, Laura Hill, Kristen Andrews,John Lens, and others in the Contemplative Practices Learning Community, graduate studentMaddy Pimental and along with all the undergraduate student focus group leaders: SachiSakaniwa, Zoe Schlosser, Maja Paulk, River Bond, and student participants of the StructuralSteel Design course.References:[1] T. Estrada and E. Dalton, "Impact of Student Mindfulness Facets on Engineering Education Outcomes: An Initial Exploration," ASEE Annual Conference & Exposition, Tampa, FL, USA, June 15, 2019.[2] B. Rieken, M. Schar, S. Shapiro, S. Gilmartin, and S. Sheppard, "Exploring the relationship between mindfulness and innovation in engineering students," in Proceedings of the American Society for
/publication/319650562[4] National Research Council, Discipline-Based Education Research: Understanding and Improving Learning in Undergraduate Science and Engineering. 2012. doi: 10.17226/13362.[5] National Research Council, “Report of a Workshop on the Pedagogical Aspects of Computational Thinking,” National Academies Press, Washington, D.C., 2011. doi: 10.17226/13170.[6] O. of the P. S. The White House, “Fact Sheet: President Obama Announces Computer Science For All Initiative,” pp. 1–16, 2016, doi: 10.1111/j.1741-5705.2009.03698.x.[7] A. N. Rinn and J. A. Plucker, “High-Ability College Students and Undergraduate Honors Programs: A Systematic Review,” Journal for the Education of the Gifted, vol. 42, no. 3
differences might seem natural before any formal designtraining occurs. They also inform educators about gaps in expected student performance inparametric tools and suggest that pre-designer education should emphasize multidisciplinaryproblem-solving to avoid narrowing student competency for those interested in designprofessions.ACKNOWLEDGEMENTS This material is based upon work supported by the National Science Foundation underGrant #2033332. Any opinions, findings, and conclusions or recommendations expressed in thismaterial are those of the author(s) and do not necessarily reflect the views of the NationalScience Foundation.The authors would also like to thank ShapeDiver GmbH for their support in providing theresearch team with access to
division division nal Co-construct Construct rs o Self-authorship Pe knowledge knowledge Discover community al Participate s s ion with guidance Pr of e COP Beginner practice Master & and discourse expertise Belonging LID r
indrawing our conclusion. Nevertheless, this work has an added value as a basis for us toconduct more extensive research in the future. Additionally, academics will have a wideropportunity to explore deep learning to produce more novel educational solutions since ourstudy discovered that only a small number of studies had investigated the application of thisAI technology.References[1] M. King, R. Cave, M. Foden, and M. Stent, “Personalised education From curriculum to career with cognitive systems,” 2016.[2] T. J. Sejnowski, The deep learning revolution. Cambridge: The MIT Press, 2018.[3] J. S. Groff, “Personalized learning: The state of the field & future directions,” 2017. [E-book]. Available: https://dam
, and what you think a more positive interaction might have looked like.Participants in this study were LAs who consented to have their responses used as part of thisanalysis. Table 2 details the participants involved in this study. Fifty responses were analyzed.Table 2. Participant information. Private Public Number of LAs 24 26 Discipline(s) Chemistry, Biology, Chemical, Biological, and Chemical and Biological Environmental Engineering Engineering, Mechanical
education often focus on increasing the useof such RBIS strategies in classrooms (e.g., PBL [3]). Such a change in practices and principles portendsfundamental shifts in the role of teachers and students in a classroom [4]. Evidence is clear that RBIS contributeto learning. However, evidence also suggests that students' own theories of learning and knowing may notperceive the shift in roles, practices, and theories of learning that come with that greater learning [5].As researchers, we are interested in students’ perception of educational role(s) and their perception of what makesgood teachers and good teaching1. We see the authentic voice of students as too-often missing from research onthe shift to student-centered teaching. Prior research shows
