engineering PE exams, 2) required courses inthe average civil engineering curriculum cover 48% to 68% of the topics on each of the fiveNCEES civil engineering PE exams, and 3) most civil engineering curriculums have theflexibility to cover 82% to 95% of the topics on each discipline specific PE exam if specificelectives are included. Students who plan to take the PE exam in their first year after graduationmust carefully plan their undergraduate elective courses around the specific topics on theNCEES PE examination of their choice.IntroductionOn April 1, 2024, the National Council of Examiners for Engineering and Surveying (NCEES)eliminated the common breadth format on the Principles and Practice of Engineeringexaminations (PE exams) in all five
as a lesson plan, amongothers; this points to an ill-structured design process. These examples highlight the potential ofsupporting first-year students to set requirements as part of framing engineering problems. Yet,they offer limited insight into the actual processes through which this occurs. The current studyaddresses this gap.MethodologyStudy designWe used design-based research (DBR) study, a methodology developed in the learning sciencesthat jointly develops and studies a learning design while also testing a theory of learning in theform of conjectures [16, 17]. This approach relies on instantiating theory into a design andtesting under real-world conditions, iteratively, with careful analysis of learning processes,learner
the curriculum at HBCUs. One of the main hurdlesis the limited resources that many HBCUs face, including outdated technology and a lack offunding for game development or acquisition [9]. For GBL to be effective, schools need the righttools and infrastructure, as well as support for teachers who need to be trained in how to use thesenew methods. However, with funding often tight at HBCUs, it might not always be feasible toinvest heavily in new technologies. Another concern is making sure that games align well withcourse objectives and aren’t just flashy distractions. Educators have to carefully plan how gamesfit into the curriculum without compromising on the quality of the content [10]. Plus, not everystudent will respond to game-based
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
involvedparticipants providing the percentage of time they spent in class on different activities (e.g.,lecture, small group discussion, videos) and ranking both their and the department’s readiness tochange when thinking about teaching innovation (on a scale of 0-10, with 0 being “no thoughtsabout it” to 10 “taking action, such as planning activities”). Respondent totals per survey distribution round are shown in Table 1. Ultimately, therespondent totals were low, but respondent totals did stay somewhat consistent between Rounds3-8. Efforts were made to increase the respondent totals, such as sending reminder messages tonon-respondents, enabling respondents to go back to the survey if they could not complete it inone sitting, attending faculty
type of experiences, finding that longer-term involvement isoften more beneficial for learning outcomes and skill development [7], [8], [9], [10]. However,these individual ELA assessments provide limited opportunities for comparing experiences toidentify the most effective approaches for preparing students for their post-graduation goals.Additionally, while fewer studies have evaluated the impact of breadth of ELA participation,findings suggest that engaging in a variety of ELA enhances interpersonal skills [11], andsignificantly predicts future career plans and early job attainment [12], [13]. These studieshighlight the need for a more detailed understanding of the post-graduation outcomes associatedwith ELA participation.The current study
section outlines demographic information about the students. The first demographicrecorded is the student major, shown in Figure 1. Out of the twelve participating students, ten aremechanical engineering (ME), one is electrical engineering (EE), and one is studying engineeringphysics (EP). Figure 2 shows the academic year, or how far the students are in their degree program.Two of the students are in their 2nd year, two are in their 3rd year, four are in their 4th year, andfour have been studying at the university for five or more years. The next two demographicsinquired about the student’s likelihood of continuing participation in the team during the 2024-2025 academic year. Figure 3 shows how many of the students plan on continuing
helpcompare resource utilization patterns and identify the role of different project spaces insupporting students’ academic and personal projects. Survey D includes the workshop and willbe administered to Cohort 2025. TABLE I SUMMARY OF SURVEY ADMINISTRATION PLAN Cohort 2024 Cohort 2025 Fall 2024 / Fall • Survey A • Survey A 2025 • Survey B • Survey B • Survey C (Cohort 2024 only) • Survey D (Cohort 2025 only) Subsequent At the end of each subsequent From Spring 2026–Fall 2028, Semesters semester (Spring 2025–Spring surveys B
