faculty, administrators, andcoordinators of peer mentoring programs to re-examine the support structures for their mentorsand seek action to further improve these experiences.References[1] J. H. Lim, P. T. Tkacik, S. Dika, B. P. Macleod, “Peer mentoring in engineering: (un)sharedexperience of undergraduate peer mentors and mentees”, Mentoring and Tutoring: Partnershipin Learning, vol. 25, no. 4, pp. 395-416, Nov. 2017, doi: 10.1080/13611267.2017.1403628[2] L. Mohandas, N. Mentzer, A. Jaiswal, S. Farrington, “Effectiveness of UndergraduateTeaching Assistants in a First-Year Design Course”, Presented at the 2020 ASEE Virtual AnnualConference Content Access, [Online], June 2020, doi: 10.18260/1-2--34503[3] Q. Tahmina, “Assessing the Impact of Peer
classroom – or we can pullout our hair and expect students to behave like learning superheros, an approach doomed to fail withour very-human students.The pace of change may or may not have accelerated, but the change is here now and it is here tostay. Though we must process feelings of disorientation for both students and faculty, thisreorganization of our engineering education is imperative if higher education is to retain itsusefulness.References[1] K. D. Foote, “A Brief History of Large Language Models,” DATAVERSITY. Accessed: Nov. 07,2024. [Online]. Available: https://www.dataversity.net/a-brief-history-of-large-language-models/[2] B. Edwards, “OpenAI’s GPT-4 exhibits ‘human-level performance’ on professionalbenchmarks,” Ars Technica. Accessed
Market Research from the University of Barcelona, Spain. Industrial Civil Engineer from the Universidad del B´ıo-B´ıo. She has three diplomas in the areas of coaching, digital marketing and equality and empowerment of women. Her professional experience is linked to higher education as a project engineer and university management in the public and private area. Teacher at different universities in matters of entrepreneurship, business plans and marketing. She currently works as a teacher and academic secretary at the Faculty of Engineering of the Andr´es Bello University. The areas of research interest are the impact, relationship and integration of the gender perspective within communications and marketing in the
Paper ID #49169Building the Pipeline: STEM Summer Camps and the Path to Gender Equalityin EngineeringDr. Bahareh Goodarzi, Concordia UniversityDr. Navid Sharifi, Concordia University Lecturer in the Department of Mechanical, Industrial and Aerospace Engineering, Concordia UniversitySara JameelProf. Anjali Agarwal, Concordia University Dr. Anjali Agarwal is currently a professor at the Gina Cody School of Engineering and Computer Science. She was the Chair of the Women Faculty in Engineering committee that conceived the idea of GirlSET in 2017. With the help of the faculty, staff and students, Dr. Agarwal organized the first
Pig, Feed Pig, Weigh Pig," Occasional Paper #23, National Institute for Learning Outcomes Assessment, 2014.6. M. Davis, "Outcomes-based education: History, philosophy, and practice," Educational Researcher, vol. 32, no. 2, pp. 21-30, Mar. 2003.7. S. R. Smith, "AMEE Guide No. 14 Outcome-Based Education Part 2-Planning, Implementing and Evaluating a Competency-Based Curriculum," Medical Teacher, vol. 21, no. 2, pp. 164-170, 1999.8. B. Frank, K. Moozeh, and S. Maw, "A systematic Review of Drivers and Barriers to Competency-Based Undergraduate Engineering Education," Proceedings of the Canadian Engineering Education Association (CEEA-ACEE) Conference, June 19-2022, 2023, Kelowna, BC. 2023, Paper 155.9. H. Lurie and R. Garrett
government has made available a collection of projects developed indifferent educational centres, centralized by CESIRE (Centre for Pedagogical Resources forSupport in Innovation and Educational Research). The platform includes a search engine thatallows filtering by educational levels and subjects. Below are three notable examples of educational projects: 1) Project "Exploring Different Biological Processes Using CO2 and O2 Sensors": This project raises initial research questions such as: a) Exploration of photosynthesis and respiration, b) Comparison between the respiration of animals and plants, c) Factors that increase the respiration rate in seeds, and d) Analysis of alcoholic fermentation and biotechnological
