Journal of Engineering Education, 43(6), 927–949. https://doi.org/10.1080/03043797.2018.1462766Faber, C., & Benson, L. C. (2017). Engineering students' epistemic cognition in the context of problem- solving. Journal of Engineering Education, 106(4), 677–709. https://doi.org/10.1002/jee.20183Gillborn, D., Warmington, P., & Demack, S. (2018). QuantCrit: Education, policy, 'big data' and principles for a critical race theory of statistics. Race Ethnicity and Education, 21(2), 158–179. https://doi.org/10.1080/13613324.2017.1377417Godwin, A. (2017). Unpacking Latent Diversity. 2017 ASEE Annual Conference & Exposition Proceedings, Columbus, OH. https://peer.asee.org/29062Godwin, A., Benedict, B., Rohde
where sectionsof the course had teams with: homogeneous, heterogeneous, and random (control) cultural competency. Culturalcompetency was examined using the Miville-Guzman Universality-Diversity Scale short form (M-GUDS-S) whichmeasures a single construct of Universal- diversity orientation (UDO) with three factors. Team dynamics weremeasured using instruments of team effectiveness at the end of the semester. The paper discusses the evidence ofreliability and validity of the self-reported instruments with an analysis of differences in the team dynamics ofsections based on homogeneous, heterogeneous, and control group of M-GUDs score. The study discusses theimplications of assessing the cultural competencies of students in the context of teamwork
students in the dataset with identities underrepresented in STEM. Questions of how to moveadditional types of engineering curricula online, how to support underrepresented students inSTEM, and how to provide an engaging learning experience in Ecampus curricula are popular butin-progress areas of engineering education research. The outcomes from our project can help tolay the groundwork for more broad and theoretical investigation into these important but complexpedagogical questions.References[1] Alhazbi, S., & Hasan, M. A. (2021). The role of self-regulation in remote emergency learning: Comparing synchronous and asynchronous online learning. Sustainability, 13(19), 11070.[2] Blayone, T. J., Barber, W., DiGiuseppe, M., & Childs, E
engineers," Proceedings of the IEEE, vol. 88, no. 8, pp. 1367-1370, 2000.[2] L. Small, K. Shacklock, and T. Marchant, "Employability: a contemporary review for higher education stakeholders," Journal of Vocational Education & Training, vol. 70, no. 1, pp. 148-166, 2018.[3] R. J. Marandi, B. K. Smith, R. F. Burch, and S. C. Vick, "Engineering soft skills vs. engineering entrepreneurial skills," The International Journal of Engineering Education, vol. 35, no. 4, pp. 988-998, 2019.[4] H. Jang, "Identifying 21st century STEM competencies using workplace data," Journal of Science Education and Technology, vol. 25, pp. 284-301, 2016.[5] L. Ballesteros-Sanchez, I. Ortiz-Marcos, and R. Rodriguez-Rivero
second instructor of the course will also be involvedin the content analysis process to ensure reliability.References[1] M. L. V. Blerkom, "Class Attendance in Undergraduate Courses," The Journal of Psychology, vol. 126, no. 5, pp. 487-494, 1992.[2] P. Friedman, F. Rodriguez and J. McComb, "Why students do and do not attend classes: Myths and realities," College Teaching, vol. 49, no. 4, pp. 124-133, 2001.[3] N. Fjortoft, "Students' motivations for class attendance," American Journal of Pharmaceutical Education, vol. 69, no. 1, pp. 107-112, 2005.[4] S. Moore, C. Armstrong and J. Pearson, "Lecture absenteeism among students in higher education: A valuable route to understanding student motivation," Journal of Higher Education