course schedule (Table 3.1) includes preparation for professional andethical conduct in a clinical setting, opportunities for sharing and dissemination of experiences,training in engineering design cycle, prototyping, and module development for future work.Table 3.1: Weekly schedule for SIDE course. Course plan includes preparatory training forprofessionalism and professional conduct in a clinical setting, as well as reporting from clinicalexperiences, and integration of clinical experiences into the product development lifecycle. Week Content Reporting/Submissions 1 Introduction, Responsible Conduct in Research, Ethics CITI Certification
Paper ID #46788Civil Engineering and the Entrepreneurial Mindset – Cultivating TeachingPractices that Enhance Entrepreneurial Minded LearningDr. Matthew D. Lovell P.E., Rose-Hulman Institute of Technology Dr. Matthew Lovell is a Professor in the Civil and Environmental Engineering Department at Rose-Hulman Institute of Technology, and he currently serves as the Senior Director of Institutional Research, Planning, and Assessment. He received his Ph.D. from Purdue University, and he holds his PE license in Indiana. Matt is very active with respect to experimentation in the classroom. He greatly enjoys problem-based learning
of the lessons were the mostintimidating to implement. One teacher, for example, expressed nervousness about leading the“imagine and plan” phase, saying, “I was actually most nervous to do the imagine and planportion because I was like, ohh, how’s this gonna go?” However, her doubts were quicklydispelled as the students exceeded her expectations: “They actually did come up with a plan andthen they executed the plan, and that ended up being the easiest lesson we did. They were likethe most engaged in that lesson, and that was so amazing.”Changes in Confidence and Beliefs about Teaching Engineering Over the course of the unit, the participants were able to realize their students’capabilities as well as their own. Throughout the project
. Topic In-class discussions & activities Assignment Project Charter • Identify the elements of project • Choose one project, can be thesis, charter that are relevant to your and start your own project charter thesis research • Write down a clear goal with • Write down the key milestones objectives and deliverables for your thesis • Start to map out all elements, including a contingency plan 4 • Join group
growthconditions, assignments were spread out on various days with pre-lab and post-lab requirementsensuring students’ active engagement with application-oriented bioprocess as they conducted thebioreactor experiment for the first time. The tasks required during the various days are:Pre-Laboratory DayStudents work in teams to prepare and submit a preliminary report. In this report, theydemonstrate their familiarity with the process equipment, objectives, parameters to beinvestigated, and propose an experimental plan. They also discuss laboratory safety, addressingchemical, physical, and biological hazards, and perform sample calculations. This assignmenthelps students become acquainted with the setup and background, preparing them to conduct theexperiment
participants pursue graduate study? RQ3. What are the educational interests of students who apply to Early Discovery? Does Early Discovery reach students who have never considered graduate school, or serve to reinforce an existing graduate school interest?This paper provides longitudinal data of the impact of different program formats to engagefreshman and sophomore level students, and it provides important aspects for professionals toconsider when planning to engage younger students to think about Graduate School.MethodsEthics StatementMethods were approved by the Purdue Human Research Protection Program and InstitutionalReview Board (IRB), and all surveys were completed in accordance with relevant guidelines
before engaging with AI tools. Assignments should includevalidation components where students verify AI outputs against fundamental calculations andcritically evaluate the reasonableness of AI-generated solutions. Assessment methods shouldevaluate both tool proficiency and conceptual understanding to ensure that technological skilldoesn't mask deficiencies in fundamental knowledge.The financial implications of AI integration extend beyond initial implementation costs.Educational institutions must consider ongoing expenses for software licensing, hardwareupgrades, and technical support. Various strategies can help manage these financial challengeseffectively. Institutions can develop phased implementation plans that spread costs over
