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to the National Center for Science and EngineeringStatistics (NCSES) recent report, the science and engineering (S&E) enterprise continues toadvance along several dimensions [11-12]. “The U.S. continues to perform the largest share ofglobal research and development, generate the largest share of research and developmentintensive industry output globally, award the largest number of S&E doctoral degrees, andaccount for significant shares of S&E research articles and citations worldwide. However, othernations, particularly China, are rapidly developing their science and technology (S&T) capacity.The changing global landscape affects the position of the United States relative to the other majorglobal players. For example, the
Paper ID #36881Creating an Industry-Academia Partnership to Prepare theWorkforce of the FutureStephanie S Ivey (Associate Dean for Research)Katie Marie Bowman © American Society for Engineering Education, 2022 Powered by www.slayte.com Creating an Industry-Academia Partnership to Prepare the Workforce of the FutureAbstractThis paper details development of a new Engineering Apprenticeship program designed toprepare engineering graduates to embrace technology, innovation, and the development ofmultidisciplinary solutions to current industry challenges. The program was
-012-9799-z.[6] Y. Kim, D. A. Eisenberg, E. N. Bondank, M. V. Chester, G. Mascaro, and B. S. Underwood, “Fail-safe and safe-to-fail adaptation: decision-making for urban flooding under climate change,” Clim. Change, vol. 145, no. 3–4, pp. 397–412, 2017, doi: 10.1007/s10584-017-2090-1.[7] J. Park, T. P. Seager, P. S. C. Rao, M. Convertino, and I. Linkov, “Integrating risk and resilience approaches to catastrophe management in engineering systems,” Risk Anal., vol. 33, no. 3, pp. 356–367, 2013, doi: 10.1111/j.1539-6924.2012.01885.x.[8] A. Al Rasbi et al., “Safe-to-Fail Adaptation Strategies for Phoenix-area Roadways Under Increasing Precipitation,” 2016.[9] Carol Considine and Emily Steinhilber, “COLLABORATIVE STRATEGIES
institutions, as well as groups composed of members fromdifferent backgrounds. The articles included in the review are presented in Table I below. TABLE I. Summary of Team Science and Cross-Organizational Collaboration Articles Authors (Year) Journal/Repor Research Results/ Setting(s) t Methods FindingsCheruvelil, K.S., Frontiers in Qualitative Interpersonal skills and member EcologicalSoranno, P.A., Ecology and the diversity are the most important ResearchWeathers, K.C., (...), Environment factors
closely partnered approach between faculty and industry fosters opportunities forindustry to serve as engineering communication role models for students. These formal andinformal opportunities also ensure that employers’ expectations and perceptions occupy animportant role in determining the skills that need to be reinforced in the engineering curriculum.References[1] R. Holden and S. Jameson, S. “Employing graduates in SMEs: Towards a research agenda,” Journal of Small Business and Enterprise Development, 2002.[2] H. Gilbert and H. Prew, “A Passion for Learning: Celebrating 80 Years of NIACE Support for Adult Learning.” National Institute of Adult Continuing Education, 21 De Montfort Street, Leicester LE11 7GE, United Kingdom
implementing effective pedagogical methods that will enhance student engagement,comprehension, and scholarship abilities.REFERENCES[1] Andre, E., Williams, N., Schwartz, F., Bullard, C. Benefits of Campus Outdoor RecreationPrograms: A Review of the Literature. Journal of Outdoor Recreation, Education, and Leadership.2017, Vol. 9, No. 1, pp 15-25.[2] Bailey, T., Alfonso, M. Paths to persistence: An analysis of research on program effectivenessat community colleges. Indianapolis, IN: Lumina Foundation of Education. 2005.[3] Bauman, S., Wang, N., DeLeon, C., Kafentzis, J., Zavala-Lopez, M., Lindsey, M.Nontraditional students’ service needs and social support resources: A pilot study. Journal ofCollege Counseling, 7, 13-17. 2004.[4] Bell, B.J., Holmes, M