a framework assessing Maker programs’ impact oncareers. Our primary activity addresses the immediate need to understand the types of metricsmost appropriate to measure career impacts of Makerspace experiences. From these results weplan to develop and calibrate the tool(s) needed to apply the metrics framework for Activity 2.In Activity 2, we will build on the framework to implement a set of tools that stakeholders canapply generally across design and fabrication studies to assess the relationship betweenmakerspace experiences and career readiness.In this Work In Progress paper, we lay the foundation for the activities of our project, and shareout some preliminary observations based on initial interviews with our target populations
contributing to their mastery?," Psicologia: Reflexao e Critica, vol. 35, 2022.[2] L. Riebe, A. Girardi, and C. Whitsed, "A systematic literature review of teamwork pedagogy in higher education," Small Group Research, vol. 47, no. 6, pp. 619-664, 2016.[3] A. Planas-Lladó, L. Feliu, F. Castro, R. M. Fraguell, G. Arbat, J. Pujol, J. J. Suñol, and P. Daunis-i-Estadella, "Using peer assessment to evaluate teamwork from a multidisciplinary perspective," Assessment & Evaluation in Higher Education, vol. 43, no. 1, pp. 14-30, 2018.[4] D. Weaver, and A. Esposto, "Peer assessment as a method of improving student engagement," Assessment & Evaluation in Higher Education, vol. 37, no. 7, pp. 805-816, Nov. 2012.[5] J. S. Kane
creativity and innovation ineducation." Journal of education and learning, 2017, pp. 201-208.[2] S. A. Kalaian and R. M. Kasim, “Effectiveness of various innovative learning methods inhealth science classrooms: a meta-analysis,” Adv in Health Sci Education, 2017 pp. 1151–1167.[3] Freeman, S., Eddy, S. L., McDonough, M., Smith, M. K., Okoroafor, N., Jordt, H., &Wenderoth, M. P. Active learning increases student performance in science, engineering, andmathematics. Proceedings of the national academy of sciences, 111(23), 2014, pp. 8410-8415.[4] Johnson, David W., and Roger T. Johnson. "Cooperative learning: The foundation for activelearning." Active learning—Beyond the future, 2018, pp. 59-71.[5] Lin, Galvin Sim Siang, et al. "Innovative
Paper ID #44482Work in Progress: Stigma of Mental Health Conditions and its Relationshipto Conditions’ Knowledge and Resource Awareness among Engineering StudentsMatilde Luz Sanchez-Pena, University at Buffalo, The State University of New York Dr. Matilde S´anchez-Pe˜na is an assistant professor of Engineering Education at the University at Buffalo – SUNY where she leads the Diversity Assessment Research in Engineering to Catalyze the Advancement of Respect and Equity (DAREtoCARE) Lab. Her research focuses on developing cultures of care and well-being in engineering education spaces, assessing gains in institutional efforts
intrinsic value was found to be a mediating factor and predictor of this behavior.Specifically within the field of engineering, Hasbun et al. 's [3] study on motivating doctoral studentssupports that the end of coursework marks a critical point in students’ motivation towards degreecompletion.Recent studies have explored engineering graduate students' motivation through different theories andframeworks, including Identity Based Motivation (IBM), Future Time Perspective (FTP),Expectancy-Value Theory (EVT), Graduate Engineering Identity (GEI), and Graduate attrition decision(GrAD) [5], [6], [7], ,[8]. Findings from these studies have shown that graduate engineering identity is akey contributor to graduate student motivation and persistence
; Beddoes, K. (2013). Team effectiveness theory from industrialand organizational psychology applied to engineering student project teams: A research review. Journalof Engineering Education, 102(4), 472-512.Cardador, M. T., & Caza, B. B. (2018). The subtle stressors making women want to leave engineering.Harvard Business Review: https://hbr.org/2018/11/the-subtle-stressors-making-women-want-to-leave-engineering?ab=at_art_art_1x1Campero, S. (2021). Hiring and intra-occupational gender segregation in software engineering. AmericanSociological Review, 86(1), 60-92.Crenshaw, K. (1989). Demarginalizing the Intersection of Race and Sex: A Black Feminist Critique ofAntidiscrimination Doctrine, Feminist Theory, and Antiracist Politics. University of
