improving the set of concepts available for furtherdevelopment in the design process.AcknowledgementsWe are grateful to Jamie Phillips for inviting us to his classroom to work with his students. Thiswork is funded by The National Science Foundation, Engineering Design and Innovation (EDI)Grant 0927474.References[1] Ahmed, S.; Wallace, K. M.; Blessing, L. T. M. (2003). Understanding the differences between how novice and experienced designers approach design tasks. Journal of Research in Engineering Design, 14, 1-11.[2] Cross, N. (2001). Design cognition: Results from protocol and other empirical studies of design activity. In C. M. Eastman, W. M. McCracken & W. C. Newstetter (Eds.), Design knowing and learning: Cognition in design
you think about graduate school? FemProf Participant: Even though I already did research, I didn‟t really understand very well the whole entire master‟s/Ph.D. degree process. At the first school I was a tutor, and really enjoyed that. Since I‟m studying engineering, I just don‟t want to be a teacher in high school, and didn‟t understand how to become a professor. FemProf coordinators have given me seminars and how about grad school works, and I have talked to them individually about their experiences in the doctoral degree, as the doctoral degree sounds like a super-hard thing but it‟s actually not as scary as it seems.Program directors highlight ways women can support one another in their
of the author(s) and do not necessarily reflect the views of the NationalScience Foundation (NSF). The authors also wish to thank Karen Clark, Research Assistant,Institute for Public Policy and Survey Research, Office for Survey Research at MSU for hertimely and efficient programming, survey administration, and data retrieval. We are alsoindebted to Mr. Timothy Hinds, the instructor of EGR 100, who has generously allowed us touse his class as a contact point for the CF program.Bibliography1. Seymour, Elaine and Nancy M. Hewitt (1997). Talking about Leaving: Why Undergraduates Leave the Sciences. Boulder, CO, Westview Press.2. Keller, J.M. (1983). Motivational design of instruction. Instructional-design theories and models: An
traditional formative frameworkassociated with K-12 education, but rather, in relation to what one might deem, the positiveoutcome framework associated with students majoring in STEM areas at the university level.The motivation for this approach is based on an argument that, while university students inSTEM disciplines are considered as STEM education achievements, fundamental flaws in basicconceptual mathematical knowledge persist; flaws that if more aggressively addressed at the K-12 level could result in attracting more youth to pursue STEM interests. The argument is basedon personal anecdotal evidence associated with the author‟s experiences. Hence, it does not havea rigorous foundation. Nonetheless, it is an argument that will hopefully resonate
: Summative instructional events are now presented. Knowledge and learner centered. Go public: This is a high stakes motivating component introduced to motivate the student to do well. Learner and community centered.Challenge 2…NThe following progressively more ambitious challenges enable the student to increasinglydeepen their knowledge of the topic being explored. Repeat the complete legacy cycle for eachchallenge.Reflect BackThis gives student the opportunity for self-assessment. Learner centered.Leaving LegaciesThe student is asked to provide solutions and insights for learning to the next cohort of students,as well as to the instructor(s). Community centered. The legacy cycle contains steps or activities that appeal to
Session 2155An Emerging Template for Professionally Oriented Faculty Reward Systemsthat Supports Professional Scholarship, Teaching, and Creative Engagement in Engineering Practice for the Development and Innovation of Technology D. A. Keating, 1 T. G. Stanford, 1 J. W. Bardo, 2 D. D. Dunlap, 2 D. R. Depew, 3 G. R. Bertoline, 3 M. J. Dyrenfurth, 3 A. L. McHenry, 4 P. Y. Lee, 5 E. M. DeLoatch, 6 S. J. Tricamo, 7 H. J. Palmer 8 University of South Carolina 1 / Western Carolina University 2 / Purdue University 3 Arizona State University East 4 / California Polytechnic State
