-methods study combining a longitudinal analysis of BSI student gradepoint average (GPA) and enrollment with results from a student experience survey. This workwas approved by the University of Calgary Research Ethics Board under REB23-1762.Longitudinal AnalysisA longitudinal analysis was conducted to evaluate the academic performance and retentionoutcomes of the first five cohorts of BSI students from 2019–2023. We examined mean GPAs infirst-year physics and physics-intensive engineering courses (circuits, statics, programming, andfluids). Yearly GPAs and retention were also tracked for each BSI cohort to assess studentperformance as they progressed through their degree. Outcomes were compared with meanGPAs and retention for general engineering
] and improves professional and personal skills,including teamwork, communication, leadership and ethical awareness [7]. Service learning alsohelps students develop a sense of social responsibility [8] and reiterates the role of engineering asa service profession, especially for underrepresented students [6], [9]. As the edited volume byTseng [10] summarizes, there are a number of examples of service-learning design projects inengineering courses. The service-learning project in this study, however, emphasizes analysisrather than design as a way to increase student interest in the topic of computer programming andstay motivated to learn an important but threshold concept with the goal of increasing retentionin the discipline.An additional
education. It would be ethical and based more on a moralresponsibility for our educational system and government to believe in and care about growingthe intellectual capital of all its citizens [2]. However, research on this topic from the CommunityCollege Research Center and engineering education researchers located the source of interest fordoing this important work as the need to meet the needs of industry. More specifically, statesneed higher education to play a large role in workforce development to meet industry demand forengineers and computer scientists [3], [4]. This reliance on higher education to train the futureworkforce was named social efficiency [5]. Beyond social efficiency, Labaree explained socialmobility was a common goal for
mechanism that strengthens problem-solving capabilities.The findings depict the complex interactions between problem design, student self-reflection, andsubsequent student performance. While non-abstracted problems are crucial in preparing students forprofessional practice, instructors need to consider interventions that will strengthen students' confidencein facing these challenges. Future research will focus on refining the abstraction rating tool (based on the“PRO” portion of the PROCESS rubric) for better inter-rater reliability and analyzing individuallyanswered test or quiz items to remove the effect of group work. References [1] Aristotle, W. Ross, J. Ackrill, and J. Urmson. The Nicomachean Ethics. Page 3. Oxford University Press, 1998. [2
“Artificial Intelligence” or “AI” in the title. The set can beexpanded to over 100 by adding terms such as “Machine Learning”, “Large Language Models”,or “Generative”. Results are spread across most ASEE divisions, reflecting the intense interestengineering educators have in using modern AI-based tools in the classroom. Proposed uses ofAI are too many to enumerate here, but broad topics include techniques for teaching studentshow to use AI, recommendations to instructors on using AI tools to assist with curriculumdevelopment and assessment, the ethics of AI use in the classroom, and advances in AI forsolving engineering problems.Given the focus on these emerging tools by educators and students alike, it is imprudent toignore their use in any field of
technologies both ethically and strategically. As technologicalinnovation continues to accelerate, cultivating the skills needed to explore and evaluatetechnology will remain essential for future leaders.References [1] J. E. Thistlethwaite et al. “The effectiveness of case-based learning in health professional education. A BEME systematic review: BEME Guide No. 23”. In: Medical Teacher 34.6 (2012), e421–e444. DOI: 10.3109/0142159X.2012.680939. [2] K. M. Bonney. “Case Study Teaching Method Improves Student Performance and Perceptions of Learning Gains”. In: Journal of Microbiology & Biology Education 16.1 (2015), pp. 21–28. DOI: 10.1128/jmbe.v16i1.846. [3] M. Krain. “Putting the Learning in Case Learning? The Effects of Case-Based
Department of Engineering Fundamentals at Michigan Technological University, where she teaches first-year engineering courses. Her research interests include engineering ethics, spatial visualization, and educatio ©American Society for Engineering Education, 2025 Complete Evidence-Based Practice: Iterative Driven Competency-Based Assessment in a First-Year Engineering Computation ModuleIntroductionIn our connected world, engineers must possess a strong foundation in applied computation.Daily engineering decisions rely on data analysis, which necessitates the use of computationaltools. This work investigates the transition from manual grading to a competency-basedautomated grading system for introductory
