knowing and instruction, such as the role of gestures during classroom teaching, learning, collaboration, and assessment. Dr. Nathan has authored over 250 peer-reviewed publications and has served as PI and co- PI for numerous research grants from the National Science Foundation (NSF), the U. S. Dept. of Education-Institute of Educational Sciences (IES), and the James S. McDonnell Foundation (JSMF); most notably the NSF-funded “Aligning educational experiences with ways of knowing engineering (AWAKEN),” and IES-funded “National Center for Cognition and Mathematics Instruction.” Dr. Nathan has served on multiple committees for the National Academies of Sciences, Engineering, and Medicine to advance science and engineering
infrastructure systems, and adaptive reuse.John S Gero (Dr)Paulo Ignacio Jr. PhD student at Virginia Tech. Working with Dr. Tripp Shealy. Passionate about human performance and wellbeing in the built environment. © American Society for Engineering Education, 2022 Powered by www.slayte.com How the use of concept maps changes students’ minds and brainsAbstractThe research presented in this paper tested whether drawing concept maps changes howengineering students construct design problem statements and whether these differences areobservable in their brains. The process of identifying and constructing problem statements is acritical step in engineering design. Concept
. from Florida State University, an MBA from Stetson University, and an Ed. S. from Kennesaw State University in Instructional Technology.Marc Weissburg © American Society for Engineering Education, 2022 Powered by www.slayte.com Biologically Inspired Design for Engineering Education: A Multiple Year Evaluation of Teachers’ Professional Learning Experiences (Evaluation)AbstractThis evaluation paper focuses on how high school engineering teachers' professional learningexperiences advance their understanding of bio-inspired design integration into engineering as aresult of the professional learning environment
/10.3200/JECE.38.2.143- 152, vol. 38, no. 2, pp. 143–152, Mar. 2007, doi: 10.3200/JECE.38.2.143-152.[5] A. Alleyne, “A fluid power lab for undergraduate education,” Proceedings of the American Control Conference, vol. 6, pp. 4398–4402, 2000, doi: 10.1109/ACC.2000.877053.[6] J. J. Heber, “Instrumented infinitely variable transmission,” Theses and Dissertations Available from ProQuest, Jan. 2011, Accessed: Feb. 03, 2022. [Online]. Available: https://docs.lib.purdue.edu/dissertations/AAI1501831[7] S. J. Ryan, B. L. Steward, and S. Kshetri, “Simulated Hands-On Laboratory Instruction for Fluid Power Systems,” American Society of Agricultural and Biological Engineers Annual International Meeting, ASABE 2021
], andeconomic factors (E), such as economic cycles, growth and production costs [12,25], on pursuingengineering opportunities. While social factors (S) have received less attention, a growingnumber of studies have explored how quality of life, cultural considerations and social trendscan give rise to new challenges and opportunities [12,23,25]. Technological factors (T), in turn,are often more readily identified by engineers, considering not only the technological aspects ofthe specific solutions they are working with, but the implications of more overarchingdevelopments such as digitalization and artificial intelligence [28]. For example, newdevelopments in opportunities in virtual prototyping can decrease development cycles and cost,opening up new
. A. Whittaker and B. L. Montgomery, “Cultivating Institutional Transformation and Sustainable STEM Diversity in Higher Education through Integrative Faculty Development,” Innov. High. Educ., vol. 39, no. 4, pp. 263–275, Aug. 2014, doi: 10.1007/s10755-013-9277-9.[3] S. Wadia-Fascetti and P. G. Leventman, “E-Mentoring: A Longitudinal Approach to Mentoring Relationships for Women Pursuing Technical Careers,” J. Eng. Educ., vol. 89, no. 3, pp. 295–300, Jul. 2000, doi: 10.1002/j.2168-9830.2000.tb00528.x.[4] M. J. Chang, M. K. Eagan, M. H. Lin, and S. Hurtado, “Considering the Impact of Racial Stigmas and Science Identity: Persistence Among Biomedical and Behavioral Science Aspirants.,” J. High. Educ., vol. 82, no. 5, pp
only to benefit engineering retention as a whole, but alsoto begin to close the retention gap for underrepresented minorities in engineering. Our resultssupport our hypothesis, suggesting that interdisciplinary studies are appealing to URMs and mayhelp alleviate the push-pull pressure by bridging engineering with careers they better identifywith. These interdisciplinary interventions have not yet been implemented or assessed for actualimpact on URM recruitment and retention.References[1] M. M. Camacho and S. M. Lord, “‘Microaggressions’ in engineering education: Climate for Asian, Latina and White women,” in 2011 Frontiers in Education Conference (FIE), Oct. 2011, pp. S3H-1- S3H-6. doi: 10.1109/FIE.2011.6142970.[2] A. J. Koch, P. R
