ASEE North Central Section Conference Copyright © 2025, American Society forEngineering EducationIn general, the web provides democratized access to information. Printed materials are onlyavailable to those who have them. AI uses information from the web. AI helps overcomebarriers because it makes the web easier to use, so information is even more democratized.Q9: What challenges or limitations do you foresee in integrating AI into engineeringeducation (e.g., cost, ethical concerns, technical barriers)?All learning should be from basic theory up to application. AI adds one more level of learningthat is required. It is one more thing that must be taught. This adds to the burden of education.There are many ethical concerns. For example, AI will
and inclusion in engineering is an ethical imperative and key to advancing scientificprogress and societal development (Delaine et al., 2016; Williams et al., 2016). As a result, thereis a growing focus on creating a diverse and inclusive environment in the engineering educationresearch community.The Role of Language in Engineering Education Inclusivity In recent publications in the field of engineering education, researchers have emphasizedthat even implicit and unintentional linguistic biases can profoundly impact underrepresentedgroups, particularly in terms of feeling socially included or excluded (Aeby et al., 2019; Golbecket al., 2016). These biases affect dimensions such as gender, race, ethnicity, and other socialidentities
that transformative leadership is a should be encouraged to start and subscribe to instructionalstandard of ethical leadership which integrates normative and blogs and podcasts to stay current on the latest trends and bestinstrumental elements of perspectives to optimize long-term practices in education leadership. Digital broadcasts can beexcellence [33]. Montuori and Donnelly wrote that the theory facilitated on locales like Anchor or Podbean, and websites canalso suggests that everyone can lead and that the process of be composed on platforms like WordPress or Blogger.transformative leadership is one in which participants cocreatethe world through choice, action, discussion, and reflection that
get caught up in these little bubbles. When you die, your bubble stops because your body [is]obsolete and becomes dated and we now need a new version. Versus building a legacy as to, you're leaving a footprint where people remember not just the title of the name, the person. That’s why I say, I'm unapologetically me. ~ Lola, Black/African American• Recall that EM is considered a cognitively based phenomena. Specifically, cognition – the way one thinks and metacognition – how one thinks about thinking.• This includes growth mindset, resourcefulness, and ethical and social responsibility but in our sample, this also represented the negative thought processes experiences by participants such as stereotype threat and imposter
higher for females highlight theirheightened sensitivity and responsiveness to environmental issues, which could be linked to amore empathetic and caretaking disposition.Conversely, male students scored higher in Basic Determinism, Religious Traditionalism, andGender Traditionalism. Higher scores in Basic Determinism suggest that male students are moreinclined to see the world in terms of fixed rules and predictable outcomes, which might makethem less flexible in adapting to new or uncertain situations. Increased scores in ReligiousTraditionalism for male students indicate a stronger adherence to traditional religious beliefs andpractices, which could influence their moral and ethical decision-making processes. Thesignificantly higher scores in
learning environments, computer science education, and Artificial IntelligenceDr. Laura E Brown, Michigan Technological UniversityDr. Jon Sticklen, Michigan Technological University Jon Sticklen is an Associate Professor with the Engineering Fundamentals Department (EF) and Affiliated Faculty with the Department of Cognitive and Learning Sciences (CLS). He served as Chair of EF from 2014-2020, leading a successful effort to design aDr. AJ Hamlin, Michigan Technological University AJ Hamlin is a Principle Lecturer in the Department of Engineering Fundamentals at Michigan Technological University, where she teaches first-year engineering courses. Her research interests include engineering ethics, spatial visualization
ofmaking design decisions in economic, environmental, and societal contexts is emphasized from theperspectives of engineering and physical and mental health.“The Intersection of Society and Design” explicitly addresses four societal impact outcomes in ABETCriterion 3: Student Outcomes 2, 3, 4, 5, which emphasize the public health and safety impacts ofdesign, ethical decision-making, collaborative productivity as a team member, and effectivecommunication with diverse audiences [2].Increasingly professionals in all fields are called upon to present technical concepts of their disciplinesto a non-technical audience [3]. Juan Felipe Pulido wrote that I wish I’d known that being an engineer involves more than just engineering—more than
