Engineering Students Ready for Work?” In The Engineering-Business Nexus: Symbiosis, Tension and Co-Evolution, edited by S. H. Christensen, B. Delahousse, C. Didier, M. Meganck, and M. Murphy, Philosophy of Engineering and Technology, Vol.32, 499–520. Cham: Springer International Publishing. https://doi.org/10.1007/978-3-319-99636-3_22[4] Shah, R., & A.L. Gillen (03 Sep 2023). “A systematic literature review of university-industry partnerships in engineering education”, European Journal of Engineering Education, https://doi.org/10.1080/03043797.2023.2253741[5] Bae, H., Polmear, M., & D. R. Simmons (2022). “Bridging the gap between industry expectations and academic preparation: Civil engineering students’ employability
academic environments, between minoritized and non-minoritized students [3,4].Minoritized students (MS), as defined in the work, identify as having African American orLatinx racial / ethnic backgrounds. Pervasive research continues to reveal that MS students aremore likely than their counterparts to attrit from STEM majors [5].Faculty play an important role in cultivating an inclusive academic culture both inside andoutside of the classroom [6]. To strengthen inclusive environments in STEM, faculty must beafforded the opportunity to participate in professional development that: a) contextualizes theexperiences of MS in STEM, b) provides them data (both qualitative and quantitative) aboutdegree completion disparities, c) shares resources, and
correct responses for (A) all questions combined, (B) individual multiple-choice questions, and (C) topics covered by the questions (Resource: 1-7, Tool: 8-11, Reading: 12) for each BME class. All results in A are statistically significant. For B and C, the solid lines indicate statistical significance
Involvement in Multidisciplinary Capstone Design Courses. International Journal of Engineering Education, 30(1), 6–13.Hauhart, R. C., & Grahe, J. E. (2015). Designing and teaching undergraduate capstone courses. Jossey-Bass.Jacoby, B., & Others, A. (1996). Service-Learning in Higher Education: Concepts and Practices. The Jossey-Bass Higher and Adult Education Series. Jossey-Bass Publishers, 350 Sansome St.Kittur, J. (2023). Conducting Quantitative Research Study: A Step-by-Step Process. Journal of Engineering Education Transformations, 36(4), 100-112.Kolb, D. A. (2015). Experiential learning: Experience as the source of learning and development (Second edition). Pearson Education, Inc.Lee, E
financial needs at community colleges,the University of South Florida, and other institutions, contributing to the development of aproficient workforce in the STEM disciplines. In accordance with this overarching goal, thispaper examines the practical application of the project. It explores how community collegetransfers utilize the up to $10,000 S-STEM scholarship toward overcoming financial challengesthey believe would otherwise stunt their progress toward an engineering bachelor’s degree.2. Research QuestionsThe research aims to address the following two questions:a. How do S-STEM scholarships allow low-income community college transfer engineering students to prepare for success at a four-year university?b. How do S-STEM scholarships
. (2016). Virtual and remote labs in education: A bibliometric analysis. Computers & Education, 98, 14–38. https://doi.org/10.1016/j.compedu.2016.03.010Ismael, D. (2023, June). Enhancing Online Hands-On Learning in Engineering Education: Student Perceptions and Recommendations. 2023 ASEE Annual Conference & Exposition, Baltimore , Maryland.Johnson, J. E., & Barr, N. B. (2021). Moving hands-on mechanical engineering experiences online: Course redesigns and student perspectives. Online Learning Journal, 25(1), 209–219. https://doi.org/10.24059/olj.v25i1.2465Kolil, V. K., & Achuthan, K. (2023). Longitudinal study of teacher acceptance of mobile virtual labs. Education and Information
