, comparative studies that assess theefficacy of various game-based learning tools could provide deeper insights into their respectiveimpacts on student learning and skills development. Investigating the long-term retention ofskills acquired through such interactive learning experiences could also offer significantcontributions to the field.References[1] Bidabadi, N. S., Isfahani, A. N., Rouhollahi, A., & Khalili, R. (2016). Effective teachingmethods in higher education: requirements and barriers. Journal of advances in medicaleducation & professionalism, 4(4), 170.[2] Cruz, M. L., Saunders-Smits, G. N., & Groen, P. (2020). Evaluation of competencymethods in engineering education: a systematic review. European Journal of
factors overscientific or theoretical knowledge, implementing targeted interventions, thus adjusting theinstructional approach and refining the use of the tool. These efforts aim to strengthen theanalysis of the lesson design’s impact on learning outcomes and explore the potential integrationof emerging technologies for enhanced effectiveness in specific educational contexts.References [1] C. Vieira, R. Aguas, M. H. Goldstein, S. Purzer, and A. J. Magana, “Assessing the impact of an engineering design workshop on colombian engineering undergraduate students,” International Journal of Engineering Education, vol. 32, no. 5, pp. 1972–1983, 2016. [2] M. A. Feij´oo-Garc´ıa., H. H. Ram´ırez-Ar´evalo., and P. G. Feij´oo-Garc´ıa., “Collaborative
understanding of how the design problem-solving behaviors ofundergraduate engineering participants differ based on their levels of spatial ability while, whysuch differences exist and how they might affect their learning outcomes is yet to be known. Futureresearch provide us some insight into it.ACKNOWLEDGMENTSThis work was made possible by a grant from the National Science Foundation (NSF #2020785).Any opinions, findings, and conclusions, or recommendations expressed in this material arethose of the authors and do not necessarily reflect the views of the National Science Foundation. 11REFERENCES 1. R. Gorska and S. Sorby, "Testing instruments for the
sampling(KMO = 0.91) and sufficient factor correlations (χ2171 = 2562.3, p < 0.001). Phase 2 also showedsuitable results (KMO = 0.92) and (χ2171 = 2690.6, p < 0.05). Table 3. Cronbach Alpha’s Value for Both Study Phases. Phase 1 Phase 2 Cronbach’s alpha Cronbach’s alpha Searching (S) 0.78 0.80 Planning (P) 0.73 0.77 Managing (M) 0.77 0.82 4 Implementing People (IP
engineeringfaculty at a research institution who collaborated on an NSF-funded research project aimed atstudying the impact of implementing oral exams in high enrollment courses. The primaryresearch questions were: How did the instructor’s perspectives and behaviors change as theyimplemented oral exams in their courses? How did the instructors act on a growth-orientedmindset?MethodsWe invited six teaching professors from the departments of Mechanical and AerospaceEngineering and Electrical Engineering to participate in the study. To protect the confidentialityof each individual, pseudonyms were used in lieu of using their full names in data analysis (SeeTable 1). Instructor Department Course(s) that implemented oral exams
integration of AI tools into STEMpedagogy. This collaborative network among key stakeholders will serve to support equity andaccessibility in education and create a more inclusive learning environment for all futurelearners.AcknowledgmentThis material is based upon work supported by the AI.R-NISTH AI for Social Good ResearchGrant at Nanyang Technological University in Singapore. Any opinions, findings, conclusions,or recommendations expressed in this material are those of the author(s) and do not necessarilyreflect the views of the AI.R program. We would like to acknowledge all the researchers, datacollectors, and students who participated in the study.ReferencesAbulibdeh, A., Zaidan, E., & Abulibdeh, R. (2024). Navigating the confluence of
in approaches and areas for improvement or learning on thepart of novices. This work will also feed into the longer term goal of this project which will thenaim to categorize students and dispositions that allow for problem solving success. For example,if we can determine that reflection, or intrinsic motivation, (for example) are critical aspects forsuccess then future work by our group or others could focus on developing these dispositions instudents or would lend weight to existing best practices for doing so.AcknowledgementsSupport for this work was provided by the National Science Foundation under Award No.2301341. Any opinions, findings, and conclusions or recommendations expressed in this materialare those of the author(s) and do not
ofsociety and engineering solutions/technologies related to each theme. They are provided withopportunities to further explore theme(s) that they are interested in through individualizedresearch-based assignments and a team project. In this course, students also learn about programrequirements and opportunities to achieve the program competencies, and develop a customizedfour-year plan for the program, i.e., they identify opportunities they would like to pursue to meeteach competency requirement and plan out when to pursue each opportunity during their fouryear journey. Due to the active learning and group based nature of this course, the first yearstudents also closely connect with their peers and the first year community in the GCSP. Moredetails