Paper ID #37127Work In Progress: Beyond Textbook: An Open EducationalResource Platform that Generates Course-Specific E-TextbooksBarney WeiMingyu ZhengMohammadreza KaramsoltaniRUI ZENGHamid S. Timorabadi Hamid Timorabadi received his BSc, MASc, and PhD degrees in Electrical Engineering from the University of Toronto. He has worked as a project, design, and test engineer as well as a consultant to industry. His research interests include the application of digital signal processing in energy systems and computer networks. He also has deep interest in engineering education and the use of technology to advance the
campus, the instructional method(s) used for each course is givenin Table 1.Table 1 - Fall 2020 Course Instructional Methods Course Instructional Method ● Fully Online Mathematics ● Online/In-Person Hybrid Model Science ● Online/In-Person Hybrid Model Engineering ● Online/In-Person Hybrid ModelIn summary, this study has two fundamental research questions: How do first-year engineering students perceive their academic progress in the mathematics, science, and engineering courses in their first semester of college? What impact has the COVID-19 pandemic had on first-year engineering students’ perception
.), Children's needs III: Development,prevention, and intervention (pp. 59–71), 2006. https://psycnet.apa.org/record/2006-03571-005(accessed Feb. 10, 2022).[3] D. Barni, F. Danioni, and P. Benevene, “Teachers' self-efficacy: The role of personal valuesand motivations for teaching,” Frontiers, 01-Jan-1AD. [Online]. Available:https://www.frontiersin.org/articles/10.3389/fpsyg.2019.01645/full. [Accessed: 02-Feb-2022].[4] A. Wigfield and J. S. Eccles, “Expectancy–Value Theory of AchievementMotivation,” Contemporary Educational Psychology, vol. 25, no. 1, pp. 68–81, Jan. 2000, doi:10.1006/ceps.1999.1015.[5] J. Schuitema, T. Peetsma, and I. van der Veen, “Longitudinal relations between perceivedautonomy and social support from teachers and students’ self
] Sandier, B., Silverberg, L., Hall, R. (1996) The chilly classroom climate: A Guide to improvethe education of -women. Washington DC: National Association of Women in Education.[5] Chang, M. J., Sharkness, J., Hurtado, S., & Newman, C. B. (2014). What matters in collegefor retaining aspiring scientists and engineers from underrepresented racial groups. Journal ofResearch in Science Teaching, 51(5), 555-580.[6] O’Connor, C., Lewis, A., & Mueller, J. (2007). Researching “Black” educational experiencesand outcomes: Theoretical and methodological considerations. Educational Researcher, 36(9),541-552.[7] Essed, P. (1991). Understanding everyday racism: An interdisciplinary theory (Vol. 2). Sage.[8] Bonilla-Silva, E. (1997). Rethinking racism
or finding a support system on campus inwhich they can identify with. This can eventually help with retention rates and sense ofbelonging in their field of study to feel comfortable and strive. Additionally, student facilitatorswill be given support and training from faculty who are teaching the class to give betterunderstanding to the students when asking for help. Creating a mutual network of help to betterbenefit the students. We are also looking into the impact of TASI during the COVID 19pandemic and developing a course of action for the return to face-to-face instruction.AcknowledgmentThis study is part of an institution wide NSF Hispanic Serving Institution grant number_____.WORK CITED [1] Herrera, F. A., & Hurtado, S. (2011
engineering students. Future work will investigate these productivebehaviors to understand better how they counteract less productive (i.e., surface modeling)behaviors.AcknowledgmentsWe thank the University of Illinois System for providing the funding for this research, as well asthe members of the mobileSHIELD team. We wish to also acknowledge the generous support ofthe UIUC Industrial and Enterprise Systems Engineering (ISE) Research Experience forUndergraduates (REU).References[1] U. Johansson-Sköldberg, J. Woodilla, and M. Çetinkaya, “Design thinking: past, present and possible futures,” Creativity and innovation management, pp. 121-146, 2013. https://doi.org/10.1111/caim.12023[2] D. P. Crismond, and R. S. Adams, “The Informed