characteristics of the space” group than contained over half oftheir “clearly relevant” information and then divided remaining “non-physical” information into“Budget,” “Maintenance,” “Room functions,” and “Purpose of the space” groups.Figure 1. Participant 9 categorization scheme4.2.2 Primary dimension sorting B: Two overarching groupsTwo participants stopped at forming two information groups. The two groups formed by each ofthese participants were not oppositional, as in the example of Participant 9. However,participants still similarly tried to minimize between-group overlap as much as could reasonablybe achieved given the complexity of provided information, which is a characteristic of primarydimension sorting approaches. Thus, we categorized these
of raw corn toethanol by yeast transformants containing a modified rhizopus glucoamylase gene. .7. Jayus, Nurhayati, Mayzuhroh A, Arindhani S, Caroenchai C. Studies on bioethanol production ofcommercial baker's and alcohol yeast under aerated culture using sugarcane molasses as the media.Agriculture and Agricultural Science Procedia. 2016;9:493. doi: 10.1016/j.aaspro.2016.02.168.8. Gunay B, Azbar N, Keskin T. The effect of corn syrup and whey on the conversion process of CO toethanol using clostridium ljungdahlii. Chemosphere. 2020;261. doi: 10.1016/j.chemosphere.2020.127734.9. Pieragostini C, Aguirre P, Mussati MC. Life cycle assessment of corn-based ethanol production inargentina. Science of The Total Environment. 2013;472:212. doi
].[19] E. Karincic (Dollarhyde), "CML Labs," GitHub, Feb 7, 2024. [Online]. Available:https://github.com/Dollarhyde/cml-labs. [Accessed: Feb. 7, 2024].[20] Y. Rekhter, B. Moskowitz, D. Karrenberg, G. J. de Groot, and E. Lear, "Address Allocationfor Private Internets," RFC 1918, February 1996. [Online]. Available:https://datatracker.ietf.org/doc/html/rfc1918. [Accessed: Jan. 25, 2024].[21] Cisco DevNet, "Adding Additional VM Images," in Cisco Modeling Labs v2.6Documentation, [Online]. Available: https://developer.cisco.com/docs/modeling-labs/#!vm-images-for-cml-labs/adding-additional-vm-images. [Accessed: Jan. 25, 2024].Appendix A: Reference Platforms in the labThese following reference platforms are represented as nodes within the lab [21]: 1
valuable professional development for the mentors involved.Throughout the process, mentors gained enhanced knowledge and a foundational understandingof various aspects of financial literacy and their implications for students, as well as for their futurecareers as computer science engineers.IV.2 Benefits: a. The development of the Financial Literacy Informational Program served as a professional development for the mentors themselves. In the process, the mentors gained increased knowledge and a basic understanding about different but general aspects of financial literacy as it impacts them as students and eventually as career-computer science engineers. b. The mentors were planning a live webinar for the State
: http://arxiv.org/abs/2303.08774.2. J. G. Meyer et al., "ChatGPT and large language models in academia: opportunities and challenges," BioData Mining, vol. 16, no. 1, p. 20, 2023. [Online]. Available: https://doi.org/10.1186/s13040-023-00339-9.3. B. A. Huberman and S. Mukherjee, "Hallucinations and Emergence in Large Language Models," SSRN, Sep. 18, 2023. [Online]. Available: https://doi.org/10.2139/ssrn.4676180.4. M. P. Georgeff and A. L. Lansky, "Procedural knowledge," Proceedings of the IEEE, vol. 74, no. 10, pp. 1383-1398, Oct. 1986. [Online]. Available: https://doi.org/10.1109/PROC.1986.13639.5. K. Bohle Carbonell et al., "How experts deal with novel situations: A review of adaptive expertise," Educational Research Review, vol
cybersecurity.Mr. Colby Lee Sawyer, East Carolina University Current Computer Science BS Student at East Carolina Unversity ©American Society for Engineering Education, 2024LoRaWAN Solution for Automated Water Drainage of Agricultural FieldsCris Exum, Tyneasha Hazard, Tyler Williams, Jesus Zapata, Khaneil Pettiford, ColbySawyer, Ciprian PopoviciuAbstract: Eastern North Carolina farmlands are often below the standing water level, facing a uniquechallenge that requires constant drainage to avoid flooding. Irrigation canals collect water frommultiple farms, and they must be emptied regularly to maintain crop viability and to protect propertylike equipment and structures. Maintaining a low water level in these canals is a
