Lesbians and Gay Men,” Journal of Counseling and Development : JCD, vol. 68, no. 1, p. 16, Sep. 1989.[27] F. Ibrahim, H. Ohnishi, and D. S. Sandhu, “Asian American Identity Development: A Culture Specific Model for South Asian Americans,” Journal of Multicultural Counseling and Development, vol. 25, no. 1, pp. 34–50, Jan. 1997.[28] J. J. Fry, “Asian American Transracial Adoptee Identity Development in College,” Journal of Student Affairs, vol. 28, pp. 61–68, 2019.[29] E. R. Hamilton, D. R. Samek, M. Keyes, M. K. McGue, and W. G. Iacono, “Identity Development in a Transracial Environment: Racial/Ethnic Minority Adoptees in Minnesota,” Adopt Q, vol. 18, no. 3, pp. 217–233, 2015.[30] J. Hoffman and E. Vallejo Pena, “Too Korean
. of Maryland, June 22-26, 2020[18] P. J. Teller, and A. Q. Gates 2001. “Using the Affinity Research Group Model to Involve Undergraduate Students in Computer Science Research”. Journal of Engineering Education, vol. 90, pp. 549–555, 2001[19] Engineering PEARLS Web Page: https://www.uprm.edu/engineering/pearls/
, E. Peters, R. E. Petty, D. G. Rand, S. D. Reicher, S. Schnall, A. Shariff, L. J. Skitka, S. S. Smith, C. R. Sunstein, N. Tabri, J. A. Tucker, S. v. d. Linden, P. van Lange, K. A. Weeden, M. J. A. Wohl, J. Zaki, S. R. Zion, and R. Willer, “Using social and behavioural science to support COVID-19 pandemic response,” Nat Hum Behav, vol. 4, no. 5, pp. 460–471, May 2020.[12] S. Chen, Q. Xu, J. Buchenberger, A. Bagavathi, G. Fair, S. Shaikh, and S. Krishnan, “Dynamics of health agency response and public engagement in public health emergency: A case study of CDC tweeting patterns during the 2016 Zika epidemic,” JMIR Public Health Surveill, vol. 4, no. 4, p. e10827, Nov. 2018.[13] V. H. Murthy, “Confronting health
Engineering Education, 1(1).[44] Liu, Q., Sweeney, J., & Evans, G. (2021, July). Exploring Self-directed Learning Among Engineering Undergraduates in the Extensive Online Instruction Environment During the COVID-19 Pandemic. American Society for Engineering Education Virtual Annual Conference.[45] American Society for Engineering Education. (2020). Engineering and Engineering Technology by the Numbers 2019. Washington, DC.[46] McCallum, F., & Price, D. (2016). Nurturing wellbeing development in education: From little things, big things grow. Routledge.[47] Verdín, D., Godwin, A., Kirn, A., Benson, L., Potvin, G. (2018). Understanding How Engineering Identity and Belongingness Predict Grit for First
Worker. In 2021 ASEE VirtualAnnual Conference Content Access.Hennecke M., Bleidorn, W., Denissen, J., and Wood, D. “A three–part framework for self–regulated personality development across adulthood.” European Journal of Personality, 2014,28(3), pp.289-299.Kim, B., Wen, R., Zhu, Q., Williams, T. and Phillips, E., 2021, March. Robots as moral advisors:the effects of deontological, virtue, and confucian role ethics on encouraging honest behavior. InCompanion of the 2021 ACM/IEEE International Conference on Human-Robot Interaction pp. 10-18.King, P.M. and Kitchener, K.S., 2004. Reflective judgment: Theory and research on thedevelopment of epistemic assumptions through adulthood. Educational psychologist, 39(1), pp.5-18.Koehler, J., Pierrakos, O
multiple days and recording panels or presentations provides additional flexibility to those who might have teaching or work conflicts and/or personal commitments at an event’s scheduled time, although it precludes participation in Q&A or panel discussions.● Attendance over time at the CIMC sessions has declined, a trend in keeping with reports of increased faculty exhaustion in the face of ongoing pandemic adjustments and increased task demands, especially for faculty mothers [45] as well as Zoom fatigue, which impacts women more than men [46]. A&A sessions had considerably less attendance than pre-pandemic sessions; however, the in-person sessions were better attended than the online sessions
