Inspection Training Group 1 (w/o Adaptive Mechanism) Group 2 (w/ Adaptive Mechanism) Participants 22 6 Samples 82 72 Statistic Time Taken (s) Hits Percentage Time Taken (s) Hits Percentage x) Mean (¯ 68.93 78 % 48.94 83 % Standard Deviation (σ) 34.93 17 % 23.89 14 % Minimum Value (xmin ) 27.00 25 % 10.00 50 % Maximum Value (xmax ) 208.00 100
. For example, three changes were made to the definition for outcome 2 “Students considerimpacts of solutions on relevant contexts.” The word “approaches” substituted “solutions” sincethe performance task prompt doesn’t ask students to specifically identify technical solutions tothe problems raised in the scenario but, rather, to propose approaches that could address or beginto solve the problems. The next modifications were to add two contexts to the existing list:professional and legal. Thus, the revised definition reads: “Students consider how their proposedapproaches to solve the problem(s) impact relevant local, global, professional, economic, legal,environmental, and cultural/societal contexts.”The fourth modification was in the last
department with plans for development as a capstone orindependent study in connection with research in the thin films lab.References[1] CHIPS and Science Act https://en.wikipedia.org/wiki/CHIPS_and_Science_Act[2] Semiconductor Industry Association, “2024 State of the US Semiconductor Industry”,https://www.semiconductors.org/2024-state-of-the-u-s-semiconductor-industry/, 2024. [Accessed13 January 2025].[3] M. Di Ventra, S. Evoy, E., and J. R. Heflin (eds.), Introduction to Nanoscale Science andTechnology, Kluwer Academic Publishers, Springer New York, NY, 2004.[4] D. M. Topasna, “Strategies and Methods for Improving Understanding of Advanced Conceptsin Introductory Nanotechnology Course”, Proc. New Perspectives in Science Education, 11thedition
Instructionˆa C™s Literacy and Language program at Purdue University. She received her B.A and M.S in Korean Language Education from Seoul National University, South Korea. She served culturally and linguistical ©American Society for Engineering Education, 2025 Improving Student Design Through Critical Evaluation: Results from Four Years of Learning by Evaluating (LbE) Research (NSF DRK-12 #2101235)IntroductionDesign is a central focus of high-school engineering courses. Curricula at this level include awide-range of engineering contexts, highlighting the consistent ways of thinking and being as anengineer [1], [2]. Design experiences foster creativity, problem solving, and
: A feminist poststructural lens on stories of women engineering faculty of color. Management Communications Quarterly, 29(3), 440–457.Garrett, S. D., Williams, M. S., & Carr, A. M. (2023). Finding their way: Exploring the experiences of tenured Black women faculty. Journal of Diversity in Higher Education, 16(5), 527–538. https://doi.org/10.1037/dhe0000213Goldberg, C. E., & Baldwin, R. G. (2018). Win-win: Benefits of expanding retirement options and increasing the engagement of retired faculty and staff. New Directions for Higher Education, 182, 69–74. https://doi.org/10.1002/he.20281Kelly, B. T., & Winkle-Wagner, R. (2017). Finding a voice in predominantly white institutions: A
concepts dehydration and sintering of clay-based ceramics to understand change in dimensions and chemistry) 9-12.S.1.2 Students will be able to evaluate and describe the impact of scientific discoveries on historical events and social, economic, and ethical issues. (use materials evolution to understand advancement of civilization) 9-12.S.2.2 Students will be able to analyze factors that could limit technological design. (use glaze chemistry to understand color generation and aesthetics)Pilot High School Program, Summer-Fall 2024Ms. Michelle Crane, co-author and high school teacherat Douglas High School, has performed scientificresearch (Summer 2024) on ceramic glaze formulationsusing 100% local materials from the Black Hills whilebeing funded by