) includes links to GitHub repositories of the students’projects. Several students are continuing their project during the summer as research assistants.5. Student Feedback and Lessons LearnedA pre-semester survey was conducted at the beginning of the semester. The survey showed that93% of the students had no previous knowledge of Python, 57% preferred to learn everything,including low level computer tasks like installing a library, and 86% of the students preferredactive learning (more hands-on exercises). Students’ perception about the EDS course wasassessed by a formal anonymous survey administered towards the end of the semester. Students’responses to questions regarding the course curriculum are shown in Appendix B. The appendixlists students
arm:𝑚𝑥̈ (𝑡) + 𝑏𝑥̇ (𝑡) + 𝑘𝑒𝑞 𝑥(𝑡) = 𝐹(𝑡) (3)where m is the mass, b is the damping constant, keq is the equivalent stiffness, 𝑥, 𝑥̇ , 𝑥̈ are theposition, velocity, and acceleration of the parallel arm, and t is the time. Also, the dynamicalmodel can be represented as a transfer function. Figure 8. Simulation of a compliant folded arm mechanism from Module 3Mechanisms with Flexible Beams. We modeled several mechanisms found in the compliantmechanisms books [23] and literature [16-18,20-24]. One such example is the compliant foldedbeam mechanism [25], also known as a forced slider with rotational output, as shown in Figure8. This mechanism converts translational input motion into rotational output motion through acompliant
Paper ID #46992Pre-College Microelectronics Curriculum Units Developed Using an IntegratedMicroelectronics Framework (Resource Exchange)Prof. Tamara J Moore, Purdue University at West Lafayette (PWL) (COE) Tamara J. Moore, Ph.D., is a Professor of Engineering Education and University Faculty Scholar at Purdue University, as well as the Executive Co-Director of the INSPIRE Research Institute for Precollege Engineering. Dr. Moore’s research is focused on the integration of STEM concepts in K-12 and postsecondary classrooms in order to help students make connections among the STEM disciplines and achieve deep understanding
teacher’s personalteaching efficacy and beliefs in engineering. It was adapted to survey STEM efficacy and to betteralign with the experiences in the summer program. Teachers were asked to use the following 4-point scale: Strongly Disagree, Disagree, Agree, and Strongly Agree to rate how much they agreewith the following questions about teaching efficacy and beliefs: A. I am continually improving my STEM teaching practice. B. I am confident that I can teach STEM effectively. C. I understand STEM concepts well enough to be effective in teaching STEM. D. I am confident that I can answer students’ questions about STEM. E. When a student has difficulty understanding a STEM concept, I am confident that I know how to help the student
design, and troubleshooting exercises weredrawn from PS experiences on the floor as former PAs. The formatting of the initial CoP and theformatting of the New CoP are compared in Figure 1 below. Figure 1. Comparison of New CoP Curriculum Timing vs Old CoP Curriculum Timing. The newly redesigned Staff CoP program launched in Fall 2024, with a total of 36 newlyhired PAs participating across six cohorts, each cohort led by a different PS for each 4-week toolrotation.Data Collection and Analysis Before each 4-week rotation, PA participants were asked to complete a pre-cohort survey(see Appendix A) before beginning each 4-week tool rotation, and a corresponding post-cohortsurvey (see Appendix B) after the rotation
engineeringeducation. This endeavor has allowed our IAB members to become active partners engaged inpromoting professional practice. Our IAB members have partnered with us over two years in a)hosting Industry Networking events every semester b) hosting professional panels and c)partnering with a new program titled PIPES. PIPES (Professional Industrial PartnershipEngagement for Students) is a unique CO-OP like opportunity for the students to work with keycompanies or local agencies for course credit. Students can replace their Junior and Seniorengineering clinic courses for a total of eight credits if they want to work outside of a faculty-ledproject. The program gives students a chance to try out the real civil engineering projects andwork side-by-side with