evaluatewhether students’ collaboration with generative AI tools reflects their proficiency in the technicaldomain and provide further insights into how to best prepare students for the rapidly evolvingworkplace.Lastly, it is important to acknowledge the concerns and risks associated with using generative AI,which were a limitation in this study. Some issues were taken into consideration; for example,students were expected to critically examine the responses and refine them based on keyprinciples and concepts of the technical field to eliminate any inaccuracies or oversights.However, other aspects, such as ethical use, bias, and data privacy, were beyond the scope of thispaper. These elements should also be addressed as part of student training on
project was successfully conducted remotelyinvolving parties in different countries.Semi-Structured InterviewTo further investigate group dynamics and challenges in IBL project teams, a semi-structuredinterview was conducted with existing IBL students about their projects. This survey wasreviewed and approved by the university’s Institutional Review Board (IRB protocol number0006441). This study adheres to the ethical standards required for research involving humansubjects. This online interview lasted approximately 30 minutes, involved volunteer participantsfrom the IBL program. It consisted of ten (10) open-ended questions focused on the team projectexperience, based on a validated Self-Efficacy Survey [11]. The questions are listed in Figure 4
also important for students to springboard from theclassrooms and do engineering by engaging in real-world problems in the local community andworking with community members.Among the body of work around students engineering for real community needs, engineeringeducation researchers study community engagement and provide examples of programs whereengineering students did engineering work for communities [5], [6], [7]. These studies identifiedcompetencies that are important for engineering students to engage ethically with communities,such as being willing to listen to the communities, and transforming their assumptions andattitudes towards the communities. Moving forward, more research needs to be done on how tofacilitate students to develop
responsibility assessment (GPRA). Online Ethics Center for Engineering. Retrieved from https://www …, 2019.[14] “Mission Statement.” Accessed: Apr. 29, 2025. [Online]. Available: https://www.slu.edu/about/catholic-jesuit-identity/mission.php[15] N. C. Zaferatos, “Environmental Justice in Indian Country: Dumpsite Remediation on the Swinomish Indian Reservation,” Environmental Management, vol. 38, no. 6, pp. 896–909, Dec. 2006, doi: 10.1007/s00267-004-0103-0.[16] J. T. Boer, M. Pastor, J. L. Sadd, and L. D. Snyder, “Is There Environmental Racism? The Demographics of Hazardous Waste in Los Angeles County,” Social Science Quarterly, vol. 78, no. 4, pp. 793–810, 1997.[17] H. M. Lane, R. Morello-Frosch, J. D. Marshall, and J. S. Apte
and experiences in writing; 3) We aim for you to become familiar with the types of infrastructure, design considerations, ethical considerations, and social, environmental, and cost constraints commonly encountered in CEE and learn how CEE engineers create value for society through their work; 4) We aim for you to develop the ability to think critically about CEE-style problems, drawing on experience you will gain by actively thinking through and observing challenges; 5) We sim got this class to build your curiosity for the profession, such that you will know where to go for more information and will have a better sense of the kinds of classes you might be interested in, the kinds of jobs you will be able
). Scott admires the ways Lewes insists “the mind bestudied not only as an individual but as a unit in the social organism” (p. 11) and the fact thatLewes looks at “literature successively from three points of view, the intellectual, the ethical, andthe aesthetic” (p. 13). In “literature in the true sense,” all three must be addressed simultaneouslyand in relation to each other (p. 13). Scott sees in Lewes’ work an approach to literary criticism. ..based on “the eternal principles of the human mind” (p. 15). Once these principles have been 7articulated, they provide a rational basis for both instruction and assessing the effectiveness
enhanced educational experience.Beyond technical objectives, this project aimed to provide a rich educational experience. Forengineering students, it offered opportunities to apply theory to an integrated system combiningCAD modeling, prototyping, and environmental control. Biology students engaged in appliedplant science, pest control, and light optimization. The hands-on nature of the work fostered softskills such as collaboration, adaptability, and creative problem-solving. This project aligns withconstructivist and experiential learning theories, as students learned through doing, reflection,and peer feedback.Applicable StandardsThe project adheres to the NSPE Code of Ethics, emphasizing safety, health, and welfare of thepublic. To address
(2019).12. Millman, K. J. & Aivazis, M. Python for scientists and engineers. Computing in Science and Engineering vol. 13 Preprint at https://doi.org/10.1109/MCSE.2011.36 (2011).13. Goktas, P., Karakaya, G., Kalyoncu, A. F. & Damadoglu, E. Artificial Intelligence Chatbots in Allergy and Immunology Practice: Where Have We Been and Where Are We Going? Journal of Allergy and Clinical Immunology: In Practice 11, (2023).14. Ray, P. P. ChatGPT: A comprehensive review on background, applications, key challenges, bias, ethics, limitations and future scope. Internet of Things and Cyber- Physical Systems vol. 3 Preprint at https://doi.org/10.1016/j.iotcps.2023.04.003 (2023).
