components ofspatial ability which may aid in the creation of more complete training.AcknowledgementsThis material is based upon work supported by the U.S. National Science Foundation underGrant No. 1712887. Any opinions, findings, and conclusions or recommendations expressed inthis material are those of the authors and do not necessarily reflect the views of the NationalScience Foundation.References[1] K. S. McGrew, “CHC theory and the human cognitive abilities project: Standing on the shoulders of the giants of psychometric intelligence research,” Intelligence, vol. 37, no. 1, pp. 1–10, Jan. 2009, doi: 10.1016/j.intell.2008.08.004.[2] D. F. Lohman, “Spatial Ability and G.” 1993.[3] A. Ramful, T. Lowrie, and T. Logan, “Measurement of Spatial
supportive option for its students.References [1] B. Bygstad, E. Øvrelid, S. Ludvigsen, and M. Dæhlen, "From dual digitalization to digital learning space: Exploring the digital transformation of higher education," Computers & Education, vol. 182, p. 104463, 2022. [2] R. P. Goldenson, L. L. Avery, R. R. Gill, and S. M. Durfee, "The virtual homeroom: Utility and benefits of small group online learning in the COVID-19 era," Current Problems in Diagnostic Radiology, vol. 51, no. 2, pp. 152–154, 2022. [3] V. G. Padaguri and S. A. Pasha, "Synchronous online learning versus asynchronous online learning: A comparative analysis of learning effectiveness," in Proc. AUBH E-Learning Conf., 2021. [4] K. Baba, N
system users andother practitioners. For example, the LSRM may enhance the CATME system by accuratelymodeling longitudinal social relations data, and thereby improving the evaluation of teamdynamics and identifying potential areas for improvement. Ultimately, this may help instructorsbetter support their students' collaborative learning experiences and foster a more inclusivelearning environment. ReferencesAgrawal, A. K., & Harrington-Hurd, S. (2016). Preparing next generation graduates for a global engineering workforce: Insights from tomorrow's engineers. Journal of Engineering Education Transformations, 29(4), 5-12.Alsharif, A., Katz, A., Knight, D., & Alatwah, S. (2022). Using
aframework comprising 12 attitudes and 17 behaviors that align with the 3Cs.Parallel to the entrepreneurial mindset, we can define an innovation mindset as a set of beliefsand attitudes that lead to developing the capacity to produce valuable novelty. There is also adistinction between individual innovativeness and the innovation mindset. For example, Hunteret al.’s conceptual model of innovativeness [11] includes constructs such as knowledge, skills,and abilities, while the innovation mindset emphasizes dispositions, attitudes, and propensities[12]. Couros [13] describes eight characteristics of an innovator’s mindset: empathic, problemfinders/solvers, risk takers, networked, observant, creators, resilient, and reflective.This paper investigates
projects. The preliminary learning outcomes and framework presented in this studycan guide students through multiple stages where incorporating contextual factors is relevant andprovide prompts for reflection and methods to do so iteratively throughout their designprocesses. The findings from this work have implications for engineering design pedagogy and,ultimately, the potential to improve engineering graduates’ abilities to develop contextuallysuitable solutions.References[1] C. B. Aranda-Jan, S. Jagtap, and J. Moultrie, “Towards A Framework for Holistic Contextual Design for Low-Resource Settings,” Int. J. Des., vol. 10, no. 3, p. 21, 2016.[2] P. Clyde et al., “25 Years of Health Care Delivery in Low- and Middle-Income Countries
Paper ID #32725Broadening the Participation of Underrepresented Minorities in theMathematical SciencesProf. Tuncay Aktosun, University of Texas at Arlington Dr. Aktosun is a professor of mathematics at the University of Texas at Arlington. His research area is applied mathematics and differential equations with research interests in scattering and spectral theory, inverse problems, wave propagation, and integrable evolution equations. He is involved in various men- toring and scholarship programs benefiting students. He has been the GAANN Fellowship Director in his department since 2006, the NSF S-STEM Scholarship
for the NOT of a logic function. 44 Design a hierarchial carry-lookahead adder. 3 Create a truth table for a logic function. 45 Design an array multiplier for unsigned binary numbers. 4 Draw the logic network of gates that implements a logic function. 46 Multiply signed binary numbers with 2’s complement arithmetic. 5 Use Boolean Algebra to reduce a logic function. 47 Convert a fixed-point binary number to decimal. Give the decimal exponent range and precision of a single- or double- 6 Prove a
