ProjectsThough research in intrusion detection has been around for several years, applications are alwayschanging and morphing. Current intrusion detection processes suffer from several limitationswhen focusing on highly vulnerable network intrusions. First, with the increasing volume ofnetwork traffic -- existing intrusion detection processes fail to analyze the vulnerabilities in timeto predict possible network intrusion(s) from the chain of actions of an intruder. Second, currentintrusion detection systems produce a high volume of false positive alerts. And third, currentapproaches consider every sequence of network vulnerability to predict future intrusions ratherthan analyzing the comparatively significant sequences. Instead of teaching
083–12 121, 2022. [4] C. Guzm´an-Valenzuela, C. G´omez-Gonz´alez, A. Rojas-Murphy Tagle, and A. Lorca-Vyhmeister, “Learning analytics in higher education: a preponderance of analytics but very little learning?” International Journal of Educational Technology in Higher Education, vol. 18, pp. 1–19, 2021. [5] B. Rienties, Q. Nguyen, W. Holmes, and K. Reedy, “A review of ten years of implementation and research in aligning learning design with learning analytics at the open university uk,” Interaction Design and Architecture (s), vol. 33, pp. 134–154, 2017. [6] A. S. Alzahrani, Y.-S. Tsai, S. Iqbal, P. M. M. Marcos, M. Scheffel, H. Drachsler, C. D. Kloos, N. Aljohani, and D. Gasevic, “Untangling connections between challenges
allowed to use generative AI tools (e.g., ChatGPT) during anystage of the writing process or they could choose not to use them. If AI assistance was used,students were asked to include the following information in the Appendix of their reports: theprompt(s) used, and other details on how the AI-assisted content was incorporated or revised.This information was collected to ensure the accuracy of the report content and the authenticityof references.2.2 Instructor’s AssessmentA total of 48 draft reports (i.e., first submission) were evaluated for this study. Reports in whichstudents self-reported the Checklist were analyzed further for this study.3. Results and DiscussionAs mentioned earlier, the primary goal of this study was to evaluate the
course will help the instructor to developa solution for the future iteration.Future research direction include the following: • Further longitudinal studies tracking the impact of OBA on student performance across multiple years. • Comparing student outcomes in Architectural Engineering with other engineering disciplines to assess cross-disciplinary effectiveness. • Developing a digital grading system that provides real-time performance tracking.References1. N. S. Madonsela, "Aligning Education and Workforce Training with Industry Needs: A perspective of Human Capital Development," Proceedings of the First Australian International Conference on Industrial Engineering and Operations Management, Sydney, Australia, Dec. 20
, attitudes, and self-reported skills related to generative AI, coding, robotics, andengineering tasks. Self-reported likert scale responses of coding ability and robotic skill werealso collected. This was triangulated by asking implicit questions about student coding ability.More specifically student responses to questions such as “If you do have prior programmingexperience: when you "get stuck" and need help, what online resource(s) would you use to figureout how to move forward?” helped assess their prior coding knowledge. For instance,generalized responses that referred to use of a search engine or asking others for help wereindicative of lesser prior knowledge in comparison to student responses that referred to StackOverflow, open source
industryleaders. As the program evolves, it will continue to empower students to explore their passions,develop critical skills, and envision a future where they can make a meaningful impact in theworld of STEM.References[1] A. Qasrawi, S. Langar and T. Sulbaran, "STEM Summer Camps in the US: Knowledge andContext," in 2023 ASEE Annual Conference & Exposition, 2023.[2] C. J. Cappelli, K. L. Boice and M. Alemdar, "Evaluating University-Based Summer STEMPrograms: Challenges, Successes, and Lessons Learned.," Journal of STEM Outreach, vol. 2, p.n1, 2019.[3] E. D. Broder, K. J. Fetrow, S. M. Murphy, J. L. Hoffman and R. M. Tinghitella, "STEMSummer Camp for Girls Positively Affects Self-Efficacy," The American Biology Teacher, vol.85, p. 432–439, 2023.[4