topics such asgeography and natural resources, African history, culture, science, inventions and innovations. Thecybersecurity and AI/ML test covered a range of topics, including Integrity, Cyber Ethics, Cryptography,Online Safety, and Artificial Intelligence. These content areas were assessed through the use of multiplechoice question prompts on both tests. Data were analyzed using SPSS to compute descriptive statisticssuch as percentages. To assess changes on the summative knowledge tests, paired (repeated-measures)t-tests were computed to see if there were statistically significant differences between average participantscores before (pre) and after (post) the UACI STEM camp program. For the participants whose pre- and post-summative
discussions the students could test each other’sunderstanding of the course content, through the group debate the students could developawareness regarding their social and ethical responsibilities as engineers. Through the debates, thestudents learned to consider the pros and cons of controversial topics like gene editing, human-animal chimera, brain organoids, and so on, and got the opportunity to learn how to be respectfulto those with different perspectives. Before beginning the group activities, the students submitteda teamwork contract. The students read online articles and watched a YouTube video on effectiveteamwork before filling out the contract, where they discussed their individual roles in the team,preferred methods of communication
, students take a practicum exam where Python serves as a vital componentof the assessment. While generative AI tools are not required or explicitly taught for the Pythonprogramming assignments, students are encouraged to use them for validation, debugging, andimproving code efficiency. Students also engage in a dedicated ethics assignment to explore theethical considerations surrounding the use of generative AI in power systems analysis anddesign.To measure the perceived effectiveness of these hands-on Python exercises, the course includes anindirect assessment in the form of midterm and end-of-term surveys, gathering feedback on thestudents’ learning experiences.A vital feature of this approach is the coupling of Python with PowerWorld, a widely
these skills, they have yet tofully adopt or integrate them into their professional practice. In addition, the lack of specific,actionable plans for skill acquisition reflects a gap between awareness and action. While studentsacknowledged the need for continuous improvement in ICC, they did not consistently providedetailed strategies for how they would develop these competencies further. This is particularlyimportant in engineering, where the ability to engage effectively with diverse perspectives isessential for designing solutions that are culturally relevant and ethically sound.Providing students with more guidance on creating actionable development plans could helpbridge this gap and ensure that they are well-prepared to apply ICC skills in
Institutional Review Board (IRB) and deemed exemptunder educational research guidelines. Ethical considerations, including informed consent andvoluntary participation, were followed to protect student confidentiality and ensure compliancewith institutional policies.ImplementationCHE CALCULATOR®’s application is best illustrated through specific examples of its use inchemical engineering courses. In the Thermodynamics course, students used the tool to calculatevapor-liquid equilibrium (VLE) properties for multicomponent systems. It is an innovative, Excel-based computational tool designed to streamline the process of determining thermodynamicproperties. It eliminates the need for students to conduct extensive searches across multiplewebsites or
discuss real-world examplesof the different power generation technologies. For the renewable half of the class, there weretwo guest speakers. The first guest speaker came in to talk to the class about the levelized cost ofelectricity and the social, political, and ethical impacts that come from variations in the cost ofelectricity and power consumption. The presentation focused on hospitals and health care andhow they are affected by these variations, especially with and without backup power systems.The second guest speaker was an engineer for a battery recycling company. Their presentationfocused on the ways that batteries are recycled and what can be done with the recoveredmaterials. Part of the presentation included information about utilizing
collaboration for successful project delivery [10]. They also have to balancemeeting technical requirements with considerations of ethical and social responsibilities. Inaddition, new technologies such as smart materials, artificial intelligence (AI), and data analyticspresent new opportunities for civil engineers to add greater value to the built environment. Thesetools, technologies, and techniques allow the management of projects to be more efficient, whilethe stakeholders can also collaborate and make decisions more effectively [10]. Civil engineersneed to work out optimal designs that minimize waste and ensure better performance ofinfrastructure [11]. As the industry continues to evolve, it becomes requisite that civil engineersadopt these
