the Knight Foundation School of Computing and Information Sciences , and the Director of the Virtual Intelligent Social AGEnts (VISAGE) Laboratory. Her long-term research goal is to create engaging virtual social agents (VISAGEs) that can help humans in a variety of contexts by interacting with them in innovative ways, through natural expressive multimodal interaction (e.g. in digital health interventions, cybertherapy, health counseling, educational serious games, cyberlearning, simulation-based social skill training systems). She conducts basic research at the intersection of human-computer interaction (HCI), affective computing (I was on the founding Editorial Board of the IEEE Transactions on Affective
dissonance between EDI.I ‘goals’ espoused by our universityand its actions on actual issues of equity, such as the university’s response to grad studentsunionizing, or to the community’s divestment demands. Looking back, I realize that my approachto EDI.I was an oversimplification and an example of applying colonial practices to‘decolonization’, or using the master’s tools to dismantle the master’s house, which, as AudreLorde has written [32], will never happen.What I did find from my master’s research was a tendency for well-meaning engineeringinstructors to justify their ‘EDI.I content’ with assumptions of profit and performance aspriorities. For example, more than one course cited studies showing how diverse teams lead tomore innovation and
National Study on the Governance of Engineering Education,” in 2019 ASEE Annual Conference & Exposition Proceedings, Tampa, Florida: ASEE Conferences, Jun. 2019, p. 32020. doi: 10.18260/1-2--32020.[44] I. M. Roffe, “Conceptual problems of continuous quality improvement and innovation in higher education,” Qual. Assur. Educ., vol. 6, no. 2, pp. 74–82, Jun. 1998, doi: 10.1108/09684889810205723.[45] Z. Huq and J. D. Stolen, “Total quality management contrasts in manufacturing and service industries,” Int. J. Qual. Reliab. Manag., vol. 15, no. 2, pp. 138–161, Mar. 1998, doi: 10.1108/02656719810204757.[46] S. Malcolm and M. Feder, “Barriers and Opportunities for 2-Year and 4-Year STEM Degrees: Systemic Change to Support
thorough understanding of nine quantumconcepts. while others answered questions about general confidence, programming skills, preferredlearning styles, and topics that interest them in the quantum field. The exit survey evaluated participants’ learning outcomes, their understanding of the nine quan-tum concepts, and their perceptions of the course. It assessed various aspects of the course structure,including design, pacing, difficulty, and workload, to ensure a balance between challenge and manage-ability. The effectiveness of the instruction was also examined, focusing on the clarity of the teachingand the use of innovative strategies. A significant part of the survey focused on the effectiveness ofsimulated and dynamic visualization slides
’ future international engineering plans. Appendix E details these results.Within one month of returning back to the US, students were asked to provide open-endedreflections from their experiences in South Africa. Key themes from student submissions aredetailed in Table 2. Notably, 71% of students commented on the unequal access to healthcarestemming from systemic inequality in South Africa. 57% of students discussed the personalimpacts of the trip, which included identifying personal privilege, feeling inspired ortransformed, and noting the importance of first-hand experiences. 57% of students also expressedthe importance of biomedical engineering innovations for the low-resource settings that theyobserved. Approximately one third of students
the two pieces of code.” 3. “The most valuable lesson I’ve learned from this exercise is that AI is not a one-size-fits-all solution. Human intuition remains essential in engineering. AI, while a powerful tool, cannot think, innovate, or match the creativity of the human mind. It complements our work but cannot replace us.” 4. “To effectively leverage AI, engineers must fully grasp core concepts and fundamental principles. These are the skills that distinguish humans from machines, providing the intuition and logical framework needed to ”fact-check” the errors and inconsistencies that AI may generate.” 5. “I believe that you need a firm understanding of the core concepts
and practitioners,” in Proceedings of the 2019 Working Group Reports on Innovation and Technology in Computer Science Education. Association for Computing Machinery, July 2019, pp. 89–109. [Online]. Available: https://dl.acm.org/doi/10.1145/3304221.3325534[10] M. Tight, “Theory application in higher education research: The case of communities of practice,” European Journal of Higher Education, vol. 5, no. 2, pp. 111–126, April 2015. [Online]. Available: https://doi.org/10.1080/21568235.2014.997266[11] M. Joy, J. Sinclair, S. Sun, J. Sitthiworachart, and J. L´opez-Gonz´alez, “Categorising computer science education research,” Education and Information Technologies, vol. 14, no. 2, pp. 105–126, June 2009. [Online