of conversationalways, that students could discover during their analysis of the interviews and include in theirworkstation designs.Table 1: Human-centered Design (HCD) Problem Workstation Design: You have been asked to design the workstations The workstation, at a minimum, that will be constructed in each faculty and staff private office for a should account for: brand-new Industrial Engineering building at the university. Each University assigned desktop computer private office will have a window. This is a workstation meant for a and monitor(s), placement of the sitting individual while working with a desktop computer. There are computer tower / central processing about the same number of male and females
furtherrefinement to the plan, and to overcome some limitations such as controlling for differencesbetween coaches. The hope is that the implementation of this plan will make an impact both interms of outcomes and in the future trajectory of individual participants, especially for first-yearstudents who struggle in their first semester.References[1] T.G. Carter, R.H. Jarman, S. Fenwick, T.O. Schrader, C.M. DiCarlo. “Improving StudentSuccess in STEM with a Student Success Coach and Intrusive Advising.” Proceedings of 2020ASEE Annual Conference and Exposition, 2020.[2] J. Ingham, W.R. McShane “Academic Skills Seminar: A Two-Year Analysis of an IntrusiveIntervention for Freshmen on Probation.” Proceedings of 1998 ASEE Annual Conference andExposition, 1998.[3
-solving skills to prepare them for the challenges of this evolving world.Dr. Michael Helms, Georgia Institute of TechnologyDr. Meltem Alemdar, Georgia Institute of Technology Dr. Meltem Alemdar is s Associate Director and Principal Research Scientist at Georgia Institute of Technology Center for Education Integrating Science, Mathematics and Computing (CEISMC). Her research focuses on improving K-12 STEM education through research on curriculum development, teacher professional development, and student learning in integrated STEM environments. Dr. Alemdar currently serves as PI and co-PI for research on various NSF funded projects that focuses on engineering education, teacher networks and STEM learning environments. Her
and practitioners should consider how SHPE programs can not onlyhelp students see themselves as engineers but also promote broader recognition of Latinxstudents as engineers within the field.References[1] J. Doane and M. D. C. Unda, “Texas’ declining diversity of the undergraduate class, 2015- 2022: A critical policy analysis of anti-DEI legislation in the 88th session of the Texas state legislature,” Texas Center for Education Policy, Report, May 2023.[2] C. J. Orr, J. L. Raphael, M. Klein, A. M. S. Corley, A. Tatem, S.-T. T. Li, M. B. Pitt, S. Gustafson, and M. A. Lopez, “Moving toward diversity, equity, and inclusion: Barriers, consequences, and solutions,” Academic Pediatrics, vol. 23, no. 8, pp. 1524-1525, Nov
? Would you recommend integrating the CHE Calculator earlier in the curriculum? If the CHE Calculator were to be improved, what feature(s) would you prioritize? (Select all that apply) What do you perceive as the strengths and weaknesses of the CHE CALCULATOR®?The survey was distributed via an online platform accessible through the university's learningmanagement system. Participation was voluntary, and no direct incentives were provided forcompleting the survey.To analyze the responses, thematic analysis was conducted by identifying recurring themes acrossstudent feedback. The project team categorized responses into key themes such as usability,documentation, and problem-solving effectiveness.This study was reviewed by the institution's
-engineering- programs-2022-2023/.[2] Al Jahwari, F., Qamar, S. Z., Pervez, T., & Al Maskari, N. (2022). “Using CDIO Principles for Teaching of Mechanical Design Courses.” 2022 IEEE Global Engineering Education Conference (EDUCON), pp. 1683- 1688. IEEE.[3] Alam, K., Qamar, S. Z., & Al-Shabibi, A. (2021). “An Outcome-Based Approach for Applied Mechanics Courses using Bloom’s Taxonomy and ABET Criteria.” 2021 IEEE Global Engineering Education Conference (EDUCON), pp. 996-1002. IEEE.[4] Al-Badrawy, A. A., Al-Nasr, A. H., & Alogla, A. F. (2022). “Engineering Design in New ABET Engineering Criteria: Understanding, Implementation, and Assessment.” International Journal of Engineering Research &
