scan(s) or photo(s) of your HW. do not take up all of the provided space in You should keep all of your original HW pages in order to your Pre-Read as you may want to add complete the HW Correction assignment at the end of the Unit. content to the space in class. Grading: • 1 point overall for quality organization and legibility of Deliverable: Upload a legible scan or photo your homework upload. This includes boxing your final of your notes page(s) for the lecture listed answers on the page and clearly numbering your problems. above. • Even Problems: 1 point for showing quality work Grading: Complete/Incomplete • Odd Problems: 1 point for showing quality work + 1
criteria.Table 1. Boolean search clause terms categorized into PICO and SPIDER frameworks. P/S O/PI (Population/ Sample) (Outcome/ Phenomenon of Interest)Search engineering student* fail* AND perception* AND learn*Clause engineering undergraduate* perspective* engag*Terms engineering major* attitude* motivat* shame reaction* mindset* response* persistence
across their entire 8-semester undergraduate engineeringprogram to support a change and time-oriented understanding of the phenomenon. Data wasanalyzed using iterative rounds of content coding, open coding, and thematic analysis toward thedistillation into the essence of what the phenomenon looks and feels like [28], [30], [31]. Allauthors contributed to the running of the cohort program, with the first, second, and fourthauthors playing a significant role in this study’s data collection and analysis.3.1 Location and ParticipantsThis study was conducted at a large, western land-grant, R1 university and focused on the lived-experiences of 14 undergraduate engineering students participating in a four-year S-STEMcohort [32], [33], [34], [35
that theory-driven professionaldevelopment efforts can lead to a meaningful increase in students’ AI competencies. These findingshighlight the necessity for ongoing professional development initiatives that not only equipstudents with technical AI competencies but also foster ethical awareness and responsible use ofAI technologies. As the landscape of AI continues to evolve, such educational efforts are essentialin preparing students to meet the challenges and opportunities presented by artificial intelligence.This work lays the groundwork for scaling such professional development efforts and provides areplicable model that can inform national and global efforts to increase AI literacy in highereducation.References[1] S. J. Russell and P
Bureau’s American Community Survey highlight similardiscrepancies between science and engineering (S&E) graduates and STEM workers. Among 50million employed college graduates aged 25–64, 37% reported a bachelor’s degree in S&E whileonly 14% reported holding a STEM job. Further, 52% of workers who majored in engineeringwork in STEM [9]. These statistics do not show directionality, whether it is the person leavingengineering or engineering not receiving the person, but the large number of engineeringgraduates not working in STEM leaves room for further study.Other factors than the salary expectations quoted above may be influencing engineering studentsto take jobs outside of engineering. In a sample of 450 engineering graduates, Bielefeldt
Paper ID #47297Exploring changes in mental health conditions’ stigma levels and help-seekingattitudes among engineering studentsMr. Syed Ali Kamal, University at Buffalo, The State University of New York Syed Ali Kamal is a doctoral student at the Department of Engineering Education at University at Buffalo. He is working as a graduate research assistant at the DARE to CARE lab. His research interests lie in the area of social justice and issues related to diversity, equity and Inclusion.Matilde Luz Sanchez-Pena, University at Buffalo, The State University of New York Dr. Matilde S´anchez-Pe˜na is an assistant professor of