, “Curriculum visualization in 3D,” in Proceedings of the twelfth international conference on 3D web technology, New York, NY, USA, Apr. 2007, pp. 177–180. doi: 10/cwn2wh.[2] S. Kriglstein, “Analysis of Ontology Visualization Techniques for Modular Curricula,” in HCI and Usability for Education and Work, Berlin, Heidelberg, 2008, pp. 299–312. doi: 10/dmvmx7.[3] R. Zucker, “ViCurriAS: A Curriculum Visualization Tool for Faculty, Advisors, and Students,” J. Comput. Sci. Coll., vol. 25, no. 2, pp. 138–145, Dec. 2009.[4] S. M. MacNeil, M. M. Dorodchi, E. Al-Hossami, A. Benedict, D. Desai, and M. J. Mahzoon, “Curri: A Curriculum Visualization System that Unifies Curricular Dependencies with Temporal Student Data,” presented at the 2020 ASEE
Paradigm of Instructional Theory, C. Reigeluth, ed., Evanston, IL,USA: Routledge, 1999, pp. 91-114.[5] S. Land, M. Hannafin, and K. Oliver, "Student centered learning environments," inTheoretical Foundations of Learning Environments, D. Jonassen and S. Land, eds., Evanston, IL,USA: Routledge, 2012.[6] J. Lu, S. Bridges, and C.E. Hmelo-Silver, "Problem-based learning," in The CambridgeHandbook of the Learning Sciences, 2nd ed., R.K. Sawyer, ed., Cambridge, UK: CambridgeUniversity Press, 2014, 298-318.[7] G. Siemens, "Connectivism: A learning theory for the digital age," Int. J. of InstructionalTechnol. & Distance Learn., Jan. 2005, http://www.itdl.org/Journal/Jan_05/article01.htm(accessed Dec. 12, 2021).[8] M. Ito, K. Gutiérrez, S. Livingstone
experience to beamong the most significant predictors. Students’ programming self-efficacy was consistentlynoted as being a good predictor of success in the course [6], [9], [12].As noted above, the last three studies mentioned here ( [2], [6], [7]) constitute the recent researchthat validated results on a separate data set, used a large sample size, and were able to predictstudent success with high accuracy while still early in a CS1 course. Our work adds to this list ofstudies, while requiring less extensive data collection. Specifically, Ahadi et al.’s method [2]requires an instrumented development environment, Liao et al’s [7] requires “clicker” data fromstudent responses to in-class questions, and Quille and Bergin’s [6] requires exit scores
as the seasonality of these time series, which will also haveenough history to apply these forecasting methods.In summary, this paper explores the use of LMS data related to assignments and other gradedactivities in gaining insights into how students advance through courses. It describes atime-based approach to using this data to predict student performance outcomes at the end of thecourse from any given time point during the course. The ultimate goal is to be able to use suchpredictions to implement early intervention measures and improve student retention.Bibliography[1] R. Umer, A. Mathrani, T. Susnjak and S. Lim, "Mining Activity Log Data to Predict Student's Outcome in a Course," in Proceedings of the 2019 International Conference on
improving theirinterest in engineering and STEM.VII. Study Limitations and Next StepsThe generalizability of the results of this study is limited by study context and participants. Thestudy took place at one private high school with one teacher and seventeen students to date, all ofwhich were advanced learners. Thus, the ability to infer potential impacts on high school scienceteachers and students is limited. The other two lessons developed during the teacher professionaldevelopment workshop will be conducted to increase the sample size of this study. Additionally,performing these lessons in schools with greater representative student diversity would alsoenhance our ability to generalize impact.VIII. References[1] S. L. Robinson and J. A. Mangold
