Hispanic Higher Education, 20(3), 297-312. 4. Prescott, A., Coupland, M., Angelini, M., & Schuck, S. (2020). Making School Maths Engaging: The Maths Inside Project. Springer. 5. Tobias, S. (1998). Anxiety and mathematics. Harvard Education Review, 50, 63–70. 6. Balfanz, R., & Byrnes, V. (2006). Closing the mathematics achievement gap in high- poverty middle schools. J. of Ed. for Students Placed at Risk, 11(2), 143-159. 7. Rowan‐Kenyon, H. T., Swan, A. K., & Creager, M. F. (2012). Social cognitive factors, support, and engagement: early adolescents’ math interests as precursors to choice of career. The Career Development Quarterly, 60(1), 2-15. 8. Bursal, M., & Paznokas, L. (2006). Mathematics
adjusted because the liftload cells counteract the moment created by the drag force due to how static mechanics work. Figure 4. Statics Diagram for Drag Moment AdjustmentUsing the statics illustrated in Figure 4, the adjustments for the lift force are [3]: 𝐹 , , =𝐹 , , −𝐹 ∗ (Eq. 1) 𝐹 , , =𝐹 , , +𝐹 ∗ (Eq. 2)Physical Models The test bed used is a Hampton H-6910 Wind tunnel with a test section of 23 in x 8 in x 8in. A cylinder of 1.6 in diameter was tested, as shown in Figure 5, to find the lift and drag forcesacting on a 3D-printed body. This was done with a flow velocity of 10.06 m/s, considering laminarflow conditions
without anyexternal disturbances, allowing them to take the test in a restful setting. All the sessions werevideo recorded with the consent of the participants.As each student completed the ping pong ball launcher design task, s/he was video recordedvia zoom. The recording of each participant was then analyzed using the following sequence: a) transcription – verbal protocol was transcribed from the video recording. b) segmentation – dividing the verbal textual data into units that could be coded using a pre-defined coding scheme [21]; c) coding – using the previously established coding scheme, a design step was chosen to describe each student’s “location” in the overall design process [22].Two coders coded each segment of the
dynamics in the construction sector. It is also vital toexplore how team performance and project outcomes are affected by the personalities ofindividuals and the entire team.References[1] M. S. Prewett, A. A. Walvoord, F. R. Stilson, M. E. Rossi, and M. T. Brannick, “The Team Personality-Team Performance Relationship Revisited: The Impact of Criterion Choice, Pattern of Workflow, and Method of Aggregation,” Human Performance, 22(4), 273–296, 2009.[2] E. Salas, E., D. L. Reyes, and A. L. Woods, “The Assessment of Team Performance: Observations and Needs,” Innovative Assessment of Collaboration, 21-36, 2017.[3] J. E. Mathieu, J. R. Hollenbeck, D. V. Knippenberg, and D. R. Ilgen, “A Century of Work Teams in the
Kristine Denman is the Director of the New Mexico Statistical Analysis Center. She has over 20 years of experience in both applied research and program evaluation, including multiple evaluation projects focused on STEM internship experiences. ©American Society for Engineering Education, 2023An Engineering/Computer Science Project with Community Service FocusAbstract:This conference paper informs about a S-STEM (Scholarships in STEM) project awarded to theUniversity of New Mexico (UNM) School of Engineering (SOE). This NSF project is focused onproviding scholarships to students with merit who also demonstrate financial need. Thisparticular NSF project was focused on professional development activities as well as
approach (Social Psychology Series). Boulder, CO: Westview Press, 1996.[6] M. H. Davis, "Measuring individual differences in empathy: Evidence for a multidimensional approach," Journal of Personality and Social Psychology, vol. 44, no. 1, pp. 113-126, 1983.[7] J. C. Oxley, The moral dimensions of empathy: Limits and applications in ethical theory and practice. New York, NY: Palgrave Macmillan, 2011.[8] S. Baron-Cohen, The science of evil: On empathy and the origins of cruelty. New York: Basic Books, 2011.[9] M. A. Clark, M. M. Robertson, and S. Young, "“I feel your pain”: A critical review of organizational research on empathy," Journal of Organizational Behavior, vol. 40, no. 2, pp. 166-192
