incorporating the practice and development ofprofessional skills into their first-year engineering courses and projects to better prepare studentsfor entering the professional workplace as they seek out internships and co-op experiences intheir second and third years (e.g., [4], [5]).While a primary purpose of first-year engineering programs is to aid in preparing students forsuccessful transitions into their specific engineering disciplinary classes with foundationalengineering skill sets and knowledge, first-year engineering courses are also well-positioned toaid in students transitions between two starkly different educational contexts: high school tocollege. The transition from high school to the first year of college in an engineering programcan
environments that make use ofdarts or target metaphors [24], or dynamical displays of stochastic processes such as a digitalGalton board as an analogy for manufacturing variation [25]. There is an opportunity to createdigital environments that allow users to virtually operate equipment, gather and analyze data,interact directly with SPC tools like run charts and control charts, and better prepare students foron-the-job problem solving. In this work we leverage the advantages of digital environments tocreate a series of interactive simulations and games to teach statistical process control in amanufacturing environment.2. Development of Process Control Interactive Simulations and Web GameFor this project, the goal of using interactive web simulations
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
system design, manufacturing, and their respective education. His system design research focuses on developing computational representation and reasoning support for managing complex system design through the use of Model Based approaches. The goal of Dr. Morkos’ manufacturing research is to fundamentally reframe our understanding and utilization of product and process representations and computational reasoning capabilities to support the development of models which help engineers and project planners intelligently make informed decisions. On the engineering education front, Dr. Morkos’ research explores means to improve persistence and diversity in engineering education by leveraging students’ design experiences
studentsparticipated in the study. We interviewed 23 S-STEM scholars and conducted four focus groupswith 16 students.Data collectionThe data were collected during the Fall semester of 2023. One of the primary components of theS-STEM program is bi-weekly meetings on Fridays that scholars are encouraged to attend.S-STEM program leadership encouraged the research to schedule interviews for an off-Friday inwhich scholars did not have a meeting because scholars are in the habit of coming to campus tomeet with advisors on Fridays. The focus groups were scheduled two weeks later on another off-Friday. The research team attended a bi-weekly meeting and explained the project and recruitedstudents to sign up for an interview or focus group slot using a shared Google
it to “check NFL player stats” or“chat when bored.”Figure 3: Summary of students responses to survey question “provide examples of how you usedAI for a non-academic purpose”.In addition, AI is used for problem-solving and personal assistance, such as troubleshootingcode, solving math problems, or seeking advice on personal issues. Students highlighted itsutility for tasks like “troubleshooting code for a personal project” or asking for“recommendations in a new country.” On a scale of 1 to 5, students expressed significant interestin learning about AI and its applications in engineering and computing, with an average interestrating of 4.1 and approximately 50% rating their interest as 5 (Very Interested). When askedabout their expectations
/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
domain-specific knowledge and skills to successfully to identify organizational needs and problems; knowledge in a shared domain with the Ideator and Implementer to be able to communicate concepts to both of those roles; knowledge of systems design and management; knowledge of enterprise systems; knowledge of the overall economic development process S- Skills in: communication, understanding people and motivation; organizations (building, and managing); managing projects; identify others strengths and weaknesses to best place them within the organization; mediation; A- Ability to: think strategically (e.g. at the big picture level) and also procedurally/sequentially; organize; identify, create and manage
keep expanding, refining, or summarizing to adhere to the norms of the disciplinaryjournals. I think this strategy can help make methods writing less daunting and avoidperformativity. It also allows the flexibility to innovate and adapt and then represent thoseinnovations transparently to your reader.If you are midway through a project or at the end of one and draw a blank regarding what,beyond the basics, to write about your methods, I hope the reflection questions in Table 1 helpelucidate some directions that can be taken even late in a study. For example, reflecting onresearch questions, deciding what they mean to you, elaborating the actual analysis process toanswer them—this is a crucial and continual reflection. At any time, asking and
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