actionimproves learning [12]. However, the instructor sometimes intervened and slightly altered thecomposition of the groups to ensure a proper and balanced mix of students in terms of academicsand work ethics among other factors.Each group was requested to seek and list three initial real highway problems as possible themesfor the projects. As seen later, a single theme would be established as the research topic of theproject for each group based on certain criteria in consultation with the instructor. Each groupwould briefly present its three possible highway problems to the entire class.One of the criteria in choosing the candidate highway problem that would be under investigationwas its location. Safety was a concern with a paramount significance
. Valdiviezo-Díaz, G. Riofrio, Y.-M. Sun, and R. Barba, “Integration of Virtual Labs into Science E-learning,” Procedia Computer Science, vol. 75, pp. 95–102, Jan. 2015, doi: 10.1016/j.procs.2015.12.224.[11] laurashalvey, Parts of the eye. 2020. [Online]. Available: https://www.tinkercad.com/things/kAFGm4qxwZG-parts-of-the-eye[12] F. Wallace-Tarry, Al the parts of the eye. 2018. [Online]. Available: https://www.tinkercad.com/things/bl8qRQVVp1t-al-the-parts-of-the-eye[13] T. Foltynek et al., “ENAI Recommendations on the ethical use of Artificial Intelligence in Education,” Int J Educ Integr, vol. 19, no. 1, Art. no. 1, Dec. 2023, doi: 10.1007/s40979-023- 00133-4.[14] B. Balamuralithara and P. C. Woods
circuits.Additionally, the course covers a range of essential electrical and electronic components,including resistors, capacitors, batteries, diodes, and servo motors, exploring their operation andapplications.To complement the technical content, the course integrates elements of engineering educationand accreditation, emphasizing the importance of ethical practices and professional standards.Students are also exposed to engineering design concepts, learning to approach problem-solvingsystematically and creatively. The course culminates in training students in effective engineeringsolution presentation and data presentation and reporting, equipping them with essentialcommunication skills for future academic and professional endeavors.Employed teaching
their peers will be held to, fostering a senseof accountability and transparency. At the end of the semester, students self-assess theirown and their peers' performance using these rubrics. This process encouragesreflection on their own work and contributions, as well as those of their classmates.Finally, students complete an anonymous survey to assess the effectiveness and successof the rubrics. This survey is designed to gather detailed feedback on various aspects ofthe rubrics, including clarity, fairness, and their impact on learning and engagement.The rubrics were implemented across two semesters. 29 students participated in thestudy during the first semester and another 22 students participated during the secondsemester. Ethics approval
]. Additionally, thedominance of authoritative publications equating EdTech with material tools like computers mayreinforce a narrow view of EdTech [4].One of the most widely adopted EdTech definitions is the 2008 definition offered by AECTdescribing EdTech as “the study and ethical practice of facilitating learning and improvingperformance by creating, using, and managing appropriate technological processes andresources” [8], incorporating both hard and soft technologies. A review of the literature indicatesthat while some studies adopt this definition (e.g., [9]), others elaborate on it (e.g., [10]) orpropose their own definitions of EdTech (e.g., [11], [12]).In this research, EdTech is defined as tools, technologies, and resources [13] that are
, DOI: 10. 1080/105112506008661663. Fask, A., Englander, F., & Wang, Z. (2014). Do online Exams Facilitate Cheating? An Experiment Designed to Separate Possible Cheating from the Effect of the Online Test Taking Environment. J Acad Ethic, 12:101–112 DOI 10.1007/s10805-014-9207-14. Charlesworth, P., Charlesworth, D.D., & Vician, C. (2006) Students’ Perspectives of the influence of Web- Enhanced Coursework on Incidences of Cheating, Journal of Chemical Education, vol. 83 No.9.5. Chegg Inc., website https://www.chegg.com, accessed on November 4th, 2024.6. ChatGPT 4o, https://chat.openai.com, accessed on November 4th, 2024.7. Coure Hero, website www.coursehero.com, accessed on November 4th, 2024.8. Nader, M
lecture-only approach) and Spring 2024 (teacher-guided approach). The exams for both semesters were identical, ensuring consistency in assess-ment, and the data was downloaded from Canvas without any personally identifiable information,thus avoiding ethical concerns.3.3.1 Data Selection and MetricsExam questions related to the LinkedSet project were manually identified based on their alignmentwith the concepts taught during the project. These questions assessed students’ understanding ofcore Java topics such as: • Interfaces and generics. • Iterators and data structures. • Polymorphism and object-oriented principles. • Set operations and structural manipulation in collections.The following metrics were analyzed for each