specifically aligned to Herzberg’s [24] motivational andhygiene factors. Additionally, future investigation should include increased stratification ofdemographics, including gender and race, to help identify the impacts that factors have onvarying groups.References[1] McTaggart, R. (1991). Principles for participatory action research. Adult Education Quarterly, 41(3), 168-187.[2] Tugden, A. “On the Verge of Burnout: COVID -19’s Impact on Faculty Well-Being and Career Plans 2020,” The Chronicle for Higher Education, Washington, DC, USA, 2020. Accessed February 2023. [Online] Available: https://connect.chronicle.com/rs/931-EKA- 218/images/COVID%26FacultyCareerPaths_Fidelity_ResearchBrief_v3%20%281%29.p df[3] Coiro M.J
to effectively argue their design solution is independent of thedisciplinary diversity of the team.Discussion and ConclusionsThe goal of this research was to investigate the relationship between disciplinary diversity andeffectiveness of design argumentation to determine if disciplinary diversity can be disregarded asa significant factor when analyzing engineering design teams’ argumentation skills. AsKrishnakumar et al.’s research on this data set determined that interdisciplinarity of a design teamdid not relate to the outcomes of the engineering projects or the quality of the design pitch asdetermined by sponsor satisfaction [41], our results also showed no statistically significantcorrelation between disciplinary distance and design
) levels to ensure that every student seeking anengineering degree is afforded the necessary support systems to complete degree requirements.Future WorkFuture work of this study includes associating the impact of grades with the socioeconomic factorsidentified by Bandura which include racial gaps, school sector, school environment, and familyconditions. A survey was created and administered in the Fall of 2022 with a cohort of studentsenrolled in a Rigid Dynamics course. Specifically, students were asked about the non-academicfactors that affect their academic performance such as family responsibilities, employment, andfinancial issues. The data is under review, and more will be collected in the Spring 2023.REFERENCES[1] Abdi, H. M., Bageri, S
-directed, intrinsically motivated learning characteristic of graduatestudents and practicing engineers.References[1] A. C. Estes, R. W. Welch, and S. J. Ressler, “The ExCEEd Teaching Model,” Journal of Professional Issues in Engineering Education and Practice, vol. 131, no. 4, pp. 218–222, Oct. 2005, doi: 10.1061/(ASCE)1052-3928(2005)131:4(218).[2] K. M. DeGoede, “A Chegg® Era Model for HW,” presented at the 2020 ASEE Virtual Annual Conference Content Access, Jun. 2020. Accessed: Feb. 07, 2023. [Online]. Available: https://peer.asee.org/a-chegg-era-model-for-hw[3] T. A. Wood, D. D. Nale, and R. K. Giles, “Closing the Homework Feedback Loop Using Dual-Submission-with-Reflection Homework Methodology,” in 2020 ASEE Virtual Annual
. By incorporating these elements, an enjoyable andinformative experience for underrepresented minority students can be attained and encourage themto pursue careers in STEMReferences[1] E. O. McGee, Black, brown, bruised: How racialized STEM education stifles innovation. Harvard Education Press, 2021.[2] M. Elam, B. Donham, and S. R. Soloman, "An engineering summer camp for underrepresented students from rural school districts," Journal of STEM Education: Innovations and Research, vol. 13, no. 2, 2012.[3] K. Kricorian, M. Seu, D. Lopez, E. Ureta, and O. Equils, "Factors influencing participation of underrepresented students in STEM fields: matched mentors and mindsets," International Journal of STEM
, 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
modules are integrated into the course to mimic real-life systems and engineeringeconomy problems. Students are given a week to complete each ISBL assignment following thelecture on the respective topic. The document that comes with each module includes adescription of the system at hand and the engineering economy problem(s) to be solved. In eachISBL module, the students are given a role. For example, in one of the modules the student is“hired” as a consultant to help a restaurant compare different loan options and select the mosteconomical alternative. Each module is also accompanied by a 3D, VR-compatible, animatedsimulation model that is to be treated as the “real-world system” under study. The ISBL modulesused in our experiments are related
/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
students: one student reported low participation inboth projects and s/he attended the classes about half in person and half online, which mighthave contributed to the low participation. The other student reported low participation in thesecond project although s/he attended the classes fully in person and s/he reported fullparticipation in the first project. There was no data to explain the reason, but project 2 wasstudent-driven by the team leader who came up with that project topic. As instructors, we need toencourage all students to contribute to the final design and prototyping.Course ManagementA mixture of teaching modalities was used in this course, as explained in the Course Setupsection.Depending on the course content, such as for