the atmosphere. One protégé's mentor was described as"more interested in blowing his own horn than in any meaningful interaction." Another protégéagreed: "I have a lot of anger about my interaction with my mentor. All he did was offend andtalk and never listened to the protégés."7The Montclair State program described above relies heavily on the group as mentor, anetworking mentoring model discussed above.2, 3 As will be seen below, that approach stands insharp contrast to the Purdue's Faculty Mentoring Network program's reliance on the dyadicinteractions of mentor and protégé(s).The Faculty Mentoring Network at Purdue UniversityThe Faculty Mentoring Network (FMN) was conceived and implemented by the TeachingAcademy at Purdue University. The
the best word(s) to branch on at each point to reduce the overall error. The result tends to be a more accurate tree (as each branching word is explicitly chosen to reduce the classification error), but for a non-‐trivial increase in the amount of time needed to identify the appropriate words. Each item took between 8 and 10 hours for this algorithm to identify the final
Foundation. The authors would also like to acknowledge Lauren Gibboney, JosephLuke, James McIntyre, John Nein, and Joshua Rush for their work developing the Adaptive Maptool.6. References[1] T. L. Russell, The No Significant Difference Phenomenon. North Carolina State University, 1999.[2] D. F. Dansereau, “Node-Link Mapping Principles for Visualizing Knowledge and Information,” in Knowledge and Information Visualization, vol. 3426, S.-O. Tergan and T. Keller, Eds. Berlin, Heidelberg: Springer Berlin Heidelberg, 2005, pp. 61–81.[3] G. W. Ellis, A. Rudnitsky, and B. Silverstein, “Using concept maps to enhance understanding in Engineering Education,” International Journal of Engineering Education, vol. 20, pp. 1012–1021, 2004.[4] M. W. A
Foundation, 2018.[2] T. Jungert and M. Rosander, “Self-efficacy and strategies to influence the study environment,” Teaching in Higher Education, vol. 15, no. 6, pp. 647–659, Dec. 2010. https://doi.org/10.1080/13562517.2010.522080[3] A. Ahmad and T. Safaria, “Effects of Self-Efficacy on Students’ Academic Performance,” Journal of Educational, Health and Community Psychology, vol. 2, no. 1, 2013.[4] R. W. Lent, S. D. Brown, J. Schmidt, B. Brenner, H. Lyons, & D. Treistman, "Relation of contextual supports and barriers to choice behavior in engineering majors: Test of alternative social cognitive models," Journal of Counseling Psychology, vol. 50, no. 4, pp. 458–465, 2003.[5] D. R. Schaefer, S
and gaining leadership experience. Also, peer mentors thought it was a funthing to do. Some wanted to give back and signed up because they cared about the success oftheir peers and younger students, and it was a good way to meet other people. Once selected, the peer mentors created a one-paragraph bio that included interestsoutside of class. The bios of all the peer mentors were then shared with all of the incomingfirst-year students. Next, a preference survey was sent out to all the first-year students to indicatewhich peer mentor(s) they were interested in being paired with. In the survey, it was noted thatthese groups were not intended to be groups of majors (i.e., all mechanical engineers), but ratherstudents were encouraged to
engineering students. 11 References[1] R. W. Bybee, “The BSCS 5E instructional model: Personal reflections and contemporary implications,” Sci. Child., vol. 51, no. 8, pp. 10–13, 2014.[2] S. Rodriguez, K. Allen, J. Harron, and S. A. Qadri, “Making and the 5E Learning Cycle,” Sci. Teach., vol. 86, no. 5, pp. 48–55, Jan. 2019, doi: 10.2505/4/tst18_086_05_48.[3] R. P. McCurdy, M. L. Nickels, and S. B. Bush, “Problem-based design thinking tasks: Engaging student empathy in STEM,” Electron. J. Res. Sci. Math. Educ., vol. 24, no. 2, pp. 22–55, 2020, Accessed: Jan. 25, 2024. [Online]. Available: https://ejse.southwestern.edu
