., textbooks, internet, computationalplatforms such as MATLAB, …), except for interaction with non-team members. At the timethese interviews were administered, generative AI was neither as mature nor as easily accessibleas it is presently.The situation for developing a team response as described above sought to emulate, to first order,an authenticity found more widely in engineering as practiced outside of the traditionalclassroom environment, including, but not limited to a) small team dynamics in addressing problems of moderate complexity, moderate ambiguity, and moderate solution duration, b) a comparatively long (relative to a timed exam) time for response to the prompt, reflecting lower time-pressure in formulation of a response to
as IEEE-Student Branch andCompTIA student clubs have played a vital role in organizing and providing events for students.The team will continue to assess the outcomes, monitor the results, and make appropriatemodifications to the course to enhance student learning and academic achievement.References[ B. B. Wildman, "UKNOWLEDGE," 2024. [Online]. Available: chrome-1 extension://efaidnbmnnnibpcajpcglclefindmkaj/https://uknowledge.uky.edu/cgi/viewcontent.] cgi?article=1117&context=epe_etds.[ A. P. a. D. E. Leib Sutcher, "Supporting Principals’ Learning Key Features of Effective2 Programs," February 2017. [Online]. Available: chrome-] extension://efaidnbmnnnibpcajpcglclefindmkaj/https://learningpolicyinstitute.org/sites/defaul t/files
agrade of C or better. It is important to note however that is relatively easy to get a C or B in theclass but moderately difficult to get an A. Only 16 percent of the class got a score of A in thosetwo semesters.The EI was computed with the following formula [10]: EI = (proportion in outcome subgroup)/(proportion in cohort)Table 1 lists the results of past data disaggregation and disproportionate impact analyses on theLatinx, and female students’ subgroups enrolled in the abovementioned course from anundergraduate engineering program in West Texas, U.S. The results show proportions and the EIvalues for the entire cohort and different subgroups. Results indicate that the female and Latinxsubgroups are totally absent in the A
lead(scrum master), (2) Set up the team account and Board in Trello, (3) Add 5 initial buckets to theirBoard, and (4) Capture a screenshot of the Board each week throughout the project timeline. Theinstructor is also added to each team’s Trello Board so that he can monitor team progress bylooking at their Boards online. The team captures the weekly screenshot and saves it into a Worddocument. For each week, they add a brief discussion about (a) What progress was made, (b)What the roadblocks were, and (c) What they need to get done in the next sprint. This documentis submitted at the end of the project along with the team report and presentation slides.3.1 Initial Buckets on the Trello BoardDuring the lectures about the Agile method, students
, 2009.[3] S. M. Lord and J. C. Chen, “Curriculum design in the middle years,” in Cambridge handbook of engineering educatinon research, A. Johri and B. M. Moskal, Eds., New York, NY: Cambridge University Press, 2014, ch. 10, pp. 181–199.[4] M. A. McDaniel, J. L. Anderson, M. H. Derbish, and N. Morrisette, “Testing the testing ebect in the classroom,” European Journal of Cognitive Psychology, vol. 19, no. 4–5, pp. 494–513, 2007, doi: 10.1080/09541440701326154.[5] C. Yang, R. Potts, and D. R. Shanks, “Enhancing learning and retrieval of new information: a review of the forward testing ebect,” Science of Learning, vol. 3, no. 1, Dec. 2018, doi: 10.1038/s41539-018-0024-y.[6] H. Choi and H. S. Lee
. 2023 ASEE Annu. Conf. Expo., Baltimore, MD, 2023.[2] G. D. Bruce, “Exploring the value of MBA degrees: Students’ experiences in full-time, part-time, and executive MBA programs,” J. Educ. Bus., vol. 85, no. 1, pp. 38–44, 2009, doi:10.1080/08832320903217648.[3] S. K. Gardner and B. Gopaul, “The part-time doctoral student experience,” Int. J. DoctoralStud., vol. 7, pp. 63, 2012.[4] M. A. Cohen and S. Greenberg, “The struggle to succeed: Factors associated with thepersistence of part-time adult students seeking a master's degree,” Contin. Higher Educ. Rev.,vol. 75, pp. 101–112, 2011.[5] J. C. Yum, D. Kember, and I. Siaw, “Coping mechanisms of part‐time students,” Int. J.Lifelong Educ., vol. 24, no. 4, pp. 303–317, 2005.[6] R. Darolia, “Working
