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and how these interactions benefitprofessionals. Open-ended responses will be thoroughly examined using qualitative analysissoftware, like NVivo, to conduct a detailed thematic and sentiment analysis to gain deeperinsights into student feedback.References[1] Douglas, E. P., & Jordan, S. S., & Lande, M., & Bumbaco, A. E. (2015, June), ArtifactElicitation as a Method of Qualitative Inquiry in Engineering Education Paper presented at 2015ASEE Annual Conference & Exposition, Seattle, Washington. 10.18260/p.23574[2] Rogers, Courtney & Valdez, Rupa. (2021). Designing for Diversity, Equity, and Inclusion inSystems Engineering Education. 10.18260/1-2--36929.[3] Landis, R. B. (1997, June), Enhancing Engineering Student Success: A
data saturation has not yet been fully achieved in this WIP study [11]. Twocodes—reverse thinking and risk management—were identified by only one participant,indicating that additional data collection may offer further insights. As we expand this study inthe future, we intend to increase the sample size to allow for a more comprehensive exploration. References[1] C. J. Atman, K. Yasuhara, R. S. Adams, T. J. Barker, J. Turns, and E. Rhone, “Breadth in problem scoping: A comparison of freshman and senior engineering students,” International Journal of Engineering Education, vol. 24, no. 2, p. 234, 2008.[2] R. S. Adams and C. J. Atman, “Characterizing engineering student design processes: An
toward achieving the program's goals. Through structuredresearch experiences, faculty mentorship, and community engagement, the program providedmeaningful opportunities for students from underrepresented backgrounds to excel incomputational sciences and engineering. The success of the program in improving academicperformance, and interest in advanced studies and STEM careers highlights its potential tocontribute to the broader goal of strengthening national competitiveness in science andtechnology.References[1] S. H. Russell, M. P. Hancock, and J. McCullough, “Benefits of Undergraduate Research Experiences,” Science, vol. 316, no. 5824, pp. 548–549, Apr. 2007, doi: 10.1126/science.1140384.[2] A. L. Zydney, J. S. Bennett, A. Shahid, and K. W
Paper ID #46201BOARD # 367: Engineering PLUS: a NSF Eddie Bernice Johnson INCLUDESAllianceMrs. Claire Duggan, Northeastern University Claire Duggan is currently Executive Director for The Center for STEM Education at Northeastern University and Co-Principal Investigator for the National Science Foundation Engineering PLUS Alliance. Claire leads the coordination of stEm PEER (Practitioners Enhancing Engineering Regionally) Academy, a key strategy for this grant. Claire has helped lead multiple NSF STEM grant efforts including but not limited to ATE, ITEST, RET, REU, and S-STEM initiatives.Mr. Richard R Harris, Northeastern
researchnetwork to explore the demonstration of psychological safety within the network. In amulti-institutional research network such as [Name of Research Network], the organization’sprimary goals involve creating new knowledge and finding new ways to tackle systemicproblems.To achieve the goals of the research network, participants are required to contribute to thecontinuous improvement of activities and research products to achieve the goals of the network.Participants make their contributions by sharing their ideas, by collaborating with otherparticipants, as well as by trying out new ways of doing things. While these activities have thepotential to benefit the goals of the research network, they could pose certain risks to theparticipant(s) involved
Examples of: a) physical qualitative versus b) computer-generated quantitative material property charts.Game Mechanics Variation with Enhanced Gamification Element: Currently, the Multi-Material Marbles Game is designed as an activity that encourages playful interaction to achievethe potential learning objectives. The tactile nature of the multi-material spheres and theopportunity to collaborate with other players keep participants engaged throughout the experience.Although there are “game mechanics”, the activity currently does not have the concept of a“winner”. Under Deterding et al.’s taxonomy of gamification, this game lies between aneducational game, a science demo, and an educational toy, see Fig 1. We believe this achieves agood balance
them to be successful in the end. They need to know that they can come totheir mentor with all the raw emotions of not knowing their goals or what their next move is. Itis theirs to shape into how they want to mold their futures, but they should feel assured byfaculty and staff that they will be there from point A to point B or Z if need be. REFERENCES[1] GALLUP and F. Lummina, "State of Higher Education 2024 Report," Lumina, Washington, D.C., 2024.[2] S. R. Covey, The seven habits of highly effective people: restoring the character ethic, New York: Simon and Schuster, 1989.[3] J. Pinchot, D. Cellante, S. Mishra and K. Paullet, "Student perceptions of challenges and the role of mentorship in