the group encountered in the virtual laboratory was to decide whatparameters to use for their first experiment. In this encounter, the group is confronted with and addressesthis gap. 1 Blue: So, now we have to pick the range. 2 Red: So, the first six, do you want to do a higher range? 3 Green: 5, 10... 15, 20, 25- 4 Red: Well, it would be up to 25 because one's a control. Right? So, we only have five. 5 Green: Well, we want to go up to a maximum of 100, right? That's the goal? 6 Red: We can do that. So, do you want to do obviously 10, but... 20's? That would give us the wide range for zero to 100 for the first run. 7 Green: We could
, including Oklahoma StateUniversity, the University of Nebraska-Lincoln, and California Polytechnic State University –San Louis Obispo, share in the grant.However, this benchmark study is limited to Oklahoma State University‟s role in the program.Oklahoma State University required the 31 participants enrolled in the pilot program to completea three-semester sequence of classes, during which they collectively completed fiveinterdisciplinary projects for clients. Two of those projects, including an arena drag and a petbed, are now in production. The program is required for senior engineering participants, but isonly recommended for participants from the other disciplines. Students who participated in thisevaluation were able to earn seven credit hours
(CEAS), the Integrated Teaching and LearningProgram (ITLP) emerged in the 1990’s from student demand and with college recognition thatattrition was a concern. At the time, CU offered hands-on experiences only in select junior- orsenior-design courses. “‘From an engineering perspective, lab classes are good because they giveyou a feeling for what you’re learning, and if you’re a visual learner, ITLP can help you learnfaster and better,’ said Eric Peers, an electrical and computer engineering senior,” who chairedthe student movement to launch more access to hands-on learning [28]. Envisioning an approachthat was more targeted for specific populations was not yet on the table.Improved student retention and satisfaction were early ITLP outcomes [29
and developed tools to study the alignment of products and services with organizational processes as an organization seeks to address needs and bring new products and services to the market.Dr. Ruth Ochia P.E., Temple University Dr. Ruth S. Ochia is a Professor of Instruction with the Bioengineering Department, Temple University, Philadelphia, Pa. Her past research interests have included Biomechanics, primarily focusing on spine-related injuries and degeneration. Currently, her research interest are in engineering education specifically with design thinking process and student motivation.Dr. Holly M Golecki, University of Illinois Urbana-Champaign Dr. Holly Golecki (she/her) is a Teaching Assistant Professor in
, Aurora University, United States – Illinois, 2018. [Online]. Available:https://www.proquest.com/docview/2384858972/abstract/CD5B029B15BE4E11PQ/1[3] H. Jabbar, L. Schudde, M. Garza, and S. McKinnon-Crowley, “Bridges or barriers? Howinteractions between individuals and institutions condition community college transfer,” TheJournal of Higher Education, vol. 93, no. 3, pp. 375–398, Apr. 2022. [Online]. Available:https://doi.org/10.1080/00221546.2021.1953339.[4] J. Koyama and S. Desjardin, “Building bridges and borders with deficit thinking,” Educ.Real, vol. 44, p. e86415, Apr. 2019. [Online]. Available: https://doi.org/10.1590/2175-623686415.[5] “Dismantling Deficit Thinking: A strengths-based inquiry into the experiences of transferstudents in and
sustainability into the supply chain supply chain decisions," Journal of Cleaner Production,processes. It has a very low-key influence on the final decision. vol. 16, pp. 1688-1698, 2008.It is indicated that integrating sustainability into the supply chain [8] S. Seuring and M. Müller, "From a literature review to aprocesses is expensive and require a big amount of money especially conceptual framework for sustainable supply chainfor small to medium enterprises. Also, lack of knowledge obviously management. ," Journal of Cleaner Production, vol. 16, pp.appears to be a common hindrance for establishing a sustainable 1699-1710, 2008.supply chain approach. Employees are