Relating Sociocultural Identities to What Students Perceive asValuable to their Professional and Learning Efficacy When Engaging in Virtual Engineering LabsAbstractVirtual, online, and digital learning tools can be used to provide equity in access to STEMknowledge. These tools also serve as the building blocks for personalized learning platforms. Theassessment instrument, Student Perceived Value of an Engineering Laboratory (SPVEL) wasdeveloped to ascertain the impact and efficacy of virtual and in-person engineering laboratories in21st-century undergraduate curriculum. SPVEL addresses an emerging need for assessingengineering labs that take place in a myriad of environments in higher education, i.e., in-person,virtual, and
. 22, 2021.[12] C. Winberg et al., “Developing employability in engineering education: A systematicreview of the literature,” European Journal of Engineering Education, vol. 45, no. 2, pp. 165–180, Mar. 2020, doi: 10.1080/03043797.2018.1534086.[13] Z. S. Byrne, J. W. Weston, and K. Cave, “Development of a scale for measuring students’attitudes towards learning professional (i.e., soft) skills,” Research in Science Education, vol. 50,no. 4, pp. 1417–1433, Aug. 2020, doi: 10.1007/s11165-018-9738-3.[14] B. K. Jesiek, Y. Shen, and Y. Haller, “Cross-cultural competence: A comparativeassessment of engineering students,” International Journal of Engineering Education, vol. 28,no. 1, pp. 144-155, Jan. 2012.[15] D. H. Cropley, “Promoting creativity and
Paper ID #43073An Online Interdisciplinary Professional Master’s Program in TranslationalData AnalyticsDr. Emily Nutwell, The Ohio State University Dr. Emily Nutwell is currently serving as the Program Director of the Masters in Translational Data Analytics at the Ohio State University. This applied program, designed for working professionals, focuses on the foundation of data analysis, computing, machine learning, data visualization, and information design. Prior to joining Ohio State, Dr. Nutwell worked at Honda R&D Americas for close to twenty years as a vehicle crash analysts specializing in computational techniques
. Cambridge, UK: Cambridge University Press, 1991.[5] C. Moos, L. Dougher, L. Bassett, M. Young, and D. D. Burkey, “Game-Based Ethical Instruction in Undergraduate Engineering,” NEAG Journal, no. 1, pp. 20–37, Mar. 2023, doi: 10.59198/8259gnir7.[6] J. L. Hess and G. Fore, “A Systematic Literature Review of US Engineering Ethics Interventions,” Science and Engineering Ethics, Apr. 2017, doi: 10.1007/s11948-017-9910-6.[7] Q. Zhu, C. B. Zoltowski, M. K. Feister, P. M. Buzzanell, W. C. Oakes, and A. D. Mead, “The Development of an Instrument for Assessing Individual Ethical Decisionmaking in Project-based Design Teams: Integrating Quantitative and Qualitative Methods.” Presented at ASEE
. Gent, B. Johnston, and P. Prosser, “Thinking on Your Feet in Undergraduate Computer Science: a constructivist approach to developing and assessing critical thinking,” Teach. High. Educ., vol. 4, no. 4, pp. 511–522, Oct. 1999, doi: 10.1080/1356251990040407.[9] D. Kang et al., “Providing an Oral Examination as an Authentic Assessment in a Large Section, Undergraduate Diversity Class,” Int. J. Scholarsh. Teach. Learn., vol. 13, no. 2, 2019, Accessed: Jan. 05, 2024. [Online]. Available: https://eric.ed.gov/?id=EJ1218283[10] Boedigheimer, M. Ghrist, Peterson, and Kallemyn, “Individual Oral Exams in Mathematics Courses: 10 Years of Experience at the Air Force Academy,” PRIMUS, vol. 25, Feb. 2015, doi: 10.1080
] T. Roberts et al., “Students’ perceptions of STEM learning after participating in a summer informal learning experience,” Int. J. STEM Educ., vol. 5, no. 1, p. 35, Sep. 2018, doi: 10.1186/s40594-018-0133-4.[5] T. J. Kennedy and M. R. L. Odell, “Engaging Students in STEM Education,” Sci. Educ. Int., vol. 25, no. 3, pp. 246–258, 2014.[6] A. Burrows, M. Lockwood, M. Borowczak, E. Janak, and B. Barber, “Integrated STEM: Focus on Informal Education and Community Collaboration through Engineering,” Educ. Sci., vol. 8, no. 1, Art. no. 1, Mar. 2018, doi: 10.3390/educsci8010004.[7] J. Miller, S. Raghavachary, and A. Goodney, “Benefits of Exposing K-12 Students to Computer Science through Summer Camp Programs,” in 2018 IEEE