critical thinking skills with more nuance and in greater depth thanwhat can be gleaned from a group setting. In the case of the individual interviews, it has beenshown that structured multiple mini-interviews (MMIs) improve evaluation reliability andfairness [13], [20]. The inclusion of all these evaluation metrics and environments is expected toachieve a more holistic assessment. B. Written application Written questions, when designed thoughtfully, allow candidates to demonstrate theirability to reflect and grow from experience, articulate complex ideas, and present well-reasonedarguments, all of which are important skills in research. The inclusion of lighthearted creativewriting prompts can additionally highlight applicants’ curiosity
iteration of themodel in a longer format soon.AcknowledgementsThis material is based upon work supported by the National Science Foundation under Grant No.2300766. Any opinions, findings, and conclusions or recommendations expressed in this material arethose of the authors and do not necessarily reflect the views of the National Science Foundation.References[1] D. Mullins, J. Swenson, and M. McVee B., “Elementary Teacher learning of Engineering for Translanguaging Infusion (Fundamental),” presented at the ASEE, Montreal, Jun. 2025.[2] D. Mullins, J. Swenson, and M. B. McVee, “WIP: Engineering and Learning Affordances for Multilingual Learners in Elementary Classrooms,” in 2024 IEEE Frontiers in Education Conference (FIE), IEEE, Oct. 2024
(interdisciplinary program) and ME (single discipline program) to determine if there is any significant difference in performance.2) Determine impacts of lab and in-person lectures by comparing students who had a) Lab and in person lectures, b) lab and online lectures, c) no lab and in-person lectures, and d) no lab and online lectures.Students were placed in one of the four various categories which included students who eithertook the course in person or online as well as with or without lab to create four sub-categoriesdescribed in study 2 above. Each section was taught in different years. The section consisting ofno-labs had n=42 students, while students with labs were n=57. In person lecture had n=66students and online were n=33 students. For
Term 2023, D Term 2023, A Term 2023, B Term 2023, C Term 2024, D Term 2024, ATerm 2024, and B Term 2024), a total of 996 undergraduate students participated in at least onemakerspace workshop, while 2,202 students used the makerspace to work on an academic orpersonal project. These undergraduate students represented a variety of majors, includingMechanical Engineering, Electrical and Computer Engineering, Robotics, Computer Science,Business, and Arts and Science, among others. Although graduate students, faculty, and staff alsoused the makerspace, only undergraduates participated in the survey component of this study.B. Data Collection WindowsTo reach a broad audience of makerspace users, the pre-survey was included as an optional add-on to
statements included the four critical aspects of a goodproblem statement: context, a specific problem, the current state, and the ideal. At the conclusionof the activity, students reflected on the potential role of GenAI in the engineering designprocess. More details of the assignment are available in Appendix B. In the subsequent projectstages, students were allowed to use GenAI tools for solution ideation by prompting a GenAItool to generate a five-paragraph solution that meets specific criteria.Student Assessment and ResultsThe focus of these activities was not to assess how well students used GenAI, but how theyperceived it as a tool in the design process and their ability to articulate relevant ethicalconsiderations regarding its use.Assessment