scalablemodel for improving STEM education and addressing disparities in graduation rates andworkforce representation.AcknowledgementThe author wishes to thank Dr. Kimberly LeChasseur, Senior Research and Evaluation Associateat the WPI Morgan Teaching & Learning Center, for administering the student survey andproviding valuable support in interpreting the response data. The author also gratefullyacknowledges the generous contributions of WPI alumni donors, whose financial support made itpossible to acquire the equipment and instrumentation used in this course.References[1] R. Ram, S. Fuller, A. Panwar, J. Schulamn, K. Young, M. Ellsworth, S. Sotudeh and H. Kaur, "Aerospace and Defense Workforce Study," Ernst & Young LLP, 2022.[2] J. Marcus
PlatformThe grading platform was tested on two sets of 50 assignments graded by the GPT-4 and Qwen.AI-generated grades were compared with the human-graded benchmarks. Figure 4 shows the meanscores and variability (mean ± standard deviation) for Labs 2 and 5, with human scores serving asthe reference for comparison. In Lab 2, the human reference mean was 16.89, with Qwen scoring16.07 and GPT-4 scoring 15.72. Qwen's score was closer to the human reference, indicating betterperformance than GPT-4 in this laboratory. In Lab 5, the human reference mean was 20.44, andQwen achieved a mean score of 22.67, whereas GPT-4 scores were 21.17. Although both LLMsscore higher than the human reference, GPT-4's score is closer, suggesting that it performs betterthan
With Disabilities: An Emergent Theoretical Model,” J. Coll. Stud. Dev., vol. 56, no. 7,pp. 670–686, 2015.[2] M. Legault, J.-N. Bourdon, and P. Poirier, “From neurodiversity to neurodivergence: therole of epistemic and cognitive marginalization,” Synthese, vol. 199, no. 5/6, pp. 12843–12868,Dec. 2021, doi: 10.1007/s11229-021-03356-5.[3] L. Clouder, M. Karakus, A. Cinotti, M. V. Ferreyra, G. A. Fierros, and P. Rojo,“Neurodiversity in higher education: a narrative synthesis,” High. Educ., vol. 80, no. 4, pp. 757–778, Oct. 2020, doi: 10.1007/s10734-020-00513-6.[4] S. K. Kapp, Ed., Autistic Community and the Neurodiversity Movement: Stories from theFrontline. Singapore: Springer, 2020. doi: 10.1007/978-981-13-8437-0.[5] L. G
institutions.AcknowledgmentThe authors gratefully acknowledge the leadership and financial support of the School ofEngineering at the Universidad Andres Bello, Chile.References[1] H. C. Chu, G. H. Hwang, Y. F. Tu, and K. H. Yang, “Roles and research trends of artificial intelligence in higher education: A systematic review of the top 50 most- cited articles,” Australasian Journal of Educational Technology, vol. 38, no. 3, pp. 22–42, 2022, doi: 10.14742/ajet.7526.[2] H. Crompton and D. Burke, “Artificial intelligence in higher education: the state of the field,” International Journal of Educational Technology in Higher Education, vol. 20, no. 1, p. 22, 2023, doi: 10.1186/s41239-023-00392-8.[3] T. Pham, T. B. Nguyen, S. Ha, and N. T. Nguyen Ngoc
. Hinings, D. Logue, and C. Zietsma, “Fields, institutional infrastructure and gov- ernance,” The Sage handbook of organizational institutionalism, pp. 163–189, 2017. [5] E. Chenoweth, Civil resistance: What everyone needs to know®. Oxford University Press, 2021. [6] A. Reuel, B. Bucknall, S. Casper, T. Fist, L. Soder, O. Aarne, L. Hammond, L. Ibrahim, A. Chan, P. Wills et al., “Open problems in technical ai governance,” arXiv preprint arXiv:2407.14981, 2024. [7] R. Søraa, AI for diversity. CRC Press, 2023. [8] T. Gebru and É. P. Torres, “The tescreal bundle: Eugenics and the promise of utopia through artificial general intelligence,” First Monday, 2024. 6
Paper ID #47276BOARD # 412: NSF RIEF: Enhancing design thinking transfer among undergraduatebioengineering students: A Dynamic Role Identity ApproachJennifer Patten, Temple UniversityDr. Avi Kaplan Avi Kaplan is an Associate Professor of Educational Psychology at Temple University in Philadelphia, PA, USA. Dr. Kaplanˆa C™s research interests focus on student and teacher motivation, self-regulation, and identity development, with a particular interestDr. Ruth Ochia, Temple University Dr. Ruth S. Ochia is a Professor of Instruction with the Bioengineering Department, Temple University, Philadelphia, Pa. Her past research
