politicalconstraints remains a crucial area for growth as the program evolves. Despite its success, theprogram is no longer funded, reflecting a shift in the NSF’s stated priorities away from explicitlyjustice-oriented initiatives. As a team deeply committed to equity and systemic change, wedisagree with this shift and remain steadfast in our belief in the necessity of programs like JEDI.AcknowledgmentThis material is based upon work supported by the National Science Foundation under AwardNumber 2318338. Any opinions, findings, and conclusions, or recommendations expressed inthis material are those of the author(s) and do not necessarily reflect the views of the NationalScience Foundation.References[1] B. Geisinger and D. R. Raman, “Why they leave
. (a) (b) Figure 1. (a) Sample handwritten student submission after pre-processing andanonymization, with student information removed. (b) Submission after digitization using Mathpix Snipping Tool. Figure 2. Interactive grading platform for automated evaluation of digitized lab submissions using multiple LLMs.3. Results and DiscussionThis section evaluates the reliability of the proposed framework by comparing AI-generated gradeswith human-graded benchmarks. Discrepancies were flagged for manual review, and iterativerefinements were made to the models based on feedback from the TAs.3.1. Digitization PerformanceTo
, Mar. 2021, doi: 10.1136/bmj.n71.[7] M. C. Ayar, “First-Hand Experience with Engineering Design and Career Interest in Engineering: An Informal STEM Education Case Study,” Educ. Sci. Theory Pract., vol. 15, no. 6, pp. 1655–1675, Dec. 2015.[8] B. Brand, M. Collver, and M. Kasarda, “Motivating Students with Robotics,” Sci. Teach., vol. 75, no. 4, pp. 44–49, Apr. 2008, doi: 10.2505/3/tst08_075_04.[9] R. T. Johnson and S. E. Londt, “Robotics Competitions: The Choice Is up to You!,” Tech Dir., vol. 69, no. 6, pp. 16–20, Jan. 2010.[10] M. Wallace and W. Freitas, “Building Teen Futures with Underwater Robotics,” J. Ext., vol. 54, no. 2, Apr. 2016, doi: 10.34068/joe.54.02.12.[11] A. Eguchi, “Educational Robotics Theories and
into themes. We considered how themes mayemerge across participant interviews, while also considering that themes or patterns may emergewithin participants’ different social identities and college experiences.We worked collaboratively to address their criteria for trustworthiness by establishing (a)credibility by member-checking with respondents; (b) transferability by using thick description;(c) dependability by having Dr. Siller Carrillo Hector—who was not involved in datacollection—serve as an external evaluator to review codes and themes; and (d) confirmability byengaging in reflexivity through journaling and dialogue.Positionality statementWe are an interdisciplinary team of faculty and graduate students with expertise in
work andthe experiences that prepared them for their global job tasks (RQ3).AcknowledgementsThis material is based upon work supported by the National Science Foundation (EEC-2308607).Any opinions, findings, and conclusions or recommendations expressed in this material are thoseof the author(s) and do not necessarily reflect the views of NSF.References[1] J. M. Grandin and E. D. Hirleman, “Educating engineers as global citizens: A call for action / A report of the national summit meeting on the globalization of engineering education,” Online J. Glob. Eng. Educ., vol. 4, no. 1, pp. 1–28, 2009.[2] K. A. Davis and D. B. Knight, “Comparing students’ study abroad experiences and outcomes across global contexts,” Int. J. Intercult. Relat
course grade below a B-. So, although prior knowledgehas some impact on course grades, it didn’t seem to stop students from getting goodcourse grades.Further StudyIn future studies, I would like to investigate whether there is a significant diAerence inscores for students taking the class remotely, and whether and how this relates to howmuch students know coming into the course (probably through another diagnostic test). Ihad hoped to study that with my data from Fall of 2024, but too few remote studentsconsented to participate in the study. I would also like to add more optional practicequestions for partial diAerential equations, so that the amount of extra practice availablefor that subject is in line with the amount of extra practice