female and minoritized student representation. We will alsowork to identify other department-level metrics that could help explain disciplinary differencesin persistence.ReferencesAstin, A. W. (1985). Achieving educational excellence: A critical assessment of priorities and practices in higher education. San Francisco: Jossey-Bass.Astin, A. W. (1993). What matters in college? Four critical years revisited. San Francisco: Jossey-Bass.Berger, J. B., & Milem, J. F. (2000). Organizational behavior in higher education and student outcomes. In J. C. Smart (Ed.), Higher education: Handbook of theory and research (Vol. XV, pp. 268–338). Agathon.Brawner, C. E., Lord, S. M., Layton, R. A., Ohland, M. W., & Long, R. A. (2015). Factors
mentor and benefits they derive from the process. Journal of Multicultural Counseling and Development. 22(1), 37–48.Bjursell, C., & Sädbom, R. F. (2018). Mentorship programs in the manufacturing industry. European Journal of Training and Development. 42(7/8), 455-469.Brown II, M. C., Davis, G. L., & McClendon, S. A. (1999). Mentoring graduate students of color: Myths, models, and modes. Peabody Journal of Education, 74(2), 105-118.Byars-Winston, A., Womack, V. Y., Butz, A. R., McGee, R., Quinn, S. C., Utzerath, E., ... & Thomas, S. B. (2018). Pilot study of an intervention to increase cultural awareness in research mentoring: Implications for diversifying the scientific workforce. Journal of
-YearExperience & Students in Transition.[8] S. Ahmed. On being included: Racism and Diversity in Institutional Life. North Carolina:Duke University Press, 2012.[9] C. Brammer. Communicating as Women in STEM. London, UK: El Sevier, Academic Press,2018.[10] A. Sithole, E.T. Chiyaka et al, “Student attraction, persistence, and retention in STEMprograms: Successes and continuing challenges,” Higher Education Studies, vol. 7, no. 1, 2017,46-59.[11] J. Wyn, H. Cuervo et al, “Gendered transitions from education to work: The mysteriousrelationship between the fields of education and work,” Journal of Sociology, vol., 53, no. 2,2018, 492–506. https://doi.org/10.1177/1440783317700736[12] P. Bourdieu. “Cultural Reproduction and Social Reproduction”, in Power
prestige.Learning Experiences Influence Outcome Expectations Related to Engineering Careers In high school 271, both 271T1 and T2 talked about influences of courses or programs ontheir students’ postsecondary outcome expectations. T1 mentioned that “taking these classes 8[basic drawing classes] in high school is good because it's helping them narrow their focus andsee if it's something that they are interested in and if they're good at it,” implying that classesthat students take can influence their postsecondary outcome expectations, particularly on theirinterest in certain fields. This is further supported by a T1’s example:“she's [one of her
Technical Direction. Professor of Practice. Emphasis on theater technical direction. Prof. J.-LA College of Liberal Arts Professor of Dance. Emphasis on contact dance improvisation. Prof. S.-LA College of Liberal Arts Professor of Art and Design. Professor of Art Education. Prof. Y.-LA College of Liberal Arts Professor of Interior Design. Data collection consisted of semi-structured interviews, which helped to understand better thecontext where the answers came from and tailor "follow-up questions within and across interviews" [10,p. 154] according to the participants' response. The questions were structured according to one element ofthe correspondence analysis
, the followingquestions were asked of all interviewees prior to conducting the interview: ● What is your name? (to ensure the correct person was interviewed) ● Are you over the age of 18? (this study was not IRB approved for minors as participants) ● Were you an LA in the Spring of 2020? ● What course(s) were you an LA for in Spring of 2020?These questions were for the purposes of pre-screening for eligibility and were not recorded as apart of the data collection process. As established in our approved Institutional Review Boardprotocol, we reviewed approved consent documents with each participant and gained verbalconsent for engaging in the interview or recording the audio.Course Contexts. The interviewees in this study supported
, Inc, 2013. doi: 10.1145/2534860.[2] R. Bockmon, S. Cooper, J. Gratch, J. Zhang, and M. Dorodchi, “Can Students’ Spatial Skills Predict Their Programming Abilities?,” in Proceedings of the 2020 ACM Conference on Innovation and Technology in Computer Science Education, Trondheim Norway, Jun. 2020, pp. 446–451. doi: 10.1145/3341525.3387380.[3] S. Cooper, K. Wang, M. Israni, and S. Sorby, “Spatial Skills Training in Introductory Computing,” in Proceedings of the eleventh annual International Conference on International Computing Education Research - ICER ’15, Omaha, Nebraska, USA, 2015, pp. 13–20. doi: 10.1145/2787622.2787728.[4] S. Jones and G. Burnett, “Spatial Ability and Learning to Program,” Hum. Technol