diverse perspectives andfemale role models in STEM (Konowitz et al., 2022). Introducing students to the narratives andaccomplishments of women, minorities, and people from various cultural backgrounds canmotivate and empower underrepresented groups to pursue careers in STEM (Cheryan et al.,2015; Gilberth, 2015). Institutions, including K-12 and higher education, should develop moreinclusive and supportive environments for students interested in STEM. This involves offeringmentorship programs, networking opportunities, professional development for teachers, andresources suited to the needs of different student demographics. Such efforts align with Yeo etal.’s (2024) preliminary work that teachers use verbal and non-verbal cues to facilitate
s sections of theengineering course at a large Midwestern university. Over the semester, students were asked toreflect after each lecture on two aspects of their learning experience, i.e., what they found 1)interesting and 2) confusing in the lecture? In total, we collected reflections from 42 lectures, andthe average class size was 80 students in each section. To inform the study, we generated areflection summary for all reflection submissions in each lecture using both NLP approaches andhuman annotators. Furthermore, we evaluated the quality of reflection summaries by assessingthe ROUGE-N measure for each lecture’s reflection summary generated by all three approaches.These summaries were then aggregated for each approach by averaging
Paper ID #43707Undergraduate Level Hands-on Ecological Engineering Course with Semester-LongProject and Laboratory ExercisesDr. Niroj Aryal, North Carolina A&T State University Dr. Niroj Aryal is an associate professor of Biological Engineering at the Department of Natural Resources and Environmental Design at the North Carolina A&T State University. His academic background includes a bachelorˆa C™s in Agricultural Engineering, a post-gradate diploma in Environment Education, MS in Biosystem Engineering, and a dual major PhD in Biosystems and Environmental Engineering. Dr. Aryal is interested in instructional
analysis was to observe a similar level of analysis bystudents individually when asked to answer the questions “What was the problem(s) youwere trying to solve as part of Project 1”?”Research questions: 1. How do FYE students comprehend and state their initial understanding of a given engineering problem? 2. How do FYE initially indentify the primary function of an engineering system (device or process) they are designing?MethodsParticipantsThe participants in this study included sixty-four students enrolled in an honors versionof the first year engineering (FYE) course at a large midwest university during the Fall2010 semester. These students self-select into the course and were accepted on a firstcome bases. These students have a
c American Society for Engineering Education, 2011 The Virginia Demonstration Project— A Summative AssessmentIntroductionThe Virginia Demonstration Project (VDP) is a middle-school-focused, educational outreachprogram that is designed to increase the interest of middle-school students in STEM (Science,Technology, Engineering and Math) careers. This is accomplished by exposing the students toreal-life, problem-based challenges, solved in a cooperative learning environment and stimulatedby lesson plans collaboratively implemented by their classroom teacher and visiting Navyscientists and engineers (S&Es). It makes science and math connections between the classroomand real life, supplies
theMechanical Engineering Technology programs at the undergraduate and graduate levels. Thetopics presented in the paper include the development of the simulation laboratory, thecurriculum, students’ response and future plans.IntroductionThe Department of Mechanical Engineering Technology at SUNY Institute of Technology atUtica/Rome, N.Y., has established a successful baccalaureate degree program over the past twodecades. The department offers B. S. and B. Tech. degrees in Mechanical EngineeringTechnology and the program is accredited by TAC/ABET. Recently a new Master of Science inAdvanced Technology (MSAT) degree program has been initiated. All of these programs aresupported by fifteen well equipped laboratories as a consequence of the fact that the
1950’s, devised a partial factorial method of experimental design that requires farfewer trials than the traditional full factorial scientific method. His method combinesengineering techniques with statistical methods in such a way that rapid improvements in qualityand cost reduction occur when optimizing product designs and manufacturing processes. “FordMotor Company was one of the first companies in the United States to recognize the value ofTaguchi’s approach to quality. Ford brought Dr. Taguchi to Dearborn, Michigan, to teach itssuppliers these techniques in 1981.” (Magowan, 1991). “The quality of Japanese automobiles isattributable largely to the widespread application of the Taguchi Method.” (Roy, 1990). It is imperative that