of gestures was produced by eight of the ten participants. (a) (b) (c) (d) (e) (f) (g) (h) Figure 1. Iconic Gestures accompanying procedural explanations for medianThe two exceptions were Ben and Jim. Ben reversed the gesture sequence by beginning with hishands extended and palms together before spreading his hands apart (Figure 1g, 1h). In hisexplanation Ben began by incorrectly explaining that the median is the most likely outcome orvalue in a data set. In contrast, Jim described the median by saying, “if you look to the left of it[the median] you have 50%, and if you look to the right of it [the median] you have 50%. Themedian would be the one element that is right in
ADMET material testing system (Figure 3.a; see Appendix C).Students drew a straight line (green) along the gauge length of an undeformed A36 steel specimen–a ductile material (Figure 3.b); material testing concluded at failure (Figure 3.c).Data Collection. Participants' pre-lab assessment and torsional testing activities were videorecorded and transcribed. Each dyad was placed in separate areas of the engineering classroomand their responses were recorded separately. Students were asked to state their common groundsolutions to the lab instructor and completed a torsional lab testing activity. Common ground wasdetermined by the natural conclusion of discussing a conceptual question, writing their solutionson a sheet of paper without further
rate for students at CSE within their first two years on campus).InSciTE students were also recruited in summer internships in 2024, including participating innational programs such as the National Science Foundation Research Experiences forUndergraduate students or the University Innovation Fellowship.Figure 6. STEM identity growth in InSciTE students compared to non-InSciTE CSE students (a) before anyInSciTE course; (b) after experiencing two InSciTE courses. The x-axis represents the 7 categories that students canchoose from when asked to select the picture that best describes the current overlap of the image they have ofthemselves and their image of what a STEM professional is [77], with A having no overlap and G being a completeoverlap of
-Bubnienė, and V.Bučinskas, “Advanced applications of industrial robotics: New trends and possibilities,” AppliedSciences, vol. 12, no. 1, Art. no. 1, Jan. 2022, doi: 10.3390/app12010135.[3] S. Anand, Gayatri, M. K. Satyarthi, P. S. Bharti, A. Kumar, and S. Rathee, “Robotic arm 3Dprinting: Technological advancements and applications,” in Industry 4.0 Driven ManufacturingTechnologies, A. Kumar, P. Kumar, and Y. Liu, Eds., Cham: Springer Nature Switzerland, 2024,pp. 293–310. doi: 10.1007/978-3-031-68271-1_13.[4] X. Jing, D. Lv, F. Xie, C. Zhang, S. Chen, and B. Mou, “A robotic 3D printing system forsupporting-free manufacturing of complex model based on FDM technology,” Industrial Robot:the International Journal of robotics research and application
University ‘MTM Engineering Camp for Girls:’ Generating Under-Represented Pathway Prospects Through A Diversity-Rich Pre-College Outreach Project,” Women in Engineering ProActive Network, Jan. 2005.[4] J. Rodriguez, S. Butt, and T. Fredericks, “Pre-college activities to promote positive perception of engineering and engineering technology careers,” In 2014 International Conference on Interactive Collaborative Learning (ICL) (pp. 715-719). Dec. 2014. IEEE.[5] P. Kotlikoff, A. S. Rahman, and K. A. Smith, “Minding the gap: academic outcomes from pre-college programs”. Education Economics, vol. 30, no. 1, pp. 3–28, 2021.[6] B. Zhou, "Effectiveness of a Precollege STEM Outreach Program." Journal of Higher
. Addressing this area requires greater faculty engagement to clarify gradingresponsibilities and expectations, given the variability across the department. Future plansinclude creating recorded models of effective student-TA interactions, expanding our case studiesto cover diverse teaching scenarios, and curating a library of engineering problems with feedbackthat emphasize metacognitive strategies. We will continue to gather data about the trainingprogram to assess its impact on TA confidence, teaching effectiveness, and student learningoutcomes. This ongoing evaluation will help refine the training by identifying areas forimprovement and ensuring alignment with both TA needs and departmental expectations.References[1] S. B. Philipp, T. R. Tretter