capabilities from the program’scurriculum [10], 2) an Engineering Leadership seminar-style class, synchronized with the ELL,where students study the academic background of leadership capabilities prior to a given ELL anddiscuss lessons-learned from the previous week’s ELL, and, 3) one from several elective courses thatfulfill a Design and Innovation Leadership Requirement focused on the engineering design processand its inherent teamwork and leadership components. The total student workload for those in theprogram’s first year, typically undergraduate juniors, is approximately that of 1.5 full credit MITcourses. The program’s second year, typically undertaken by undergraduate seniors, constitutes anadditional workload approximately equal to two more
Computer Science Program, Bina Nusantara University, Jakarta, Indonesia 11480*Corresponding Author: Arief S. Budiman (suriadi@alumni.stanford.edu) ABSTRACTAchieving the Net Zero Emissions scenario by 2050 requires more solar energy production – butit must not be at a cost to traditional agricultural land uses. We report an innovative photovoltaicconfiguration to optimize solar energy generation in agricultural settings without compromisingor competing with agricultural production (also known as Agrivoltaics). It indeed enhances theoutcome quality of agricultural production. Polymer-based greenhouse structures (or solar domes)are typically part of the agricultural ecosystems, especially for those
), Chemtrade Logistics, International Petroleum, and the Canadian Mining Innovation Council. ©American Society for Engineering Education, 2025What Makes a Leader? Conceptualizations of Leadership and Implications for Teamwork in First Year DesignIntroductionLeadership identity development for engineers is more critical than ever to create sustainable andequitable solutions in today’s complex world. Despite its importance, leadership remains achallenging competency for students to develop, and engineering educators to teach. A keycomponent of leadership development is understanding what leadership means to an individual[1]. This can be quite challenging for students, as leadership is a complex
teleoperations in aerospace parts fabrication– that is, partsmanufacturing from a remote location [7]. These examples are but few of many that highlightVR’s potential to increase efficiency, safety, and innovation in the aerospace industry.Use in EducationImmersive VR has seen a variety of uses in K-12 education [8–12] and university-levelapplications, including topics such as physics [13], chemistry [14, 15], architecture [16, 17], andmost extensively, medicine [10, 14, 18, 19]. These implementations not only enhance studentengagement and comprehension but also offer interactive, experiential opportunities thattraditional methods struggle to efficiently replicate. As an added bonus, institutions that integrateVR courses into their curricula often gain
requires new strategies thatpromote active learning, personalized interaction, and deeper reflection on ethical responsibilities [11].AI Chatbots and Enhanced LearningAs engineering education seeks to better prepare students for professional challenges, emergingtechnologies offer promising new tools for supporting ethical reasoning development. Artificialintelligence (AI) and digital platforms are already transforming the broader economy and workforce [12],and within education, AI-powered chatbots have been explored as innovative resources for tutoring,coaching, and skill development [13], [14]. Systematic reviews confirm that AI chatbots can enhanceeducational access, personalize learning experiences, and support student engagement across
strengths. Recently, additive manufacturing has been at theforefront of innovative manufacturing [5]. One such process is Fused Deposition Modeling(FDM), which uses thermoplastic filaments to create 3D objects. FDM has become increasinglycommon, especially in undergraduate curricula. The main advantage of FDM printers is the lackof rigid constraints for production, allowing the process to manufacture components too complexfor other machines. In comparison to other manufacturing processes, the material and the 3Dprinters are generally low-cost. As interest increases and widescale availability improves forFDM manufacturing, engineering education is generally lagging behind current technology [6].The new additive manufacturing trend has forced