JEE special reports “The National Engineering Education Research Colloquies” and “The Research Agenda for the New Discipline of Engineering Education.” He has a passion for designing state-of-the-art learning spaces. While at Purdue University, Imbrie co-led the creation of the First-Year Engineering Program’s Ideas to Innovation (i2i) Learning Laboratory, a design-oriented facility that engages students in team-based, socially relevant projects. While at Texas A&M University Imbrie co-led the design of a 525,000 square foot state-of-the-art engineering education focused facility; the largest educational building in the state. Professor Imbrie’s expertise in educational pedagogy, student learning, and teaching has
electro- chemical energy storage systems.Dr. Corin L. Bowen, California State University, Los Angeles Corin (Corey) Bowen is a postdoctoral researcher in the College of Engineering, Computer Science and Technology at California State University - Los Angeles, where she is working on the NSF-funded Eco- STEM project. Her engineering education research focuses on structural oppression in engineering sys- tems, organizing for equitable change, and developing an agenda of Engineering for the Common Good. She conferred her Ph.D. in aerospace engineering from the University of Michigan - Ann Arbor in April 2021. Her doctoral research included both technical and educational research. She also holds an M.S.E. in aerospace
common academic responsibilities and goals such asmajors, classes, and projects or assignments or individuals whom the participant considers to bea friend. The assumption that friends be considered as peers is acceptable given that references tofriends in participant narratives referred ostensibly to individuals who belonged to the samegeneration as the participants. Shared objectives and responsibilities allowed participants todiscuss specific issues such as the implications of academic choices on access to futureopportunities in education and career. Dinar’s comments on mentorship reflect this view of peersas mentors: “Mentors? Uh, I think my peers, like who I have classes with and same major as me,we- I think we kind of help each other out
research projects and jobs inthe field (both on campus and off) as being factors in one’s chance of being admitted. Of all ofthese, however, grades seemed to be what most students thought was given the greatest weight inthe decision about their futures in engineering. This is not surprising, given that much of the Page 12.428.9assessments given by advisors relied heavily upon GPA. The other things, like activities played asupporting role. They were things used to bolster or prop up one’s chances, if one’s GPA was notbelieved to be strong enough.The students who were most confident in their chances, like Joe and Renee, talked very little, ifat all
) Biomaterials Science: AnIntroduction to Materials in Medicine and Dowling’s Mechanics of Materials books wereespecially useful references 28,29. Callister’s Fundamentals of Materials Science andEngineering text also contains a web based supplemental chapter 30 that is helpful as is theUniversity of Cambridge’s on-line Teaching and Learning Package (TLP) on the structure ofbone and implant materials 31. In fact, having the students complete this well-developed andinteractive TLP as a homework assignment or in-class project (if computers are available) is anexcellent way to introduce your students to biomedical materials and design. Dr. Pruitt’s Page
to favor some parts of their brain more than other parts in learning.Indeed, Kolb has devised a learning-styles inventory (LSI), which can determine the test-taker’spreferred learning style.1,23 Theoretically, this preference reflects something about the way inwhich a student would like to learn, but does not limit learning to only one part of the cycle.With this information in hand, it may be possible to determine why some students get excited byand excel at certain aspects of a project, whereas other aspects of the same project seem boringor too difficult. Since effective learning requires the whole brain,18 one goal of InnoWorks is tohelp students develop those parts of the learning cycle that they are less inclined to use.It can be a
Ennis, University of Colorado Boulder TANYA D. ENNIS is the current Engineering GoldShirt Program Director at the University of Colorado Boulder’s College of Engineering and Applied Science. She received her M.S. in Computer Engineering from the University of Southern California in Los Angeles and her B.S. in Electrical Engineering from Southern University in Baton Rouge, Louisiana. Her career in the telecommunications industry included positions in software and systems engineering and technical project management. Tanya most recently taught mathematics at the Denver School of Science and Technology, the highest performing high school in Denver Public Schools. Tanya is currently a PhD candidate in the School of
ininstructional activity may influence these student perceptions, both through the quality withwhich the task is carried out and via the social influence of projected confidence [45]. Therefore,TSE can be instrumental in enabling TAs to meet student expectations and also in strengtheningthe beneficial outcomes that emerge from successful interactions with them.Our study focuses on the role of TSE in engineering classrooms that are managed by TAs anddiffers from existing studies in several ways. First, the research on TSE in higher educationdescribed above has relied on teachers’ self-report of their own sense of self-efficacy. Researchexamining links between teacher self-efficacy and student perceptions is limited [46] and to ourknowledge has not been