[31]. As design thinking is naturally embedded within engineeringproblems, it is essential for students to start to be exposed as early as possible to acquire thenecessary problem-solving skills. To initiate, teachers should be equipped to teachengineering in their teaching subjects [32]. Carroll et al. [33] combined DT with a classroomlearning environment in various manners and found how DT linked to academic standardsand the learning of content in the classroom. Meanwhile, DT is interdisciplinary [34],building new scholarly spaces by combining disciplines. McLaughlin et al.’s [35] workproved this view and portrays DT’s validity across fields and institutions.In engineering, design is seen as the main or distinguishing activity [9]. As such
deployment phase, faculty see the potential benefitsof the approach despite the challenges associated with low process maturity and the time required toimplement the tagging-based approach. BibliographyAmos, J. R., Angra, S., Castleberry, C., & Stadie, O. (2021, March). Using Gradescope to Facilitate Tag- Enhanced Student Feedback [Conference presentation abstract].52nd ACM Technical Symposium on Computer Science Education. https://doi.org/10.1145/3408877.3432498Fayyad, U., Piatetsky-Shapiro, G., & Smyth, P. (1996). From data mining to knowledge discovery in databases. AI magazine, 17(3), 37-37. https://doi.org/10.1609/aimag.v17i3.1230Ideaedu.org. (n.d.). Idea's history. IDEA
between attitude andperformance outcomes.References[1] Z. Ismail, “Benefits of STEM Education,” p. 14.[2] Y. Xu and C. Maitland, “Mobilizing Assets: Data-Driven Community Development with Refugees,” in Proceedings of the Ninth International Conference on Information and Communication Technologies and Development, Lahore Pakistan: ACM, Nov. 2017, pp. 1– 12. doi: 10.1145/3136560.3136579.[3] S. I. van Aalderen-Smeets, J. H. Walma van der Molen, and I. Xenidou-Dervou, “Implicit STEM ability beliefs predict secondary school students’ STEM self-efficacy beliefs and their intention to opt for a STEM field career,” J. Res. Sci. Teach., vol. 56, no. 4, pp. 465– 485, 2019, doi: 10.1002/tea.21506.[4] Y. Liu, S. Lou, and R. Shih
, 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
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
and R. L. Hite, “Enhancing student communication competencies in STEM using virtual global collaboration project based learning,” Research in Science & Technological Education, vol. 40, no. 1, pp. 76–102, Jul. 2020. doi:10.1080/02635143.2020.1778663[5] H. J. Yazici, L. A. Zidek, and H. St. Hill, “A study of critical thinking and cross-disciplinary teamwork in Engineering Education,” Women in Industrial and Systems Engineering, pp. 185–196, Sep. 2019. doi:10.1007/978-3-030-11866-2_8[6] S. Zajac, A. Woods, S. Tannenbaum, E. Salas, and C. L. Holladay, “Overcoming challenges to teamwork in Healthcare: A Team Effectiveness Framework and evidence-based guidance,” Frontiers in Communication, vol. 6, Mar. 2021
innovations both within our course and across our curriculum. Any futuredevelopments should generate solutions while looking through the lens of student experience,with a goal to better prepare students to be technically excellent, iterative, collaborative,empathetic, and confident engineers.References1. Santana S. Instrumentation for Evaluating Design-learning and Instruction Within Courses and Across Programs. In: 2021 ASEE Virtual Annual Conference Content Access. 2021.2. Sanchez A, Blake LP, Chen D, Jones M, Mao S, Mendelson L, et al. Building Better Engineers: Critical Reflection as a High Impact Practice in Design Learning. In: 2022 ASEE Annual Conference \& Exposition. 2022.3. McNair TB, Bensimon EM, Malcom-Piqueux