capability. Many universities have industrial advisory boards that IV. DATA COLLECTION provide feedback and support, so universities can betterA. Professor McAdams understand their employment skills needs. They identify gaps that they experience in their workforce. These gaps In Fall 2024, more than 50 students attended UB’s Ethics consistently include lack of communication, critical thinking,and Economics graduate course, in which 80% were from the problem solving
artificial intelligence generates artworks similar to aexpression. Walter Benjamin (1936) argued that mechanical training dataset, a challenge to the definition of art arises. If areproduction transformed the art world, altering notions of generative algorithm is trained on Van Gogh paintings andoriginality and authorship. Similar discussions arise with AI- generates a new painting, Van Gogh is the creator, even thoughgenerated art, as artists navigate new ethical and creative dead.challenges. Similarly, input data denotes authorship for an AI-modelThe democratization of artistic tools, fueled by AI, allows trained on human-generated
innovation and technology whileanalyzing methodologies for agriculture settings. Lastly, students are given an opportunity toobserve policy and ethics in the field of smart agriculture as a means to finalize their courseworkwhile working on the completion of their research.Again, a unique challenge is present with students in that individuals may not come from anagriculture background. Thus, both undergraduate and graduate tracks are designed to help thosewith a non-agriculture background understand the field while catering to those who may alreadyunderstand agricultural core concepts. General theory and broad overview courses are embeddedwithin the program to help students capture any missing knowledge they may lack in terms ofproduction. The
ethical considerations. Theoretical FrameworkOur analysis integrates three complementary theoretical perspectives to understand AI's role inengineering education. Building on Sweller's (1988) Cognitive Load Theory, we examine howAI tools can reduce extraneous cognitive demands in complex engineering tasks. Mayer's (2019)analysis of multimedia learning environments demonstrated that AI-supported cognitivescaffolding reduced cognitive load by an average of 35% while improving problem-solvingaccuracy by 42%. These findings align with Johnson and Smith's (2018) longitudinal study of1,200 engineering students, which found that AI-enhanced mastery experiences led to a 40%increase in student self-efficacy ratings and
lap around the building with minimal humanintervention. This will be accomplished in a cost effective and sustainable way, subject toenvironmental constraints and the longevity of the materials. Additionally, ethical constraintsalong with state and local laws and regulations will be adhered.The long-term production goal for this project is to create a full package autonomous kit that canretrofit any SMV. With a robust control framework and a focus on safety, the autonomousdriving retrofit system could be extended in terms of application to other types of vehicles, suchas tractors, mowers, mobility scooters and more. This entails stricter adherence to accessibilitywith the intent goal of reducing mobility issues on campuses and facilities by
critiques of teaching methods (Q6) and However, several challenges regarding teaching prompt skills assessment performance.engineering have been identified in the literature. In [3], the We used three primary instruments:authors note that while structured training can enhance students'AI literacy, there are concerns about the varying levels of prior 1. Pre- and Post-Intervention Surveys: Six Likert-scaleknowledge among students and the need for discipline-specific questions (1–5 scale) assessed understanding of AIadaptations. The authors in [4] further discuss the ethical (Q1), proficiency in prompt engineering (Q2), problem-implications and potential over-reliance on AI tools, which
University where he teaches courses on ethics/professionalism and water resources. Dr. Carpenter has served as the University Director of Assessment and theAlyssa TaubeLynne Seymour ©American Society for Engineering Education, 2025 Collaborative Outreach to Inspire Interest in Civil and Environmental Engineering Through Stormwater Design using Best Management PracticesAbstractThis paper presents an engaging activity developed for the outreach event Blue Planet Jobs:Careers in Water, hosted by the nonprofit organization Pure Oakland Water (POW).Approximately 250 high school students participating in career readiness programs exploredopportunities in various water
; Inside Higher Ed, 11/22/247. Brendon Lumgair: The Effectiveness of Webinars in Professional Skills and Engineering Ethics Education in Large Online Classes; American Society for Engineering Education, 2018 Conference8. Kimberly Bernadine Catton, Abril Galang and Alexander T Bulk: Disruption in Large Classes during Active Learning Sessions,;American Society for Engineering Education, 2016 Conference9. Tom McCormick, James C. Squire, Gerald Sullivan: Pedagogical Effectiveness of Classroom Demonstrations Devices; American Society for Engineering Education, 2018 Conference