workshop’s impact.Evaluation and Impact AssessmentThe study evaluates workshop effectiveness based on participant responses and engagementlevels. Data from the pre-and-post surveys are analyzed to identify trends in belonging,awareness, and perceived retention. Thematic analysis of qualitative responses helps uncover keythemes related to mentorship support and professional identity development.Workshop Implementation Status The workshop series has not been implemented yet. The design phase is currently underway,with plans for initial sessions to be launched in the near future. Data collection will commenceonce the workshops are conducted, and findings will be analyzed to assess their impact onfaculty belonging, awareness, and retention. This
participants. Bridging the program content to classroom application remainsa challenge; one-on-one planning sessions and ongoing academic-year support may help. Table 1: Summary of Results Pre-test Post-test Construct Mdn./Std. error Mdn./Std. error W p Content Test (% correct): Pre to Post 40.00 (3.29) 66.67 (3.81) 3 0.001 Content Test (% correct): Pre to Post (9 mo.) 40.00 (3.29) 53.33 (3.41) 12 0.007Feedback suggests tailoring the pSEMI and ZeroToASIC speaker series to participants’backgrounds, making sessions more interactive. Additionally, incorporating informal
fromparticipants regarding their knowledge, skills, and overall satisfaction indicates that the programsuccessfully met its objectives.To foster a cohesive program environment and ensure that all participants felt welcome andvalued, various activities were organized throughout the day to encourage student interaction.Shared activities, such as light breakfasts, progress reports, and daily planning, enhancedengagement among participants. Figure 6 illustrates student perceptions regarding the quality ofinteractions within the research group. Fig. 6: Perceptions of quality of the interactions with the research groupConclusionThe first cohort of participants in the REU site at the University of Houston-Downtowndemonstrated significant progress
, 18 scholars were selected instead of the initially planned 25.Demographics Table 1: Scholar Information for Cohort 1 Gender Race1 Department2 1st Gen Cohort Total3 M F A AA H W BME ChE CME ECE CS MIE U Y N Fall ‘24 9 9 3 3 10 2 2 2 1 4 4 4 1 11 7 181 Race - A: Asian, AA: African American, H: Hispanic, W: White.2 Department - BME: Biomedical Engineering, ChE: Chemical Engineering, CME: Civil,Materials, and Environmental Engineering, ECE: Electrical & Computer Engineering, CS:Computer Science, MIE: Mechanical and Industrial Engineering
lessons around extreme weather problems specific to theirplace. The second of these PLCs afforded participants time to work collaboratively in grade-levelbreakout rooms to finalize their CRED lesson plans. Participants were also given access to avariety of electronic supports via a Google Classroom and materials for teaching these lessons.MeasuresWe administered the Teacher Efficacy and Attitudes toward STEM (T-STEM) Survey (FridayInstitute for Educational Innovation, 2012) before and immediately following the summer PLinstitute. Participating teachers completed the Engineering Teaching Efficacy and Beliefs (11items) and the Engineering Teaching Outcome Expectancy (9 items) subscales of the T-STEMSurvey via Qualtrics. A delayed post-PL survey was
the development of the debugging training curriculum to be implemented in laterresearch stages.Gender GapAlthough the sample size is too small for definitive conclusions, data from the first group ofstudents suggests an emerging trend. All three female (100%) students successfully debugged themisoriented op-amp circuit within 30 minutes, compared to 5 of 23 (22%) male students. Onlymale students attempted the incorrect equipment settings and component specification problems.Are female students better at debugging? It may be too early to tell. If this trend persists as thesample size grows, we plan to investigate other potential contributing factors, such as finalcourse grades and composite GPAs, before determining whether a baseline
practices within their home institutions and beyond.5. Sustainability – a team that ensures the long-term vision and viability of the Engineering PLUS Alliance and its mission beyond the immediate grant funding.6. CIDER (Continuous Improvement through Data, Evaluation, and Research) – a multidisciplinary team of data scientists, researchers and evaluators that support and lead the data-focused research and evaluation activities of the Alliance.ImpactsImplementation and scale of evidence-based practices across all partner institutions is central tothis Alliance’s efforts. stEm PEER Fellows, informed by data, are guided in their development ofan Action Plan to support the design and scale of strategies that impact recruitment, retention
