, we share the design aims and lessons learned from delivering the workshop tofurther the discussions on generative AI among faculty through an interdisciplinary, collaborativelens – in doing so, we identify two primary themes among our participants' perspectives ongenerative AI that are relevant to our future work: 1) a need for generative AI curriculumintegration and skill development and 2) a need for more exploration of its ethical and socialimplications.Structure of the WorkshopOur workshop explored four interconnected themes, thoughtfully chosen to promote a holisticand interdisciplinary understanding of generative AI and its societal impact. Drawing from ourexpertise in communication, philosophy, computer science, and engineering
. Such a report helps the Leonhard Center to assess project impacts and processes. Table 1 in thebelow “Project evaluation” section provides descriptive results from the evaluation. Some recent projecthighlights include: using emerging technologies like Virtual Reality (VR)/Augmented Reality (AR) andArtificial Intelligence (AI) to promote classroom engagement; creating micro-credentials for robotics,engineering literacy, engineering writing, inclusive teaming, extra-curricular clubs recognition, and ethics;multiple department-level Diversity, Equity, and Inclusion (DEI) programs; creating an Academic Job MarketSeminar for graduate students; and many more.Themes through the yearsAppendix A shows a timeline of the history of the Leonhard Center
of GenAI presentsunique opportunities and challenges. In medicine, faculty must address the use of GenAI toenhance diagnostic accuracy, streamline administrative tasks, and analyze patient data, whilealso teaching students to navigate ethical concerns such as patient privacy, diagnostic errors, andthe balance between human clinical judgment and AI-assisted decision-making. Similarly, inteacher preparation programs, faculty are tasked with guiding future educators to critically assessGenAI tools for fairness, inclusivity, and their impacts on learning outcomes, ensuring thesetechnologies are applied ethically and effectively in diverse classrooms. In engineering education, faculty may leverage GenAI to enhance problem-solving skills
are fourkey areas which will be most impacted: TK, TPK, TCK and TPACK as a whole. TechnologicalPedagogical Knowledge (TPK) focuses on how AI can enhance instructional methods, such asusing AI-driven analytics to track student progress or implementing chatbots for personalizedtutoring. Technological Content Knowledge (TCK) addresses how AI can facilitatesubject-specific instruction, such as using AI-driven simulations in engineering or automatedtranslation tools in language learning. Recent studies emphasize the importance of facultydevelopment in AI literacy, particularly in establishing clear institutional guidelines on ethical AIuse and assessment (Gambhir et al., 2024).While TPACK provides a structured approach to technology integration
and equity causes” [6, p.708]. As such, Black facultymentors see current and prospective student mentees as an extension of themselves [6]. In response,Black faculty mentors apply social empathic and equity ethic practices in their mentoringapproaches, which builds trust and rapport with students [6]. As a result, Black faculty mentors areflooded with a disproportionate number of requests from students as well as institutions toparticipate in formal and informal diversity-related service as compared with their Whitecounterparts [6]. However, there is still an overall lack of knowledge of the types of asset-basedstrategies used by Black faculty mentors [8]-[10] in lieu of their cultural taxation [6] and howprofessional development can be used
Kanika Sood, California State University, Fullerton Daisy Tang, California State Polytechnic University, PomonaThis work-in-progress study describes our grant-funded efforts in developing a computer sciencefaculty learning community (FLC) across six California state institutions. With an emphasis onsocially responsible computing (SRC), the faculty development effort that prepares faculty forSRC lesson implementation has integrated social scientists with computer science faculty in therotating leadership team. It works collaboratively to facilitate dialog around experiences ofimplementing lessons that focus on social justice and ethical decision-making. Our data-drivenFLC and course transformation effort was initiated by
and professional developmentsupport. As a woman of color with a STEM background and a doctorate in higher education, theprogram director set out to address expected resistance to the program’s success at the institutionduring scholars’ recruitment. When she became a Fellow in a national leadership developmentprogram, she interviewed senior leaders across the university. This included leaders who oversawacademic, fiscal, and other business decisions at college and university levels. From theseinterviews, she discovered more about the inner workings of human resources, institutionalequity, general counsel, ethics and compliance, and diversity, equity, and inclusion units. When she poked into the daily actions of the organization