):• I definitely really liked the fact that you chose to solve the problems live - it helped understand your thought process for each step. Your explanations were really well explained and detailed. I also like how for question two, for example, you didn't just write the units, but you explained the meaning of Kp, the equation and how you got your final units.• The explanation was very thorough and the exam solutions themselves were very neat and easy to follow. the only error I noticed was that in #5, your math for the limit is slightly wrong, as when s goes to 0, there is still the + 1 in each parenthesis, meaning the terms dont reduce to 0, but the K value instead. I believe there should be an s in the
Degree Programs,” in 2020 ASEE Virtual Annual Conference Content Access Proceedings, Virtual On line: ASEE Conferences, Jun. 2020, p. 34069. doi: 10.18260/1-2--34069.[2] E. A. Kuley, S. Maw, and T. Fonstad, “Engineering Student Retention and Attrition Literature Review,” Proc. Can. Eng. Educ. Assoc. CEEA, Aug. 2015, doi: 10.24908/pceea.v0i0.5813.[3] A. Sithole, E. T. Chiyaka, P. McCarthy, D. M. Mupinga, B. K. Bucklein, and J. Kibirige, “Student Attraction, Persistence and Retention in STEM Programs: Successes and Continuing Challenges,” High. Educ. Stud., vol. 7, no. 1, pp. 46–59, 2017.[4] M. W. Ohland, R. A. Long, S. M. Lord, M. K. Orr, and C. E. Brawner, “Expanding Access to and Participation in the
. Studentsindicated that industry involvement aided them in improving their performance in five corecourse outcomes, as well as increasing project deliverable quality and gaining additionalemployability skills. Industry members likewise perceived an improvement in student outcomes,community outcomes, and a net benefit for themselves and their employers through theirengagement. This partnership model could be adopted by other programs to increaseparticipation of industry members in their programs.References[1] S. R. Brunhaver, R. F. Korte, S. Barley and S. D. Sheppard, Bridging the gaps between engineering education and practice. In US engineering in the global economy, Chicago, IL: University of Chicago Press, 2017.[2] W. Groeneveld, J. Vennekens and K
Paper ID #38334Analysis of factors that influence the academic performance offirst-year Chilean engineering studentsMs. Cristian Saavedra-Acuna, Universidad Andres Bello, Concepcion, Chile Cristian Saavedra is an assistant professor at the School of Engineering at the University Andres Bello in Concepcion, Chile. He holds a bachelorˆa C™s degree in Electronics Engineering and a masterˆa C™s degree in Technological Innovation and EntrepreneurshiDr. Monica Quezada-Espinoza, Universidad Andres Bello, Santiago, Chile Monica Quezada-Espinoza is a professor and researcher at the School of Engineering at the Universidad Andres
evaluations: the causal role ofdepartment gender composition. Proceedings of the National Academy of Sciences 120(4):e2118466120 DOI:10.1073/pnas.2118466120Beigpourian, B., Ohland, M. W., & Ferguson, D. M. (2020) Effect of Psychological Safety on theInteraction of Students in Teams. Paper presented at 2020 ASEE Virtual Annual ConferenceContent Access, Virtual On line . 10.18260/1-2—34497Carlone, H.B. and Johnson, A. (2007) Understanding the science experiences of successfulwomen of color: Science identity as an analytic lens. Journal of Research in Science Teaching44(8): 1187-1218.Claussen S., Tsai, J.Y., Johnson K., Blacklock J. and Leydens J.A. (2021) Exploring the nexusbetween students’ perceptions of sociotechnical thinking and construction
minute podcast again (or modify your original plan)5 Production 10 - 13 Update Storyboard Based on Feedback: Look at and planning address provided revisions, practice for time and consider format items (intro/outro, other sound items?)6 Podcast 14 - 16 Final Project + Reflection: Produce final podcast(s) and production and upload for distribution. Complete the final Metacognitive distribution Reflection.3.2 Data Collection The data was collected using a metacognitive reflection assignment consisting of twosections, with three questions in each section. The first set of three