protocols for interference mitigation.The WSU author had the privilege of teaching a senior/first-year graduate student class onantennas and RF propagation in the Fall 2020. The anTpaTT system was demonstrated andmeasured results were compared to simulated results as part of the exercise.Students employed by a DoD contractor expressed appreciation for ‘real-world’ applications thatapplied directly to their job(s). Course evaluations were positive, and the department plans tocontinue a long-term plan to build an applied-EM curriculum.The anTpaTT system also offers opportunities for a wide variety of undergraduate research andsenior capstone projects due to its interdisciplinary nature; potential topics include signalprocessing to improve pattern
and creativetechniques in the classroom.For future work, this study can be expanded to include more participants, or even participantsfrom different backgrounds. The study can be replicated with a different creative intervention ordesign problem, to see if the hypothesis hold true. More research can be done on how a creativeintervention effects work that we do not generally view as creative, like math or science. Futureresearch can aim to answer the following research questions: 1) How does completing a creativity activity over a long period of time effects self- perception of creativity and novelty of a design? 2) How does a creativity intervention effect the outcomes of a non-design engineering course?References[1] S. M
. Owen, "Implementing virtual learning environments: Looking for holistic approach." Journal of Educational Technology & Society 3.3 (2000): 39-53.[3] J. M. Spector, “The potential of smart technologies for learning and instruction,” Int. j. smart technol. learn., vol. 1, no. 1, p. 21, 2016.[4] B. J. DiSalvo and A. Bruckman, “Questioning video games’ influence on CS interest,” in Proceedings of the 4th International Conference on Foundations of Digital Games - FDG ’09, 2009.[5] M. Papastergiou, “Digital Game-Based Learning in high school Computer Science education: Impact on educational effectiveness and student motivation,” Comput. Educ., vol. 52, no. 1, pp. 1–12, 2009.[6] N. Jain, P. Youngblood, M. Hasel, and S
?. Science, Technology,& Human Values, 39(1), 42-72.8. Leydens, J. A., Johnson, K., Claussen, S., Blacklock, J., Moskal, B. M., & Cordova, O.(2018). Measuring change over time in sociotechnical thinking: A survey/validation model forsociotechnical habits of mind. In 2018 Proceedings of the American Society for EngineeringEducation.9. Malazita, J. W., & Resetar, K. (2019). Infrastructures of abstraction: how computer scienceeducation produces anti-political subjects. Digital Creativity, 30(4), 300-312.10. Slaton, A. E. (2015). Meritocracy, technocracy, democracy: Understandings of racial andgender equity in American engineering education. In International perspectives on engineeringeducation (pp. 171-189). Springer, Cham.11. Riley, D
and numeric data together and uncover multivariate data associations fromdata. The PVAD algorithm was used to obtain data associations. Each association is in the formof X retention = YES, where X represents specific value(s) of one or multiple variables.Hence, X in each data association reveals characteristics of students whose retention variable(s)indicates them staying in engineering after the first year at ASU. In this study, we looked intoonly 1-to-1 data associations with X containing one variable and its specific value, because p-to-1 data associations, p > 1, with X containing multiple variables and their specific value are oftencombinations of characteristics from 1-to-1 data associations. A supporting instance of a 1-to-1data
provided instructors with critical information about theirstudents’ behaviors in courses. For example, learning analytics supply insight into the numberand time of student interactions [12]–[14] and the frequency of viewing content pages [15] andtools [10], [16]. Student behavior analytics is often compared to student performance and provento correlate significantly. Joksimovic et al. (2015) found that the count of student-studentinteractions in an entirely online course significantly correlated with the students’ grades. Also,the time spent interacting with the instructor had positive effects on the final learning outcomes[13]. Agudo-Peregrinal et al. (2014) looked at Moore (1989) and Hillman et al.’s (1994)interaction types and their correlation
, Student 6noticed missing representations in their conceptual model. Students 5 and 12 expressed theyadded additional descriptive details to their models like parking lots, arrows, words, andsediment to their second models. While noticing details and context is important to anyengineering design activity, the way in which quality was determined showed that many students(27/39 students for pictorial quality and 23/39 students for numerical quality) did not change inquality. Below we provide the conceptual models of Student 5, shown in Figure 4. (a) Before activity (b) After activity Figure 4: Conceptual models of Student 5Student 5’s conceptual model before the peer comparison