agricultural production systems," Renewable Agriculture and Food Systems, pp. 285-295, 2008, doi: 10.1017/S174217050700213X.[7] S. L. Wang, R. A. Hoppe, T. Hertz and S. Xu, "USDA-ERS #302: Farm labor, human capital, and agricultural productivity in the United States," 2022.[8] G. L. Baldwin, V. Booth Womack, S. E. LaRose, C. S. Stwalley and R. M. Stwalley III, "Using broad spectrum technological projects to introduce diverse student populations to Biological & Agricultural Engineering (BAE): a work in progress," in 2021 ASEE Annual Conference & Exposition (Long Beach), Washington, DC, 2021, archived @ https://strategy.asee.org/37986.[9] G. L. Baldwin, V. Booth Womack, S. E. LaRose, C. S. Stwalley and R. M
. (2021). Criteria for Accrediting Engineering Programs. ABET. https://www.abet.org/wp-content/uploads/2022/01/2022-23-EAC-Criteria.pdfBland, L., Kusano, S., & Johri, A. (2016). Engineering Competitions as Pathways to Development of Professional Engineering Skills. 2016 ASEE Annual Conference & Exposition Proceedings, 26629. https://doi.org/10.18260/p.26629Burt, B. A., Carpenter, D. D., Finelli, C. J., Harding, T. S., Sutkus, J., Holsapple, M., Bielby, R., & Ra, E. (2011). Outcomes of engaging engineering undergraduates in co-curricular experiences. ASEE Annual Conference and Exposition. https://hdl.handle.net/2027.42/86117Carberry, A. R., Lee, H.-S., & Swan, C. W. (2013). Student
to cope with stress.References[1] K. Levecque, F. Anseel, A. de Beuckelaer, J. van der Heyden, and L. Gisle, "Work organization and mental health problems in PhD students," Research Policy, vol. 46, no. 4, pp. 868– 879, 2017.[2] T. M. Evans, L. Bira, J. B. Gastelum, L. T. Weiss, and N. L. Vanderford, "Evidence for a mental health crisis in graduate education," Nature Biotechnology, vol. 36, no. 3, pp. 282– 284, 2018.[3] M. Schmidt and E. Hansson, “Doctoral students’ well-being: a literature review,” International Journal of Qualitative Studies on Health and Well-being, vol. 13, no. 1, 2018.[4] J. Hyun, B. Quinn, T. Madon, and S. Lustig, "Mental health need, awareness, and use of
N. Beard. "What do we teach when we teach tech ethics?: A syllabi analysis," in Proc. 51st ACM Tech. Symp. Comp. Sci. Educ. Portland, OR, USA, 2020, pp. 289-295.[2] B. C. Stahl, J. Timmermans, and B. D. Mittelstadt, "The ethics of computing: A survey of the computing-oriented literature," ACM Comp. Surv. (CSUR), vol. 48, no. 4, pp. 1- 38, 2016.[3] S. R. Komives, N. Lucas, and T. R. McMahon, Exploring Leadership: For College Students Who Want to Make a Difference, 3rd ed., San Francisco, CA, USA: John Wiley & Sons, 2009.[4] M. J. Quinn, “On teaching computer ethics within a computer science department,” Sci. and Eng. Ethics, vol. 12, pp. 335-343, 2006.[5] R. T. Johnson, D. R. Johnson
noted as one persistent attribute that students exhibit during theseexperiences. For instance, one aspect of Behroozi et al.’s work [7] compared anxiety levels thattheir participants exhibited while conducting mock technical interviews either in a public settingor in a private setting. It was determined that participants who conducted technical interviews ina public setting exhibited higher levels of anxiety than their counterparts who were in a privatesetting. Similarly, Hall and Gosha [23] conducted a study that measured the correlation ofanxiety and preparation in a technical interview that targeted junior and senior CS majors at aSoutheastern Historically Black College/University (HBCU) in the United States. Keyinformation collected during
impact on improving student understanding ofspecific course concepts. However, these results counter that of Leininger-Frézal andSprenger [19], who find the use of a VFT did help to enhance student understanding.Common between ours and Dada, et al. [15]’s results are a high percentage (>75%) ofagreement to the pre-survey statement, and thus it is more difficult to make a meaningfulimprovement on student understanding.Comparatively, the remaining 4 statements showed significant differences between pre- andpost-DST survey results (p < 0.05). Observations from Figure 3 in conjunction with this dataimplies the DST was ineffective in assisting students to develop problem solving skills,enabling teamwork, and improving their ability to