, Departments and Programs. Washington, DC: American Society for Engineering Education, 2016.2. B. N. Geisinger and D. R. Raman, “Why they leave: Understanding student attrition from engineering majors”, International Journal of Engineering Education, vol. 29, pp. 914-925, 2013.3. J. Roy, Engineering by the Numbers. Washington, DC: American Society for Engineering Education, 2019.4. X. Chen, C. E. Brawner, M. W. Ohland, and M. K. Orr, “A taxonomy of engineering matriculation practices”, in 120th ASEE Annual Conference and Exposition, 2013.5. D. C. Howell, Statistical Methods for Psychology, 5th edition. Pacific Grove, CA: Duxbury, 2002.6. S. W. Raudenbush and A. S. Bryk, Hierarchical Linear Models: Applications and Data Analysis. Thousand
Paper ID #36715Environments Affecting Black Student Thriving in Engineering (BSTiE)Stephanie A Damas, Clemson University Stephanie Ashley Damas is currently a graduate student at Clemson University studying to get her Ph.D. in Engineering and Science Education. Her area of interest is Diversity and Inclusion in Engineering. She holds a bachelorˆa C™s degree in electrical engiDr. Lisa Benson, Clemson University Lisa Benson is a Professor of Engineering and Science Education at Clemson University, and the past editor of the Journal of Engineering Education. Her research focuses on the interactions between student
statistical analyses toaddress complex and nuanced research questions important to the field. Our results are consistent with Borrego et al. (2009), highlighting the importance ofquantitative methods in engineering education research. Nevertheless, our results alsodocumented the prevalence of using all quantitative, qualitative, and mixed methods in JEE, asasserted in Borrego et al. (2009). Finally, our results echo Borrego et al. (2009)’s call for usingadvanced quantitative research methods beyond the boundary of disciplinaries, as many of theadvanced methods originated from other social sciences fields. While the excessive reliance onbasic descriptive statistics is still common, our results underscore joint efforts made byengineering
education for social justice (pp. 67-84). Springer.Daly, S. R., Mosyjowski, E. A., & Seifert, C. M. (2014). Teaching creativity in engineering courses. Journal of Engineering Education, 103(3), 417-449.Dringenberg, E., Kramer, A., & Betz, A. (2022). Smartness in Engineering Education: Undergraduate Student Beliefs. Journal of Engineering Education, 111(2), 283-307. https://doi.org/https://doi.org/10.1002/jee.20452Ellestad, R. M. (2013). Bazinga! You’re an engineer… you’re_! A Qualitative Study on the Media and Perceptions of Engineers. 2013 ASEE Annual Conference & Exposition,Gena Davis Institute on Gender in Media, s. C. F., J Walter Thomason Intelligence. (2018). The "Scully Effect": I Want to Believe...In
teaching methodologies. Anotherlimitation was the inaccessibility of some articles that appeared promising for full-text screeningafter passing the abstract screening phase, due to the lack of access to the publishing journals andwebsites.AcknowledgmentThis project was supported by the Provost’s Summer Undergraduate Research and CreativeActivities (UReCA) Fellowship. Its contents, including findings, conclusions, opinions, andrecommendations, are solely attributed to the author(s) and do not necessarily represent the viewsof the Provost’s OfficeReferences 1. Allen, I. E., & Seaman, J. (2016). Online report card: Tracking online education in the