issupported by the National Science Foundation Innovations in Graduate Education Program undergrant 1954946.References[1] A. B. Badiru, C. F. Rusnock, and V. V. Valencia, Project Management for Research: A Guide for Gradaute Students. CRC Press, Taylor & Francis Group, 2018.[2] D. K. Sherman, L. Ortosky, S. Leong, C. Kello, and M. Hegarty, “The Changing Landscape of Doctoral Education in Science, Technology, Engineering, and Mathematics: PhD Students, Faculty Advisors, and Preferences for Varied Career Options,” Front. Psychol., vol. 12, p. 711615, Dec. 2021, doi: 10.3389/fpsyg.2021.711615.[3] D. Denecke, K. Feaster, and K. Stone, Professional Development: Shaping Effective Programs for STEM Graduate Students. Washington, DC
movement in education,” Curr. Issues Comp. Educ., vol. 25, no. 2, 2023.[4] J. Peloso, “Environmental justice education: Empowering students to become environmental citizens,” Penn GSE Perspect. Urban Educ., vol. 5, no. 1, pp. 1–14, 2007.[5] L. Pulido and J. De Lara, “Reimagining ‘justice’in environmental justice: Radical ecologies, decolonial thought, and the Black Radical Tradition,” Environ. Plan. E Nat. Space, vol. 1, no. 1–2, pp. 76–98, 2018.[6] M. L. Miles, A. Schindel, K. S. Haq, and T. Aziz, “Critical examination of environmental justice education: a systemic review.,” Rev., n.d..[7] R. D. Bullard, Dumping in Dixie: Race, class, and environmental quality. Routledge, 2018.[8] D. Schlosberg and L. B. Collins, “From
Education, 2024 Work in Progress: Education, Experience, and Certification Through Micro-Credential Program in Radio Frequency Engineering for Engineering Technology StudentsIntroductionRadio Frequency (RF) Engineering is a field in electrical engineering that studies the propertiesand applications of signals in various frequency ranges from tens of hertz (Hz) to a few hundredgigahertz (1 GHz is 109 Hz). The main subjects in RF engineering include topics such asantennas, transmission lines, signal propagation, and components used in RF systems.The demand for RF engineers has been increasing recently due to the proliferation of wirelessdevices and applications in both commercial and defense settings. There is
scopingefforts may take multiple iterations, but it’s worth the time investment since the scope of theproject drives the effort and impacts the success rate of all projects.Recruiting the StudentsFor the BPI EXL program, students are informed the semester prior about the program and areencouraged to apply. Students are selected by the course instructor following their applicationsubmission and must meet the following three requirements: 1 – Students must have taken atechnical course (Advanced SQL, Data Mining, Application Programming in JAVA or Python, DataWarehousing, or Data Analytics); 2 – Students must have a recommendation from that course’sinstructor; and 3 – Students must have received a B or better in the prerequisite course.For the CySec EXL
members from the ECE department. This expansion aims to increase the number ofparticipants as well as to understand faculty’s perspectives, ultimately contributing to thedevelopment of comprehensive guidelines for mentoring meetings. These guidelines will beparticularly beneficial for new faculty members who are leading these sessions for the first time,enhancing the overall effectiveness of the mentoring process.References[1] M. S. Jaradat and M. B. Mustafa, “Academic advising and maintaining major: Is there a relation?” Social Sciences, vol. 6, no. 4, p. 151, 2017.[2] A. M. Lucietto, E. Dell, E. M. Cooney, L. A. Russell, and E. Schott, “Engineering technology undergraduate students: A survey of demographics and mentoring,” 2019.[3] J. K
. 2005, doi: 10.1002/j.2168-9830.2005.tb00832.x. [8] J. A. Lyon and A. J. Magana, “Computational thinking in higher education: A review of the literature,” Computer Applications in Engineering Education, vol. 28, no. 5, pp. 1174– 1189, Sep. 2020, doi: 10.1002/cae.22295. [9] T. Doleck, P. Bazelais, D. J. Lemay, A. Saxena, and R. B. Basnet, “Algorithmic thinking, cooperativity, creativity, critical thinking, and problem solving: exploring the relationship between computational thinking skills and academic performance,” Journal of Computers in Education, vol. 4, no. 4, pp. 355–369, Dec. 2017, doi: 10.1007/s40692-017-0090-9. [10] J. del Olmo-Muñoz, R. Cózar-Gutiérrez, and J. A. González-Calero, “Computational