onSemiconductor Processing and Metrology Techniques. Another objective is to enhance their careerreadiness through elevator pitch interview sessions and resume preparation. We plan to increasethe number of scholars involved and expand access to university-wide the resources. For futureresearch, we will explore the broader impact of learning teams as cooperative learning, role ofnear-peer graduate mentors in improving self-efficacy, as well as well as the impact of careercompetency.AcknowledgmentsThis material is based upon work supported by the National Science Foundation under Award No.2030861.References[1] “College Navigator - Polk State College,” Ed.gov, 2022.https://nces.ed.gov/collegenavigator/?q=Polk+State+College&s=all&id=136516#retgrad
content,teach it as if to a child, fill the gaps in understanding or explanation, and further simplify [5].This technique was loosely adapted to evaluate the student’s understanding of instructions andconcepts. The new steps were the following: a. Study research material and instructions related to the upcoming week’s tasks. b. Reteach material and instructions back to the group in your own words, signaling comprehension. c. Pose questions and incorporate feedback to fill gaps in student’s understanding. d. Develop and solidify a plan for the upcoming week based on refined understanding. The student was also encouraged to focus on the foundational concepts from the initialpapers and constantly realign his plan with the goal of
factors that they could control. Suchcontrollable factors might be: studying habits of planning, monitoring, and regulation, as well asother existing skills, related to self-control.Students who scored highly on the Metacognitive Self-Regulation scale were also more likely tobe organized in their study methods and employ elaboration strategies during their study. Theybelieved that they had built systematic connections between the knowledge that was beingabsorbed, rather than purely reciting back course material. This correlation should not vary bysemester or by instructor, but we will analyze this pattern in the following sections. For each termin the study, the medians, inter-quartiles, minima and maxima are shown (as well as the
progress. Moving forward, I plan to deepen the analysis byexploring intersections between participants’ disciplinary specializations and their ethicalframeworks. Additionally, I will examine how institutional messaging, mentorshippractices, and policy structures shape the development of ethical reasoning duringdoctoral education. The ultimate goal is to offer concrete recommendations forembedding ethics more meaningfully into the fabric of engineering education at thedoctoral level.ReferencesABET. (n.d.). Criteria for accrediting engineering programs, 2019–2020.https://www.abet.org/accreditation/accreditation-criteria/criteria-for-accrediting-engineering-programs-2025-2026/Bucciarelli, L. L. (2008). Ethics and engineering education. European
, students (1) designed a data-driven approach to learn about carbon dioxideemissions and (2) planned for the quantitative analysis of decarbonization strategies. The firstpart involved students collecting data from different carbon dioxide sources with an Arduinosensor. Then, they used the data to practice data visualization and analyze the impact of thoseemissions on the environment. The second part involved students estimating the impact thatspecific decarbonization strategies could have in NM. For example, if a student chose thestrategy of switching to all electric vehicles in NM, they would estimate how much carbondioxide could be reduced if that strategy is fully implemented in 2050. Additionally, theyestimated how the strategy might change if
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
Appendix A.The team also surveyed students regarding their future plans and motivation after the course,with an emphasis on activities related to research and entrepreneurship (Figure 2). In bothcohorts, students reported an increased likelihood of contacting a professor about undergraduateresearch or applying for a summer position focused on research after completing ESE activitiesin their course. Notably, a greater share of students in the full intervention cohort, which includedvideos, described themselves as being somewhat or extremely more likely to (i) apply to anindustry internship or position focused on research (partial: 54%; full: 75%, Figure 2), (ii)contact a professor about an advertised undergraduate research opportunity (partial: 52
career planning tools to provide end-to-end solutions.ConclusionDeveloping a recommendation engine leveraging GPT-4 and the RAG method the authorsdemonstrated a significant advancement in personalized learning solutions. By utilizingOpenAI’s text-embedding-3-large model and Pinecone’s vector database, the system efficientlyaddresses the challenges of personalization, scalability, and accuracy in courserecommendations. Integrating OpenAI's assistant API further enhances its capabilities, offeringseamless interactions and context-aware suggestions.Our results highlight the potential of LLMs to transform how individuals discover and engagewith learning opportunities. The positive outcomes underline the benefits of adopting cutting-edge AI