economical, environmental, and on developing interfaces; prototyping and ethical aspects of a proposed design. Main topics include: design for manufacturing. An idea of patents detailed design of a mechanical systems, modeling and and intellectual property, and economics of simulation in design, materials selection and materials in design, product design will be discussed. reliability/safety, economic decision making, and communicating the design and applications. Figure-1 Course descriptions of two of the design-stream coursesA typical set of activities involved in the engineering design process is shown in Fig-2. Design is
adoptstandards conservatively, mandating multiple levels of basic science, engineering sciences,technical mechanical courses, lab experiences, plus humanities, social sciences, and professionaland ethical responsibility requirements. The outcome is often a double-layered curriculum thatcan be difficult to streamline.By contrast, CS tends to be more flexible, as the CC/Course value indicates. Accreditationframeworks for computing, while existent, are generally less prescriptive and less universallyadopted as it is often considered optional [24]. These differences may explain why many of thetop-tier CS programs in the United States are not accredited [24]. Accreditation can addstructural complexity; for instance, one study found that students in
isimplemented to teach the human skeletal anatomy. Thus, visualization and interaction of abstractscientific concepts are carried out. In this paper, an interactive learning tool that complements thelessons of the school syllabus is presented. It is an outcome of a research collaboration betweenthe University of Sheffield, England and Tecnologico de Monterrey, Mexico, and it has beenimplemented in different environments in England, which contributes to being evaluated fromdifferent perspectives [10]. The research work uses AR technology to further users’ learningexperience. Additionally, responsible and ethical applications of Artificial Intelligence (AI) areperformed.Literature ReviewQuality EducationBased on the Sustainable Development Goals (SDG) of
sectionfocuses on the quantitative analysis of the data. Section 4 contains the qualitative results heavily 2relying on the video recorded interviews. The last part of our work focuses on the conclusions andpossible future work that can be undertaken by other educators and researchers.2. Research MethodologyThis study was conducted at a public university in the Northeastern United States by a PrincipalInvestigator (P.I.) and a team of five research assistants. The research was approved by theInstitutional Review Board (IRB) to ensure that human rights and ethics are applied properly. Asurvey and follow-up interviews were conducted with the participants
thesupport provided by an expert to learners, continuing their engagement in learning activitiesbeyond their current abilities; for example, to help students solve a problem and justify anunfamiliar method [19], [20]. Here, scaffolding support will be provided by an AI agent. However,our goal is to explore how researchers have delineated students' problem space in a way that stillallows creativity and agency. We want AI agents to respect the complexities of the problem whilesupporting it, motivating students to be interactive.Previous systematic reviews of design thinking and AI have focused on other issues. For instance,[22] considered justice, bias and ethics embodying AI in the design process, with a focus onbusiness design. Chen et al. [28
guidance of a singleinterviewer ensured consistency in the questioning approach and data collection. To facilitateinterview, participants received the interview guide in advance via email.The study maintained ethical protocols throughout the data collection process. All participantsreceived the information about the study's objectives and data management procedures. Writtenconsent was obtained from each participant prior to their involvement, ensuring informed andvoluntary participation in the research.Data AnalysisThe interview data were analysed using NVivo 14, a qualitative data analysis software, tomanage and code the data. Following grounded theory methodology [15], the process began withopen coding, which involved identifying patterns and
: Diversity Trends at Programs [18]The College actively partners with regional high schools and community colleges to expandawareness of engineering careers. Outreach activities, including hands-on demonstrations andmentoring, have proven effective in encouraging broader participation in STEM [18]–[21].Additionally, the curriculum design draws on prior experience with vertically integrated coursesequences, which reinforce skill development from foundational to advanced levels [22].Courses that address global and ethical engineering dimensions help students understand theirwork's societal impacts and the diverse communities they may serve [10]. Beyond the classroom,student-led organizations enrich the academic experience by offering peer mentoring
, minimum and maximum scores, and time spenton quizzes.This study does not include direct measures of learning outcomes, such as final grades orassessments beyond the embedded video quizzes. It focuses on student interaction patterns, and giventhe course-specific context and small sample size, the findings should be interpreted as exploratory.Our university's Institutional Review Board (IRB) approved the research protocol for this study,ensuring that all data collection, analysis, and reporting processes met ethical and legal standards,with a strong emphasis on protecting student privacy. Identifiable data were anonymized by replacingpersonal identifiers with unique numerical identifiers.Course Context and Design RationaleBackgroundThis paper