marginalizedcommunities. Through our four-year collaboration, we have demonstrated how creative, hands-on activities incorporating art and design can expand young students' perceptions of engineeringand help them envision themselves as future engineers. By leveraging the enthusiasm andexpertise of university faculty, undergraduate mentors, and elementary school teachers, we havedeveloped sustainable programming that integrates into the elementary classroom while inspiringboth students and educators alike. Through this relationship, we have documented key pragmaticlessons to help bring two educational communities together.References1. A. Master, S. Cheryan, A. Moscatelli, & A. N. Meltzoff, “Programming experience promotes higher stem motivation among
, "A literature review on immersive virtual reality in education,"eLearning and Software for Education, vol. 1, pp. 133–141, 2015.[4] C. T. Fosnot, Constructivism: Theory, Perspectives, and Practice, 2nd ed. New York, NY,USA: Teachers College Press, 2013.[5] M. Schcolnik, S. Kol, and J. Abarbanel, "Constructivism in theory and in practice," EnglishTeaching Forum, vol. 44, no. 4, pp. 12–20, 2006.[6] M. P. Driscoll, Psychology of Learning for Instruction, 2nd ed. Boston, MA, USA: Allyn &Bacon, 2000.[7] M. Langley, D. W. Carruth, and M. Denny, "Virtual reality training improves real-world taskperformance in physical therapy and rehabilitation," IEEE Trans. Neural Syst. Rehabil. Eng., vol.24, no. 9, pp. 1041–1050, 2016.[8] G. Martin, J. Clarke
confidence developed during the first year and theongoing support offered by the program. Tracking future retention and graduation rates of thestudents in this study is planned, which will provide additional insights into the long-termoutcomes of SSP participants. Further research is needed to isolate and evaluate the specificeffects of SI on performance in first math and engineering courses, as well as its contribution tooverall academic success and persistence.Acknowledgement of Support and DisclaimerThis material is based upon work supported by the National Science Foundation under Grant No.2221638.Any opinions, findings, and conclusions or recommendations expressed in this material are thoseof the author(s) and do not necessarily reflect the
, I’m not sure, no but itprobably helps, or not at all. The collective results of this study point to the benefit ofconvergence of nursing and engineering to solve pressing societal challenges of theAnthropocene.MethodsInstitutional context. Located in Rolla, Missouri, the Missouri University of Science andTechnology was founded in 1870 as the Missouri School of Mines. In 2023, a total of more than7,000 students (approximately 1,500 graduate and 5,500 undergraduate) are enrolled inapproximately 100 degree programs. Currently characterized as a Carnegie R2, a doctoraluniversity with high research activity, S&T is home to three colleges. Within the College ofEngineering and Computing, the Department of Civil, Architectural, and
& Make: Annual Global Report,” Autodesk, https://www.autodesk.com/hk/insights/research/state-of-design-and-make (Accessed August 13, 2024).[2] B. Caldwell and G. M. Mocko, “Product Data Management in Undergraduate Education,” Volume 3: 28th Computers and Information in Engineering Conference, Parts A and B, pp. 433–441, Jan. 2008. doi:10.1115/detc2008-50015.[3] R. O. Buchal, “The Use of Product Data Management (PDM) Software to Support Student Design Projects,” Proceedings of the Canadian Engineering Education Association (CEEA), Aug. 2011. doi:10.24908/pceea.v0i0.3862[4] K. Del Re, S. Yun, E. Kozikowski, T. Fuerst, and J. Camba, “Integrating a Product Life- Cycle Management System into a
challengingworking conditions, many Disabled Workers contribute to the sector yet struggle to participatefully in all work areas. Besides the ethical imperative for justice and inclusivity, the growinglabor shortage is an additional spur to better solutions that can both retain and encourage morediversity in the workforce and better educational programs that address inclusive methods in thebuilding process. This paper reports on a review of existing accessibility practices and conditionson four worksites within the UK. The results from this investigation are informing the inclusionof health and safety (H&S) as well as diversity, equity, and inclusion (DEI) topics within a newBSc Construction Management degree being launched in September 2025 at the New
