. In addition, each teamsubmitted a project report at the end of the second CAD project.During the first three years of ME/CEE 1770 instruction, instructors, teaching assistants, andstudents identified a number of issues of concern regarding the design of the course. Some issueswere the result of overlooking students’ lack of prior knowledge. Some were the result ofcounterproductive assessment techniques.During the first assigned team project in the fall of 1999, students’ lack of prior knowledgebecame evident. Most students had few team skills. Instructors and teaching assistants scrambledto inject team management instructions into an already full teaching schedule. They deliveredhandouts and examples about generating timelines, holding
fastest growing multidisciplinary fieldsat the intersection of computer science and mathematics, and concerns the construction and study ofsystems that can learn from data. A core objective of a learner is to generalize knowledge gained fromthe experience8. Generalization in this context is the ability of a learning machine to perform correctlyon new, unseen data samples or tasks9. For example, a pattern recognition system could be trained onemail messages to learn distinguishing between spam and non-spam messages. After learning, it canthen be used to classify new email messages into spam and non-spam folders10. Pattern Recognition hasa broad range of applications spanning from computational neuroscience and medical diagnosis to stockmarket
facilitating assessments [8,9]. They offeropportunities to enhance student engagement, support the creation of teaching materials, anddeliver personalized educational approaches [10].However, integrating LLMs into education presents several practical and ethical challenges, suchas insufficient technological readiness, a lack of transparency, and privacy concerns [8]. Toovercome these obstacles, researchers suggest updating existing innovations with advancedmodels, supporting open-sourcing initiatives, and taking a human-centered approach todevelopment [4]. Furthermore, educators and students must cultivate new skills to understandand critically assess outputs generated by LLMs [10].Despite these challenges, LLMs can transform educational practices and
theeffectiveness of the ME program. The assessment tools include university course evaluations,ME web-based course exit surveys, senior exit surveys, Engineering Advisory Council meetings,Review Board meetings, alumni surveys, and ME faculty meetings, amongst others. Anassessment process is in place to provide feedback based on the above evaluations for continuousimprovement in the program. The following six steps summarize the current assessmentpractice: 1. Assessment process done employing several evaluation tools. 2. Results of assessment are fed back to the ME faculty, Engineering Advisory Board and/or the Industrial Review Board, depending on the issues. 3. Action plan is developed. These action items drive the changes
institutional factors that are necessary for persistence in engineering? Using grounded theory,persistence factors have emerged inductively from the body of qualitative data (i.e. unstructuredethnographic interviews). The six persistence factors that surfaced were: (1) family influences;(2) financial motivation; (3) mathematics and science proficiency; (4) academic advising; (5)quality of instruction; and (6) availability of faculty. The findings of other researcherspertaining to these factors and their impact on students of color are highlighted below.Family InfluencesPearson and Bieschke1 found that family relationships influenced career development. Earlierworks by Ogbu2 and Leslie, McClure, and Oaxaca3 had considered the impact of familyinfluences
performance [2], stress is a topreason students cite for “stopping out,” or leaving, degree programs [3]. Even more concerning,studies have shown that suicide is the second leading cause of death of college students (~1.1klives/year). Issues are well-presented in engineering. UES have suggested that stress is a“necessity,” demonstrating how harmful engineering cultures create pervasive narratives againstwell-being [4]. Culture has also been shown to have a repeated effect on UES help-seekingbehaviors and faculty support of mental health [5]. We believe that novel mental healthinvestigations are needed to support UES development. We wonder whether UES’ thinkingregarding mental health and well-being is connected to the choices they make about their
implementation of AI in higher education requires careful considerationof data privacy, ethical issues, and the digital divide. Strategies must be developed to ensure thatAI tools are used responsibly and that all students have access to the necessary technology andresources. Additionally, ongoing faculty training and support are essential to maximize thepotential of AI in education.As AI continues to evolve, its role as a catalyst in higher education will undoubtedly grow,offering unprecedented opportunities for the advancement of teaching strategies and academicachievement. By addressing the challenges and leveraging the benefits of AI, educators andinstitutions can revolutionize higher education, making learning more efficient, inclusive