inengineering practices.AcknowledgementsThis work was supported by the National Science Foundation under Grant DRL-1742195. Anyopinions, findings, and conclusions or recommendations expressed in this material are those ofthe authors and do not necessarily reflect the views of the National Science Foundation.ReferencesAmerican Society for Engineering Education (2020). Framework for P-12 engineering learning. American Society for Engineering Education. https://doi.org/10.18260/1-100-1153-1Askew, M., Brown, M., Rhodes, V., Wiliam, D., & Johnson, D. (1997). Effective Teachers of Numeracy in Primary Schools: Teachers' Beliefs, Practices and Pupils' Learning.Capobianco, B., & Lehman, J. D., & Huang, Q., & Nyquist, C. (2016, June
time investment when first creating these problems is about one to two hours. Afterthey are created, they can be reused for subsequent classes with usually only minor updates (e.g.,adding clarity to the problem statement). The automated grading does save time but can generatea substantial increase in student questions. The quantity of these questions can be managed bythe following guidelines: • Provide students with a “MATLAB Grader Q & A” worksheet that contains answers to commonly asked questions regarding MATLAB Grader. • Insist that students come prepared with neatly written work describing their process instead of just their code. • Update the feedback within MATLAB Grader tests to reflect common errors or
Consumer Protection. https://datenethikkommission.de/wp-content/uploads/DEK_Gutachten_engl_bf_200121.p dfDesai, S. (2021, April). Stanford University CS 21SI: AI for Social Good. https://explorecourses.stanford.edu/search?view=catalog&filter-coursestatus-Active=on& page=0&catalog=&academicYear=20192020&q=CS%2021SI%3A%20AI%20for%20So cial%20Good&collapse=D’Ignazio, C., & Klein, L. F. (2020). Data Feminism. MIT Press.Ethics & Compliance Initiative (ECI). (2021). The PLUS Ethical Decision Making Model—Ethics & Compliance Toolkit. Ethics and Compliance Initiative. https
Globalized World: Philosophy of Engineering and Technology, vol 22, C. Murphy, P. Gardoni, H. Bashir, C. Harris, Jr., and E. Masad, Eds. New York: Springer, 2015, pp. 229-247.[9] Q. Zhu and B. K. Jesiek, “A pragmatic approach to ethical decision-making in engineering practice: Characteristics, evaluation criteria, and implications for instruction and assessment,” Science and Engineering Ethics, vol. 23, no. 3, 2017, pp. 663–679.[10] S. J. Hitt, C. E. P. Holles, and T. Lefton, “Integrating ethics in engineering education through multidisciplinary synthesis, collaboration, and reflective portfolios
respective fields, but this will all come with time and I am excited to learnmore.” Devin was an exception during week 1, his comments illustrated his feelings assomewhat of an outsider when he stated, “Given that we talked about what my topic may havebeen I felt I could have provided more insight or ideas to what it was, but felt my opinion did notmatter since they were the lab that was accepting me.”Table 3. Results of the Weekly Pulse Survey Name Q Week 1 Week 2 Week 3 Week 4 Week 5 Week 6 Week 7 Week 8 Christine 1 Somewhat No group Strongly No group Strongly No group Somewhat No group Agree meeting Agree meeting Agree meeting Disagree meeting
. Computers & Education, 55(3), 1171–1182[40] Le, Q. T., Pedro, A., & Park, C. S. (2015). A social virtual reality based construction safety education system for experiential learning. Journal of Intelligent & Robotic Systems, 79(3), 487-506.[41] Schwaab, J., Kman, N., Nagel, R., Bahner, D., Martin, D. R., Khandelwal, S., ... & Nelson, R. (2011). Using second life virtual simulation environment for mock oral emergency medicine examination. Academic Emergency Medicine, 18(5), 559-562.[42] Schofield, D. (2014). A Virtual Education: Guidelines for Using Games Technology. Journal of Information Technology Education, 13.[43] Juliani, A., Berges, V. P., Teng, E., Cohen, A., Harper, J., Elion, C., ... & Lange, D
disagree and 5=strongly agree. All Has Hispa LGB First- Short Stude F M Asian Black White Disab Q Key nic T+ Gen description nts n=17 n=48 n=39 n=3 n=45 ility n=9 n=22 n=12 n=76 n=14 Weed-out
Ac te O In rg n io O st ue Q Figure 4: Number and Quality of Lessons Across Evaluation Areas Average Lesson Evaluation Excellent
eight years of data, some minor increases and decreases areobserved, but there are no significant trends versus time. 100 Pre Post 80 Mean Score Q 3 (%) 68.9 68.7 65.4 62.3 64 60.3 63.2 60 60 50