, using either a PI or PID + filter controllers. After completing eachtrial, students compare the experimental data to the expected behavior from a Simulink blockdiagram model that they must construct using process gains and time constants estimated fromexperimental data. A critical learning objective is for students to construct Simulink blockdiagram using the correct transfer functions to model the plant and reproduce the experimentaltrials. Fig. 3 illustrates how typical results from the VR experiment complement modeling inMATLAB and Simulink. The experimental data represent the closed-loop response obtainedafter a change in the liquid level setpoint in tank 1. The closed-loop transfer function g CL(s) forthe system is second order
. A. Mejia, and T. Perez, “Arrebatos and institutionalized barriersencountered by low‐income Latino/a/x engineering students at Hispanic‐Serving Institutions(HSIs) and emerging HSIs,” Journal of engineering education (Washington, D.C.), vol. 113, no.4, pp. 1177–1197, 2024, doi: 10.1002/jee.20612.[13] S. Secules, “On the importance of (white) humility: Epistemological decentering as apositional orientation toward research,” Journal of engineering education (Washington, D.C.),vol. 112, no. 2, pp. 258–261, 2023, doi: 10.1002/jee.20508.[14] S. Secules, A. Gupta, A. Elby, and E. Tanu, “Supporting the Narrative Agency of aMarginalized Engineering Student,” Journal of engineering education (Washington, D.C.), vol.107, no. 2, pp. 186–218, 2018, doi
proposed timeline detailed in the section above topublish a full paper in a future ASEE conference.References[1] S. Malcolm, “Strengthen the case for DEI,” Science, vol. 383, no. 6690, Mar. 28, 2024. [Online]. Available: https://doi.org/10.1126/science.adp4397. [Accessed: Dec. 29, 2024].[2] “Pivotal moments in higher education DEI,” Insight into Diversity, Sept. 17, 2023. [Online]. Available: https://www.insightintodiversity.com/pivotal-moments-in-higher- education-dei/. [Accessed: Dec. 30, 2024].[3] K. Kearney, C. D. Wilson, and E. Ramirez, “Overcoming barriers of incorporating diversity, equity, and inclusion initiatives in nursing schools,” Journal of Nursing Education, vol. 63 (1), pp. 1-4, Sept. 2023.[4] R.H. Stout, C. Archie
’ journeys through the program, allowing adjustments to foster greater self-efficacy,reinforce the richness of learning experiences, and clarify outcome expectations.References:[1] K. Bartlett, O. Burkacky, L. Li, R. Vrijen, and B. Wiseman, “A roadmap for US semiconductor fab construction,” McKinsey and Company, Jan. 2023. Accessed: Jan. 12, 2025. [Online]. Available: https://www.mckinsey.com/industries/industrials-and- electronics/our-insights/semiconductor-fabs-construction-challenges-in-the-united-states#/[2] US GAO, “Semiconductor Supply Chain: Policy Considerations from Selected Experts for Reducing Risks and Mitigating Shortages,” U. S. Government Accountability, GAO-22- 105923, Jul. 2022. Accessed: Jan. 12, 2025. [Online
-Aguilar, P. R. Álvarez-Pérez, and P. A. Toledo- Delgado, "Dropping out of higher education: Analysis of variables that characterise students who interrupt their studies," Acta Psychologica, vol. 252, p. 104669, Feb. 2025, doi: 10.1016/j.actpsy.2024.104669.[2] Cruz L., Li T., Ciner L., Douglas K., Greg C., (2022) Predicting learning outcome in a first-year engineering course: a human-centered learning analytics approach. Recuperado de: https://peer.asee.org/predicting-learning-outcome-in-a-first-year- engineering-course-a-human-centered-learning-analytics-approach.pdf[3] G. Bilquise, S. Abdallah, and T. Kobbaey, "Predicting Student Retention Among a Homogeneous Population Using Data Mining," in Proceedings
AR cycle involves a clear rationale for pedagogical intervention,reflection upon this exercise, and preparation for another cycle [30]. All faculty membersinvolved in this exercise were empowered to create similar hybrid student-AI activities in theirupcoming classes. They were aware of both the added value of such assignments and their abilityto provide critical reflection on the limitations of GenAI. Consistent with Wach et al.’s [43] emphasis on responsible use of GenAI tools, facultymembers were aware of the need to move beyond mere restriction to ethical use. Facultymembers consistently relayed their belief that the best means forward is to expose students toGenAI tools within a controlled class environment, in a manner like the