of the proposed educational toolshowed a wide range of variations. Future study could consider the scale-up project byinvestigating the long-term impact of the embodied learning educational tool to young learnerswith the increased sample size.References[1] Y. Kim, J. Hwang, S. Lim, M.-H. Cho, and S. Lee, “Child–robot interaction: designing robot mediation to facilitate friendship behaviors,” Interact. Learn. Environ., vol. 32, no. 8, pp. 4169–4182, Sep. 2024, doi: 10.1080/10494820.2023.2194936.[2] J. Hwang, S. Lee, Y. Kim, and M. Zaman, “Evaluating Young Children’s Computational Thinking Skills Using a Mixed-Reality Environment,” in HCI International 2023 Posters, vol. 1834, C. Stephanidis, M. Antona, S. Ntoa, and G. Salvendy
comparisons to validate these findings across different contexts. Investigation ofspecific intervention strategies could help identify the most effective approaches for developingboth team skills and intercultural competence. Development of standardized assessment toolsand examination of industry outcomes would also provide valuable insights for improving STEMeducation practices.References[1] S. Majid, Z. Liming, S. Tong, and S. Raihana, “Importance of Soft Skills for Education and Career Success,” Int. J. Cross-Discip. Subj. Educ., vol. 2, no. Special 2, pp. 1036–1042, Dec. 2012, doi: 10.20533/ijcdse.2042.6364.2012.0147.[2] P. Bahrami, Y. Kim, A. Jaiswal, D. Patel, S. Aggrawal, and A. J. Magana, “Information Technology Undergraduate
," Cogent Education, vol. 11, no. 1, 2024. doi: 10.1080/2331186X.2024.2309738.[3] C. R. Mann, A Study of Engineering Education. New York, NY, USA: The Carnegie Foundation for the Advancement of Teaching, 1918.[4] S. M. Vidalis and R. Subramanian, "Impact of AI tools on engineering education," in 2023 Fall Mid Atlantic Conference: Meeting Our Students Where They Are and Getting Them Where They Need to Be, Oct. 2023. doi: 10.18260/1-2--45122.[5] L. Agrawal, P. Lanjewar, S. Deshpande, P. Jawarkar, V. Gaur, and A. Dive, "The impact of AI on communication skills training: Opportunity skills and challenges," Nanotechnology Perceptions, pp. 1167-1173, 2024. doi: 10.62441/nano-ntp.v20iS7.96.[6] M. Itani and I. Srour, "Engineering students
(3)where, S is a stride step (if s=1, we move the filter one pixel at a time on the image), K is number of filters used, F is filter size, W and H are width and height of input image.The output of the first convolutional layer is passed to a max pooling layer, which reduces thespatial dimensions while retaining essential features. The pooling window is of size 2×2 with astride of 1. The dimensions of the output feature map are computed using equations (4-6). 𝑊−𝐹 𝑊" = +1 (4) 𝑆
-González, M., & Robles, G. (2020b). LearningML: A Tool to Foster Computational Thinking Skills through Practical Artificial Intelligence Projects; Revista de Educación a Distancia; 20(63).[5] Rodríguez-García, J. D., Moreno-León, J., Román-González, M., & Robles, G. (2021). Evaluation of an online intervention to teach artificial intelligence with learningML to 10-16-year-old students. In Proceedings of the 52nd ACM technical symposium on computer science education (pp. 177–183).[6] Sakulkueakulsuk, B. S.;Witoon, P. Ngarmkajornwiwat, P. Pataranutaporn, W. Surareungchai, P. Pataranutaporn, P. Subsoontorn (2018). “Kids making AI: Integrating Machine Learning, Gamification, and Social Context in STEM
address specific challenges identified by students, improve student success,and promote a more inclusive BME community.References[1] C. Donham, C. Pohan, E. Menke, and P. Kranzfelder, "Increasing Student Engagement through Course Attributes, Community, and Classroom Technology: Lessons from the Pandemic," Journal of Microbiology & Biology Education, vol. 23, no. 1, pp. e00268-21, 2022, doi: doi:10.1128/jmbe.00268-21.[2] J. Grodotzki, S. Upadhya, and A. E. Tekkaya, "Engineering education amid a global pandemic," Advances in Industrial and Manufacturing Engineering, vol. 3, p. 100058, 2021/11/01/ 2021, doi: https://doi.org/10.1016/j.aime.2021.100058.[3] R. S. Heller, C. Beil, K. Dam, and B. Haerum