develop theirpedagogical and entrepreneurial mindsets.Reference[1] H. H. Choi, Y. W. Chen, A. M. Beckman, L. Anderson, B. E. Johnson, M. D. Goodman, C. Migotsky, and N. Johnson-Glauch, “Integrative Engineering Leadership Initiative for Teaching Excellence (iELITE),” in Proc. ASEE Annu. Conf. & Expo., Salt Lake City, UT, USA, Jun. 2018. doi: 10.18260/1-2--30696.[2] Y. W. Chen, H. H. Choi, B. E. Johnson, M. A. Beckman, and L. Anderson, “Board 85: Integrated Engineering Leadership Initiative for Teaching Excellence (iELITE) Year Two: Assessment of Intermediate-Term Outcome for Graduate Teaching Assistant Training,” in Proc. ASEE Annu. Conf. & Expo., Tampa, FL, USA, Jun. 2019. doi: 10.18260/1-2--32445.[3] H. H. Choi, S
b. Bers’ Engineering Model [12] Figure 3. EngineeringEngineering for Early ChildhoodEngineering in early childhood involves using materials to build physical items that addressspecific problems or needs. It is a process driven by purpose and creativity, often requiringchildren to define a problem based on criteria such as available resources and time constraints.Bers outlined an engineering cycle for young learners that includes six steps: suggestingpossible solutions, selecting the most suitable one, creating a prototype, testing it, and refiningthe design. These steps encourage problem-solving and iterative thinking, making engineeringan effective hands-on learning approach for early childhood
engineering doctoral education: Experiences of students with minoritized sexual identities. Annual Meeting of the American Educational Research Association; Denver, CO.[5] Ehrhart, M. G., Schneider, B., & Macey, W. H. (2013). Organizational Climate and Culture: An Introduction to Theory, Research, and Practice. New York: Routledge. https://doi.org/https://doi.org/10.4324/9781315857664[6] Ehrhart, M., & Schneider, B. (2016). Organizational climate and culture. Oxford Research Encyclopedia of Psychology.[7] Schneider, B., & Barbera, K. M. (2014). The Oxford handbook of organizational climate and culture. Cheltenham, UK: Oxford University Press.[8] Hurtado, S., Milem, J. F., Clayton-Pedersen, A. R., & Allen, W. R
33−19is ( 33 ) % = 40%, and between Spring 2019 and Summer 2024 ( 33 ) % = 42%, as in Table7. Note also the 4% increase in the course retention between the two semesters. Dynamics Spring 2019 - 252 Students Dynamics Spring 2023 -167 Students No. Of Class No. Of Class Grades Grades Students Percentage Students Percentage A 45 18% A 54 32% B 65 26% 44% As&Bs B 56 34
in community-based projects. Eventhose that capture information gathering as an ongoing process do not always capture thenuance that community autonomy plays in shaping students’ design thinking in situ. Forexample, we often assume that the information gathered at Time C is a function of theinformation gathered at Time B, which itself is a function of the information gathered at Time A.However, in the EDA project, we quickly learned that such a conception of the design processwas incompatible with the ethos of the project, which elevated community autonomy, as well asthe active participation of community members, in problem definition, resource management,and decision making.That the design goals, budgets, materials and supplies, or even the
atechnical design challenge. At the end of the week, students’ responses indicated that they feltstatistically significantly more proficient in all technical skills with the exception of their codingand programming skills. This is shown in Figure 2. Students’ self-efficacy was higher at the endof the program in all areas, including working on teams on a technical challenge, 3D modeling,manufacturing, and working with electronics and microcontrollers.The results are broken down by responses from first-year students and transfer students inFigures 2b and 2c, respectively. Both groups reported statistically significantly higher levels of (a) Total sample (b) First-year students
understanding of the historical and socialdimensions of civil engineering projects, with a specific focus on highway construction in the1960s. The assignment incorporated the following elements: a) Contextual Background: Students were provided with a historical overview of the U.S. interstate highway program, including its goals and the rationale for expansion into urban areas. b) Case Study Approach: The students were divided into four groups and each group researched on a specific highway project (e.g., I-10 in New Orleans, I-81 in Syracuse, I- 85 in Atlanta, or I-75 in Detroit) to investigate in-depth. The case study framework required students to examine: o The demographic, economic, and cultural