both teams,adapting validated instruments such as the Global Diversity and Inclusion Benchmarks (GDIB),the Team Innovation Implementation (TII) [50], [51], [52], and the Social Capital instruments[53]. These tools were targeted at assessing various aspects of team diversity, communication,trust, collaboration, and innovation. The responses were collected using a 5-point likert scale,ranging from 1 to 5 (i.e. Strongly Disagree to Strongly Agree) [54]. See table 1Table 1. Sample questions from the questionnaire. S/No Question Strongly Agree Neutral Strongly Disagree Agree (A) (N) Disagree (D
, 2012.[2] V. Albino, U. Berardi and R. M. Dangelico, "Smart Cities: Definitions, Dimensions, Performance, and Initiatives," Journal of Urban Technology, vol. 22, no. 1, pp. 3-21, 2015.[3] H. T. S. Alrikabi and N. A. Jasim, "Design and Implementation of Smart City Applications Based on the Internet of Things," Int. J. Interact. Mob. Technol, vol. 15, no. 13, pp. 4-15, July 2021.[4] O. Andrisano, I. Bartolini, P. Bellavista, A. Boeri, L. Bononi and A. Borghetti, "The Need of Multidisciplinary Approaches and Engineering Tools for the Development and Implementation of the Smart City Paradigm," Proceedings of the IEEE, vol. 106, no. 4, pp. 738-760, 2018.[5] D. Kim, D. Kwon, L. Park, J. Kim and S. Cho, "Multiscale LSTM-Based Deep
Colleges andUniversities (AAC&U)'s Center for the Advancement of STEM Leadership have successfullyimplemented formal coaching for Black women STEM faculty [35], [49]-[50].Although primarily leadership-focused, these programs include participants across variousacademic ranks. In these programs, faculty engage in structured sessions with experiencedevidence-based coaches who adhere to the eight ICF coaching competencies, (e.g., developingand maintaining a mindset that is open, curious, and client-centered; creating a safe, supportiveenvironment that promotes mutual respect and trust; and facilitating client insights and learningthrough powerful questioning and reflective practices, etc.). These programs have successfullyenhanced participants
forefront in the discourse on AI regulation and ethicsand are developing the norms of the international community with their policies [21]. 4) India is unique inits AI policy focus on inclusive AI development, making it a useful country to examine when it comes toAI in developing economies [22].For a rigorous and representative analysis, this study reviews official AI strategy and regulatory documents.Below is a list of documents chosen and reasoning for the choice: • U.S.’s Blueprint for an AI Bill of Rights: Making Automated Systems Work for the American People [23]: A non-binding document from the Office of Science and Technology Policy (OSTP) which represents US government’s ethical AI principles , that demonstrates the industry
exponential growth in the human consumption of raw and processedmaterials. As postulated by Thomas Malthus in 1798 in, “An Essay on the Principle ofPopulation,” the growth in both population and consumption may eventually exceed the ability toproduce, which suggests a need to make substantial change(s) to the nature of human activity [4].As an exercise in systems thinking, planetary boundaries have been described to measure theconsumption of raw materials - such as water, nutrients, and atmosphere – as well as biodiversity,which are under threat from depletion [5]. While there are those who hold to an alternative viewof resource abundance through technological innovation [6], on noted measures of planetaryscale phenomena the consumption of resources
asked to falsifydata (Diana Bairaktarova - DB). The course introduced the speakers via the syllabus, whichprovided a description of their profile and a profile photo (Table 2). The timing of eachsession was linked to specific lecture content, as seen in Table 1.Table 2. Organisation of living library sessions Order Guest speaker / Storyteller Linked lecture(s) of thematic sessions 1 Laura Nolan is a software engineer with two decades of Risk and uncertainty experience, with a focus on reliability in distributed in decision-making systems. In 2018, Laura left Google after being asked to
course.Active participation points were earned by students taking notes during all interviews and askingat least two questions during the semester. A Word document was provided with space to takenotes, including guided prompts such as: 1. What problem(s) are the speaker trying to solve using synthetic biology? 2. What stands out to you about the speaker’s path and/or their work or advice? 3. Describe the biological systems that the speaker builds with their work. Item Potential Points Pre-Assessment 10 Post-Assessment 10 Active Participation 20