focus our analysison domestic applicants to four engineering programs (aerospace, chemical, electrical, andmechanical) at a large public research university in the U.S. between 2010 and 2022. We focuson domestic applicants because previous research has found substantial cross-nationaldifferences in norms for writing LORs and we wanted to minimize the influence of thosedifferences [5]. We selected four programs to sample from to provide variation in program size,selectivity, and diversity.1 This research was initially funded by the National Science Foundation under Grant No. 2225209, awarded in 2022.Funding was discontinued by the NSF in April 2025 because the project’s focus on broadening participation inSTEM “no longer effectuate[s] the
Assessment. Washington, D.C.: National Academies Press, 2001, p. 10019. doi: 10.17226/10019.[2] J. Perry, D. Lundie, and G. Golder, “Metacognition in schools: what does the literature suggest about the effectiveness of teaching metacognition in schools?,” Educational Review, vol. 71, no. 4, pp. 483–500, Jul. 2019, doi: 10.1080/00131911.2018.1441127.[3] J. D. Stanton, A. J. Sebesta, and J. Dunlosky, “Fostering Metacognition to Support Student Learning and Performance,” LSE, vol. 20, no. 2, p. fe3, Jun. 2021, doi: 10.1187/cbe.20-12- 0289.[4] N. Zhao, J. G. Wardeska, S. Y. McGuire, and E. Cook, “Metacognition: An Effective Tool to Promote Success in College Science Learning,” Journal of College Science Teaching, vol. 43, no. 4, pp
consume and produce data with concrete experience in authenticresearch settings.AcknowledgmentsThis material is based upon work supported by the National Science Foundation under Grant No.2236241. Any opinions, findings and conclusions, or recommendations expressed in this materialare those of the authors and do not necessarily reflect the views of the National Science Foundation. References[1] S. Purzer, C. Zoltowski, W. Zakharov, and J. Arigye, “Developing the Design Reasoning in Data Life-Cycle Ethical Management Framework,” in 2024 ASEE Annual Conference & Exposition, June 2024.[2] J. Quintana-Cifuentes and S. Purzer, “Semantic Fluency in Design Reasoning,” International Journal of
transfer in biological systems. Students worked in teams to build confidence withexperimental and analytical skills while deepening their understanding of biological systems. Inthis project, students tested the properties of soils that emulated other permeable materialsrelevant to bioengineering.Forming Teams with CATMECATME’s Team-Maker software [19] was utilized to diversify teams of students in BIOE 120.Students completed a survey that requested data about their racial and ethnic identity, genderidentity, college (e.g., Engineering, Liberal Arts and Sciences, Business), major(s), and classyear (Table 2a). They were then asked to rate their experience level with various technical skillsas well as their preferred leadership style and if they
prerequisite concepts, and implementing strategies thatreshape students' perceptions of difficult courses. By addressing the challenges identified in thisstudy, educators can help students navigate the rigors of engineering statics, ultimately reducingfailure rates and fostering a more engaging and effective learning experience. This workunderscores the need for intentional instructional practices that not only improve academicsuccess but also prepare students for the demands of their engineering careers.References[1] S. Rajasekaran, Engineering Mechanics Statics And Dynamics. Vikas Publishing House, 2009.[2] P. S. Steif, “An articulation of the concepts and skills which underlie engineering statics,” in 34th Annual Frontiers in Education
. For example, Scenario 3 on‘general-purpose’ AI is inspired by the EU AI Act’s requirement [28] that proprietors of ‘generalpurpose’ AI systems report details about model architecture and training processes to national AIauthorities. Each scenario, along with the proposed AI regulations that Congress can vote on, aredescribed in Appendix B. To start the game, only members of Evil Inc. are told internal companyinformation that motivates their lobbying efforts. For example: “Evil Inc.’s large language modelis only successful because its model architecture is kept a secret, so Evil Inc. should preventCongress from requiring the disclosure of any model architecture information.” Each round, EvilInc. members decide how to distribute a limited
, emphasizing that entrepreneurial metacognition is rooted in theexternal environment, metacognitive awareness, metacognitive knowledge and experience,metacognitive strategies, and metacognitive monitoring [15]. This model highlighted howentrepreneurs develop a "higher-order" cognitive process in nature to navigate and succeed intheir entrepreneurial pursuits. This study adjusted Haynie et al.’s entrepreneurial metacognitionmodel to build the conceptual model (Figure 1). The model demonstrated how students’entrepreneurial metacognition awareness developed through the metacognitive monitoring andmetacognitive reflection processing (Figure 1).Figure 1Adjusted entrepreneurial mindset metacognition model External Environment Student