a study to examine the factors that impact theproduction of African American Ph.D.’s in engineering, as well as those factors that affectthe pathway to tenured faculty positions in engineering. Their findings have highlightedthe need to discuss race and gender and its impact on developing a more diverseengineering workforce [1-4].References[1] E. O. McGee, W. H. Robinson, L. C. Bentley, and S. L. Houston II, "Diversity stalled: Explorations into the stagnant numbers of African American engineering faculty," in ASEE Annual Conference and Exposition, Seattle, WA, 2015.[2] W. H. Robinson, E. O. McGee, L. C. Bentley, S. L. Houston II, P. K. Botchway, and R. Roy, "Racial and gendered experiences that dissuade a
9 10If for instance you were pursuing a mechanical engineering (ME) degree and through the courseof the Perseus II project you gained significant new ME relative knowledge and reinforcedinformation from classes throughout your UG career relative to ME that enhanced your abilityto apply ME knowledge you would select something on the higher end of the spectrum torepresent what you feel is a significant educational impact. ii. In a discipline/s of your Perseus II teammates : 1 2 3 4 5 6 7 8 9 10If for instance you were pursuing a mechanical engineering (ME) degree and through the courseof the Perseus II project you gained significant new naval engineering relative knowledge, forexample the knowledge and ability to assess and design
Engineering Ambassadors reflected on student learning andtheir own practice after each presentation. The EAs responded individually to a six-questionopen-ended survey (Appendix C). Responses that were general in nature are displayed in Figure3.Figure 3. Engineering Ambassadors’ General Reflections on Lesson PresentationsBriefly describe Which part(s) Which part(s) Which part(s) What will you What your lesson of the lesson of your lesson of your lesson do to make that knowledge went really will you do the will you change? and/or skill well? same? change
. In addition, she runs a faculty devel- opment and leadership program to train and recruit diverse PhD students who wish to pursue academic positions in engineering or applied science after graduation. Dr. Sandekian earned B.S. and M.S. degrees in Aerospace Engineering Sciences at CU Boulder in 1992 and 1994, respectively. She went on to earn a Specialist in Education (Ed. S.) degree in Educational Leadership and Policy Studies in 2011 and a Ph.D. in Higher Education and Student Affairs Leadership in December 2017, both from the University of Northern Colorado. She is a Founding Leader of the American Society of Engineering Education (ASEE) Virtual Community of Practice (VCP) for LGBTQ+ Inclusion in Engineering
processes around EBIP-implementation. We hope that this model will facilitate moreeffective mentoring and training programs.References[1] A. Brooks, K. Heath, S. Brown, H. Dominguez, P. Shekhar, and J. Knowles, “One Size Does Not Fit All: Understanding how Faculty Implement Evidence-Based Instructional Practices in Their Engineering Courses,” presented at the IEEE Frontiers in Education (FIE), IEEE, 2022.[2] A. Brooks, J. Knowles, E. Clement, S. Prateek, and S. Brown, “Are All ‘EBIPs’ Created Equal? An Exploration of Engineering Faculty Adoption of Nine Evidence-Based Instructional Practices,” ASEE Annu. Conf. Expo., 2023[3] J. Knowles, A. Brooks, E. Clement, P. Shekhar, S. Brown, and M. Aljabery, “A Qualitative Exploration of
, Abdul Hamid et al. (2018) explored engagement prediction by manpower, including Healthcare, Construction, Entertainment, Computer Conference (EDUCON), Mar. 2022, doi: https://doi.org/10.1109/educon52537.2022.9766690. using AI-assisted facial expression detection. Their model used the Bag of • Ovidiu Andrei Schipor, S. G. Pentiuc, and M. D. Schipor
able to: Summarize the problem into research Synthesis. Relate knowledge from several question(s) areas i.e. compose, combine, create Design the experiment in steps, at least Evaluation. Making choices based upon identify variables to be manipulated and reasoned arguments responding variables Predict the behavior or have hypothesis Synthesis. Relate knowledge from several areas i.e. compose, combine, create Collect and organize the data in table(s) that Analysis. Organization of parts. Identification is logical and understandable of components (order, classify, arrange) Plot the data
satisfaction regardless of the venue. The typical way to show results from a 5-point Likert scale is to show the values indistribution bars. Visualizing in this way is helpful for research when measuring impact but lesshelpful to inform decisions on actions to take based on the results. In this work, we convert theresponses into a percentage to support program benchmarking and facilitate goal setting and thenuse that to assign a letter grade. We then convert the results from each student to a percentage bysumming up all the scores given by the student and dividing by 35 (i.e., seven items x five-pointscale). For example, a student who responds to the PS items with 5's to six items and 4 to oneitem, provides a score of 34 out of 35 possible points
