there has alsobeen an assumption that fundamental vectors skills are imparted in upstream math courses suchas Pre-Calculus or somewhere in the Calculus sequence. Review of the curricula of theinstitution’s math courses and discussion with administration in the math department hasindicated that these courses do not cover vectors, and it is not until Calculus III
, curriculum, and performgrading tasks. If it cannot be trusted to answer MCQs at higher cognitive levels in aerospaceengineering, should we trust it to tutor students or to grade their work? Can it effectively designlessons and projects that authentically assess a student’s knowledge and engineering skills? Ifstudents become overreliant on ChatGPT, how will it affect the creativity that is needed inengineering? These are questions that will need to be grappled with in the upcoming years asgenerative AI becomes more pervasive and are areas that would benefit from future study.References[1] “Facts and Figures : About Us,” College of Engineering - Purdue University. https://engineering.purdue.edu/Engr/AboutUs/FactsFigures/school_facts.html[2
Engineering Education. His research focuses on preparing the next-generation STEM workforce through student academic enrichment and workforce development training programs. For this, he has received multiple federal, state, local, and foundation grants. He is the Founding Director of NJIT’s Grand Challenges Scholars Program. He also has worked on several research projects, programs, and initiatives to help students bridge the gap between high school and college, community college and university, as well as to prepare students for the rigors of STEM education, especially mathematics. He is also involved in various engineering education initiatives focusing on the integration of novel technologies into the engineering
Paper ID #47753Redefining Electrical and Computer Engineering Faculty with LongitudinalSupport for Women and Underrepresented MinoritiesDr. Barbara E. Marino, Loyola Marymount University Dr. Barbara E. Marino is an Associate Professor in the Department of Electrical and Computer Engineering at Loyola Marymount University. Dr. Marino received the B.S.E.E. degree from Marquette University and the M.S. and Ph.D. degrees in electrical engineering from the University of Notre Dame. Dr. Marino has many years of industry experience including work at the Naval Research Laboratory in Washington, D.C. on projects related to military
experiment / failureDesign. Edu., project that forces them2016 to confront failure often.[27], ASEE Examine interventions to US First year Quantitative • attrition,Ann. Conf., reduce attrition. engineering Mathematics retention, and2016 students, 2 years intervention persistence[28], REEN Identify the pedagogy of UK First and second Mixed • attrition,Ann. Symp., failure and examine the year engineering Data analytics retention, and2017 issues behind ‘failure’ students, 2 years
, body-based interactions with learning content can facilitate new understandings, and how games and simulations can be effectively designed to take these types of interactions as input. He has been PI of several NSF-funded research projects examining how people learn in technology-enhanced environments, and his research lab has created several prototype digital games and simulations with museums and classrooms across the US. ©American Society for Engineering Education, 2025 The Power of Movement: Exploring Gestures as Tools for Engineering Students Conceptualizing Statistics Junior Anthony Bennett1, Tiffany Reyes Denis2, Sourabh Garg2, Logan Hillary Lauren2
scope Determine Define screening Coding the Condense and of project and relevant sources process literature and organize all focus for search of literature record vital information information collected into a report Outcome Inclusion and References for Eligible Literature data for Identify current exclusion criteria study references analysis literature trends
activities that explore spatialreasoning, such as mapping exercises, geometry projects, or community walks that allowstudents to analyze and visualize mathematical concepts in their surroundings. Wood’s [24]research highlighted the effectiveness of collaborative discourse in the classroom based onreal-world problems to move their mental effort from contextual understanding to a moreabstract or formal understanding of math itself. Besides contextual discourse, Brizuela andStrachota [20] encouraged the use of visual tools showing real-world scenarios, allowingstudents to explore ideas with joy and curiosity, making learning more meaningful andapplicable to their lives. Resnick’s [21] shifted the idea from visual tools towards the focuson mental models
/9781003287483-22.[2] B. Smith, Demystifying the higher education system: Rethinking academic cultural capital,social capital, and the academic mentoring process, Ph.D. dissertation, The University ofWisconsin-Madison, 2004.[3] B. Tekerek and M. Tekerek, “Emotional intelligence in engineering education,” TurkishJournal of Education, p. 88, Apr. 2017, doi: 10.19128/turje.306499.[4] C. O. Skipper and S. Brandenburg, “Emotional intelligence and academic performance ofengineering students,” Engineering Project Organization Journal, vol. 3, no. 1, pp. 13–21, Jan.2013, doi: 10.1080/21573727.2012.738669.[5] X. Zhou, "Assessment and analysis of emotional intelligence in engineering students,"2010.[6] H. Shuler, V. Cazares, A. Marshall, E. Garza-Lopez, R