very good, good, poor, very poor,or prefer not to answer.The results of two iterations are shown in Figure 3a, while comparing the responses of directand transfer students in the most recent iteration are shown in Figure 3b. Here, respondentsin the second iteration generally indicated a slightly worse evaluation of their mental healthshift towards respondents indicating a slightly worse evaluation of their mental health, withTX respondents having worse evaluation of their mental health than RX respondents. (a) (b) Figure 3. Change in Mental Health for (a) All respondents by year, and the (b) TX or RX cohortA similar analysis was undertaken on evaluating
capturing tasks,including laser scanning (see Figure 2-a and Figure 2-b), 360-degree reality capturing and pointcloud processing technologies (see Figure 3). Figure 2 outlines the initial workflow, whichinvolved utilization of Faro laser scanning technology for automated point cloud generation andsurveying. While these methods provided a foundational understanding of this technology,challenges such as misaligned reference points and outdated scanning tools compromised thequality of the generated point clouds. a. b. Figure 2. Reality capture process alternative 1 - laser scanningTo address these challenges, students transitioned to an alternative workflow, illustrated in
attempting this term?8) On-Campus Job: On average, how many hours do you work at an on-campus job each week?9) Off-Campus Job: On average, how many hours do you work at an off-campus job each week?10) Major: What is your major or primary area of study?11) Writing: Rate your writing skills:12) Hands-On: Rate your skill with hands-on build or repair tasks: a) None b) Basic c) Average d) Good e) Expert13) Commitment Level: In this course, you intend to work how many hours per week outside of class (not counting lectures or labs): a) 2-4 hours per week b) 5-7 hours per week c) Whatever it takes14) Leadership Role: What is your preferred leadership role? a
favor of embracing a measured approach of introducing Generative AI in computingeducation, we decided to instrument Codio Coach, a conversational AI learning assistant with thefollowing three modules available to learners: a) Summarize what I need to do - Provides learners with a simple summary of the programming assignment's tasks as well as a list of requirements based on the question specification. b) Explain this error - Offers plain English explanations for compiler error messages, pinpointing the cause of the error. - The explanation is concise (3-5 sentences) with no fixes or solutions. - If applicable, it also underlines common misconceptions relevant to the
://docs.lib.purdue.edu/open_access_dissertations/995[4] K. L. Tonso, “Student learning and gender,” Journal of Engineering Education, vol. 85, no. 2, pp. 143–150, 1996, doi: 10.1002/j.2168-9830.1996.tb00223.x.[5] S. Secules, A. Gupta, A. Elby, and C. Turpen, “Zooming out from the struggling individual student: An account of the cultural construction of engineering ability in an undergraduate programming class,” Journal of Engineering Education, vol. 107, no. 1, pp. 56–86, 2018, doi: 10.18260/p.26239.[6] M. Matters, C. B. Zoltowski, P. M. Buzzanell, and A. O. Brightman, “WIP: Exploring an engineering faculty’s intention toward inclusive teaching,” ASEE Annual Conference and Exposition, Conference Proceedings, vol. 2020-June
i iii (b) (a) (b) Figure 1. SolidWorks rendering of the Figure 2. SolidWorks rendering of the handheld tool (a), and exposed internal internal structure with dowel pin (a) features of manufactured parts (b). and manufactured internal structure (b). Table 1. Outline of components and design updates for the handheld tool. Component Label Qty Design Updates Handle housing i 4 Updated to match the redesigned internal structure
” (EAMU) vector (Table 2). The description and nominalmeasurement ranges for each level are set as appropriate to the task associated with the KPI.Table 2. KPI assessment results for BME 3113. KPI Semester E A M U Avg i-1 (L3): Collect relevant technical information, data, F2018 7 9 0 0 2.4 and ideas from multiple sources. 2-b (L4): Examine realistic constraints related to the F2019 12 2 0 0 2.9 proposed solution 3-a (L3) Construct and deliver a logical and articulate