%, 11.3%, and 11.1%. Since MARR is given in theproblem statement as 11%, options A and B are eliminated because their i* is less than MARR.Since all options have the same duration, n = 8 years, Option C has the highest value of i*, whichcan be expected to declare Option C is the best. However, to complete the incremental RORprocess taught in the course, a comparison between Options C and D can still be done bysubtracting D – C, as shown in Table 2 and calculating on the increment a rate of 10.4%, whichis less than MARR. This conclusively identifies Option C as the best among the four mutuallyexclusive options. Table 2, Comparing Option C to Option DFig. 1, Bonus assignment statementNext, the students are asked to use
load flow data injection attack simulation model, as follows: • Initial Stage: Mitigation retracking was performed on a specified data frame, which involved the creation of load flow data profiles, including but not limited to, active generator power, active load power, and reactive load power of lines (see Fig. A and Fig. 4). • Mid-Stage: Retracking at specific time intervals provided insights into the dynamics that may prevail within the grid (see Fig. B and Fig. 5). • Final Stage: Refinement of the load flow data injection network model resilience was achieved through mitigation retracking by implementing percentage adjustments (see Fig. C and Fig. 6).Injecting the results of the load flow data into the virtual
platform with other existing educational systems at various universities. This includes integration with other academic management systems, institutional databases, and external credential-validation platforms. In addition, use cases can be explored in university consortia, such as: a. Issuance and verification of academic certificates b. Academic identity management c. Transparency in the recording of grades and evaluations d. Management of intellectual property and copyright e. Funding and scholarships f. Transfer of academic credits and recognition of degrees g. Access and distribution of academic material h. Collaboration in
Finite Element Analysis to Second Year Students,” in 2001 ASEE Annual Conference & Exposition, 2001.[10] L. C. Brinson, T. Belytschko, B. Moran, and T. Black, “Design and Computational Methods in Basic Mechanics Courses,” Journal of Engineering Education, vol. 86, no. 2, pp. 159–166, 1997.[11] A. Coksun, M. Abedi, and K. Wan, “Building a Load-bearing Truss for Introductory Statics Course,” in 2020 ASEE Northeast Section Meeting, 2020.[12] J. M. Papadopoulos, C. Papadopoulos, and V. C. Prantil, “A Philosophy of Integrating FEA Practice throughout the Undergraduate CE/ME Curriculum,” in 2011 ASEE Annual Conference & Exposition, 2011.[13] H. Cooke, “Fifteen-Plus Years of Strength of Materials with Pool Noodles and More
aeducational utility. Fourier transform through equations, writing explanations, and representing visual graphs [6]. This is more engaging and In engineering education, this evolution means that AI is personalized, which ultimately improves learning outcomes.moving from a background analytic tool to a foregroundcreative partner in the learning process. For instance, whereprevious systems might have evaluated a student’s answer on a B. Personalized Assessment and Feedbackproblem set, Gen AI can now generate personalized hints, Traditional assessments often fail to capture thedetailed solutions, or
Paper ID #47946The Role of Need for Cognition in Enhancing Innovation Capacities amongInterdisciplinary Graduate Students: An Equity-Focused ApproachMiss Yun-Han Weng, The Ohio State University Yun-Han Weng (she/her) is a third-year Ph.D. candidate in the Higher Education and Student Affairs program. She serves as a Graduate Research Associate at the College Impact Laboratory at Ohio State University. In this role, she investigates graduate students’ learning outcomes and experiences within an interdisciplinary STEM training program (evaluator), as well as examines the representation of Asian students and underrepresented