Education, vol. 14, no. 3, pp. 340–352, 09 2021. [Online]. Available: https: //www.proquest.com/scholarly-journals/s-dude-culture-students-with-minoritized/docview/2348348625/se-2[13] J. Misra, J. H. Lundquist, E. Holmes, S. Agiomavritis et al., “The ivory ceiling of service work,” Academe, vol. 97, no. 1, pp. 22–26, 2011.[14] N. A. Fouad, W.-H. Chang, M. Wan, and R. Singh, “Women’s reasons for leaving the engineering field,” Frontiers in psychology, p. 875, 2017.[15] J. Walther, N. W. Sochacka, and N. N. Kellam, “Quality in interpretive engineering education research: Reflections on an example study,” Journal of engineering education, vol. 102, no. 4, pp. 626–659, 2013.[16] K. J. Cross, S. Farrell, and B. Hughes, Queering STEM
gratefullyacknowledged.References[1] A. R. Bielefeldt, M. Polmear, D. W. Knight, N. Canney, and C. Swan, “Educatingengineers to work ethically with global marginalized communities,” EnvironmentalEngineering Science, vol. 38, no. 5, pp. 320–330, 2021.[2] L. Roldan-Hernandez, A. B. Boehm, and J. R. Mihelcic, “Parachute Environmental Scienceand Engineering,” Environmental Science & Technology, vol. 54, no. 23, pp. 14773–14774,2020.[3] D. Sedlak, “Crossing the imaginary line,” Environmental Science & Technology, vol. 50,no. 18, pp. 9803–9804, Sep. 2016.[4] M. A. Edwards, A. Pruden, S. Roy, and W. J. Rhoads, “Engineers shall hold Paramount thesafety, health and welfare of the public - but not if it threatens our research funding?,” FlintWater Study , 10-Oct-2016
“Computer Science Principlesand Cybersecurity Pathway for Career and Technical Education”.References[1] E. Lally, At home with computers. Routledge, 2020.[2] M. Javaid, A. Haleem, S. Rab, R. P. Singh, and R. Suman, “Smart performance of virtual simulation experiments through Arduino tinkercad circuits,” Sensors International, vol. 2, no. 100121, pp. 1–10, 2021.[3] D. Morley and C. S. Parker, Understanding computers: Today and tomorrow, comprehensive. Cengage Learning, 2014.[4] H.M.D. Toong, Microprocessors. Scientific American, 237(3), pp.146-161, 1977[5] L. D. Wittie, “Microprocessors and microcomputers,” Encyclopedia of Computer Science, vol. January, no. 2003, pp. 1161–1169, 2003.[6] J. H. Davies, MSP430
real, applicable value in a rapidly advancing world. In this landscape, creativity, design, and engineering are making their way to the forefront of educational considerations, as tools such as 3D printers, robotics, and 3D modeling web-based applications become accessible to more people. Proponents of makerspaces for education highlight the benefit of engaging learners in creative, higher-order problem solving through hands-on design, construction, and iteration. [2, p. 40]In 2005 Make: magazine began publication and started sponsoring “maker faires” around theU.S. and in other countries the following year [3]. In fact, Make:’s maker faires became sopopular they caught the attention of the
regularly throughout the semester.References[1] M. K. Hartwig and E. D. Malain, “Do students space their course study? Those who do earn higher grades.,” Learn Instr, vol. 77, p. 101538, Feb. 2022, doi: 10.1016/J.LEARNINSTRUC.2021.101538.[2] A. Latimier, H. Peyre, and F. Ramus, “A Meta-Analytic Review of the Benefit of Spacing out Retrieval Practice Episodes on Retention,” Educ Psychol Rev, vol. 33, no. 3, pp. 959– 987, Sep. 2021, doi: 10.1007/S10648-020-09572-8/FIGURES/4.[3] C. R. Bego, P. A. Ralston, K. B. Lyle, and J. Immekus, “Introducing Desirable Difficulty in Engineering Mathematics with Spaced Retrieval Practice.” Jul. 26, 2021.[4] R. F. Hopkins, K. B. Lyle, J. L. Hieb, and P. A. S. Ralston, “Spaced
). Data Analytics in Educational Management System.International Journal of Computer Applications, 975, 8887.[2] Nghe, N. T., Janecek, P., & Haddawy, P. (2007, October). A comparative analysis oftechniques for predicting academic performance. In 2007 37th annual frontiers in educationconference-global engineering: knowledge without borders, opportunities without passports (pp.T2G-7). IEEE.[3] Hamsa, H., Indiradevi, S., & Kizhakkethottam, J. J. (2016). Student academic performanceprediction model using decision tree and fuzzy genetic algorithm. Procedia Technology, 25,326-332.[4] Lepenioti, K., Bousdekis, A., Apostolou, D., & Mentzas, G. (2020). Prescriptive analytics:Literature review and research challenges. International Journal of
Chemical and Biomolecular Engineering department as well as the Envi- ronmental Engineering and Earth Sciences department. Prior ©American Society for Engineering Education, 2023 WIP: Leveraging Elements of the Researcher Development Framework Embedded in Entrepreneurial Attributes to Improve Graduate Student Professional Development Jennifer S. Brown1, Emma Buell1, Karen High1, and Stephanie Cutler2 Clemson University1, The Pennsylvania State University2Introduction and Motivation Traditionally, faculty members in STEM fields encounter silo-ed approaches toprofessional development, and this trend extends to their graduate students (future