, monitoring, evaluating, andmaking relevant changes to produce desirable solutions, may need to be strategically built intothe teaching curriculum and explicitly taught. Currently, qualitative analyses are in progress tounderstand how students’ metacognitive knowledge about task (MKT) inform their self-regulation of Cognition (SRC) and how students’ SRC dynamically evolve during problemsolving.AcknowledgmentThis material is based upon work supported by the National Science Foundation under Grant No.2110769. Any opinions, findings, and conclusions or recommendations expressed in this materialare those of the author(s) and do not necessarily reflect the views of the National ScienceFoundation.References[1] H. A. Simon, The Sciences of the Artificial
gestures and facial expressions when talking. Creates an environment in the class where you can easily ask Democratic Attitude questions Value Dimension It makes you feel that s/he gives importance to your opinions. Respect Dimension It makes you feel that s/he respects your opinions. B. Population and sampling The population of the study consisted of capstone design projects students from 5 departments in Engineering school, including Mechanical Engineering (ME), Electrical and Computer Engineering (ECE), Civil & Environmental Engineering (CEE), Engineering entrepreneurship (E-ship), and Chemical
air quality, environmental justice, and engineering education efforts to create inclusive classrooms and programming.Dr. Melissa M. Bilec, University of Pittsburgh Dr. Bilec is an associate professor in the Swanson School of Engineeringˆa C™s Department of Civil and Environmental Engineering. Dr. Bilecˆa C™s research program focuses on the built environment, life cycle assessment, sustainable healthcare, and energy imDr. Amy Hermundstad Nave, Colorado School of Mines Amy Hermundstad Nave is a Faculty Developer in the Trefny Innovative Instruction Center at the Col- orado School of Mines. She earned a BS in Mechanical Engineering from Colorado State University before going on to earn her PhD in Engineering Education
‘Inspiration phase,’” Medium, Mar. 18, 2020. https://medium.com/@neemz/design-thinking-steering-the-inspiration-phase-36cd53f6feaf (accessed Apr. 26, 2020).[6] J. P. Goetz and M. D. LeCompte, “Ethnographic research and the problem of data reduction,” Anthropology & Education Quarterly, vol. 12, no. 1, pp. 51–70, 1981, doi: 10.1525/aeq.1981.12.1.05x1283i.[7] Y. S. Lincoln and E. G. Guba, Naturalistic Inquiry. SAGE, 1985.[8] H. S. Wilson and S. A. Hutchinson, “Triangulation of Qualitative Methods: Heideggerian Hermeneutics and Grounded Theory,” Qual Health Res, vol. 1, no. 2, pp. 263–276, May 1991, doi: 10.1177/104973239100100206.[9] N. Torabi, “Design Thinking — brainstorming through the ‘Ideation’ phase,” Medium, Mar
platform was a significant factor in improving average overalland project grades even after considering the effects of the control variables (i.e., GPA, major,family background, field experience, effort level, and past BIM experience). It is expected thatOER is effective in helping students to learn building information modeling more effectively.KEYWORDS: Open Educational Resource; Innovative Teaching, Flipped Classroom, BuildingInformation Modeling (BIM); Architecture, Engineering, and Construction Pedagogy;Quantitative MethodsINTRODUCTIONThe Internet has enabled access to open information resources since early 1990’s. Online learningmediums such as e-books, podcasts, streamed videos, and virtual participatory environments suchas social
, Florida, 2019.[2] S. Papert and I. Harel, Situating Constructionism: Cambridge, MA: MIT Media Laboratory., 1990.[3] C. Hayes and Y. Graham, "Understanding the building of professional identities with the LEGO® SERIOUS PLAY® method using situational mapping and analysis," Higher Education, Skills and Work-Based Learning, vol. 10, pp. 99-112, 2020.[4] C. Nerantzi and S. McCusker, "A taster of the LEGO(R) Serious Play(R) method (LSP) for Higher Enducation," in OER14 Building Communities of Open Practice, Newcastle, UK, 2014.[5] P. Kristiansen and R. Rasmussen, Building a Better Business using the LEGO Serious Play Method: Wiley, 2014.[6] A. R. James, "Lego Serious Play: a