issues. • Reward teaching excellence and educational innovation”.Underlying these recommendations was the view that “technological literacy is concernedwith sophisticated and heterogeneous combination of “knowledge, ways of thinking andcapabilities”.This was followed up by a National Academy sponsored workshop on “The TechnologicalLiteracy of Undergraduates. Identifying the Research Issues” organized by John Krupczakand David Ollis [34]. It identified the need for an organization to serve as a focal point fortechnological literacy. To meet this need ASEE fostered a Constituent Committee for thispurpose, and given its initial success ASEE formed a Division for Technological Literacy in2008. Prior to the foundation of the Division Kathryn
professional interactions more effectively. This focus on agency around communication aligns seamlessly with her broader mission to equip engineers not just with technical skills but with the leadership, mentorship, and communication competencies essential for driving innovation and fostering inclusive growth in the field. Her groundbreaking contributions to engineering education, supported by nearly $8 million in federal funding and over 100 refereed publications, continue to redefine the standards of excellence in the profession. Dr. Simmons’s dedication to empowering underrepresented groups and guiding minority-serving institutions earned her the esteemed honor of Fellow Member in the American Society for
Experience For Engineering And Technology Students Paper presented at 2001 Annual Conference, Albuquerque, New Mexico. 10.18260/1-2--9457[10] Sathyamoorthy, M. (2003, June), An Innovative Co Op Program At WVU Tech Paper presented at 2003 Annual Conference, Nashville, Tennessee. 10.18260/1-2--12406[11] Cala, M., & Patel, J., & Kudav, G., & Davis, B. (2004, June), Industry University Partnership A Model For Faculty Continuing Development And Student Co Op Opportunities Paper presented at 2004 Annual Conference, Salt Lake City, Utah. 10.18260/1-2--12858 10[12] Bankes, W., & Eastman, M., & Trippe, A., & Lillie, J
coursework. By leveraging AI, this study contributes to ongoingdiscussions about innovative teaching methods and the future of engineering economiceducation.IntroductionArtificial Intelligence (AI) is rapidly transforming industries and society, and its influence inhigher education, particularly engineering education, is becoming increasingly significant. AItechnologies are reshaping how knowledge is imparted and how students engage with complexconcepts. The integration of generative AI, such as large language models like ChatGPT, presentsnew opportunities to enhance personalized learning, improve problem-solving skills, and fostermore interactive educational experiences. As AI continues to advance, it is crucial thateducational systems adapt
and Mechanical Engineering MS degrees from Purdue University in 2020 and 2021, respectively, and graduated from Calvin College in 2015 with a B.S.E. concentrating in Mechanical Engineering. Beyond instruction, he continues to conduct research focusing on student experience and experiential learning in context with innovative instructional practices.Iman Shayegani, University of Cincinnati Iman Shayegani is a Ph.D. student at University of Cincinnati. He received his Bachelor’s degree in Electrical Engineering from University of Tehran and his Master’s degree in the same field from Shiraz university. He had been an educational consultant and a mathematics teacher for over 10 years in Iran, and helped more than 1000
University at West Lafayette (PWL) (COE) Muhsin Menekse is an Associate Professor at Purdue University with a joint appointment in the School of Engineering Education and the Department of Curriculum & Instruction. Dr. Menekse’s primary research focuses on exploring K-16 students’ engagement and learning of engineering and science concepts by creating innovative instructional resources and conducting interdisciplinary quasi-experimental research studies in and out of classroom environments. Dr. Menekse is the recipient of the 2014 William Elgin Wickenden Award by the American Society for Engineering Education. He is also selected as an NSF SIARM fellow for the advanced research methods for STEM education research. Dr
simple, certain, and objective. Similarly,students’ epistemic beliefs can clash with their experiences or outcome expectations, resulting indifficulties for both instructors and other students, particularly in innovative educational settings[76]. These examples highlight the important role of epistemic cognition in students’ learningand success, development of critical thinking skills, and transition to real-world engineeringpractice. Consequently, educators should consider students’ evolving epistemic cognition andwork to integrate pedagogical strategies, evaluation practices, support systems, and curricularmaterials to support its development.Given the parallels between epistemic cognition and engineering judgment, we argue thatepistemic