course schedule (Table 3.1) includes preparation for professional andethical conduct in a clinical setting, opportunities for sharing and dissemination of experiences,training in engineering design cycle, prototyping, and module development for future work.Table 3.1: Weekly schedule for SIDE course. Course plan includes preparatory training forprofessionalism and professional conduct in a clinical setting, as well as reporting from clinicalexperiences, and integration of clinical experiences into the product development lifecycle. Week Content Reporting/Submissions 1 Introduction, Responsible Conduct in Research, Ethics CITI Certification
Paper ID #47581Contextualizing Engineering Education by incorporating Indigenous KnowledgeSystems (IKS) in the Curriculum DesignDr. Brainerd Prince, Plaksha University Brainerd Prince is the Associate Professor of Practice and the Director of the Center for Thinking, Language and Communication at Plaksha University. He teaches courses such as Reimagining Technology and Society, Ethics of Technological Innovation, and Art of Thinking for undergraduate engineering students and Research Design for PhD scholars. He completed his PhD on Sri Aurobindo’s Integral Philosophy from OCMS, Oxford – Middlesex University, London. He
funding fromother crucial educational priorities, forcing institutions to make difficult trade-offs.Significant disparities exist in AI implementation across institutional contexts, with resourcelimitations and technical infrastructure constraints creating educational equity concerns, asdocumented by Yigitcanlar et al. [7] and Sleem and Elhenawy [13]. This threatens to create a two-tiered system where only students at well-resourced institutions benefit from cutting-edgeapproaches. Additionally, ethical considerations surrounding algorithmic bias and transparency ineducational AI tools require attention, as students may internalize flawed patterns embedded inthese systems.The successful integration of AI in sustainable construction education
[11]. Therefore, combining technicalskills with interpersonal abilities is necessary to meet modern professional demands.Engineers lead multidisciplinary teams, manage complex projects, and adapt to globalchallenges [1], [2]. Beyond project management, leadership in engineering demandsstrategic foresight, ethical decision-making, and the ability to integrate technical and socialdimensions in complex systems [12]. This underscores the need for leadership training inengineering education to equip graduates with both technical and managerial skills.Leadership is a skill that involves communication, teamwork, and problem-solving, whichdrive innovation and help achieve goals. Many institutions adopt transformationalleadership models, which have
method continues to be used, and thispersistence is in part because the results can be analyzed at different levels, as will be explained inmore detail later.The paper is structured into three basic sections. The experimental conditions are explained inSection 1. The surveyed results are then presented in Section 2 and analyzed in Section 3. Basedon this data analysis, conclusions are drawn, and possible future work is discussed.Ethics approval for this research project was duly obtained from the University of OttawaResearch Ethics Board (REB), under file number H-02-24-10020.Description of Experimental MethodDuring this study, in the GNG1103 - ”Introduction to Engineering Design” course at theUniversity of Ottawa, students were taught
[1] listed in italics: • Keep careful, complete and systematic records of laboratory work (experiment) • Understand the importance of, and appropriate methods for, the calculation of errors and uncertainties. (experiment, data analysis) • Carry out experiments, using key equipment to make appropriate calculations and solve realistic, open engineering problems. (experiment) • Analyse data collected, apply theory to one’s own experimental measurements, evaluate results and draw conclusions. (data analysis) • Write technical reports to justify experimental study, record procedures in the laboratory, communicate results and make concise robust conclusions. (communication,ethics)The activity
byintelligent prompting and integrations like Wolfram Alpha [5]. Undergraduate perspectives onLLM-based tools were explored, revealing diverse perceptions regarding their benefits andchallenges. These findings contribute to discussions on balancing AI assistance with ethicalconsiderations and human engagement [6]. Additional insights into the evolving role of generative AI tools, such as ChatGPT, ineducation, draw parallels between the adoption of generative AI and historical technologicaldisruptions, emphasizing the need for responsible integration to address ethical and pedagogicalchallenges [7]. Complementing this discussion, another study outlined trends in engineeringeducation research, providing context for the integration of digital