improved confidence among students in their informationsearching abilities. Other studies have shown similar results, although Han & Schuurmans-Stekhoven [27] note that graduate students also feel that these benefits are diminished if theylack effective composition and communication skills, especially among those who speakEnglish as a second language.The lasting impact of IL instruction on undergraduate students in various academic domainshas also been demonstrated in the literature, particularly in the North American context [9],[16], [28]. One of the earliest examinations is Hardesty et al.’s [29] three-year study ofDepauw University’s undergraduate population. Walters et al. [20] conducted a five-yearyearly assessment of an IL program at
, Policy, Practice, Springer,Singapore, pp. 189–201, 2019.[2] S. Ariyaratne, K. P. Iyengar, N. Nischal, N. C. Babu, and R. Botchu, “A comparison ofChatGPT-generated articles with human-written articles,” Skeletal Radiology, vol. 52, no. 9, pp.1755–1758, 2023.[3] S. Bansal, “Textstat: Calculate statistical features from text,” [Online]. Available:https://pypi.org/project/textstat/. [Accessed: Jul. 19, 2024].[4] P. Basken, “Class attendance in US universities ‘at record low,’” Times Higher Education,Dec. 6, 2023. [Online]. Available: https://www.timeshighereducation.com/news/class-attendance-us-universities-record-low. [Accessed: Jul. 19, 2024].[5] I. Blagoev, G. Vassileva, and V. Monov, “From Data to Learning: The Scientific Approachto AI-Enhanced
capture photos/images in response to prompts,however, photovoice is a methodology designed to support participants in documenting,communicating, and reflecting on their experiences. Photo elicitation is not a full methodology,but a qualitative method used to yield rich data and circumvent some of the limitations oftraditional interviews.Concept mappingA concept map as a research technique aims to visualize how people connect and relate differentconcepts. Concept maps are hierarchical, and different concept nodes are connected with arrowsthat explicitly define the relationship(s) between the concepts. For example, a concept map aboutphoto synthesis may have ‘the sun’ and ‘plant life’ as two nodes, and the relational arrow fromsun to plant may be
outcomes”, Journal of Cleaner Production, Volume 330, 2022, 129734, ISSN 0959-6526, doi: 10.1016/j.jclepro.2021.129734. 3. R. Pawson, T. Greenhalgh, G. Harvey, K. Walshe. “Realist review--a new method of systematic review designed for complex policy interventions”. J Health Serv Res Policy. 2005 Jul;10 Suppl 1:21-34. doi: 10.1258/1355819054308530 4. S. Sterling, “A commentary on education and sustainable development goals.” J. Educ. Sustain. Dev. 10 (2), 208–213. 2016 doi: 10.1177/0973408216661886 5. M. Rickinson, A. Reid, “Synthesis of research in higher education for sustainable development”, M. Barth, G. Michelsen, M. Rieckmann, I. Thomas (Eds.), Routledge Handbook of Higher Education for Sustainable
development.References[1] V. G. Goulart, L. B. Liboni, and L. O. Cezarino, “Balancing skills in the digital transformation era: The future of jobs and the role of higher education,” Ind. High. Educ., vol. 36, no. 2, pp. 118–127, Apr. 2022, doi: 10.1177/09504222211029796.[2] W. Medina-Jerez, “Science Education Research Trends in Latin America,” Int. J. Sci. Math. Educ., vol. 16, no. 3, pp. 465–485, Feb. 2018, doi: 10.1007/s10763-016-9785-z.[3] G. Marinoni, H. Van’t Land, T. Jensen, and others, “The impact of Covid-19 on higher education around the world,” 2020.[4] S. Giannini, “COVID-19 y educación superior: de los efectos inmediatos al día después,” Rev. Latinoam. Educ. Comp. RELEC, vol. 11, no. 17, pp. 1–57, 2020.[5] M. Akour and M
CommercialApplications,” U.S. Government Accountability Office (GAO), Q&A Report to Congressional Requesters GAO-24-106946, Jun. 2024. Accessed: Jan. 05, 2025. [Online]. Available: https://www.gao.gov/assets/870/869770.pdf.[7] Y. Liu and H. Wang, Who on earth is using generative AI ? Washington, DC: World Bank, 2024.[8] McKinsey & Company, “The state of AI in early 2024: Gen AI adoption spikes and starts to generate value,” QuantumBlack AI by McKinsey, May 30, 2024. https://www.mckinsey.com/capabilities/quantumblack/our-insights/the-state-of-ai#/ (accessed Jan. 05, 2025).[9] S. Vidalis, R. Subramanian, and F. Najafi, “Revolutionizing engineering education: the impact of AI tools on student