simulators. The following is an example of how the contents of thejunior-year separations (equilibrium stage and mass transfer) course(s) can be coordinated withthe senior design course(s) to enable chemical engineering graduates at the B.S. level to makesignificant contributions in the workplace. It presupposes that prior to the separations course(s),the student completes a solution thermodynamics course that covers modern methods ofdetermining multicomponent phase equilibriaIn the summer of 1998, a new process design textbook by Seider, Seader, and Lewin21, entitled,"Process Design Principles: Synthesis, Analysis, and Evaluation", will be published by JohnWiley & Sons. The table of contents of this textbook is shown in Table 1. The most
society’s needs.CONCLUSIONWe have developed a concept map that uses philosophical concepts to organize AI technologyfor use in the high school classroom. The purpose of the map is to increase learning by helpingstudents organize their knowledge in a meaningful and holistic way. We have also developedassociated activities that help students learn about the concepts presented in the map. Page 10.977.6 Proceedings of the 2005 American Society for Engineering Education Annual Conference & Exposition Copyright À 2005, American Society for Engineering Education1. Develop initial map(s) Decide on the scope of the
done using the electrical analogy.The author learned of this approach at North American Aviation in the early 60’s. This approachis useful for setting up the difference equations and boundary conditions for use in a Spreadsheet.An electrical analogy for heat transfer in a 1-D wall broken into nodes is shown in Figure 3. Inthis analogy, boundary nodes and surface nodes do not have a means for storing energy whereasinternal nodes have a mass associated with them and therefore a thermal capacitance. Thethermal capacitance represents the amount of energy per unit temperature change and is theproduct of the specific heat and mass of a node. The resistances between nodes can be analogousto convection, conduction and even radiation.In Figure 4 an
encourageengagement and knowledge exchange in both student-student and student-ChatGPT interactions.Therefore, gaining a deeper understanding of ChatGPT’s role as a conversation agent in CSCLbecomes increasingly critical. By elucidating the specific contributions of ChatGPT incollaborative learning settings, we can better harness its potential to enhance student engagement,knowledge sharing, and learning outcomes.References [1] L. S. Vygotsky and M. Cole, Mind in society: Development of higher psychological processes. Harvard university press, 1978. [2] D. D. Suthers, “Technology affordances for intersubjective meaning making: A research agenda for cscl,” International Journal of Computer-supported collaborative learning, vol. 1, pp. 315–337
learningoutcome into three components: reading comprehension [N/S LO2a], critical understanding [N/SLO2b], and informed judgment [N/S LO2c]. The blind evaluation used an aggregate figure [N/SLO2] for these three elements, which is compared against an average of the instructor’s threevalues at Times 1 and 3. This “critical understanding” learning outcome is the primary metric bywhich student performance was measured.In addition to course learning outcome evaluation, seven additional ASHE Education forSustainability (EfS) learning outcomes were assessed: 1) Each student will be able to define sustainability. [EfS LO1] 2) Each student will be able to explain how sustainability relates to their lives and their values, and how their actions impact
those of the author(s) and do not necessarilyreflect the views of the National Science Foundation.We would also like to acknowledge all of the individuals who participated in the studiesassociated with this work. We would also like to acknowledge the people who supported thiswork with their time and help.References1. Stevens, R., O’Connor, K., Garrison, L., Jocuns, A., & Amos, D. M. 2008. Becoming an engineer: Toward a three dimensional view of engineering learning. Journal of Engineering Education, 97(3), 355–368.2. Johri, A. and Olds, B. M. (2011), Situated Engineering Learning: Bridging Engineering Education Research and the Learning Sciences. Journal of Engineering Education, 100: 151–185. doi: 10.1002/j.2168-9830.2011
Page 24.1144.3 1 Giersch, S., & McMartin, F. (2014). Promising Models and Practices to Support Change in Entrepreneurship Education. Epicenter TechnicalBrief 2. Stanford, CA and Hadley, MA: National Center for Engineering Pathways to Innovation. http://epicenter.stanford.edu/documents/1912.1 Selecting Resources through an Iterative Search and Review ProcessBbK team members employed an iterative search process using the web and reference databases(see Bibliography) from the library systems of New York University and the University ofCalifornia at Berkeley during June-July 2013. During the first phase of assessing the searchresults
educational technology to plan, prepare, and deliver robotics lessons tofifth graders at a local school. The meeting times for the two courses were scheduled to overlapfor 75 minutes a week, allowing the engineering and education students to work collaborativelyduring multiple class sessions. Each team comprised one or two engineering student(s), onepreservice teacher, and one or two fifth grader(s). The teams engaged in the followingcollaborative activities over the course of the semester: ● Training phase. The first two collaborative sessions involved engineering students and preservice teachers meeting in a classroom on campus and partnering in teams to: ○ train with the Hummingbird BitTM hardware (e.g. sensors, servo motors) and