, and R. White, “The internet of things – the future or the end of mechatronics,” Mechatronics, vol. 27, pp. 57 – 74, 2015. [5] P. Eichinger, B. Hofig, and C. Richter, “Education 4.0 for mechatronics – agile and smart,” in 2017 International Conference on Research and Education in Mechatronics (REM), 2017, pp. 1–7. [6] S. Freeman, S. L. Eddy, M. McDonough, M. K. Smith, N. Okoroafor, H. Jordt, and M. P. Wenderoth, “Active learning increases student performance in science, engineering, and mathematics,” Proceedings of the National Academy of Sciences, vol. 111, no. 23, pp. 8410–8415, 2014. [7] J. Gao and J. Hargis, “Promoting teachnology-assisted active learning in computer science eduation,” The Journal of Effective
Concept(s) Conventional + Assigned Readings Learning Working of Example(s) Activity + Practice: Homework Feedback and Low-Stakes Productive + Quizzes Failure Walkthrough of Concept Assigned Videos and Short Readings
.2016.02.002.[4] J. Tuttas and B. Wagner, "Distributed online laboratories," in International Conference on Engineering Education, 2001, pp. 6-10.[5] T. De Jong, S. Sotiriou, and D. Gillet, "Innovations in STEM education: the Go-Lab federation of online labs," Smart Learning Environments, vol. 1, no. 1, pp. 1-16, 2014.[6] M. Hernández-de-Menéndez, A. Vallejo Guevara, and R. Morales-Menendez, "Virtual reality laboratories: a review of experiences," International Journal on Interactive Design and Manufacturing (IJIDeM), vol. 13, no. 3, pp. 947-966, 2019/09/01 2019, doi: 10.1007/s12008-019-00558-7.[7] M. Abdulwahed and Z. K. Nagy, "Applying Kolb's Experiential Learning Cycle for Laboratory Education
' cultural backgrounds and departmental culture might influencestudents’ motivational orientations.References[1] A. Wigfield and J. S. Eccles, “Expectancy-value theory of achievement motivation,” Contemp. Educ. Psychol., vol. 25, no. 1, pp. 68–81, 2000, doi: 10.1006/ceps.1999.1015.[2] J. Guo, P. D. Parker, H. W. Marsh, and A. J. S. Morin, “Achievement, motivation, and educational choices: A longitudinal study of expectancy and value using a multiplicative perspective,” Dev. Psychol., vol. 51, no. 8, pp. 1163–1176, 2015, doi: 10.1037/a0039440.[3] J. Allen and S. Robbins, “Effects of Interest-Major Congruence, Motivation, and Academic Performance on Timely Degree Attainment,” J. Couns. Psychol., vol. 57, no. 1
engagement. The tradeoff is that time is needed for problem design,but these problems could be reused and allow automatic grading and customized feedback.In Fall 2019 when Mastering was tried, the author did a survey in the middle of the semester.Despite their willingness to continue using Mastering in that course and potentially in futurecourses, when the students were asked if they would pay for Mastering, no one said yes, asshown in Figure 11. Table 1 has summarized student opinions regarding the Mastering platform.This was the driving motivation for the author to explore alternative approaches to implementmulti-part problems with parameter randomization in LMSs. S T U D E N T P E R C E P T I O N I N FA L L 2 0 1 9 O N M A S T E R I N
Example “I would use a parallel circuit because if one light 1 light(s) 48 goes off, the other will continue working.” “Maybe we could take this, tape it or drill it on a 2 tape 39 tree or something.” “It didn't work the first time, so we tried a second 3 work 36 time and it didn't really work. It just didn't move.” “So we were reading in the kit that the
PrairieLearn’s collaborative assessments to extract the timestamp ofeach student’s submissions to a given collaborative problem. Each submission was labeled asquick (Q), medium (M), or slow (S) based on its duration and whether it was shorter or longerthan the 25th and 75th percentile. We then applied sequence compacting techniques, sequentialpattern mining, and correlation analysis to identify latent patterns that characterize variousproblem-solving strategies across three database query languages (SQL, MongoDB, Neo4j). Theobjective of this study is to investigate the potential of temporal information - the amount of timespent on each submission attempt – in uncovering the recurrent patterns in groups’ submissionsequences. The next step is to perform