responses are collected via a structured inputformat (e.g., CSV exports from an LMS like Canvas). Each response contains a true/falseassertion and text to justify the answer. Student responses are then parsed by an Open WebUI‘model’ and returned in a structured .json format. See Appendix B. Note: Open WebUI 33 is aself-hosted interface for AI models which runs on a local machine. Our platform uses Ollama 37 torun Meta’s Llama3.2-8B model 38 . An Open WebUI ‘model’ is akin to a custom GPT 35 fromOpenAI 39 but with the entire generative AI model and interface running locally thus mitigatingany compliance concerns. An Open WebUI ‘model’ should not be confused with a fine-tuned‘model’ or even large-language ‘model’.2. Student Short Answer Analysis and
. National Academies Press, 1991.[2] National Academy of Engineering, Infusing Ethics into the Development of Engineers. National Academies Press, 2016.[3] ABET, “Criteria for Accrediting Engineering Programs, 2021-2022,” Oct. 2020. [Online]. Available: https://www.abet.org/accreditation/accreditation-criteria/criteria-for-accrediting-engineeri ng-programs-2021-2022/[4] A. Colby and W. M. Sullivan, “Ethics Teaching in Undergraduate Engineering Education,” J. Eng. Educ., vol. 97, no. 3, pp. 327–338, 2008.[5] R. Foley and B. Gibbs, “Connecting Engineering Processes and Responsible Innovation: A Response to Macro-Ethical Challenges,” Eng. Stud., vol. 11, no. 1, pp. 9–33, 2019.[6] D. R. Haws, “Ethics Instruction
-2—161335. Edalgo, S., & High, K. A., & Lichtenstein, G., & Lee, C. M., & Main, J. B. (2021, July), Exploring How FacultyMentoring Influences Faculty Productivity Paper presented at 2021 ASEE Virtual Annual Conference ContentAccess, Virtual Conference. 10.18260/1-2—371446. Bilen-Green, C., & Green, R. A., & McGeorge, C., & Birmingham, E. J., & Burnett, A. (2013, June), MentoringPrograms Supporting Junior Faculty Paper presented at 2013 ASEE Annual Conference & Exposition, Atlanta,Georgia. 10.18260/1-2--222837. Mendez, S. L., & Conley, V. M., & Haynes, C. L., & Gerhardt, R. A., & Tygret, J. (2018, June), The IMPACTMentoring Program: Exploring the Benefits of Mentoring for Emeriti Faculty
individuals toward entrepreneurial pursuits. When rank ordering the β-weights, or standardized Betas, Equity Aspirations emerges as the top-ranked predictor, indicatingthat it has the strongest and most consistent relationship with ENT Intent among the includedvariables. This suggests that students' desire to create equitable businesses is a particularlypowerful predictor of their entrepreneurial intentions.Table 1. Regression ModelOutcome Variable: ENT Intent B Std. Error Beta (β) t Sig.(Constant) 0.08 0.47 0.18ENT Self Efficacy 0.33 0.15 0.27 2.23 0.029*ENT Passion
. Res Sci Edu 50(2), 573-597. (2020).[6] B. Schneider, , J. Krajcik, , J. Lavonen, , K. Salmela-Aro, C. Klager, L. Bradford, , ... & K. Bartz,Educ Researcher, 51(2), 109-121. (2022)[7] M. Windschitl, J. Thompson, & M. Braaten. (2020). Ambitious science teaching. HarvardEducation Press.[8] Dimcheff(2021).https://record.umich.edu/articles/project-based-learning-yields-better-student-outcomes-studies-show/[9] R. Kumar, A. Zusho, & R. Bondie. Educ. Psychol, 53(2), 78-96. (2018)[10] G. Ladson-Billings. (1995). Am. Educ. Res. J., 32(3), 465-491.[11] G. Gay. (2002). J Teach Educ, 53(2), 106-116.[12] Anonymize for review.[13] T. A. Benson, & S. E. Fiarman. Unconscious bias in schools: A developmental approach toexploring race and racism
Graphics ToTeach Structural Engineering.” ASEE Conferences, Honolulu, Hawaii, 2007.[11] A. F. G. Jr., “Using the Spreadsheet as a Tool for Teaching the Fundamentals ofEngineering.” ASEE Conferences, AT&T Executive Education and Conference Center,Austin, Texas, 2019.[12] G. J. Privitera and L. Ahlgrim-Delzell, “Research methods for education.” SagePublications, 2018.[13] S. S. Condoor, B. MacGavin, and R. P. V. Shekar, “Teaching the Concept of Tipping inStatics: Pedagogy, Practical Examples, and Potential Activities,” in ASEE Annual Conferenceand Exposition, 2023.[14] T. W. MacFarland and J. M. Yates, “Introduction to nonparametric statistics for thebiological sciences using R,” Springer International Publishing, 2016, pp. 103–132.