, and from psychology. The overarching goal of the course was to develop aninterdisciplinary understanding of the necessary balance between the needs of society andengineering design. It explicitly addresses four societal impact outcomes in ABET Criterion 3:public health and safety impacts of design, ethical decision-making, collaborative productivity,and effective communication with diverse audiences [1]. This course is supportive of theEngineering One Planet (EOP) program of the American Society for Engineering Education(ASEE) [2]. In addition, the importance of making design decisions in economic, environmental,and societal contexts is emphasized from the perspectives of engineering and physical andmental health.IntroductionA new technical
ethical implications and societal impacts ensures they areprepared to develop responsible and sustainable solutions. With the increasing reliance ontechnology and the internet, protecting sensitive information from cyber threats has become a toppriority for individuals, businesses, and governments alike, and incorporating AI/ML into theprogram empowers students to become future leaders who drive progress in an increasingly digitalworld, with a strong emphasis on the critical field of cybersecurity. Approaching this need to fuseAI/ML in our cybersecurity curriculum starts by identifying the key applications of AI/ML incybersecurity. Once these are identified, we can determine the freshman, sophomore, and juniorcourses that can prepare the students
Engineering graduates will: • Have established successful careers in robotics, automation, or related fields, demonstrating their ability to apply principles of robotics engineering to responsibly solve complex problems. • Engage in continuous learning and professional development to stay abreast of advancements in robotics and emerging technologies. • Demonstrate leadership, ethical conduct, and effective communication in multidisciplinary teams, contributing to the progress of the robotics profession and society. • Contribute to the advancement of robotics and automation through innovation, research, or entrepreneurial endeavors, showcasing the ability to push the boundaries of knowledge and technology in
. deliverable based on human inputs. Engage in metacognitive reflection; Identify pros and cons of various holistically appraise ethical courses of action; develop and check consequences of other courses of against evaluation rubrics. Evaluate action; identify significance or situate within a full historical disciplinary context. Critically think and reason within the Compare and contrast data, infer cognitive and affective domains; trends and themes in a narrowly Analyze justify analysis in depth and with defined context; compute; predict; clarity
StrategiesSeveral commonly used grouping strategies emerged from the analysis of methods used bystudents to group the topics from the course into categories. Figure 3 summarizes these commonstrategies and reports the proportion of students who utilized each. Figure 3: Proportion of students who utilized each commonly used grouping strategy.Students who used Strategy 1 divided the course topics into three major categories: academic,personal, and well-being. The academic category included skills that might lead to betterperformance in their college coursework. The personal category included skills that could helpthem improve certain aspects of their personal lives, such as their work ethic or socialrelationships. The well-being category included skills
DEIBinitiatives is influenced by individual factors, such as racial and ethnic identity, as well asinstitutional culture and available resources. To be ready for change, faculty must see that changeis necessary, that the needed change will occur, and that there will be positive outcomes from thechange [7], [30]. Faculty of Color often bear the additional burden of advocating for DEIBchange while simultaneously navigating the challenges of systemic racism and discrimination[9]. For instance, even though Black faculty had higher service loads than their peers, they tookon additional voluntary diversity service, like mentoring Black students and anti-deficit teachingstrategies [31]. McGee describes this mindset as an equity ethic. An equity ethic requires
craft professional resumes that highlight their academic achievementsand extracurricular experiences. Personal statement writing prepares them for interviews. Theprogram also offers sessions on study abroad opportunities, helping students navigate theapplication process and understand the benefits of global experiences. Workshops on academicstanding and academic integrity teach students how to monitor and maintain their academicperformance, as well as how to uphold ethical standards in their coursework. Degree auditworkshops help students with course selections for the upcoming semester, ensuring timelygraduation and helping with reserving courses for masters’ programs. These workshops areintegral to preparing students not only for their
, the teaching communityhas raised substantial concerns regarding academic integrity, student learning, ethical application, 1and the dynamics of human-AI interaction [4, 5, 6, 7, 8]. While empirical studies on LLM usage ineducation have been conducted in this early stage of adoption, given the current novelty of LLMsin education and the myriad ways they might be incorporated into an educational setting, additionalresearch is crucial for better understanding the short-term and long-term effects of LLM-based AIon teaching and learning in computer science.Due to the relative lack of evidence from early research in this area, we believe the immediate ef-fects of using generative AI in classroom