prevalent in engineering projects. The Dramatistsseemed to have a consistent role-based infrastructure that different plays run atop of, each playassigning its own roles to actors and making its own demands of the different technical positions.I recognized this model as being analogous to an engineering administrative one: assigning aproject manager, a software lead, a senior developer for backend, etc. Still, the students I spoketo saw the structure as meaningfully distinct. This distinction is perhaps explained by somestudents’ inexperience with industry teaming structures. However, I believe more is going on.Perhaps, the particulars of the Dramatists’ system is flexible enough so as to encourage effectiveteamwork, whereas hierarchies on
is important tounderstand how “STEM” outreach activities, that often involve robotics, coding, and design,align with actual workforce demands/projections in the industry of manufacturing as it can spana wide range of careers in regard to the individuals who work to design, produce, transport, andsupport the company’s products. Therefore, this study focused on investigating children’sperceptions of manufacturing before and after an industry-education initiative titledManufacturing Week, that was developed through a regional commerce group and co-hosted byseveral large manufacturers in one Midwestern town located within a vibrant manufacturingecosystem. Research Questions The research questions that
typically done outside of the classroom anyway (homework, projects, classpreparation assignments, etc.), this concern is not specific to online courses. For exams andquizzes, one can potentially be even more confident in an online environment than in a F2Fenvironment that the work credited to a given student is their own. This can require significantresources, if one chooses the policing route, but is possible as outlined below. Alternatively, onecould take the approach of designing quizzes and tests that allow students to use a broader arrayof resources (internet, book, notes, maybe even each other, etc.) to minimize the monitoringrequirements. This second option also comes closer to mimicking what students will be asked todo “in the real world
(CHEER) published by Cam- bridge University Press, New York, NY. Dr. Johri earned his Ph.D. in Learning Sciences and Technology Design at Stanford University and a B.Eng. in Mechanical Engineering at Delhi College of Engineering.Dr. Aqdas Malik, George Mason University Aqdas Malik is a Postdoctoral Research Fellow at the Department of Information Sciences and Tech- nology, George Mason University. His multidisciplinary academic and industry experience spans two key disciplines: Human-Computer Interaction and Social Media Communication and Analytics. He is currently engaged in a number of research projects funded by the National Science Foundation (NSF). In some of his recent projects he has applied big data techniques
across the United States. Tull is on the board of advisors for the PNW-COSMOS Alliance to increase the number of American Indian/Alaska Native (AI/AN) students who complete STEM graduate programs, and is a speaker on ”GRADLab” tour with the National GEM Consortium, giving talks across the US each Saturday morning during the Fall. Tull researched speech technology as former member of the faculty at the University of Wisconsin-Madison. She has co-authored several publications on achievement in STEM fields, and is a mentoring consultant for Purdue, Carnegie Mellon, Cornell, and MIT. She co-leads the ”ADVANCE His- panic Women in STEM” project in Puerto Rico, and the Latin and Caribbean Consortium of Engineering
so that additional requests for retention data for newcategories or subcategories could be calculated in minutes. An undergraduate computer sciencemajor was hired at $10 per hour and spent about 25 hours working on developing the program.The hours include the time the student needed to learn the basics of Python.Python was chosen since a student group as part of a class project had recently used thislanguage to create what was called a “deficiency” report. This project allowed for reports onstudents who, for example, failed courses more than the allowed amount, or had a low grade pointaverage for too many semesters in a row, etc. Python is relatively easy to learn, and it is veryreadable so it is easy to maintain the program. This program
, and socially just. She runs the Feminist Research in Engineering Education (FREE, formerly RIFE, group), whose diverse projects and alumni are described at feministengineering.org. She received a CAREER award in 2010 and a PECASE award in 2012 for her project researching the stories of undergraduate engineering women and men of color and white women. She has received ASEE-ERM’s best paper award for her CAREER research, and the Denice Denton Emerging Leader award from the Anita Borg Institute, both in 2013. She was co-PI of Purdue’s ADVANCE program from 2008-2014, focusing on the underrepresentation of women in STEM faculty positions. She helped found, fund, and grow the PEER Collaborative, a peer mentoring group of
. This age is estimated to be about 13.7 × 109 years = 13.7billion years. According to the Wilkinson Microwave Anisotropy Probe project of NASA, theestimated age of the universe is between 13.5 and 13.9 billion years. Thus to obtain the optimalglobal minimal path for a TSP of only 26 cities, the fastest available computer of 2006 wouldneed about 5 × 1017 years compared to which even the estimated age of the universe is anumerical zero. Even if a TSP solution is given, its verification is also intractable. This isbecause the TSP is an NP (nondeterministic polynomial time)-hard problem. Designing apolynomial-time deterministic algorithm for a TSP is and has been an open problem forcenturies. We, therefore, attempt to solve a symmetric TSP by