The University of Texas at Arlington, Arlington, TX Copyright © 2025, American Society for Engineering Education 10 AcknowledgmentWe would like to acknowledge the Klesse College of Engineering and Integrated Design (KCEID)and the Office of Sustainability at The University of Texas at San Antonio (UTSA) for supportingthis project through the KCEID Incentive Opportunity Award. Any opinions, findings, conclusions,or recommendations expressed in this material are those of the author(s) and do not necessarilyreflect the views of UTSA. ReferencesAbioye, S. O., Oyedele, L
belowsummarizes the findings from our analysis of each article.Each article included undergraduate (and sometimes graduate) students working on anengineering design problem in teams of varying sizes. We focused on understanding the contextof each paper, the technique(s) used to elicit the mental model (“Elicitation Process”) from theteams and then the process used by the research team or the students themselves to generate arepresentation of that mental model (“Model Generation Process”). The design contexts in whichstudents were working were different and included topics related to issues with transportation insnow (Helm et al., 2017), designing low-income housing (Quinones et al. 2009), or designing anew desk lamp (Muller et al., 2009). The
participants a copy of the transcripts to obtain their feedback. Weare committed to exclude any language that the participants deem necessary.ResultsBased on the outcomes of our data analyses, the findings are forthcoming. Our findings will highlight the waysin which CCW influences Black and Hispanic women’s persistence in computing education in response to ourcollective need to better support this population in their attainment and representation in STEM+C disciplines.AcknowledgementThis material is based upon work supported by the National Science Foundation under Grant No. 2046079.Any opinions, findings, and conclusions or recommendations expressed in this material are those of theauthor(s) and do not necessarily reflect the views of the National
offemale role models. One additional explanation is the presence of several supportprograms such as the TWU Multi-Ethnic Biomedical Research Program, the Women IneNgineering (WIN), and the Computer Science, Engineering, and Mathematics Scholars(CSEMS).According to the National Science Foundation1, the percentage of earned bachelor’sdegrees for the year 2000 in science and engineering for underrepresented minorities is15.6%. This 15.6% total in bachelor ‘s degrees earned in science and engineering breaksdown into 8% Blacks / No- Hispanics, 6.9% Hispanics and 0.7% American Indian orAlaskan Natives. At TWU the total percentage of underrepresented minorities in thesciences is 38.8% of the 484 total science majors with known ethnicity. In fact, 24.79
moreaccurately assess whether the online sketching questions are indeed measuring what we intendthem to measure.As noted previously, the first five weeks of the semester in EGT 120 are devoted solely to handsketching, before introducing CAD work, and the sketching activities continue throughout thesemester. Considerable time is spent in class providing formative and summative feedback withthese conventional sketching practices. Because of the importance of sketching in developingvisualization abilities, even with the success of the format change on exams, there are no plans toreplace current lecture and lab sketching activities with items and exercises similar to those beingused on exams.References[1] N.L. Veurink, A.J. Hamlin, J. C. M. Kampe, S. A