expressed in this material are those of the author(s) and donot necessarily reflect the views of the National Science Foundation.REFERENCES[1] E. O. McGee, “Interrogating Structural Racism in STEM Higher Education,” EducationalResearcher, vol. 49, no. 9, pp. 633–644, Dec. 2020, doi: 10.3102/0013189X20972718.[2] Y. A. Rankin, J. O. Thomas, and S. Erete, “Real Talk: Saturated Sites of Violence in CSEducation,” in Proceedings of the 52nd ACM Technical Symposium on Computer ScienceEducation, Virtual Event USA: ACM, Mar. 2021, pp. 802–808. doi: 10.1145/3408877.3432432.[3] E. W. Huff et al., “Going Through a Process of Whitening: Student Experiences WithinComputer Science Education,” in Proceedings of the 52nd ACM Technical Symposium onComputer
Paul, Oregon State University ©American Society for Engineering Education, 2023 Lab Safety Awareness in Incident and Near-miss Reporting by Students Participating in Engineering Societies: A Case StudyAcademic laboratory safety has gained considerable attention from researchers and researchinstitution administrators since several high-profile incidents in the late 2000’s. Another part ofstudent learning in engineering, though informal, occurs in co-curricular activity such asengineering societies and team competitions where students conduct hands-on activities toachieve certain objectives, usually with minimal (if any) authoritative figures in presence. Thesafety aspect of these co-curricular
Affecting the Future Career Pathway Decisions of Lower-income Computing Students1. IntroductionWithin research on broadening participation in computing, the experience and perspectives ofundergraduate students have been important elements of exploration. As undergraduate studentsare experts of their own experience, conducting research that focuses on understanding theirperspective can help those who organize programmatic efforts to respond to student needs andconcerns. This paper emerges from the context of a specific National Science Foundation (NSF)-funded Scholarships in Science, Technology, Engineering, and Mathematics (S-STEM) program.As with all S-STEM programs, Florida Information Technology Graduation
Feb 12, 2023].[3] R. B. Sepe and N. Short, “Web-based virtual engineering laboratory (VE-LAB) for collaborative experimentation on a hybrid electric vehicle starter/alternator,” IEEE Transactions on Industry Applications, vol. 36, no. 4, pp. 1143-1150, July 2000.[4] H. Hodge, H. S. Hinton, and M. Lightner, “Virtual circuit laboratory,” Journal of Engineering Education, vol. 90, no. 4, pp. 507-511, Oct. 2001.[5] H. Gurocak, “E-Lab: An electronic classroom for real-time distance delivery of a laboratory course,” Journal of Engineering Education, vol. 90, no. 4, pp. 695-705, Oct. 2001.[6] M. Koretsky, C. Kelly, and E. Gummer, “Student perceptions of learning in the laboratory: Comparison of industrially situated virtual
startup and casting safety protocols aspart of her M.S. project.Referencesi R. W. Heckel, W. W. Milligan, C. L Nassaralla, J. Pilling, M. R. Plichta, “Benefits of CapstoneDesign Courses in Materials Education,” Science and Technology of Polymers and AdvancedMaterials, P. N. Prasad, J. E. Mark, S. H. Kandil, Z. H. Kafafi, (eds), Springer, Boston, MA., 1998.https://doi.org/10.1007/978-1-4899-0112-5_75ii M. Schaefer, “Use of Casting Simulation and Rapid Prototyping in an Undergraduate Course inManufacturing Processes,” ASEE Annual Conference & Exposition, 2016.iii K. Molyet, “Providing a Meaningful Lab Experience for a Manufacturing Processes Course,”(,” ASEE IL-IN Section Conference, 2019. https://docs.https://docs.lib.purdue.edu/aseeil
