transportation engineering with lecture and laboratorycomponents at the Pennsylvania State University. Specifically, the study seeks to determine howthe transition to remote instruction impacted student perceptions of the learning environment asit relates to the development of their professional expertise. Students’ perception on the learningenvironment was measured using the Supportive Learning Environment for ExpertiseDevelopment Questionnaire (SLEED-Q) [1]. The SLEED-Q was administered to students in Fall2018 and Fall 2019 (normal instruction) and compared with responses obtained from Fall 2020(remote instruction). Prior data (2018, 2019) was collected for baseline comparison as part of alarger curricular revision project to examine the impact of
teachers may ask students when exploring the Report Card and relatedactivities are as follows: • Q: Which of these infrastructure types do you see and/or use in your daily activities? o Activities: A discussion with students could include the infographic “How Much Infrastructure Do You Use Before Noon?” Students choose one category of infrastructure to explore in more detail through creation of a short report, a photo collage of that infrastructure type (younger students), Teachers lead a field trip around their community and have students identify the different infrastructure components around them
flexural bucklingstress, Fcr, via a Q-factor which was a function (in part) of the effective area of the cross sectionof slender elements. These equations are shown in Figure 3, the typical lecture slides, as theyshould be. However, especially to the inexperienced student, this is likely just a mess ofmeaningless equations which they will simply follow blindly. Providing even a little context –making a connection between Q and the flexural buckling strength curve – at minimum will givestudents a better feeling for what the equations do. Similarly, the new method overall strategyshown in Figure 4, and it is clear that in concept nothing changed between old and new methods.This, again, instills confidence in the future designer. When students are
potentially important variables for predicting future grade of the students in statics course. Onthe other hand, chi-square statistics also shows that gender, number of prior attempts and inclusionof adaptive learning module do not significantly influence the grade.MODEL AND ESTIMATION RESULTSEconometric ModelIn this research, we employ the ordered logit model for studying the ordinal categorical variablegrade with the categories defined as Fail/Withdraw (DFW) and Pass (ABC).Let j be the index for the discrete outcome that corresponds to grade for student q. In orderedresponse model, the discrete grade levels (𝑦𝑞 ) are assumed to be associated with an underlyingcontinuous latent variable (𝑦𝑞∗ ). This latent variable is typically specified as the
Decision Making? A Mixed Methods Study,” J. Educ. Res., vol. 107, no. 3, pp. 167–176, 2014.[15] L. Klotz, G. Potvin, A. Godwin, J. Cribbs, Z. Hazari, and N. Barclay, “Sustainability as a route to broadening participation in engineering,” J. Eng. Educ., vol. 103, no. 1, pp. 137– 153, 2014.Authors, 2014.[16] R. W. Lent and S. D. Brown, “Social cognitive approach to career development: an overview,” Career Dev. Q., vol. 44, no. 4, pp. 310–321, Jun. 1996.[17] R. W. Lent, S. D. Brown, and G. Hackett, “Toward a unifying social cognitive theory of career and academic interest, choice, and performance,” J. Vocat. Behav., vol. 45, no. 1, pp. 79–122, 1994.[18] A. Wigfield and J. S. Eccles, “Expectancy–value theory
✓ ✓ ✓ ✓f. Codes and Standards ✓ ✓ ✓g. Quantity Estimating ✓ ✓ ✓h. Permitting ✓ ✓ ✓i. Health and Safety ✓ ✓ ✓j. Application Programming ✓ ✓ ✓k. Cost Estimating ✓ ✓ ✓l. Construction Document ✓ ✓ ✓ Packagingm. Contracts ✓ ✓ ✓n. Quality Assurance and Quality ✓ ✓ ✓ Controlo. Technical Documents ✓ ✓ ✓p. Specialized Software ✓ ✓ ✓q. Project Management
outcomes that correspond to the undergraduate pathway (i.e., receiving andresponding). Table 2. SEE course: Bloom’s taxonomy cognitive student outcomes (Q: video quiz, WS: in-class worksheet, HW: weekly homework). Student Assessment type Assessment type Demonstrated ability (Comprehension) outcomes (Knowledge) Identify basic concepts and methods in solving civil and environmental Knowledge engineering problems from a systems
] H. M. Matusovich, R.A Streveler, and R. L. Miller, “Why Do Students Choose Engineering? A Qualitative, Longitudinal Investigation of Student’s Motivational Values,” Journal of Engineering Education, pp. 289- 303, October 2010. [Online]. Available: https://onlinelibrary.wiley.com/doi/10.1002/j.2168-9830.2010.tb01064.x. [Accessed January 13, 2019].[7] Q. Li, D. B. McCoach, H. Swaminathan, and J. Tang, “Development of an Instrument to Measure Perspectives on Engineering Education Among College Students,” Journal of Engineering Education, pp. 47-56, January 2008. [Online]. Available: https://onlinelibrary.wiley.com/doi/epdf/10.1002/j.2168-9830.2008.tb00953.x. [Accessed January 13, 2019].[8] B. D. Jones, M. C. Paretti, S. F. Hein
engineering education andcommunity service: Themes for the future of engineering education. Journal of EngineeringEducation, 95(1), 7-11.[17] Mihelcic, J. R., Crittenden, J. C., Small, M. J., Shonnard, D. R., Hokanson, D. R., Zhang,Q., ... & Schnoor, J. L. (2003). Sustainability science and engineering: the emergence of a newmetadiscipline. Environmental Science & Technology, 37(23), 5314-5324.[18] WL. Filho, E. Manolas and P.Pace, “The future we want, Key issues in sustainabledevelopment in higher education after Rio and the UN decade of education for sustainabledevelopment,” International Journal of Sustainability in Higher Education, v16 n1, pp. 112-1292015.[19] Vairavamoorthy, Kala, “Water and the SDGs,” The Source, October 2019, pp. 18
. Navarro, and L. Y. Flores, “First-Generation College Students’ Persistence Intentions in Engineering Majors,” J. Career Assess., vol. 25, no. 1, pp. 93–106, 2017.[20] E. A. Cech and T. J. Waidzunas, “Navigating the Heteronormativity of Engineering: The Experiences of Lesbian, Gay, and Bisexual Students,” Eng. Stud., vol. 3, no. 1, pp. 1–24, 2011.[21] E. A. Cech and W. R. Rothwell, “LGBTQ Inequality in Engineering Education,” J. Eng. Educ., vol. 107, no. 4, pp. 583–610, 2018.[22] A. Haverkamp, A. Butler, N. S. Pelzl, M. K. Bothwell, D. Montfort, and Q.-L. Driskill, “Exploring Transgender and Gender Nonconforming Engineering Undergrad- uate Experiences through Autoethnography,” in Proceedings of the 2nd Annual