upon didactic class meetings delivered by a faculty instructorsupplemented with hands-on laboratory sessions led by graduate teaching assistants (GTAs).Two, identical sections of class meetings were offered each semester to an enrollment of no morethan 30 students, each. Three identical sections of laboratory were offered each semester to anenrollment of no more than 20 students, each. A total of 60 students could complete the courseeach semester, and 120 students could complete the course each academic year. If studentdemand exceeded these caps, an additional course was offered during the summertime. Afaculty instructor delivered each section of class meeting. New concepts were introduced in theclass meeting. Subsequently, reading assignments
effectively evaluating students’knowledge.To attempt to reconcile these shortcomings, oral examinations were used in two sections of anundergraduate engineering course (Introduction to Fluid Mechanics). Oral examinations, usedfor most graduate and post-graduate programs to assess whether or not a student is qualified tocontinue in the program, are well known to be effective in determining a student’s level ofunderstanding8. However, the time-intensive nature of individual oral examinations is perceivedto be prohibitive of their use in today’s undergraduate class sizes and faculty work loads. Toaddress this issue, an innovative technique of team-based oral examinations was attempted. Thebenefits of an oral defense of a student’s solution, peer review
sustainability.Since then the faculty members have taken steps towards developing such programs, beginningwith offering the “Sustainable Development Principles and Practice” course that coverssustainable development, international practices, policy, and ethics and complements the“Construction Systems and Planning” and “Civil Engineering Systems Management” coursewhere engineering and architecture students create a detailed proposal for a semi-realistic teamproject (1). Subsequently, a task group examined the feasibility of further courses. A new studentchapter of EWB has been founded at the university, which crystallizes the interest of theengineering students in bringing their skills to developing regions and which is enjoying anexceptionally active group of
notgo on to take upper division courses. The first course in the sequence is DC Circuit Analysis(DCA) and the second is AC Circuit Analysis (ACA). This retention problem leads to reducedclass size and potential cancellation of second year course sections. Additionally the NationalScience Foundation1, National Research Council 1 and ABET 2 are calling for educational reformsthat focus on student learning outcomes instead of the traditional material coverage.Introduction For this paper, “retention” is defined as the percentage of students who either take thenext course in the sequence, ACA, or repeat the first course, DCA. Several factors lead to lowretention. Based on faculty perspective, student performance feedback, and analysis of
States.ERCs focus on the definition, fundamental understanding, development, andvalidation of the technologies needed to realize a well-defined class ofengineering systems with the potential to spawn whole new industries or radicallytransform the product lines, processing technologies, or service deliverymethodologies of current industries. Also, ERCs must fulfill NSF’s goal toincrease the diversity of the scientific and engineering workforce by including allmembers of society regardless of race, ethnicity, or gender in all aspects of thecenter’s activities. In an effort to fulfill this mission, ERCs produce an enormousamount of data and information. This means the amount of information to beconsidered by this research has the potential to be
paper, we present a model for an introductory freshman-level course that helps addressstudent enrollment and retention issues. Our course is based on three tenets: (1) the course drawsproblems from, and teaches about, an interesting and relevant domain in which students alreadyare familiar, (2) the course encourages teamwork and peer communication, (3) the student isactively responsible for their education. To address these, the class teaches game design in acollaborative environment in which students are given open-ended assignments to promotecreativity. We address instructor grading concerns, various student skill levels, and individualassessment. In our approach, we encourage the implicit acquisition of basic computer scienceconcepts and
“Proceedings of the 2003 American Society for Engineering Education Annual Conference & ExpositionCopyright © 2003, American Society for Engineering Education”achieving personal and professional goals (e.g., obtaining funding for projects; receivingpromotions to greater responsibilities). Industry spends substantial amounts on training—yet oftenremains displeased with the results. In spite of rapid interconnectivity via e-mail and the Internet,many remain concerned that usable results of technical research paid for with public dollars arenot being issued substantially more understandably than in the past.18 Yet, to make difficultdecisions that impact us all and to compete effectively, government and industry leaders musthave access to engineering
workload remained as challenges.When asked on the survey whether students felt prepared for university-level math prior to thesummer bridge program, 50% disagreed or strongly disagreed while only 25% agreed or stronglyagreed (Figure 1), indicating that the majority were concerned about the transition to college.Students further elaborated in the open response questions, citing concerns around the difficultyand pace of the courses, managing the workload, and their prior knowledge, including a lack ofrecall and insufficient preparation from previous courses. They also worried about their ability tounderstand new concepts. Interestingly, while all students voiced concerns, only one expressed a“positive” challenge, fearing that they would not be