= 104 n = 48 and Robotics education in formal and informal education Records centered around Records excluded for not being Robotics Education journal articles n = 56 n=7 Comparison: Traditional Records excluded for: curricula v/s AI, Robotics 1. Not being relevant or Eligibility enriched
is a summary of our findings in scholarly literature.The most helpful articles in navigating through all the literature were systematic or exploratoryreviews, where researchers provide summaries of a multitude of academic articles in AI. Webegin by discussing the broader core conceptual frameworks that were identified. In Ng, et al.’s[11] exploratory review of academic literature on AI, they offer four broad aspects of fosteringAI literacy, based on Bloom’s taxonomy: know and understand, use and apply AI, evaluate andcreate AI, and AI ethics. In a more recent review of the literature, Amatrafi et al [12] similarlyidentified five core constructs in framing AI literacy: recognize (be aware), know andunderstand, use and apply, evaluate, create
model,processes, and results, we inspire others to implement similar models aimed at advancing ourdisciplines.8. References[1] R. B. Mitchell and C. S. Weiler (2011). Developing next-generation climate change scholars:The DISCCRS experience. Journal of Environmental Studies and Sciences, 1(1), 54-62.[2] M. Mobjörk, C. Berglund, M. Granberg and M. Johansson (2020). Sustainable developmentand cross-disciplinary research education: Challenges and opportunities for learning. HögreUtbildning, 10(1), pp.76-89.[3] National Academy of Sciences (2005). Facilitating interdisciplinary research. Washington,DC: The National Academies Press.[4] D. McGunagle and L. Zizka (2020). Employability for 21st-century STEM students: Theemployers’ perspective. Higher
, research, planning,conducting interview(s), editing, and assessing. The development phase includes topic selectionand story arc refinement, to ensure a clear vision heading into each episode. Next, the interviewershould research the topic, guest(s) and other relevant materials needed for question preparation.Interviewers may conduct pre-interview with the guest to learn specifics for the episode, as needed.A team member from the Journalism Department in the College of Media prepared a lecture called,“Interviewing 101”, to provide faculty with a step-by-step guide for preparing for interviews.RecordingGiven the popularity of podcasts as a media platform multiple podcast studios exist on campus,available for use free of charge. So far, we have found
competitive advantage. In this paper, we argued that lifelong learning is not merelyan individual pursuit but a strategic imperative for engineering workforce development. Futureresearch could explore the distinct challenges faced by engineers in specialized sectors likeaerospace, healthcare, or renewable energy, and the strategies to foster lifelong learning ofengineers in their own contexts. These sectors demonstrate fields where lifelong learning is notonly beneficial but also essential for both individual career endurance and societal impact.Studies can provide targeted recommendations to enhance workforce development efforts inthese specific sectors.References[1] G. Lokesh, K. Harish, V. S. Sangu, S. Prabakar, V. S. Kumar, and M. Vallabhaneni
Attending department retreats Attending short courses and workshops. Reading non-technical books/journals papers. Ex: Leadership, Writing, Communication, Goal setting, etc. Reading technical books/journals - both teaching and research Responding to reviews/criticism for grants, papers, etc. Serving as a session chair or co-chair Serving on committee(s) (internal or external) Setting annual goals. Ex: Submitting proposals, obtaining funding, winning awards, strengthening CV, etc. Taking breaks. Ex: Regular sleep, weekly downtime, annual vacation Talking to friends/mentorsTherefore, various habits help faculty succeed in their multi-faceted job. How faculty learn aboutor form these habits relates to the responses to our research questions, which are