has over 8 years of work experience in the A/E/C (Archite ©American Society for Engineering Education, 2024 Technological Infrastructure Equity for Minority Serving Institutions in Construction EducationAbstract: In the U.S. and its territories, over 800 identified Minority Serving Institutions (MSI)exist. Despite the number of MSI and the diverse population that they targeted, there is a gap inthe number of higher education degrees obtained by minority students in relation to non-minoritystudents. The root cause(s) of the gap must be determined to take tangible actions to reduce and,ideally, eliminate this obtainment gap. When considering this gap, there is a question of
outlook," 2023. [Online]. Available: https://www.bls.gov/careeroutlook/2018/article/engineers.htm.[5] A. Kodey, J. Bedard, J. Nipper, N. Post, S. Lovett and A. Negreros, "The US Needs More Engineers. What’s the Solution?," Boston Consulting Group, Boston, MA, 2023.[6] T. Robinson, A. Kirn, J. Amos and I. Chatterjee, "The Effects of Engineering Summer Camps on Middle and High School Students’ Engineering Interest and Identity Formation: A Multi-methods Study," Journal of Pre-College Engineering Education Research (J- PEER), vol. 13, p. 6, 2023.[7] L. Chu, V. Sampson, T. L. Hutner, S. Rivale, R. H. Crawford, C. L. Baze and H. S. Brooks, "Argument-Driven Engineering in Middle School Science: An Exploratory Study of Changes in
First-year Engineering Experience at Case Western Reserve University. She received her M. S. in physics and B. S. in electrical engineering and applied physics from CWRU and her Ph. D. in physics, specializing in physics education research, from The Ohio State University.Michael William Butler, Case Western Reserve University 15th Annual First-Year Engineering Experience Conference (FYEE): Boston, Massachusetts Jul 28Work in Progress: Increasing Maker Space Participation through First-Year EngineeringIntroductionWe added an additional component to a design module in the First-Year Engineering course atCase Western Reserve University with the goals of increasing utilization of the campusmaker
-levelthemes that capture the essence of the interview corpus, but it performed poorly in mapping theconcepts to specific files. Therefore, a hybrid approach that leverages the strengths of both AIand human expertise may be the most effective strategy for analyzing complex qualitative data ineducational research.AcknowledgmentThis material is based upon work supported by the U.S. National Science Foundation (NSF)under Grant No. (DUE 2120936). Any opinions and findings expressed in this material are of theauthors and do not necessarily reflect the views of the NSF.References:[1] S. Kulturel-Konak, "Overview of Student Innovation Competitions and Their Roles in STEM Education," in 2021 Fall ASEE Middle Atlantic Section Meeting, 2021. [Online
) which is a first-order differential equation forthe velocity of the car. Set m=1100-kg, c=40-N-S/m, F=1000-N. Determine the velocity of carafter 120-s. After 120-s, the driver brake and stop the car with -500-N braking force. Simulink isa Matlab add-in that allows one to simulate a variety of engineering system. Simulink is adifferent tool, which is much more graphical and visual for complex system. (Appendix E)5. Helical compression spring design with user defined functions in Simulink. A spring is madefrom music wire, ASTM A228 steel, where the free length of spring is 1.75-in, Outer diameter is0.561-in, and the wire diameter is 0.055-in. The total number of coils is 10.0. The ends aresquared and ground. The operating load of spring is 14-lb
(KPIn ) we used in this effort are listed below and we developedfunctions to drive our algorithms in our custom database dashboard. 1. 100% 1st article 2. Inventory each kit 3. On-Time Delivery 4. Percentage of revenueIn equation 1, KPI1 is defined as how much time (T ) it takes to get a final working product that istested. For example, we can compute the time between dates such as physical work start (P W S)date, material procurement dates, 1st article test (1AT ) dates, and final article test dates. KP I1 = TP W S − T1AT . (1)In equation 2, KPI2 is defined as how long it takes to inventory each kit. For example, we candetermine the function by comparing timestamps
Assessment Program, 2003.[2] C. R. Pace and G. G. Stern, “An approach to the measurement of psychological characteristics of college environments,” Journal of Educational Psychology, vol. 49, no. 5, pp. 269–277, Oct. 1958, doi: http://dx.doi.org/10.1037/h0047828.[3] P. T. Terenzini and E. T. Pascarella, “Twenty Years of Research on College Students: Lessons for Future Research,” Research in Higher Education, vol. 32, no. 1, pp. 83–92, 1991.[4] C. Kandiko Howson and F. Matos, “Student Surveys: Measuring the Relationship between Satisfaction and Engagement,” Education Sciences, vol. 11, no. 6, Art. no. 6, Jun. 2021, doi: 10.3390/educsci11060297.[5] P. C. Wankat and F. S. Oreovicz, Teaching Engineering