Large Language Models (LLMs). Taiwo is known for his ability to collaborate effectively within and across organizations to meet project goals and drive transformative results. He excels in leading technical teams, offering strategic IT consultations, and implementing solutions that enhance productivity.Lexy Chiwete Arinze, Purdue University at West Lafayette (COE) Lexy Arinze is a first-generation PhD student in the School of Engineering Education at Purdue University and a Graduate Research Assistant with the Global Learning Initiatives for the Development of Engineers (GLIDE) research group. Lexy’s research interests include early career engineers, Artificial Intelligence, experiential learning, and global
and practice fosters conceptual change[4, 25]. Effective instruction involves identifying misconceptions and using targetedscaffolding—such as simulations or design projects—to refine students’ mental models throughexperimentation and validation [28].Methods of tracking misconceptionsGoris and Dyrenfurth [28] emphasized that misconceptions in engineering education arise fromthe interconnected domains of science, technology, and problem-solving, deeply rooted instudents’ prior experiences and mental models. These misconceptions are resistant to change,requiring targeted diagnostic methods and interventions guided by conceptual change theories,such as cognitive conflict. Goris and Dyrenfurth [28] highlight the necessity of
Beverages Pvt. Ltd. and Saint-Gobain India Pvt. Ltd. (Research & Development). His interest in areas such as improvement in instructional techniques, faculty perspectives and teaching methodologies, drove him towards the domain of Engineering Education. Specifically, the question of how engineering education can be made more effective and engaging fascinated and motivated him to pursue research in this domain. He is working with his major professor on an NSF funded project dealing with communities and relationships that enable and empower faculty and students in engineering.Deborah Moyaki, University of Georgia Deborah Moyaki is a doctoral candidate in the Engineering Education and Transformative Practice program
physics and engineering education. In addition to his teaching and research endeavors, Mr. Halkiyu has actively engaged in various community service projects. ©American Society for Engineering Education, 2025 Time Management Challenges Faced by Online Students in Higher Education: A Mixed-Methods StudyAbstractThis mixed-methods study explores the time management challenges encountered by onlinestudents in higher education, focusing on how these challenges vary across demographic groupssuch as age, gender, ethnicity, and educational background. As online course enrollmentscontinue to grow, it is essential to understand these challenges to design effective instructionalinterventions
project.4.1 Introductory SurveysEach student was given an introductory survey during the first week of the class. This surveyasked for demographic information (gender, prior programming experience (PPE), year in school,GPA, and major), general information (if the student was also taking the lab associated with thiscourse and how many hours of prior programming experience they had), as well as what grade theyexpected to receive in the course by the end of the semester. Students were given a drop-down menuof achievable grades in the class and asked to choose which grade option they expected themselvesto receive. Finally, the students were asked questions about their perceptions of programming andlearning preferences. For each question, five
. Doubting of actions (DA) is another prevalent feeling among engineeringstudents regarding the sufficiency of their projects and their level of satisfaction. The next sectionwill explore the limitations of current scales within the engineering domain.6 Limitations of Current Perfectionism Scales for Engineering StudentsExisting perfectionism scales, which are commonly employed to assess perfectionism, often focuson broad populations, and their dimensions are extensively used (such as [10], [14], [36]). First,none of the existing scales directly focuses on measuring perfectionism among undergraduateengineering students. Secondly, currently, there is no currently existing scale capable of measuringthe dimensionality of perfectionism
earned a graduate degree in engineering themselves.Participant recruitment followed a snowball sampling approach. After interviewing associatedeans and faculty members for a different aspect of a broader project focused on nonacademiccareer pathways of graduate students in engineering, we requested that they recommend alumniin industry or government who could offer insights about how graduate education prepared themfor their current work. Some of the participants who agreed to this interview were recent alumniacross engineering disciplines, and others were senior executives within structural engineering.Snowball sampling was further employed during the interview process, as participants wereasked to recommend colleagues who might also contribute
witheventual success in the field after graduation [4-6]. Some universities have implementedintervention strategies by gearing curriculum and department culture towards supportingstudents’ development of their individual engineering identities with this known promise ofstudent success [6]. Some major curricular changes surround the emphasis on design problemsused throughout engineering courses that inherently help students to feel more like an engineerafter completing the project [7]. Because the act of problem-solving correlates with the directdevelopment of all three of Godwin’s facets of engineering identity, providing more opportunityfor students to solve real-world problems correlates to retention [8] and success in the field [9].Studies have