of the technology used for theShinkansen was developed during the war for non-peaceful purposes. However, post-warJapanese engineers felt the need to expunge their guilt at having developed such technologyand instead utilised it for more peaceful purposes. The learning outcomes from this lecture were measured by filling out a questionnaire.Most of them mentioned their redemption by developing technology used for the war,importance of having a peaceful mindset, safety, and/or the contribution of the threeengineers as the most impressive lessons learned (see their feedback in ‘Program evaluation’below). Figure 4: Some slides from Lectures on ShinkansenProgram evaluation1. Quantitative analysis: MGUDS-S SIT values
. In the following sections, the studies on the effectiveness of game-basedlearning (GBL) are summarized first and review on its implementation potential to engineeringeducation is provided as well. Then, the developed game is explained briefly with the learninggoal and topics. We implemented this learning module in two different settings, first for 25 highschoolers at a civil and environmental engineering departmental summer camp and second for alittle under 30 community resilience researchers at the National Institute of Standards andTechnology (NIST)’s Center of Excellence for Community Resilience semi-annual meeting.Feedback was collected after the second implementation which is presented as well to discuss themodule’s future development
students’ learning. Dr. Darabi’s research has been funded by federal and corporate sponsors including the National Science Foundation, and the National Institute of Occupational Health and Safety.Mrs. Rezvan Nazempour, The University of Illinois, Chicago Rezvan Nazempour is a graduate research assistant at the University of Illinois at Chicago. She is com- pleting her Ph.D. in Industrial Engineering and operations research at the Mechanical and Industrial En- gineering Department. She received her BSIE fromDr. Peter C. Nelson, The University of Illinois, Chicago Peter Nelson was appointed Dean of the University of Illinois at Chicagoˆa C™s (UIC) College of Engi- neering in July of 2008. Prior to assuming his
institution.Faculty participating in our study were asked to develop projects and course integrations that aim todevelop some aspect(s) of students EM. The final deliverable, at the conclusion of the 2-year period, isthe submission of an Engineering Unleashed Card [8]. These cards function as a combination of blog andresource-sharing website all in one page, documenting the course plans/activities with sufficient detailthat other faculty could then take the plan/activity and modify it to fit and deploy it in their own courses.Research on mentoring models for faculty developmentThere has been a growing body of research on the effectiveness of peer mentoring programs rooted insocial cognitive theories and research on influence [9]. Social cognitive theory, SCT
slight increase in drowsiness. One participantfelt the video was longer than in actuality, while the other two felt it was shorter than in actuality. Theclinical immersion video (see appendix Table 5) elicited an average level of engagement at 6.33, with twoof the participants beginning to feel bored at around 10 minutes. No participant fell asleep, one felt adrowsiness level of 7 out of 9 while the other two did not experience any drowsiness from watching thevideo. Interestingly, all participants felt that the video was longer than in actuality.Discussion:Due to issues during data acquisition, the EEG statistical analysis was inconclusive despite observingstatistical difference in subjects 2 and 3 (see appendix Table 1). Namely, Subject 2’s
. 5 Resources[1] K. Krippendorff, Content analysis : an introduction to its methodology, 3rd ed. Beverly Hills: Sage Publications, 1980.[2] G. L. Gray, D. Evans, P. Cornwell, F. Costanzo, and B. Self, "The Dynamics Concept Inventory Assessment Test: A Progress Report," in Proceedings of the 2005 American Society for Engineering Education Annual Conference, Portland, OR, 2005.[3] G. L. Gray, D. Evans, P. Cornwell, F. Costanzo, and B. Self, "Toward a Nationwide Dynamics Concept Inventory Assessment Test," in Proceedings of the 2003 American Society for Engineering Education Annual Conference, Nashville, TN, 2003.[4] P. S. Steif and J. A. Dantzler, "A Statics
,” National Student Clearinghouse Research Center, Herndon, VA, Signature Report 19, Dec. 2020. [Online]. Available: https://nscresearchcenter.org/wp-content/uploads/Completions_Report_2020.pdf[2] D. Shapiro, A. Dundar, F. Huie, P. Wakhungu, A. Bhimdiwala, and S. Wilson, “Completing college: A state-level view of student completion rates includes for the first- time, race and ethnicity outcomes for four-year public institutions,” National Student Clearinghouse Research Center, Herndon, VA, 16a, Feb. 2019. [Online]. Available: https://www.studentclearinghouse.org/blog/completing-college-a-state-level-view-of- student-completion-rates-includes-for-the-first-time-race-and-ethnicity-outcomes-for-four- year-public