40 12 7 1 36 101Figure 1: Survey Demographics – 100% Stacked Columns show the survey demographicresponses for (a) gender, (b) ethnicity, and (c)international status disaggregated by degreeprogram. Figure 2d shows the total number of responses disaggregated by the samedemographics.The responses were disaggregated along demographics, and degree programs and compared theenrollment data to understand survey representativeness as shown in Figure 2. Survey Representativeness -40.0% -30.0% -20.0% -10.0% 0.0% 10.0% 20.0% 30.0% 40.0% MALE Gender
their project-based second semester foundations of engineering course. These students will not have declaredan engineering major at this stage, although some of them may have already decided which fieldof engineering to pursue.Our results can then be used to inform the improvement of our course content to better reflect thereality of engineering work. We also expect to use our results as a starting point for furtherexploration into specific aspects of imagination-based prompt design to encourage reflectivethinking in first-year students about working as an engineer, even as many of them may possessa limited exposure to the everyday realities of the engineering profession.References[1] D. Jonassen, J. Strobel, and C. B. Lee, “Everyday problem
A includes the interview protocol for the focus group, whileAppendix B and Appendix C provides the protocol for the first round and second round of follow-up interviews.In this paper we use data from focus groups and the interviews with the 10 GTAs who participatedin both rounds of interviews. Pseudonyms are used to represent the selected participants. Theseparticipants represent all three departments involved in the project. Among the participants, sixwere IGTAs from various parts of Asia, while four were local Domestic GTAs (DGTAs). This mixprovides a diverse set of perspectives, allowing for a nuanced understanding of the experiences ofboth IGTAs and DGTAs. Additionally, the group consists of seven male and three femaleparticipants
Services, Inc. DEKRA CTL08 – Dust X-Screening Apparatus “Acrylic” Price Quote.11. Orathy, B. D. D.; Mooers, J. A.; Warren, M. M.; Mich, J. L. EXPERIMENTS TO DEMONSTRATE CHEMICAL PROCESS SAFETY PRINCIPLES. Chemical Engineering Education.12. E27 Committee. Standard Test Method for Dust Explosions in a 1.2-Litre Closed Cylindrical Vessel (Withdrawn 2007).13. E27 Committee. Test Method for Explosibility of Dust Clouds. https://doi.org/10.1520/E1226- 19.
the surveys, there wereeleven primary leaders and nine secondary leaders. Figure 2b indicates the breakdown of primaryand secondary leaders for each type of program. For each program, there were instructors withdiverse leadership experience, from individuals running their first program to those who have ledmore than five programs. Figure 2c illustrates the number of instructors in each program typewho have led one program, two to four programs, or five or more programs. 16 16 a) 14 b) 13 Number of Faculty/Staff
toinspire interest in future STEM learning (A). Further, Videos, Dichotomous Keys, DrawingBoards, Discussions, and Online Mapping learning tools were found to be statistically similar toeach other for this same purpose (B). However, UAVs were found to be different and greaterthan all other tools to inspire interest in future STEM learning (C). (Figure 2, Table 2). Student Perceptions of Traditional vs. GSS Technology Learning Tools for Inspiring Interest in Future STEM Learning (Assessed by Pairs) (N=43) 7.00 Mean Rating 6.00 5.00 AB AB AB AB A C B
support,” Journal of Further and Higher Education, vol. 45. Pp.1-13, 2021 doi:10.1080/0309877X.2021.1875200.[8] W. K. Zimmer, C.-N. Chang, B. M. Semma, and D. Fowler, “Developing graduate writinghabits and skills: Establishing writing sessions with STEM graduate students,” Collegeteaching, vol. 70, no. 2, pp. 133–144, 2022, doi: 10.1080/87567555.2021.1909524.[9] S. Madden, M. Eodice, K. T. Edwards, A. Lockett, “Chapter 11: Dissertation boot camps:developing self-efficacy and building community,” Learning from the Lived Experiences ofGraduate Student Writers. Logan Utah: Utah State University Press and University Press ofColorado, 2020.[10] C. Vincent, É. Tremblay-Wragg, C. Déri, I. Plante, and S. Mathieu Chartier, “How writingretreats represent