] Mok, R.; Campanelli, M.; Datta, A.; Gupta, A.; Hickman, R.; Osthus, F.; Zwart, P. Using AILarge Language Models for Grading in Education: A Hands-On Test for Physics. arXiv preprintarXiv:2411.13685, 2024[4] J. Raj, A. Muppa; A. Dipukumar; R. Nirmal; A. Laddha; T. Kamath, S. Hong, M. Potla and M.Boicu. "Quantitative Analysis of Rubric-based Feedback Received From Claude 3.5 Sonnet onMathematical Programming Problems," 2024 IEEE MIT Undergraduate Research TechnologyConference (URTC), Cambridge, MA, USA, 2024, pp. 1-5,doi: 10.1109/URTC65039.2024.10937532.[5] H. McNichols, J. Lee, S. Fancsali, S. Ritter, and A. Lan, “Can Large Language ModelsReplicate ITS Feedback on Open-Ended Math Questions?,” 2024, arXiv: 2405.06414[6] K. M. Collins et al
correct responses to conceptual knowledge questions, and (b) Average student self-confidence ratings for structural reasoning concepts. Confidence ratings: 1 = Not confident, 5 = Very confident. Color coding is consistent across both parts of the figure to represent shared conceptual topics.References[1] Y. C. Chen, H. L. Chi, W. H. Hung, and S. C. Kang, “Use of tangible and augmented realitymodels in engineering graphics courses,” J. Prof. Issues Eng. Educ. Pract., vol. 137, no. 4, pp.267–276, 2011.[2] A. Behrouzi, J. C. Carroll, and B. Dymond, “Teaching the Equivalent Rectangular StressBlock,” in American Concrete Institute, vol. 359, p. 109, 2023.[3] A. Z
method(s)? 3) In which subjects have you used an iPad or electronic device to take notes? 4) In which subjects have you used a physical notebook to take notes? 5) What type of visual note-taking have you done in your classes or research? 6) What courses have you taken in the past 2 quarters, and how have professors presented information in these classes? 7) If you use an electronic device, what challenges have you faced with notetaking? 8) If you use a physical notebook, what challenges have you faced with notetaking? 9) If you do not use an iPad, what are your reasons? 10) If you do not use an iPad and the school provided a free iPad for academic purposes, would you switch to using the iPad for note-taking? Please
ensuring that the next generation of professionals is equipped to thrive in anincreasingly data-centric world.AcknowledgementsThis material is based upon work supported by the National Science Foundation under GrantNumber DUE-1917002. Any opinions, findings, and conclusions or recommendations expressedin this material are those of the author(s) and do not necessarily reflect the views of the NationalScience FoundationReferences1. Bonfert-Taylor, P., Ray, L., Pauls, S., Loeb, L., Sankey, L., Busch, J., & Hickey, T. (2022, August). Infusing Data Science into the Undergraduate STEM Curriculum. In 2022 ASEE Annual Conference & Exposition.2. Dartmouth DIFUSE: The github home for Dartmouth College’s Data Science Infused in STEM
, graduate students are still completing monthly reflections and are meeting with theirindustry mentors. Moving forward, we plan to conduct follow up interviews with students whocompleted the MCTQ in the Fall 2024 to gain insight into the reasoning behind their responses.Additionally, we plan to interview the non-academic mentors to determine their perspectives onthe projects, and improvements that can be made in the future.AcknowledgementsThis material is based upon work supported by the National Science Foundation under Grant No.224724 and the Graduate Assistance in Areas of National Need No. P200A210109.References[1] A. Collins, J. S. Brown, and S. E. Newman, “Cognitive Apprenticeship: Teaching the Crafts of Reading, Writing, and Mathematics