Centres. His other specialties are engineering education and the relationship of technology with sustainability, ethics and human rights. Since 1991 he has been working as a lecturer in the Department of Computer Architecture at the UPC (Barcelona, Spain), where he has been a associate professor since 2001. He has been a consultant for the Universitat Oberta de Catalunya. His thesis dissertation was about architecture design, optimization and numerical code compilation. Since 2004 he has made engineering education and its relationship with ethics and sustainability his main research topic, with more than one hundred and fifty scientific and press papers published in these years. He has participated in a dozen research
the responses to the 3 open-ended questions (we used an iterativeprocess to code the themes). We also analyzed the 34 applications in terms of the nature of theproject and how the budget was used.This study was conducted as part of a quality assurance and improvement evaluation of theELATE initiative and TLIF program and as per Article 2.5 of the Tri-Council Policy Statement :Ethical Conduct for Research Involving Humans [21], Research Ethics Board review was notrequired.Findings and discussionDetails on the TLIF projectsSince the inception of the TLIF program, 34 projects, including those in progress at the time ofwriting, have been funded. These 34 projects involved 32 different faculty members(approximately 20% of the Faculty’s academic
mentorship insupporting EBIP adoption. Theoretical saturation was achieved when no new themes or insightsemerged from the data.Rigor and trustworthiness were supported through reflexive memo-writing, peer debriefing, andthe use of constant comparative analysis to enhance credibility [25]. Team members who werefamiliar with the project but not involved in the interviews or analysis reviewed the findings toprovide an addition check on accuracy and validity [27]. Ethical considerations includedobtaining informed consent, protecting participant confidentiality, and ensuring secure datastorage [28]. These measures upheld ethical integrity and strengthened the dependability of thestudy.By employing constructivist GT, this study provided a nuanced
grading [3]. Major issues associated with grading includesubjectivity and bias, grade inflation, a focus on grades over learning, and the allocation offaculty time [4]. Grading may also have political and social dimensions, and can involve powerdynamics, issues of agency, and other complex ethical issues [5]. The paper by Schinke andTanner [6] provides a good summary of the history of grading, a discussion of the primarypurposes of grading, and examines some of the pitfalls and challenges. For decades, educatorshave been exploring ways to make grading more effective and efficient (e.g. [7]). However, inengineering in particular, papers specifically describing studies of grading practices are few [8].While grading practices of engineering faculty
incorporate some combination of these key contributors. The Penn UndergraduateResearch Mentoring Program (PURM) [7] is a great example that focuses on fostering strongmentor-mentee connections. PURM offers summer research opportunities for first- and second-year students under the guidance of a Penn research faculty. The program equips students with thenecessary skills through workshops on data management, Python programming, data analysis, andvisualization. Participants also receive training in networking, public speaking, presentation skills,and research ethics. As an additional resource, there are research peer advisors (RPAs) fromvarious research fields like engineering and sciences, business, language studies, arts, etc. RPAsprovide support in
-minded efforts that focused on discussions centered aroundunderrepresented and minority groups. For example, teaching modules to discuss ethics andimplicit bias, doing literature reviews from authors of diverse backgrounds, and facilitatinggroup reflection on stories of people from disadvantaged groups and how they encountered andovercame different engineering challenges. “I have ethics modules in each of my courses so I try to review those modules and make sure I have up to date information about how engineering design impacts as many identity groups”While the team could identify specific efforts of equity-minded teaching in their classroom,many struggled to recall concrete examples of success stories that directly resulted
culturallyresponsive teaching methods. Participation in the Community of Practice training played a pivotalrole in equipping instructors with strategies to promote inclusivity and engagement, as evidencedby the reduction in negative practices and the enhancement of equitable teaching approaches.By demonstrating the significance of infusing CR into course content to foster respectful, inclusiveclassroom environments, this study contributes to the broader discourse on equity in STEMeducation. The current study adhered to ethical guidelines to ensure the integrity of the studyfindings. Future research could focus on expanding this framework across broader contexts andintegrating adaptive technologies for real-time feedback to enhance its