J Environ Res Public Health, vol. 16, no. 23, p. 4804, 2019.[4] A. Miranda, C. Berenguer, B. Roselló, and I. Baixauli, “Relationships between the social communication questionnaire and pragmatic language, socialization skills, and behavioral problems in children with autism spectrum disorders,” Appl Neuropsychol Child, vol. 9, no. 2, pp. 141–152, 2020.[5] P. Lagos et al., “L-PECs: Application for inclusive work environments,” Procedia Comput Sci, vol. 184, pp. 396–403, 2021.[6] C. Lord, J. B. McCauley, L. A. Pepa, M. Huerta, and A. Pickles, “Work, living, and the pursuit of happiness: Vocational and psychosocial outcomes for young adults with autism,” Autism, vol. 24, no. 7, pp. 1691–1703, 2020.[7
students:Comparative evidence from Poland and Egypt. British Journal of Educational Technology.https://doi.org/10.1111/bjet.13425[5] Tlili, A., Shehata, B., Agyemang, M., Bozkurt, A., Hickey, D. T., Huang, R., & Agyemang,B. (2023). What if the devil is my guardian angel: ChatGPT is a case study of using chatbotsin education. Smart Learning Environment. https://doi.org/10.1186/s40561-023-00237-x[6] Helfrich, T. Why Robotics and Artificial Intelligence Are The Future of Mankind.Forbes Technology Council (2022).https://www.forbes.com/councils/forbestechcouncil/2022/05/31/why-robotics-and-artificial- intelligence-are-the-future-of-mankind[7] Kelly, Rhea. Digital Education Council Global AI Student Survey
. Trellinger, B. Jesiek, C. Troy, J. Boyd, and R. Essig, “Engineering Faculty on Writing:What They Think and What They Want,” in 2016 ASEE Annual Conference & ExpositionProceedings, 2016. [Online]. Available: https://doi.org/10.18260/p.26645.[5] M. F. Cox, J. Zhu, O. Cekic, R. Chavela, and J. London, “Knowledge or Feelings: First-YearStudents’ Perceptions of Graduate Teaching Assistants in Engineering,” The Journal of FacultyDevelopment, vol. 24, no. 1, pp. 27–34, 2010.[6] R. Tormey, C. Hardebolle, and S. Isaac, “The Teaching Toolkit: Design of a One-DayPedagogical Workshop for Engineering Graduate Teaching Assistants,” European Journal ofEngineering Education, vol. 45, no. 3, pp. 378–392, 2020.[7] R. Kajfez and H. M. Matusovich, “Competence
high schoolstudents participating in a new engineering summer program. Through employing severalresearch-supported strategies to promote engagement and build interest [4] with authenticengineering content, the goal of this program is to create situational interest and provideopportunities for students to explore individual interest. Situational interest, if supported, candevelop into long-term pursuit of STEM domains in college and/or careers.We explored situational interest through the following questions: 1. How do high school students' interest levels change from beginning to end of a weeklong engineering camp in: a. Triggered Situational Interest (engagement)? b. Maintained Situational Interest-Feeling (enjoyment
finaldesign project to build spatial skills. These assignments were scaffolded to ensure that skillsintroduced early were reinforced and expanded upon. 4.4.1 Hands-on Activities Relevant to Spatial Vis ProgramThe hands-on activities developed by eGrove Education were integral to the course andcomplemented the Spatial Vis™ program. While some activities followed the original design, theinstructor slightly modified others to align with course goals. These activities offered studentspractical, interactive opportunities to apply spatial reasoning skills, enhancing theirunderstanding through tactile and visual engagement. a) b) Figure 2: (a) Example of top-view plans from the Lesson 2 module in the Spatial
composition of their academic and workplace environments.The demographic data indicates that participants were a diverse sample in terms of major,academic year, number of internships completed, and race and ethnicity (see Appendix B). Allinterviews have been completed, and data analysis is in progress. This article presentspreliminary findings based on a randomly selected subset of 4 of the 15 women and 1 of the 5men. To ensure anonymity, each participant was assigned a unique ID, and no personallyidentifiable information was recorded. Appendix B provides the demographic composition of thefull sample, while Appendix C presents details of the five participants analyzed in this paper.Data AnalysisInductive thematic analysis was conducted [22, 23] by