institution.” Journal of Hispanic Higher Education, vol. 20, no. 3, pp. 297-312, 2021.[4] M. F. Rogers-Chapman. "Accessing STEM-focused education." Education and Urban Society, vol. 46, no. 6, pp. 716-737, 2014.[5] J. L. Petersen and J. S. Hyde. "Trajectories of self-perceived math ability, utility value and interest across middle school.” Ed. Psych., vol. 37, no. 4, pp. 438-456, 2017.[6] D. L. and Z. Lavicza, “Dissecting a Cube as a Teaching Strategy for Enhancing Students’ Spatial Reasoning,” Proceedings of Bridges 2019, pp. 319–326,[7] u/diegolieban, “GeoGebra and 3D printing: Mathematics as a creative practice,” GeoGebra, Feb. 03, 2020. www.geogebra.org/m/pkfzccjw (accessed Jan. 16, 2021).[8] Y. Gao, S. Liu, M. M. Atia, and A
optimize NLP use in qualitative analyses and demonstrate itsefficacy in further expanding qualitative research capacity in engineering education research.Future research will also explore code and theme frequency by gender, race, and ethnicity andalso explore error rates among those different groups.References[1] E.D. Liddy, "Natural Language Processing," in Encyclopedia of Library and Information Science, 2nd Ed., NY, Marcel Decker, Inc., 2001.[2] S. Tenny, J. M. Brannan, G. D. Brannan, Qualitative Study. Treasure Island, FL: StatPearls Publishing, 2022. Available from: https://www.ncbi.nlm.nih.gov/books/NBK470395/[3] "About e-rater", Educational Testing Service (ETS). [online]. Available: https://www.ets.org/erater/about.html[4] A
.[6] K. Mite-Baidal, C. Delgado-Vera, E. Solís-Avilés, A. H. Espinoza, J. Ortiz-Zambrano, and E. Varela-Tapia, “Sentiment analysis in education Domain: A systematic literature review,” in Technologies and Innovation, R. Valencia-García, G. Alcaraz-Mármol, J. Del Cioppo- Morstadt, N. Vera-Lucio, and M. Bucaram-Leverone, Eds., Cham: Springer International Publishing, 2018, pp. 285–297.[7] Y. Sun, Z. Ming, Z. Ball, S. Peng, J. K. Allen, and F. Mistree, “Assessment of Student Learning Through Reflection on Doing Using the Latent Dirichlet Algorithm,” J. Mech. Des., vol. 144, no. 12, Sep. 2022, doi: 10.1115/1.4055376.[8] U. Naseem, I. Razzak, K. Musial, and M. Imran, “Transformer based Deep Intelligent
Encyclopedia of Communication Research Methods. pp 1-11. 10.1002/9781118901731.iecrm0011[2] Bajwa, M. (2014). Emerging 21(st) Century Medical Technologies. Pakistan journal of medical sciences, 30(3), 649-655. https://doi.org/10.12669/pjms.303.5211[3] Costanza-Chock, S. (2020). Design Justice: Community-Led Practices to Build the Worlds We Need. MIT Press.[4] Oudshoorn, N., Rommes, E., & Stienstra, M. (2004, 2004/01/01). Configuring the User as Everybody: Gender and Design Cultures in Information and Communication Technologies. Science, Technology, & Human Values, 29(1), 30-63. https://doi.org/10.1177/0162243903259190[5] Cutting, K., & Hedenborg, E. (2019). Can Personas Speak? Biopolitics in Design
., judging) student work on these two tasks. Participation in actual ACJ panelswill enable judges to gain a “feel” for what this assessment technique entails and how it couldbe used to enhance first-year engineering students learning experiences. At the end of theFYEE conference, results from the panels will be available for those who are interested.AcknowledgementThis work was made possible by a grant from the National Science Foundation (NSF#2020785). Any opinions, findings, and conclusions, or recommendations expressed in thismaterial are those of the authors and do not necessarily reflect the views of the NationalScience Foundation.References[1] G. J. Strimel, S. R. Bartholomew, S. Purzer, L. Zhang, and E. Yoshikawa Ruesch, “Informing
).In the first step of the analysis, the percent success scores of the cohort in the attainment of eachof the seven SO by graduation is calculated (Table 1). Table 1: Percent Achievement of Student Outcomes by Class 2021The percent success scores of the cohort in each course are defined as the percentage of studentsthat are considered successful by achieving the benchmark score in the assessment rubric of therelevant SO. Table 1 summarizes which SO is assessed in which course(s) and semester. Forexample, in Course 5, 88% of the students scored equal or higher than the benchmark score of 3out of 4 in SO6. This assessment analysis is already part of Criterion 4. The average SO percentscores in Table 1 are calculated by arithmetic