the airflow around a smallwind turbine with a diameter of 1.8 meters and revealed that the maximum power coefficient andtorque coefficient are observed at a wind speed of around 10 m/s and an optimum angle of attackof 5 degrees. In addition, Wang et al. (2019) used pressure-based anemometry to measure theairflow around a small wind turbine with a diameter of 1.2 meters. The study showed that thewake's velocity deficit and turbulence intensity increase with the increase in downstream distance,and the maximum velocity deficit and turbulence intensity were observed at a distance of 3-5D(where D is the rotor diameter) downstream. Over the past year, UVU has hosted a multi-faceted research project which aims atdeveloping an autonomous
, Abdulkarim S. Ahmed3,5, Fatai O. Anafi1,5,Adrian O. Eberemu4,5, Ayodeji N. Oyedeji1,5,6, Kazeem A. Salami1,6, Akinlolu Akande7, David Dodoo-Arhin8 1 Department of Mechanical Engineering, Ahmadu Bello University, Zaria, Nigeria 2 Department of Educational Foundations and Curriculum, Ahmadu Bello University, Zaria, Nigeria 3 Department of Chemical Engineering, Ahmadu Bello University, Zaria, Nigeria 4 Department of Civil Engineering, Ahmadu Bello University, Zaria, Nigeria 5 Africa Centre of Excellence on New Pedagogies in Engineering Education, Ahmadu Bello University, Zaria, Nigeria 6
Brimacombe Memorial Lecture Award in 2010, and She and her co-authors also received the AIST Josef S. Kapitan Award in 2005 and 2016, the AIST Computer Applications Best Paper award in 2006. She was awarded 2017 Outstanding Faculty in Engagement by Purdue University Northwest and Gerald I. Lamkin Fellow for Innovation & Service by the Society of Innovators. Dr. Zhou has been a Fellow of the American Society of Mechanical Engineers since 2003. She has been very active in profes- sional societies. She has served in various boards and committees such as the AIST Foundation Board of Trustees.Tyamo Okosun, Purdue University, NorthwestArmin Silaen ©American Society for Engineering Education, 2023
ReviewA brief review of literature on the incorporation of curricula related to DEI and the assessmentmethods utilized was conducted. These treatments ranged from separate courses related to DEI[3], activities embedded into first-year courses [4,5,6], design courses and design experiences[3,6,7], and embedded activities across multiple courses within the curricula [6,7]. The methodsutilized to assess the impact of DEI curricula were survey instruments using a Likert scale. Theseinstruments varied in breadth and degree of validation. The short form of the Miville-GuzmanUniversality Diversity Scale (M-GUDS-S) [8] was considered to be too general and not directlyapplicable to the engineering profession. Even the short form has 42 items in the survey
- ciation for Uncrewed Vehicle Systems International (AUVSI) Florida Peninsula Chapter, a member of the National Business Aviation Association (NBAA)’s Emerging Technologies committee, and a reviewer for ERAU’s Faculty Innovative Research in Science and Technology program.Emily Faulconer, University of FloridaDr. Kelly A George, Embry-Riddle Aeronautical University, Worldwide Kelly Whealan George is an Associate Professor with the College of Aviation at Embry-Riddle Aeronauti- cal University – Worldwide. She is the Graduate Curricular Chair for the Department of Graduate Studies. Her research interests include online education, aviation economics, economic impact studies and under- graduate research. Dr. Whealan George
Support Students’ Diverse Pathways. Washington, DC: The National Academies Press. https://doi.org/10.17226/21739., 2016.[6] S.-A. A. Allen-Ramdial and A. G. Campbell, “Reimagining the pipeline: Advancing STEM diversity, persistence, and success,” BioScience, vol. 64, no. 7, pp. 612–618, 2014.[7] G. N. Arellano, O. Jaime-Acuña, O. A. Graeve, and L. D. Madsen, “Latino engineering faculty in the United States,” MRS Bulletin, vol. 43, no. 2, pp. 131–147, 2018, doi: 10.1557/mrs.2018.23.[8] National Center for Science and Engineering Statistics, “National Survey of College Graduates: 2019,” Alexandria, VA: National Science Foundation., 2021.[9] University of New Mexico School of Engineering, “Enrollment and Graduation Data,” Sep. 2022