. Eng. Educ., vol. 107, no. 4, pp. 556–582, 2018, doi: 10.1002/jee.20234.[3] I. R. Beattie and M. Thiele, “Connecting in class? College class size and inequality in academic social capital,” J. High. Educ., vol. 87, no. 3, pp. 332–362, 2016.[4] C. R. Glass, E. Kociolek, R. Wongtrirat, R. Jason Lynch, and S. Cong, “Uneven experiences: The impact of student-faculty interactions on international students’ sense of belonging,” J. Int. Stud., vol. 5, no. 4, pp. 353–367, 2015, doi: 10.32674/jis.v5i4.400.[5] B. K. Iverson, E. T. Pascarella, and P. T. Terenzini, “Informal faculty-student contact and commuter college freshmen,” Res. High. Educ., vol. 21, no. 2, pp. 123–136, 1984, doi: 10.1007/BF00975100.[6] A. Pitt, F. Oprescu, G
.[3] N. S. King and B. Upadhyay, “Negotiating mentoring relationships and support for Black and Brown early‐career faculty,” Science Education, vol. 106, no. 5, pp. 1149-1171, 2022.[4] R. E. Zambrana, C. R. Hardaway, and L. C. Neubauer, “Beyond role strain: Work–family sacrifice among underrepresented minority faculty,” Journal of Marriage and Family, vol. 84, no. 5, pp. 1469-1486, 2022.[5] D. C. Bates and E. Borland, “Fitting in and stalling out: Collegiality, mentoring, and role strain among professors in the sciences at a primarily undergraduate institution,” Polymath: An Interdisciplinary Arts and Sciences Journal, vol. 4, no. 2, pp. 50-68, 2014.[6] E. O. McGee, D. Naphan-Kingery, M. L. Miles, and
Engineering Product DEIB AnalysisReferences[1] Ş. Purzer, J. Quintana‐Cifuentes, and M. Menekse, “The honeycomb of engineering framework: Philosophy of engineering guiding precollege engineering education,” J. Eng. Educ., vol. 111, no. 1, pp. 19–39, Jan. 2022, doi: 10.1002/jee.20441.[2] K. A. Thiemann and B. H. Hamlin, “Implementation of game-based programming as a means to engage and excite students in first-year engineering courses,” in 2022 IEEE Frontiers in Education Conference (FIE), Uppsala, Sweden: IEEE, Oct. 2022, pp. 1–5. doi: 10.1109/FIE56618.2022.9962382.[3] M. Lande and T. Machamer, “What is cool stuff? Exploring engineering students’ motivation to
map exceeds apredefined threshold t: SKP = {(x, y) | M (x, y) > t} (3)These keypoints are then rescaled to match the original image resolution.In the feature tracking phase, i.e., Phase 2, the selected keypoints are propagated across adjacentframes using the Lucas-Kanade optical flow method. Tracking is conducted in both upward and Figure 1: Adductor longus muscle [24].downward directions. Phase 2 (a) shows the upward direction toward the proximal side near thehip, while Phase 2 (b) shows the downward direction toward the distal side near the knee.Segmentation Mask GenerationTo generate the segmentation mask, a convex hull algorithm is employed on
engineering design in three concurrent course sections,each led by a different instructor. Data was gathered over five distinct terms with different cohortsof students. The course is offered in both English and French. In the Fall 2021 term, there werethree different instructors: A, B and C, with class sizes that varied from 63 to 84 students,depending on the specific section. For the Winter and Fall 2022 terms, instructor C was replacedby a new one, D, to create a new set of instructors: A, B and D. Replacing the third instructoreach time, the 2023 Winter term instructor set became: (A, B, E) and then changed to (A, B, F) inthe final 2024 Winter term. The details of the course sections are given in Table 1.All course assessments, lecture content
. Parra-Vega, A. S´anchez-Orta, V. H. Benitez, and J. d.-J. Lozoya-Santos, “A challenge-based learning intensive course for competency development in undergraduate engineering students: Case study on UAVs,” Electronics, vol. 11, no. 9, p. 1349, 2022.[18] F. R. Kools, C. M. Fox, B. J. Prakken, and H. V. van Rijen, “A mixed method study investigating the key translational competencies acquired during a challenge-based course,” BMC Medical Education, vol. 24, no. 1, pp. 1–16, 2024.Appendix: Survey QuestionsDemographic QuestionsIn this section, some basic demographic questions are asked, primarily concerned with when you took your capstoneclass and what your major is/was. • Are you currently an undergraduate student at Kettering