factors were attributed to the nativelanguage being English (yes/no).Results and DiscussionTable 1 Breakdown of averaged Turnitin scores for each submission (S). Turnitin Scores (%) All YES Eng NO Eng YES Biol NO Biol YES Native NO Native S #1 20 ± 19 22 ± 12 15 ± 16† 20 ± 19 23 ± 19 14 ± 12 25 ± 21† S #2 14 ± 14* 13 ± 10** 10 ± 13* 12 ± 10** 19 ± 18† 10 ± 7** 17 ± 16**,†YES/NO refers to their background in: Biol = Biological Sciences, Eng = Engineering. *,**denotes statistically significant differences (t-test) between submissions (*p<0.05, **p<0.01); †between YES and NO categories (†p<0.01
, J., & Merrill, T., & Sood, S., & Greene Ryan, J., & Attaluri, A., & Hirsh, R. A. (2017,June), Clinical Immersion and Team-Based Design: Into a Third Year Paper presented at 2017 ASEEAnnual Conference & Exposition, Columbus, Ohio. 10.18260/1-2--28040[7] Muller-Borer, B. J., & George, S. M. (2018, June), Designing an Interprofessional EducationalUndergraduate Clinical Experience Paper presented at 2018 ASEE Annual Conference & Exposition,Salt Lake City, Utah. 10.18260/1-2—30279[8] Zapanta, C. M., & Edington, H. D., & Empey, P. E., & Whitcomb, D. C., & Rosenbloom, A. J. (2017,June), Board # 18: Clinical Immersion in a Classroom Setting (Work in Progress) Paper presented at 2017ASEE Annual
yearly competitions such as IIDA, AIA,Solar Decathlon, etc. These institutions, and many others sponsor both annual competitionsReferencesPooley, Alison and Wanigarathna, Nadeeshani (2016) Integrating students through amultidisciplinary design project. In: Integrated Design Conference id@50, 29 June - 1 July2016, University of Bath.Gerber, D. J., & Lin, S. H. E. (2014). Designing in complexity: Simulation, integration, andmultidisciplinary design optimization for architecture. Simulation, 90(8), 936-959.Flager, F., & Haymaker, J. (2007, June). A comparison of multidisciplinary design, analysis andoptimization processes in the building construction and aerospace industries. In 24thinternational conference on information technology in
. 4ReferencesAnderson, E.L., Williams, K.L., Ponjuan, L., & Frierson, H. (2018). The 2018 Status Report onEngineering Education: A Snapshot of Diversity in Degrees Conferred in Engineering, Association ofPublic & Land-grant Universities: Washington, D.C.Anzaldúa, G., & Moraga, C. (1981). This bridge called my back. New York: Kitchen Table.Conchas, G. Q., & Acevedo, N. (2020). The Chicana/o/x dream: Hope, resistance, and educationalsuccess. Harvard Education Press.Hurtado, A. (2003). Voicing Chicana feminisms: Young women speak out on sexuality and identity (Vol.1). NYU Press.McAlear, F., Scott, A., Scott, K., & Weiss, S. (2018). “Women and girls of color in computing.” Databrief. Kapor Center, 2018. Available: https://www.wocincomputing.org
Regional Education Board.Brophy, S., Klein, S., Portsmore, M., & Rogers, C. (2008). Advancing engineering education inP‐12 classrooms. Journal of Engineering Education, 97(3), 369-387.Gottfried, M. A., & Plasman, J. S. (2018). Linking the timing of career and technical educationcoursetaking with high school dropout and college-going behavior. American EducationalResearch Journal, 55(2), 325-361.Hmelo-Silver, C. E. (2004). Problem-based learning: What and how do studentslearn?. Educational psychology review, 16, 235-266.Lynch, S. J., Peters-Burton, E., Behrend, T., House, A., Ford, M., Spillane, N., Matray, S., &Means, S. (2017). Understanding inclusive STEM high schools as opportunity structures forunderrepresented students: Critical
. Through real-world engineering applications, Dr. Bairaktarovaˆa C™s experiential learning research spans from engineering to psychology to learning ©American Society for Engineering Education, 2023 Assessment Instruments for Engineering Ethics Education: A Review and Opportunities AbstractAssessment plays an important role in education, and there is no exception in engineering ethicseducation. However, although there have been efforts to evaluate students’ learning inengineering ethics classrooms, relatively limited efforts have been made to utilize valid andreliable assessment instruments to evaluate students’ achievement of learning objectives inengineering ethics