purpose.Acknowledgment: “This material is based upon work supported by the National ScienceFoundation under Grant EEC-BPE 2135080” Disclaimer: Any opinions, findings, andconclusions or recommendations expressed in this material are those of the author(s) and do notnecessarily reflect the views of the National Science Foundation.”References[1] National Science Board, Science and Engineering Indicators 2020. Arlington: National SciBoard. Available: https://www.nsf.gov/nsb/news/news_summ.jsp?cntn_id=299268&org=NSB.[2] E.L Kryst, S Kotok and A. Hagedorn, Pursuing higher education in rural Pennsylvaniaschools: Shaping the college path. The Rural Educator, pp. 1 – 11, Winter 2018.[3] G. Saw, C. N. Chang, and H. Y. Chan, Cross-sectional and longitudinal
(Bahia), Brazil” in the Proceedings of the 2019 ASEE Annual Conference, Paper ID 26202,Tampa, June, 2019.[10] Building Better Bridges into STEM: A Synthesis of 25 Years of Literature on STEMSummer Bridge Programs. Michael Ashley,† Katelyn M. Cooper,† Jacqueline M. Cala, and SaraE. Brownell*CBE Life Sci Educ December 1, 2017 16:es3. DOI:10.1187/cbe.17-05-0085[11] Merriweather, S. Lamm, H. Walton, S. Butler-Purry, K. Rausch Jr., J. Harris, K . TAMUSLSAMP Project: 25 Years of Success - Finding and Implementing Best Practices for URMSTEM StudentsAmerican Society for Engineering Education, 2017 Paper ID #18491[12] Pando, M. Suarez, L. Rodriguez-Marek, A. Loree Dika, S. Wartman, J. Asimaki, D. Cox, B.A Bridge To The Doctoral Program Strategy For
. It falls into the directive category because she is using rhetorical questioning toremind the students of a different homework problem and the procedure that they used there.This pattern held across morning and afternoon sections. That is, while there was a small shift inwhich was higher between the morning and afternoon, narrow eliciting and directive advancingwere still significantly higher than any of the other categories.LA1’s move distribution 20% Percent coded of all 15% utterances 10% 5% 0
tosynthesize knowledge across multiple domains, modes of inquiry, historical periods, andperspectives, as well as the ability to identify linkages between existing knowledge and newinformation. Individuals who engage in integrative thinking are able to transfer knowledgewithin and beyond their current contexts. We collected two things to assess the above objectivesbroadly for the University: 1. Student scores on the element(s) of the assignment aligned with integrative thinking (scored using the rubric developed in collaboration with faculty teaching integrative thinking courses provided in Appendix A). 2. Students’ perceptions of their own integrative thinking skills collected via a survey administered by OPA later in the
/aimag.v40i4.5289[2] S. Anwar, N. A. Bascou, M. Menekse, & A. Kardgar, (2019). “A Systematic Review of Studies on Educational Robotics”. Journal of Pre-College Engineering Education Research (J-PEER), 9(2), Article 2. https://doi.org/10.7771/2157-9288.1223[3] National Science and Technology Council Committee on Technology. 2016. “Preparing for the future of Artificial Intelligence”. Technical Report. Office of Science and Technology Policy.[4] J. J. Lu and L. A. Harris. 2018. “Artificial Intelligence (AI) and Education”. Technical Report. Congressional Research Service. https://fas.org/sgp/crs/misc/IF10937.pdf[5] T. Narahara and Y. Kobayashi. 2018. “Personalizing homemade bots with plug & play AI for
://scholarworks.iu.edu/journals/index.php/josotl/article/view/3264.[3] J. Schinske and K. Tanner, “Teaching More by Grading Less (or Differently),” CBE-Life Sci. Educ., vol. 13, no. 2, pp. 159–166, Jun. 2014, doi: 10.1187/cbe.CBE-14-03-0054.[4] S. Toledo and J. M. Dubas, “A Learner-Centered Grading Method Focused on Reaching Proficiency with Course Learning Outcomes,” J. Chem. Educ., vol. 94, no. 8, pp. 1043– 1050, Jun. 2017, doi: 10.1021/acs.jchemed.6b00651.[5] S. B. Boesdorfer, E. Baldwin, and K. A. Lieberum, “Emphasizing Learning: Using Standards-Based Grading in a Large Nonmajors’ General Chemistry Survey Course,” J. Chem. Educ., vol. 95, no. 8, pp. 1291–1300, Jul. 2018, doi: 10.1021/acs.jchemed
253 600Students were asked to self-report their GPA. GPA was based on a scale of 4, with an “A” being a4.00, a “B” being a 3.00, a “C” being a 2.00, a “D” being a 1.00, and an “S” being a 0.00. Someclasses also used a “+” or “–” system. A “+” adds 0.33 to the base grade, while a “-” subtracts0.33. For example, a “B+” would quantitatively be a 3.33 (3.00 + 0.33), while a “B-” would be a2.77 (3.00 - 0.33).Data was gathered on students’ expected majors. Out of a total of 600 students, 311 (51.8%) weremechanical and/or aerospace engineering students, 114 (19.0%) were civil and/or environmentalengineering students, 102 (17.0%) were biomedical engineering students and 73 (12.2%) studentshad other majors. This data can be seen in Figure 2