able to conclusively demonstrate the existence of an AI implementation gap between the twocountry blocs, which is further widened if two major Global South players (India and China) are excluded from theanalysis. It is likely this AI gap also impacts the realization and actualization of the E.D. 5.0 – I.D. 5.0 – Society 5.0vision globally.Conflicts of InterestThe authors declare no conflicts of interest.References[1] Adel, A. (2024). The convergence of intelligent tutoring, robotics, and IoT in smart education for the transitionfrom industry 4.0 to 5.0. Smart Cities, 7(1), 325-369.[2] Ahmad, I., Sharma, S., Singh, R., Gehlot, A., Priyadarshi, N., & Twala, B. (2022). MOOC 5.0: A Roadmap to theFuture of Learning. Sustainability, 14(18
, “Motivation and cognitive load in the flipped classroom: definition, rationale and a call for research,” Higher Education Research and Development, vol. 34, no. 1, pp. 1–14, Jan. 2015, doi: 10.1080/07294360.2014.934336.[6] M. Mojtahedi, P. Eng, I. Kamardeen, H. Rahmat, and C. Ryan, “Flipped Classroom Model for Enhancing Student Learning in Construction Education,” 2019, doi: 10.1061/(ASCE)EI.2643-9115.0000004.[7] B. Schmidt, “Improving Motivation and Learning Outcome in a Flipped Classroom Environment,” in International Conference on Interactive Collaborative Learning (ICL), Dubai: IEEE, Dec. 2014, pp. 689– 690.[8] S. J. DeLozier and M. G. Rhodes, “Flipped Classrooms: a Review of Key Ideas and Recommendations
, ABET, 2022.[3] W. H. Guilford, "Teaching peer review and the process of scientific writing," Advances in physiology education, vol. 25, no. 3, pp. 167-175, 2001.[4] J. Ford and S. Teare, "The right answer is communication when capstone engineering courses drive the questions," Journal of STEM education, vol. 7, no. 3, 2006.[5] W. E. Britton, "What is technical writing?," College Composition and Communication, vol. 16, no. 2, pp. 113-116, 1965.[6] C. Brooks and R. P. Warren, Understanding Poetry: By Cleanth Brooks and Robert Penn WOrren. Holt., 1960.[7] A. F. Warsame, "The Gap Between Engineering Education and Post-graduate Preparedness," Ed.D., Walden University, United States -- Minnesota, 10634462
, and conclusions or recommendations expressed in thismaterial are those of the author(s) and do not necessarily reflect the views of the NationalScience Foundation. ReferencesAckermann, S. P. (1990). The Benefits of Summer Bridge Programs for Underrepresented and Low-Income Students.Andalib, M. A. (2021). Simulation of the leaky pipeline: Gender diversity in U.S. K-graduate education. Journal of Simulation, 15(1–2), 38–50.Ahn, M. Y., & Davis, H. H. (2023). Students’ sense of belonging and their socio-economic status in higher education: a quantitative approach. Teaching in Higher Education, 28(1), 136-149.Banda, R. M., & Flowers, A. M. (2018). Critical qualitative
Science Foundation under Grant No. 1943098. Opinions,findings, and conclusions are those of the authors and do not necessarily reflect the views of theNSF. BibliographyArdoin, S. (2017). College aspirations and access in working-class rural communities: The mixed signals, challenges, and new language first-generation students encounter. Lexington Books.Carrico, C. A. (2013). Voices in the mountains: A qualitative study exploring factors influencing appalachian high school students’ engineering career goals. https://vtechworks.lib.vt.edu/items/c342c9ca-2037-4700-be5a-5eaa85626b26Sciences, N. A. of, Behavioral, D. of, Sciences, S., Policy, Affairs, G., Education, B. on S
Paper ID #48061Personalized Learning Paths: LLM-Based Course Recommendations in ManufacturingEducationProf. Xiaoning Jin Prof. Xiaoning (Sarah) Jinˆa C™s research focus is in the area of modeling and analysis for intelligent and advanced manufacturing processes and systems, with a specialization in diagnostics and prognostics (D&P), control and predictive decision making.Dr. Sagar Kamarthi, Northeastern University Sagar Kamarthi is a Professor of Mechanical and Industrial Engineering and the Founding Director of the Data Analytics Engineering Program at Northeastern University, Boston. He received his MS and Ph.D