were performed as separate steps. Claude-2 is agenerative text model developed by Anthropic. We used Claude-2 because it is a comparativelyhigh-performing model [23]. It is an example of an autoregressive generative text model thatgenerates text in response to input text. This specific model is also an example of a constitutionalmodel that is designed to follow the 3H principles of harmless, honest, and helpful [24].For each task we instructed Claude-2 to perform, we needed to draft a clear prompt. For thequestion generation step, we varied the prompt along multiple dimensions. Starting with thedefinition of mental models as the internal representations people use to (a) describe, (b) explain,and (c) predict the (i) state, (ii) form, (iii
.[11] P. J. Wickramaratne et al., "Social connectedness as a determinant of mental health: A scoping review," PLoS ONE, vol. 17, no. 10, p. e0275004, 2022.[12] D. A. Jorgenson, L. C. Farrell, J. L. Fudge, and A. Pritchard, "College connectedness: The student perspective," Journal of the Scholarship of Teaching Learning, vol. 18, no. 1, pp. 75-95, 2018.[13] M. Suhlmann, K. Sassenberg, B. Nagengast, and U. Trautwein, "Belonging mediates effects of student-university fit on well-being, motivation, and dropout intention," Social Psychology, 2018.[14] L. R. M. Hausmann, F. Ye, J. W. Schofield, and R. L. Woods, "Sense of belonging and persistence in White and African American first-year students," Research
education,” Cham, Switzerland: Springer, 2019.[11] B. Hughes, et al. “Do I think I’m an engineer? Understanding the impact of engineeringidentity on retention,” 2019 ASEE Annual Conference & Exposition, Tampa, Florida, 2016.10.18260/1-2--32674.[12] A. Godwin, “Development of a measure of engineering identity,” 2016 ASEE AnnualConference & Exposition, New Orleans, Louisiana, 2016. 10.18260/p.26122.[13] J.C. Major, A. Kirn, “Engineering identity and project-based learning: How does activelearning develop student identity?” 2017 ASEE Annual Conference & Exposition, Columbus,Ohio, 2017. 10.18260/1-2--28255.[14] O. Pierrakos, T. K. Beam, J. Constantz, A. Johri and R. Anderson, "On the development of aprofessional identity: engineering
Paper ID #41098Race to R1: An Analysis of Historically Black Colleges or Universities (HBCUs)Potential to Reach Research 1 Carnegie Classification® (R1) StatusDr. Trina L. Fletcher, Florida International University Dr. Trina Fletcher is an Assistant Professor of Engineering and Computing Education at Florida International University and the founder of m3i Journey, a start-up focused on research-based, personalized, holistic, innovative, relevant, and engaging (PHIRE) financial literacy education. She serves as the Director of the READi Lab (readilab.com) where her research portfolio consists of equity, access, and inclusion
most complex. When we learn arithmetic inschool it is the last of the arithmetic operations taught after first learning addition, subtraction,and multiplication. This is the case, again, since division is the most complex of the fouroperations to learn, and similarly, from a digital implementation standpoint, division is the mostcomplex. In undergraduate digital system design courses, we typically teach addition, subtraction,and maybe multiplication, but division is treated as a more complex algorithm that is rarelytouched upon. We believe this is the case because of the complexity of division and its generallack of use in most algorithms. From our exploration of where division is used, it appears in theDiffie-Helmann algorithm and pseudo
change. Since we currently have a small sample size,we may need to examine a larger sample before drawing broad conclusions.AcknowledgementsThe authors wish to acknowledge the American Association for Engineering Education (ASEE)Archival Publication Authors Workshop for Engineering Educators (APA-ENG) program, whichis based on Engineering Unleashed faculty development and supported by the Kern FamilyFoundation.References[1] J. Lee, H. J. Jeong, and S. Kim, “Stress, Anxiety, and Depression Among Undergraduate Students during the COVID-19 Pandemic and their Use of Mental Health Services,” Innov High Educ, vol. 46, no. 5, pp. 519–538, 2021, doi: 10.1007/s10755-021-09552-y.[2] K. M. Soria and B. Horgos, “Factors Associated With College