, Tools, & Practice I (ENGR110), and Engineering Methods, Tools, & Practice II (ENGR 111). ENGR 110 is an introductionto the profession and some fundamentals of engineering. ENGR 110 introduces engineeringgraphics, ethics, professionalism, Python programming, teamwork, etc. ENGR 111 is taught in a15,000 𝑓𝑡 2 makerspace, this makerspace is controlled and directed by the SSOE. ENGR 111incorporates application and integration of fundamental engineering skills learned in ENGR 110.ENGR 111 consists of instruction for skills such as teamwork, circuitry, Arduino microcontrollers,three-dimensional graphics, 3D-printing, and technical writing.ENGR 111 includes a semester long team-based Cornerstone project that all student teamscomplete
and Historical Foundations” (CHF), (3) “Data and QuantitativeReasoning” (DQR), (4) “Engineering, Technology, and Society” (ETS), (5) “Literatures” (LIT),(6) “Natural and Physical Sciences” (NPS), (7) “Social Analysis, Politics, and Ethics” (SPE), and(8) “World Languages” (WOL). Although engineering faculty could contribute to anyperspective, their courses typically fall within the ETS perspective. As Union College increases 3the offerings within this new general education curriculum, all students will need to take coursesfrom all eight “Perspectives.” This inclusion of engineering within Union’s general educationcurriculum is a step toward both creating a
words diversity, equity, inclusion, andaccess from all accreditation criteria, the organization has stated that it remains committed tothese principles. Furthermore, regional accreditation bodies such as the Higher LearningCommission (HLC) require universities to demonstrate that their “processes and activitiesdemonstrate inclusive and equitable treatment of diverse populations” [19]. Previous studies alsoprovide examples of success in meeting new criteria and curriculum expectations [20] and [21].As one of the oldest and largest communities of infrastructure professionals, ASCE promotesDEI in both infrastructure and education policies. The ASCE Code of Ethics explicitly states thatengineers must “acknowledge the diverse historical, social, and
, including femaleengineers, can help students envision themselves in the field and increase a sense of belonging.In this study, we have also used AI-generated audio content to create realistic soundscapes andspoken narratives to transform passive learning into interactive experiences consistent with theresearch from Urmeneta and Romero [3]. Moreover, by converting text-based lessons andtechnical documentation into audio formats, AI can support students with disabilities, such asvisual impairments or dyslexia. We recognize that there are ethical considerations in the use ofAI-generated content–such as ensuring that it does not perpetuate biases or misinformation orinclude nonconsensual usage of faces and voices–that need to be carefully
community outcomes were less optimal. The resultsdraw attention to important issues in the hopes of inspiring interest, attention to best practices,and cautions.IntroductionAs the interest and application of community engaged research (CER) is increasing inengineering, it is becoming clear that there is a lack of consensus on best practices and a generalunderappreciation of ethical challenges. This research aims to help address these shortcomings,by amplifying the voices of academic women of color who have engaged in CER in STEMfields. This paper begins by providing background information on CER, then moves to theresearch methods, and concludes with the findings.At its most basic, CER brings together two ideas: research and community
educational practices and professional outcomes. The integration of empathyinto engineering education and practice enhances the ability of engineers to design solutions thatare not only technically sound but also socially responsible and user-centered. Empathy helpsengineers understand and address the diverse needs of users, leading to more inclusive andeffective design solutions. This perspective is supported by various studies that highlight the roleof empathy in engineering education and practice [2], [5], [6], [7], [8], [9]. Empathy is considered a necessary interpersonal skill for modern engineers, supportingcreativity, ethical decision-making, and collaboration. However, perceptions of its importance inpedagogy vary among instructors
onstudents’ success. The ACCESS project incorporates several co-curricular professionaldevelopment and student engagement elements, including social events, seminars, mentoring,undergraduate research, and participation in cybersecurity-related student organizations.Participating in social and professional development events fosters social connections anddevelopment of life skills such as discipline, self-esteem, and ethical behavior [5]. Facultymentoring and professional development seminars encourage persistence in students’ academicpaths and prepare them for their future careers by providing career guidance, relevantinformation, and networking opportunities [6]. Participations in subject-based studentorganizations and competitions increase student