with the courses students are currently enrolledin at the time of the study, such as the types of courses they are taking and the available resourcesas part of the courses. Hilliger et al.’s [32] grounded theory model of what makes coursesdemanding to students provides a suite of contextual and external variables that could impactperceived usefulness and perceived ease of use, such as content complexity, faculty support,workload, and student interests. This work fits into a larger project on how students usemetacognitive strategies with these external resources, especially large language model-basedtechnology like ChatGPT, so metacognitive strategies will be explored as a potential moderatingvariable for the intentions to use and elements of
. Prichard, "Sleep Patterns and Predictors of Disturbed Sleep in a Large Population of College Students," Journal of Adolescent Health, pp. 124-132, 2009.[2] S. P. Becker, M. A. Jarrett, A. M. Luebbe, A. A. Garner, G. L. Burns and M. J. Kofler, "Sleep in a large, multi-university sample of college students: sleep problem prevalence, sex differences, and mental health correlates," Elsevier, pp. 174-181, 2018.[3] L.-L. Tsai and S.-P. Li, "Sleep patterns in college students: Gender and grade differences," Journal of Psychosomatic Research, pp. 231-237, 2004.[4] S. H. Cheng, C.-C. Shih, I. H. Lee, Y.-W. Hou, K. C. Chen, K.-T. Chen, Y. K. Yang and Y. C. Yang, "A study on the sleep quality of incoming university students," Psychiatry
] M. Ridgway et al., “Equality, diversity, and inclusivity in engineering, 2013 to 2022: a review,” Royal Academy of Engineering, Nottingham Trent University, 2023. doi: 10.17631/RD-2024-0002-DREP.[2] S. Appelhans et al., “From ‘leaky pipelines’ to ‘Diversity of thought’: What does diversity mean in engineering education?,” in 126th ASEE Annual Conference and Exposition: Charged Up for the Next 125 Years, ASEE 2019, June 15, 2019 - June 19, 2019, in ASEE Annual Conference and Exposition, Conference Proceedings. Tampa, FL, United states: American Society for Engineering Education, 2019.[3] D. E. Chubin, G. S. May, and E. L. Babco, “Diversifying the Engineering Workforce,” J. Eng. Educ., vol. 94, no. 1, pp. 73–86
decision-making in engineering education.AcknowledgmentsThis study was funded by the National Science Foundation (NSF) under grants DUE-2152282,DUE-2111510, and DUE-2111386. Any opinions, findings, or recommendations expressed inthis study are those of the authors and do not necessarily reflect the views of the NationalScience Foundation. The authors would like to thank the undergraduate students who helpedwith the data collection for this study.References[1] M. Fuller, & R. Moore, An Analysis of Jane Jacobs's The Death and Life of Great AmericanCities. Macat Library, 2017.[2] J. Speck,. Walkable city: How downtown can save America, one step at a time. Macmillan,2013.[3] M. Tobin, S. Hajna, K. Orychock, N. Ross, M. DeVries, P. J. Villeneuve
analyze data. Finally, our interpretation ofthe conceptual nature and contexts for the items we reviewed is based on our ownunderstandings, experiences, and assumptions. We do not know the intentions of the authors ofthose concept inventories beyond what was present in their prior publications. It is possible thatour own misunderstandings or misconceptions could have influenced these results.AcknowledgmentsMany thanks to Dr. Eric Davishahl, Dr. Scott Danielson, Dr. Christopher Papadopoulos, and Dr.Paul Steif for their responses and support of this project. Many more regards and appreciationalso go out to all the other professors who helped provide their concept inventories for initialreview.References[1] A. Madsen, S. B. McKagan, and E. C. Sayre
Nuclear Power: Environmental Considerations Power Grid Vulnerabilities Hydraulic Fracturing Facial Recognition Water Projects in Developing CountriesWhile reading the scenario the students are given a series of questions to guide the discussion.These discussion prompts direct the students to identify the important problem/s and to discussstakeholders, impacts, unknowns, and possible solutions. The EPSA discussion prompts areshown in Table 3Table 3. EPSA Discussion PromptsImagine that you are a team of engineers working together for a company or organization onthe problem/s raised in the scenario. 1. Identify the primary and secondary problems raised in the scenario. 2. Discuss what your team