related programming. ReferencesAlavi, M., Visentin, D.C., Thapa, D.K., Hunt, G.E., Watson, R. & Cleary, M. (2020). Chi-square for model fit in confirmatory factor analysis. JAN: Leading Global Nursing Research 76 (9), 2209-2211. https://doi.org/10.1111/jan.14399Bayback, M.A. & Green, S. (2010). Confirmatory factor analysis: An introduction for psychosomatic medicine researchers. Psychosomatic Medicine 72 (6), 587-597. https://doi.org/10.1097/PSY.0b013e3181de3f8aBen-Shachar M, Lüdecke D, Makowski D (2020). Effectsize: Estimation of Effect Size Indices and Standardized Parameters. Journal of Open Source Software, 5(56), 2815. https://doi.org/10.21105/joss
," 2010 IEEE Frontiers in Education Conference (FIE), 2010, pp. S3G-1-S3G-6, doi: 10.1109/FIE.2010.5673256. 2. Rahman, F., & Andrews, C., & Wendell, K. B., & Batrouny, N. A., & Dalvi, T. S. (2019, June), Elementary Students Navigating the Demands of Giving Engineering Design Peer Feedback (Fundamental) Paper presented at 2019 ASEE Annual Conference & Exposition, Tampa, Florida. 10.18260/1-2--32699 3. Pintrich, P. R., & De Groot, E. V. (1990). Motivational and self-regulated learning components of classroom academic performance. Journal of Educational Psychology, 82(1), 33–40. https://doi.org/10.1037/0022-0663.82.1.33 4. Pintrich, P. R., Marx, R., & Boyle, R. (1993). Beyond
Paper ID #38789Stigma of mental health conditions within engineering culture and itsrelation to help-seeking attitudes: Insights from the first year of alongitudinal study ˜ University at Buffalo, The State University of New YorkMatilde Luz S´anchez-Pena, Dr. Matilde S´anchez-Pe˜na is an assistant professor of Engineering Education at University at Buffalo – SUNY where she leads the Diversity Assessment Research in Engineering to Catalyze the Advancement of Respect and Equity (DAREtoCARE) Lab. Her research focuses on the development of cultures of care and wellbeing in engineering education spaces
-visual applications.References[1] M. C. Linn and A. C. Petersen, “Emergence and Characterization of Sex Differences in Spatial Ability: A Meta-Analysis,” Child Dev., vol. 56, no. 6, pp. 1479–1498, 1985, doi: 10.2307/1130467.[2] D. F. Lohman, “Spatial Ability and G.” 1993.[3] J. Buckley, N. Seery, and D. Canty, “Investigating the use of spatial reasoning strategies in geometric problem solving,” Int. J. Technol. Des. Educ., vol. 29, no. 2, pp. 341–362, Mar. 2019, doi: 10.1007/s10798-018-9446-3.[4] N. S. Newcombe, “Picture This: Increasing Math and Science Learning by Improving Spatial Thinking,” Am. Educ., vol. 34, no. 2, p. 29, 2010.[5] H. B. Yilmaz, “On the Development and Measurement of Spatial Ability,” Int. Electron. J
Jared Markunas who assisted in the development of the survey that will inform the engagementguide prototype.References[1] D. R. Fisher, A. Bagiati, and S. Sarma, “Developing Professional Skills in Undergraduate Engineering Students Through Cocurricular Involvement,” J. Stud. Aff. Res. Pract., vol. 54, no. 3, pp. 286–302, Jul. 2017, doi: 10.1080/19496591.2017.1289097.[2] G. Young, D. B. Knight, and D. R. Simmons, “Co-curricular experiences link to nontechnical skill development for African-American engineers: Communication, teamwork, professionalism, lifelong learning, and reflective behavior skills,” in 2014 IEEE Frontiers in Education Conference (FIE) Proceedings, Madrid, Spain, Oct. 2014, pp. 1–7. doi: 10.1109/FIE
. Wiebe, “Intuition in insight and noninsight problem solving,” Memory & Cognition, vol. 15, no. 3, pp. 238–246, May 1987.[6] D. H. Jonassen, “Toward a design theory of problem solving,” Educational Technology Research and Development, vol. 48, no. 4, pp. 63–85, 2000.[7] S. E. Dreyfus, “Five-stage model of adult skill acquisition,” Bulletin of Science, Technology & Society, vol. 24, no. 3, pp. 177–181, 2004.[8] M. T. H. Chi, R. Glaser, and M. J. Farr, The nature of expertise, 1st ed. 1988.[9] E. E. Miskioglu et al., "Situating Intuition in Engineering Practice," Journal of Engineering Education, vol. 112, no. 2, pp. 418-444, 2023, doi: 10.1002/jee.20521.[10] K. A. Ericsson, N. Charness, P. J