laboratory conditions, the research aims to provide practical insights for educatorsconsidering these tools. The findings will contribute to broader discussions about technology-enhanced learning and the evolving relationship between artificial intelligence and humaninstruction in technical disciplines.Literature ResearchRecent advances in LLMs have shown their potential to transform educational settings, particularlyin programming courses where timely, detailed feedback is important. Fagbohun et al. [1] statesthat LLMs can automate grading with personalized feedback but that they still require carefulhandling of biases combined with human supervision to ensure that LLMs are fair and efficientand to reduce the occurrence of ethical risks like
engineering (i.e. developing prompts to maximizeoutput accuracy), evaluation of AI responses, and ethical considerations [9-11].Due to its versatile nature, AI has the capacity to be used in nearly every academic discipline,similar to the use of the internet. However, AI may be most effective in fields where students arerequired to complete more ill-defined tasks such as writing lab reports or creative writing [1],[8]. Similarly, AI has been used in marketing and other business fields for content creation, salesoptimization, and for customer service chatbots [12-13]. In science education, the use of AI hasbeen shown to can boost students’ motivation and participation in learning exercises, but it haslimitations regarding complex subjects, and can
the multidisciplinary and rapidly developingfield of nanotechnology. Topics include nanomaterials, micro/nanofabrication, microscopy,nanoelectronics, biological nanotechnology, nanoterrorism, social and ethical implications, etc.”A detailed list of topics covered during the course includes introduction to semiconductors,micro/nanofabrication (including alternative methods of nanofabrication such as microcontactprinting, nanoimprint lithography, self-assembly), scanning probe microscopies (scanningelectron microscopy (SEM) and atomic force microscopy (AFM)), nanomaterials (fullerenes,carbon nanotubes, graphene, quantum dots, nanoparticles), optical tweezers, magnetic storage,magnetoresistive materials, optoelectronic nanostructures
. Participants86 completed voluntary pre- and post-course surveys, which explored their motivations,87 prior experiences, perceived learning gains, and attitudes toward STEM. Institutional 2 88 review board approval ensured ethical compliance, and students retained the option to 89 withdraw at any time. By analyzing pre- and post-survey results, the study captured 90 shifts in engagement, confidence, and interest in STEM careers, providing insights 91 into the effectiveness of CURE within HBCUs. 92 Statistical analyses were performed using SPSS 27.0. Descriptive statistics 93 summarized key aspects such as students’ demographics, motivations for course 94 enrollment, perceived learning
engineering students but did not surpass experienced professionals. Yanget al [4] identified the advantages of implementing AI chatbots in education as enhancing studentengagement through interactive simulations, reducing workload for administrative staff byautomating routine tasks, and personalizing education for diverse user needs.Despite AI-powered chatbots' potential, the development process remains challenging. The lackof accessible tools and streamlined frameworks has created a gap in the effective adoption of thistechnology [5]. Shahriar et al [6], explored the evolution, capabilities, and limitations ofChatGPT, the state-of-the-art AI chatbot by OpenAI. The authors call for enhanced modeltraining, ethical guidelines, and improved transparency
. Each track aligns with scholars’ career goals, emphasizing practical skills and industry certifications to improve employability [14].• Tech Up Space STEMinar Series hosts virtual and recorded lectures featuring industry leaders and workforce readiness experts. Topics include portfolio building, networking, technical interviews, graduate school preparation, AI ethics and responsibility, and leadership. The blended format of lectures and podcasts allows students to access the content at their convenience, integrating learning into their academic schedules [15, 16].Methodology & Key OutcomesTo assess REP’s impact, a comprehensive evaluation was conducted, including semester surveys,focus groups across the three EmTech
117 Figure 1 illustrates the persistence of students enrolled at the end of the semesters and courses listedin Table 1. The mean and median of the data are 4.6 and 4.8, respectively, which reflects the very positiveskew present in Figure 1.Figure 1: Overall persistence for the participants who completed the survey. The responses to the open-ended survey question regarding the students’ perceptions ofengineering practice were coded systematically to uncover common themes. Students perceive thefollowing ten themes as being part of engineering practice: 1) considers ethics, 2) considers safety, 3)considers efficiency, 4) considers complexity, 5) utilizes knowledge, 6) collaborates with others, 7)improve or make designs, 8) solves