Addiction Research Center at the University ofNebraska-Lincoln.References [1] A. Vaswani, N. Shazeer, N. Parmar, J. Uszkoreit, L. Jones, A. N. Gomez, L. Kaiser, and I. Polosukhin, “Attention Is All You Need,” Dec. 2017. arXiv:1706.03762 [cs]. [2] A. Roberts, C. Raffel, and N. Shazeer, “How much knowledge can you pack into the parameters of a language model?,” in Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP) (B. Webber, T. Cohn, Y. He, and Y. Liu, eds.), (Online), pp. 5418–5426, Association for Computational Linguistics, Nov. 2020. [3] A. Chowdhery, S. Narang, J. Devlin, and et al., “PaLM: Scaling Language Modeling with Pathways,” oct 2022. arXiv:2204.02311 [cs]. [4] K. Mahowald, A
in Psychology, 3(2):77–101.Chang, H. (2021). Science teachers and students metavisualization in scientific modeling. Science Education. https://doi.org/10.1002/sce.21693Citrohn, B. & Svensson, M. (2020). Technology teacher’s perceptions of model functions in technology education. International Journal of Technology and Design Education, 32(2), 805-823. https://doi.org/10.1007/s10798-020-09632-8Coppola, B. P. (2019). Engineering education: The role of pedagogical self-efficacy in teaching engineering design. Journal of Engineering Education, 108(2), 197-2015. https://doi.org/10.1002.jee.20236Dauer, J., Momsen, J., Speth, E., Makohon-Moore, S., & Long, T. (2013). Analyzing change in students
applyengineering design to produce solutions that meet specified needs with consideration of publichealth, safety, and welfare, as well as global, cultural, social, environmental, an societal contexts”(ABET, 2021, p. 8). Both ABET’s student outcomes (s/o) and CEAB’s graduate attributes (g/a)also require graduating students to have the ability to communicate well with colleagues as wellas non-engineers (ABET s/o 3, CEAB g/a 7), possess effective teamwork and leadership skills(ABET s/o 5, CEAB g/a 6), be able to appreciate the impact of their work on society and theenvironment (ABET s/o 4, CEAB g/a 9), and make decisions that reflect the ethical requirementsof the profession (ABET s/o 4, CEAB g/a 8,10)(ABET, 2021; CEAB, 2022). The presence of user-focused
"assessment of risk." Through this framing, they exposedstudents to research as early as possible in their curriculum, emphasizing these EML concepts. InBurkey et al.'s [9] paper, they piloted an REU program integrated with EM, including placingstudents in research projects that had commercialization goals and introducing EM topicsthrough weekly seminars such as "Entrepreneurs and their Paths" and "Opportunity Assessment."Through this experience, two cohorts of students reported that they felt more knowledgeableabout commercialization of products, and were able to develop and conduct experiments,generate creative ideas, and recognize business opportunities [9].Direct integration of EM into undergraduate research experiences exists very minimally
FIE, ICER, and ASEE, and brings years of teaching experience in software engineering and foundational computing courses.Dr. Mohsen M Dorodchi, University of North Carolina at Charlotte Dr. Dorodchi has been teaching in the field of computing for over 35 years of which 25 years as an educator. He has taught the majority of the courses in the computer science and engineering curriculum over the past 25 years such as introductory programming, data structures, databases, software engineering, system programming, etc. He has been involved in a number of National Science Foundation supported grant projects including Scholarship for STEM students (S-STEM), Researcher Practitioner Partnership (RPP), IUSE, and EAGER
faculty to effectively navigatethrough their emotional experiences. Improving emotional experiences will not only be a benefitto engineering faculty but beneficial to engineering faculty’s’ students and their administration.Further, the CGT model will highlight the power of positively improving strategies forimproving emotion regulation in faculty. Additionally, we aim for this study to be a basis forfurther research understanding the complex emotional experiences of engineering faculty.AcknowledgementsThis work was supported through funding by the National Science Foundation (NSF CAREER#2045392). Any opinions, findings, and conclusions or recommendations expressed in thismaterial are those of the author(s) and do not necessarily reflect the