Postsecondary Research., Bloomington, 2007.[2] S. H. Russell, M. P. Hancock and J. McCullough, "Benefits of Undergraduate Research Experiences," Science, vol. 316, no. 5824, pp. 548-549, 2007.[3] A. L. Zydney, J. S. Bennett, A. Shahid and K. W. Bauer, "Impact of Undergraduate Research Experience in Engineering," Journal of Engineering Education, vol. 91, no. 2, pp. 151 - 157, 2002.[4] R. S. Hathaway, B. A. Nagda and S. R. Gregerman, "The Relationship of Undergraduate Research Participation to Graduate and Professional Education Pursuit: An Empirical Study," Journal of College Student Development, vol. 43, no. 5, pp. 614-631, 2002.[5] B. A. Nagda, S. R. Gregorman, J. Jonides, W. v. Hippel and J. S. Lerner, "Undergraduate
Agenda for Research. Washington, DC: The National Academies Press, 2014.[3] B. London, S. Rosenthal, S. R. Levy, and M. Lobel, “The influences of perceived identity compatibility and social support on women in nontraditional fields during college transition,” Basic and Applied Social Psychology, vol. 33, pp. 304-321, 2011.[4] N. D. Watkins, R. W. Larson, and P. J. Sullivan, “Bridging intergroup difference in a community youth program,” American Behavioral Scientist, vol. 51, pp. 380-402, 2007.[5] R. F. Catalano, M. L. Berglund, J. A. M. Ryan, H. S. Lonczak, and J. D. Hawkins, “Positive youth development in the United States: Research findings on evaluations of positive youth development programs,” The
/publications/tracking-transfer-institutional-state-effectiveness.html, 2016.6. T. Bailey, “Can community colleges achieve ambitious graduation goals?”, in Getting to Graduation: The Completion Agenda in Higher Education, A. P. Kelly & M. Schneider Eds. Baltimore, MD: The Johns Hopkins University Press, 2012, pp. 73-101.7. B. L. Yoder, “Engineering by the numbers,” American Society for Engineering Education, 2017.8. Bureau of Labor Statistics: U.S. Department of Labor, “Employed persons by detailed occupation, sex, race, and Hispanic or Latino ethnicity,” 2015. Available: http://www.bls.gov/cps/cpsaat11.htm.9. National Science Foundation, “How many S&E graduates attended community college?”, 2016. Available: http://www.nsf.gov/nsb
need is by using teams (Varvel, Adams,Pridie, & Ruiz Ulloa, 2004). Organizations recognize the importance for employees tounderstand how to work effectively with others, but also express that new employees do notbring adequate teaming skills to the workplace (S. Adams & Ruiz, 2004; Pascarella &Terenzini, 2005). Despite calls to promote teamwork as “an indispensable quality forengineering”(Lingard & Barkataki, 2011) engineering schools have been generally slow indeveloping pedagogies that successfully promote collaborative behaviors. Several initiativeshave been done in engineering education -like project-based learning and team-basedlearning to try to promote teamwork skills (Felder & Brent, 2009; Prince, 2004). However
engineering studentparticipation but the association with success outcomes for non-Black student members is also afuture area of interest. Additional insights into quantitative relationships can be gained by graded categorizationof NSBE membership that accounts for factors such as number of years of involvement, whenthey first joined the organization (e.g. freshman vs later years), level of involvement, and otherstudent success outcomes (e.g. GPA). Exploring how and why particular associations exist canalso be supported by more rigorous qualitative explorations of NSBE members decisions topersist or leave engineering and/or the organization and what unique role NSBE played in thesedecisions.References[1] D. E. Chubin, G. S. May, and E. Babco
I can do it can do itI can make a good scientific hypothesis. 0 1 2 3 4 5 6 7 8 9 10 Cannot Pretty sure For sure I do it I can do it can do itI can get myself to do my science school work. 0 1 2 3 4 5 6 7 8 9 10 Cannot Pretty sure For sure I do it I can do it can do it ReferencesAndrew, S. (1998). Self-efficacy as a predictor of academic performance in science. Journal of advanced
explore. For this paper, researchers present findings from theanalysis of the final cohort(s) of the original pilot program with an emphasis on characteristics ofinterest, as well as an exploration of the factors involved in place-attachment for alumni.IntroductionThe Bowman Creek Educational Ecosystem (BCE2) in South Bend, Indiana is a community-university, cross-institutional partnership [1] developed with a multiplicity of outcome aims – toattract and retain underrepresented groups in engineering and science; to improve the quality oflow-income neighborhoods; and to build STEM literacy across the regional workforce. Corepartners in the BCE2 pilot have involved a diversity of higher education institutions (Ivy Techcommunity college, Indiana