replace failed projectswith new projects before the consequences get out of hand.Matt was not as descriptive on risk analysis as Lola, but he had a very similar way ofdetermining which problems were actually worth solving in terms of what financial risks theysolved. “If we see something that’s unique or a mystery and if its truely a million dollar or more problem and it looks like it is going to be a long term problem... then we will make an effort to develop a computer model to understand the issue.”Problems that are less than a million dollars do not have as large of an impact on companyprofits and those kinds of problems tend to take longer than thousand dollar projects.Determining which problems to take on is a risk evaluation as
Paper ID #29335Integrating Ethics into the Curriculum through Design CoursesProf. Scott A Civjan P.E., University of Massachusetts, Amherst Scott Civjan is a faculty member at UMass Amherst where he has taught a wide variety of undergraduate and graduate courses over the past 20+ years. He has 4 years of consulting experience between obtaining his BSCE from Washington University in St. Louis and his MS and PhD in Structural Engineering from the University of Texas Austin.Prof. Nicholas Tooker, University of Massachusetts Amherst Nick Tooker is a Professor of Practice at the University of Massachusetts Amherst. He teaches
Director of the Center for STEM Education Department of Cur- riculum and InstructionDr. Todd L. Hutner, University of Texas at AustinDr. Stephanie Rivale, University of Texas at Austin Stephanie Rivale is a research faculty member at the Center for STEM Education at the University of Texas. She received her Ph.D. in STEM Education at the University of Texas. She received her B.S. in Chemical Engineering at the University of Rochester and her M.S. in Chemical Engineering at the University of Colorado. She has collaborated on engineering education research with both the VaNTH Engineering Research Center, UTeachEngineering, and the TEAMS Program at the University of Boulder. Dr. Rivale’s research uses recent advances in
concern which does not apply to the same extent for the othermembers of the truss, partly because these members would not have been subjected to nearly thesame number of load cycles that the hangers would have experienced. The effects of fatigue arealso not reflected by the Cooper rating analyses. Thus, in all, these results support the hypothesisthat the hangers were indeed among the most vulnerable of members in the Fish’s Eddy Bridge.V. ConclusionsHistorical background has been presented regarding the O&W’s three-span pin-connectedthrough truss bridge near Fish’s Eddy, New York, erected in 1882. The bridge experienced twomajor failures, the first taking place in 1886 when a derailed train struck an end post andcollapsed the northernmost
satisfaction from their own service to the local community in this project. · They learned that taking a design from paper to physical product is a lot harder than it looks and that simpler is almost always better. · They learned to manage construction, to include reacting to delayed shipments, missed deliveries, and constructability issues. · They learned that engineers often face design challenges that are not covered in textbooks. There was no reference showing how to connect an aluminum decking system to a polyethylene floatation module. They had to apply fundamental principles in new ways to devise their own solution methodologies.IV. AssessmentIn addition to our many discussions
Paper ID #6028Learning Expectations and Outcomes for an Engineering Leadership Princi-ples ClassKirsten S. Hochstedt, Penn State University Kirsten S. Hochstedt is a graduate assistant at the Leonhard Center for the Enhancement of Engineer- ing Education. She received her M.S. in Educational Psychology with an emphasis in Educational and Psychological Measurement at Penn State University and is currently a doctoral candidate in the same program. The primary focus of her research concerns assessing the response structure of test scores using item response theory methodology.Mr. Andrew Michael Erdman, Pennsylvania State
concern themselves with? 2. What are students’ overarching narratives that orient them to energy transitions?Institutional and Course ContextWe situated this study in an upper level crossdisciplinary undergraduate course on sustainable energies,co-taught by two faculty members, one in political science and one in mechanical engineering. The coursehas been taught at a State University in the Northeast region of the United States for thirteen years—shifting the curriculum as issues of energy transition have changed. The course has been co-taught by apolitical science faculty and an engineering professor in each of these iterations. We note that the facultymembers are not the authors of this study but are involved in the overarching research