Paper ID #49232A complex systems approach to studying the outcomes of initiatives supportingwomen engineering faculty.Matilde Luz Sanchez-Pena, University at Buffalo, The State University of New York Dr. Matilde S´anchez-Pe˜na is an assistant professor of Engineering Education at the University at Buffalo – SUNY where she leads the Diversity Assessment Research in Engineering to Catalyze the Advancement of Respect and Equity (DAREtoCARE) Lab. Her research focuses on developing cultures of care and well-being in engineering education spaces, assessing gains in institutional efforts to advance equity and inclusion, and
qualitativedata collection and analysis, such as interviews, which could have provided a deeperunderstanding of how and why students develop these mindsets over time.References[1] C. J. Atman, R. S. Adams, M. E. Cardella, J. Turns, S. Mosborg, and J. Saleem, "Engineering Design Processes: A Comparison of Students and Expert Practitioners," J. Eng. Educ., vol. 96, no. 4, pp. 359-379, 2007, doi: https://doi.org/10.1002/j.2168- 9830.2007.tb00945.x.[2] P. Biney, Assessing Abet Outcomes Using Capstone Design Courses. 2007, pp. 12.261.1- 12.261.20.[3] C. L. Dym, A. M. Agogino, O. Eris, D. D. Frey, and L. J. Leifer, "Engineering design thinking, teaching, and learning," (in English), J. Eng. Educ., Review vol. 94, no. 1
College Students with Disabilities in STEM,” JPED, vol. 24, no. 4, pp.375–388.[7] E. A. Cech, “Engineering’s Systemic Marginalization and Devaluation of Students andProfessionals With Disabilities,” in Proceedings of the 2021 ASEE Annual Conference VirtualMeeting: American Society of Engineering Educators, Jul. 2021. Accessed: Jan. 11, 2025.[Online]. Available: https://peer.asee.org/engineering-s-systemic-marginalization-and-devaluation-of-students-and-professionals-with-disabilities.pdf.[8] C. Funk, “Black Americans’ Views of and Engagement with Science,” Pew Research Center,Apr. 2022.[9] C. Funk and M. H. Lopez, “Hispanic American’s Trust in and Engagement with Science,”Jun. 2022. Accessed: Jan. 11, 2025.[10] J. C. Richard, S. Y. Yoon, M. C
indicated "strong agreement" or "always or almost always true of me." The first twosections were adopted from [5]’s survey, while the other survey sections were adopted from[20]'s survey. These scales allowed respondents to share distinct perceptions and experiencesrelated to the development of their pedagogical and entrepreneurial mindsets attributed to thecourse.Analysis ProcedureIn this study, the analysis focuses on evaluating the KEEN Entrepreneurial Mindset trackcompared to the general pedagogical and leadership development from the GTA course. Thesurvey was utilized, with each section corresponding to crucial topics within the course andKEEN tracks. The two surveys used in this study are valid and reliable [5], [20]. The impact ofthe KEEN
the IEEE, 105(9), 1836-1847. https://doi.org/10.1109/JPROC.2017.2714564Allen, A. (2017). Power/Knowledge/Resistance. Foucault and epistemic injustice. In The Routledge handbook of epistemic injustice (pp. 187–196). Routledge.Anderson, E. (2012). Epistemic justice as a virtue of social institutions. Social Epistemology, 26(2), 163- 173. https://doi.org/10.1080/02691728.2011.652211Baquero-Sierra, M. J. A., Vargas-Ordóñez, C. E., McDermott, J. E., & McBride, S. M. (2023, June). Understanding international graduate engineering students’ well-being: What do they need to thrive? (Work in Progress). Paper presented at the 2023 ASEE Annual Conference & Exposition, Baltimore, Maryland. https://doi.org
. [2] O. C. Jenkins, J. Grizzle, E. Atkins, L. Stirling, E. Rouse, M. Guzdial, D. Provost, K. Mann, and J. Millunchick, “The Michigan Robotics undergraduate curriculum: Defining the discipline of robotics for equity and excellence,” arXiv preprint arXiv:2308.06905, 2023. [3] T. Balch, J. Summet, D. Blank, D. Kumar, M. Guzdial, K. O’hara, D. Walker, M. Sweat, G. Gupta, S. Tansley, et al., “Designing personal robots for education: Hardware, software, and curriculum,” IEEE Pervasive Computing, vol. 7, no. 2, pp. 5–9, 2008. [4] I. M. Souza, W. L. Andrade, L. M. Sampaio, and A. L. S. O. Araujo, “A systematic review on the use of LEGO® robotics in education,” in IEEE Frontiers in Education Conference (FIE), pp. 1–9, IEEE, 2018