over time. Also, a comparison between construction and relevant programs (e.g.,architecture, civil engineering, etc.) may highlight similarities and differences. The findingsdiscussed in this paper provide valuable insights for construction education programs andindustry stakeholders. By addressing gender-specific factors in recruitment, retention, andsupport strategies, programs can work towards creating a more diverse and inclusive learningenvironment and, ultimately, a more balanced workforce in the construction industry.References[1] T.-D. T. Nguyen, "Gender Gap in College Enrollment," Encyclopedia of Business and Professional Ethics, pp. 955-957, 2023.[2] S. Cheryan, S. A. Ziegler, A. K. Montoya and L. Jiang, "Why are some STEM fields
struggles with subjective elements suchas creativity, critical thinking, and originality [6]. These limitations raise concerns about thefairness and reliability of AI in grading assignments requiring higher-order cognitive skills.Bias is another critical issue in AI grading. Since AI models are trained on existing data, theymay inadvertently replicate biases in the training datasets [4]. For instance, studies havereported disparities in grading outcomes for non-native English speakers and minority groups,raising ethical questions about the use of AI in academic assessment [11].2.4. Comparing AI and Human GradingComparative studies between AI-assisted and human grading have yielded mixed results.While some studies report high levels of agreement
university-based and consulting efforts have led to over $40M in funding for projects to support initiatives in STEM and changes to policies and practices of global engineering organizations. Pearson is a registered Professional Engineer, an ENVISION® Sustainability Professional, and a Commissioner on ABET’s Engineering Accreditation Commission. Among her awards and honors are ABET’s Claire L. Felbinger Award for Diversity and Inclusion, ASCE’s Professional Practice Ethics and Leadership Award, the Society of Women Engineers’ Distinguished Engineering Educator Award, the UT System Regents Outstanding Teaching Award, and ASCE’s President’s Medal, one of the highest honors awarded in this global organization of over
education. Her main research interests include Improving engineering students’ learning, innovative ways of teaching and learning, and how artificial intelligence can be used in education in a creative and ethical way.Ms. Amanda Kate Lacy Amanda Lacy is a PhD student at Texas A&M University in the department of Computer Science and Engineering. Her interests are broad, with an emphasis on applying computing to promote access to information and spaces, both virtual and physical. She holGene Sung-Ho Kim, Stanford UniversityDr. Gibin Raju, Texas A&M University Gibin Raju is a Postdoctoral Researcher at Texas A&M University in the Department of Multidisciplinary Engineering. He completed his Ph.D. in Engineering
helpful for the new assessmentprocess piloted for UPSILON and to accommodate the scheduling and constraints of the directorand staff to accommodate changes in the program schedule.Considerations for Focus GroupsWhen planning and conducting the focus groups, several key considerations were addressed toensure a supportive and productive environment. We reviewed relevant literature on focus groupmethodologies and consulted with facilitators who had experience working with similaraudiences [20], [21]. The protocol used for the focus groups is available upon request.Given the age of the participants and the sensitive nature of discussing gender and racial issues,certain ethical considerations were paramount. It was important to create an environment
required to ensure ethical data collection, storage, andprocessing. Mishandling user data can lead to privacy breaches, undermining trust in the system.Adaptability to Evolving Threats − Phishing tactics constantly evolve, making it difficult for static rule-based systems to remain effective. Attackers continuously refine their methods to bypass detection,necessitating a system that can dynamically learn from new threats and adapt in real time. Regular updatesand AI-driven improvements are crucial for maintaining robust phishing detection. These challengeshighlight the need for a more advanced, adaptive approach that integrates multilingual NLP, strong dataprivacy safeguards, and continuous learning mechanisms to effectively combat phishing
defense contractor to develop advanced ceramic materials, radar, and novel electronic fabrication methods applied to the development of guided munitions, electro-optic imaging systems, and medical devices. At GVSU he created and maintains electronic prototyping courses and co-created the School of Engineering’s professional ethics curriculum. Karl received his Ph.D. in Applied Electromagnetics from the University of Michigan. ©American Society for Engineering Education, 2025 Tuition Equity: Adverse effects of tuition policy on engineering studentsAbstractWhile there has been much research addressing the equity of college access, the equity of tuitionand fees have been less studied. Despite efforts