writing in productive ways. This work was supported inpart by NSF Grant No. 2315294. Any opinions, findings, conclusions, or recommendationsexpressed in this work are those of the authors and do not necessarily reflect those of the NSF.References[1] D. Brandt, The rise of writing: Redefining mass literacy. Cambridge University Press, 2014.[2] K. J. Levine, S. Allard, and C. Tenopir, “The changing communication patterns of engineers [point of view],” Proceedings of the IEEE, vol. 99, no. 7, pp. 1155–1157, Jul. 2011.[3] J. A. Donnell, B. M. Aller, M. Alley, and A. A. Kedrowicz, “Why industry says that engineering graduates have poor communication skills: What the literature says,” in 2011 ASEE Annual Conference & Exposition
reflect the views of the National Science Foundation.References[1] S. Gehrke and A. Kezar, “STEM Reform Outcomes Through Communities of Transformation,” Change: The Magazine of Higher Learning, vol. 48, no. 1, pp. 30–38, Jan. 2016, doi: 10.1080/00091383.2016.1121084.[2] A. Kezar, S. Gehrke, and S. Bernstein-Sierra, “Communities of transformation: Creating changes to deeply entrenched issues,” Journal of Higher Education, vol. 89, no. 6, pp. 832–864, 2018, doi: 10.1080/00221546.2018.1441108.[3] V. Svihla, S. C. Davis, and N. N. Kellam, “The TRIPLE Change Framework: Merging Theories of Intersectional Power, Learning, and Change to Enable Just, Equitable, Diverse, and Inclusive Engineering Education
of confidence and competence (self-efficacy) in teaching engineering is reflected in bothquantitative and other qualitative data and is testimony to the success of the MEERC RET Site.AcknowledgementsThis material is based upon work supported by the National Science Foundation under AwardNumber 2055138. Additional support was provided by Montana State University.References[1] S. Wilger, "Definition of Frontier," in "National Rural Healt Association Policy Brief," National Center for Frontier Communities, 2016.[2] EIA. "Montana State Profile and Energy Estimates." https://www.eia.gov/state/analysis.php?sid=MT (accessed 2024).[3] D. Showalter, R. Klein, J. Johnson, and S. L. Hartman, "Why Rural Matters 2015-2016
Taskforces Concerning Critical Issues in US Undergraduate Education in the Sciences, Mathematics and Engineering (no. 3). National Science Foundation, 1989.[2] Y. Jia, T. Wang, C. Chen, and Y.-F. Jin, "Board 410: Tracing the Evolution of NSF REU Research Priorities and Trends," in 2024 ASEE Annual Conference & Exposition, 2024.[3] L. Martin-Hansen, "Examining ways to meaningfully support students in STEM," International Journal of STEM Education, vol. 5, no. 1, p. 53, 2018.[4] Y. Jin, C. Qian, and S. Ahmed, "Closing the Loop: A 10-year Follow-up Survey for Evaluation of an NSF REU Site," in ASEE Annual Conference and Exposition, Minneapolis, MN., 2022. [Online]. Available: https://peer.asee.org/41048
-School High School Science Experiences and Influence on Students’ Engineering Choices,” Journal of Pre-College Engineering Education Research (J-PEER), vol. 6, no. 2, Jan. 2017, doi: 10.7771/2157-9288.1131.[5] F. Lewis, J. Edmonds, and L. Fogg-Rogers, “Engineering science education: the impact of a paired peer approach on subject knowledge confidence and self-efficacy levels of student teachers,” Int J Sci Educ, vol. 43, no. 5, pp. 793–822, Mar. 2021, doi: 10.1080/09500693.2021.1887544.[6] M. Riojas, S. Lysecky, and J. Rozenblit, “Adapting Engineering Education to Resource- Constrained Middle Schools: Teaching Methodologies and Computing Technologies,” in 2010 17th IEEE International Conference and
of the central roles of the designer in TD is to co-evolveboth the design space and the objective space by iteratively generating new design artifacts byarranging different combinations of variable parameters and testing their performance [5]. This iswhat we term Forward Design, which occurs when a (team of) human(s) leads the designprocess and objective-design space co-evolution by manually generating design artifacts in thedesign space and subsequently evaluating them in the objective space. However, design featuringgenerative AI-based tools, i.e., Generative Design (GD), requires the human designer to take aninverse approach to co-evolving the design and objective spaces. GD tools prompt the designerto begin by computationally defining