and Research for the new University of Georgia College of Engineering.Ms. Qianqian Ma, University of GeorgiaDr. Caner Kazanci, University of Georgia Dr. Caner Kazanci is a native of Izmir, Turkey and received his M.S. and Ph.D. degrees in Mathemati- cal Sciences Department from Carnegie Mellon University at Pittsburgh, Pa. His graduate work was on mathematical biology, and was concerned with modeling and analysis of large biochemical pathways. He is currently an associate professor at the University of Georgia, in a joint appointment in Department of Mathematics and Faculty of Engineering. He is the developer of EcoNet, a cloud-based software for ecosystem modeling, simulation and analysis. He and Dr. Tollner
Perceptions:The following results were drawn from the daily blog11, student reflections, the formal program Page 25.1445.12evaluations that were conducted by Academic Programs Abroad (APA), surveys conducted bythe CxC program, as well as an informal analysis that the director conducted on the last day ofclass. The APA formal evaluations, CxC surveys, and the informal analyses were anonymous sothat students could freely comment on the program, classes, and faculty without concern forbeing identified.Global Awareness: One student commented on the informal analysis that the program allowedhim to “live like the Germans do” and to “learn to not waste as much
model to introduce faculty andstudents to new ideas for interdisciplinary collaboration. The small group of faculty listed here isan example of this collaboration. Each member brings his/her own expertise and whenintegrated makes the total more than just the sum of the individuals.This interdisciplinary research encompasses hierarchical mathematical and stochastic simulationmodeling for semiconductor manufacturing, from the release of raw wafers at the start throughthe completion and shipment of the devices. The implementation of “optimal schedulingpolicies” has recently been recognized as an important and challenging problem in theSemiconductor Industry2,7,18,20,45,46. The competitive operation of modern fabrication processesrequires the
students' well-being, addressing any challenges they may face, and providing timely support. We will also try to gain a grasp of how well the other team members are performing and if there should be any concerns so we can prevent any last minute issues. We will also analyze this semester's team assessment surveys in comparison to those from the previous semester to determine whether the implementation of guided check-ins has led to an overall improvement in team members' satisfaction.3. Methodology3.1. Dissemination of the Research Self-Efficacy Scale (RSES)Participants who completed both seminar classes (defined as Cohorts) were encouraged to fillout the Research Self-efficacy Scale (RSES) [9] via email.The Research Self-Efficacy Scale
technician education. Advances in DM technologies haverevolutionized key aspects of manufacturing including design, development, testing, etc.The Deloitte Review (GMCI, 2016) points out a concern that is relevant in this context: “A skillsgap is the US manufacturing sector’s Achilles’ heel, with nearly 3.5 million jobs at stake overthe next decade. It is no longer a short-term issue of filling current hard-to-fill open positions, orone that can reasonably be expected to be solved in time by government policy-makers.” Thefollowing excerpt from EMSI (2015) is especially relevant from the perspective of ‘training-the-trainers’: “According to EMSI quarter 2 data it is projected that between 2016-2025 there willbe over 21,000 new high-tech manufacturing
students. As we worked with the students, we noticed from their questions and remarks Page 22.1228.4during meeting ice breakers that the transfer students were dealing with a different set of issuesand concerns than the native students. The transfer students didn’t know where “standardresources” were located, had difficulty getting into stud y groups, felt isolated, and were not verypersistent in getting their problems solved, primarily because they did not know how and feltoverwhelmed with all of the issues of being a “new student”. No matter how well they had doneat the Community College, they were now starting all over with a 0.0 GPA. It
better introduction before higher-levelprogramming courses, and connect learning to the real world [22]. The researchers had a singulargoal: ”to increase the retention of African-American CS undergraduates in the first two years ofstudy.” The Googler in Residence (GIR) program was established and placed a Googler at theschool as a faculty member. Then Google Computer Science Summer Institute (a Google programdesigned to teach programming to incoming freshmen) curriculum was combined with theexisting CS 0 curriculum to create a new course for first-year students. The GIR program helpedstudents connect to real-world applications of CS and created a connection between the universityand Google. Similarly, Florida Agricultural and Mechanical
in the 21st century is one of the primary goals ofuniversity educators [1-5]. Enabling students to practice self-learning, to find solutions to designproblems that are sustainable, helping them recognizing that they are part of community are justa few of our educational goals. Energy and power engineering education has undergonesignificant changes over the last decades, together with an increased student interests into suchengineering programs. The issues surrounding this theme are also receiving significant interestsform faculty and quite often administration. Today electrical energy industry professionals arerequired to have significant techno-scientific capabilities, deep interdisciplinary understandings,and soft engineering skills, such