for manufacturing training. Quantitative data are analyzed usingstatistical methods, while qualitative data are examined through LDA topic modeling, an NLPapproach.3. XR Environments for Manufacturing TrainingTwo immersive environments, VR and MR, are designed with an interactive module centered onthe assembly tasks of a hydrostatic bike. This bike was chosen for its complex mechanical designand hydraulic circuit, making it suitable for teaching assembly practices. Its mechanicalstructure, shown in Figure 1, consists of highly coupled subsystems: (A) Front-Lower Assembly,(B) Back-Upper Assembly, (C) Back-Lower Assembly, and (D) the Bike Frame. Thecomprehensive nature of the bike system allows for the exploration of various UI controls
individual and group work such that 41% of the total projectgrade was based on individual activities and 59% of the total project grade was based on theperformance of the team. A significant proportion of the grade was based on individual activitiesto encourage all students to be accountable to the team. It was also important to have a strongproportion of the grade be based on success of the team to promote interdependence of the team. a. Automatic Paper Plane Launcher b. Fish Feeding Rowboat c. Coin Dispenser d. Light Sensing Robotic Car Figure 1 Teams created a range of robotic systems such as those illustrated here. These systems were expected to meet the requirements for the 4-H Robotics requirements for
Paper ID #46247BOARD # 199: Comparing Computational Thinking Learning and Engagementin First-Grade Boys and Girls: A Study of Algorithm Design and Debugging(Work-In-Progress)Ms. B´arbara Fagundes, Purdue University I hold a Ph.D. in Engineering Education and an M.S. in Computer Science, focusing on integrating computational thinking into pre-college education. My experience includes developing and implementing engineering and computer science curricula and actively participating in professional development for teachers to establish inclusive and innovative learning environments. At Purdue University’s Center for
] Read “Facilitating Interdisciplinary Research” at NAP.edu. doi: 10.17226/11153.[4] L. R. Lattuca, D. B. Knight, H. K. Ro, and B. J. Novoselich, “Supporting the Development of Engineers’ Interdisciplinary Competence,” J. Eng. Educ., vol. 106, no. 1, pp. 71–97, 2017, doi: 10.1002/jee.20155.[5] A. M. Claus and B. S. Wiese, “Development and test of a model of interdisciplinary competencies,” Eur. J. Work Organ. Psychol., vol. 28, no. 2, pp. 191–205, 2019, doi: 10.1080/1359432X.2019.1567491.[6] E. J. Hundey et al., “A Shifting Tide: Recommendations for Incorporating Science Communication into Graduate Training,” Limnol. Oceanogr. Bull., vol. 25, no. 4, pp. 109– 116, 2016, doi: 10.1002/lob.10151.[7] I. Direito and A. Freitas
Paper ID #46322BOARD # 347: Creating Inclusive Engineers through Humanitarian EngineeringProjects: A Preliminary Model and Framework for Integration (NSF RIEF)Dr. Kirsten Heikkinen Dodson, Lipscomb University Kirsten Heikkinen Dodson (pronouns: she/her) is an Associate Professor and the Chair of Mechanical Engineering in the Raymond B. Jones College of Engineering at Lipscomb University. She earned her B.S. in Mechanical Engineering from Lipscomb University and her Ph.D. from Vanderbilt University before returning to her alma mater. Her research interests focus on the connections between humanitarian engineering
beliefs - The longitudinal picture,” ASEE Annual Conference and Exposition, Conference Proceedings, pp. 15967–15980, 2005, doi: 10.18260/1-2--14149.[6] R. Marra and B. Bogue, “A Critical Assessment of Online Survey Tools,” Women in Engineering ProActive Network, 2006.[7] K. Thakare et al., “Design and Development of a Horizontal CTE Curriculum to Prepare Students for the New Manufacturing Economy (Work in Progress),” ASEE Annual Conference and Exposition, Conference Proceedings, Jul. 2021, doi: 10.18260/1-2-- 36905.[8] “Opening Doors: How Selective Colleges and Universities Are Expanding Access for High-Achieving, Low-Income Students - Jack Kent Cooke Foundation.” Accessed: Jan. 05, 2025. [Online
DeliveryReviews, vol. 175, p. 113804, May 2021, doi: 10.1016/j.addr.2021.05.014.[4] J. B. Rubin, B. Hameed, M. Gottfried, W. M. Lee, and M. Sarkar, “Acetaminophen-inducedacute liver failure is more common and more severe in women,” Clinical Gastroenterology andHepatology, vol. 16, no. 6, pp. 936–946, Dec. 2017, doi: 10.1016/j.cgh.2017.11.042.[5] D. Zuckerman, “Hip implant failure for men and women,” JAMA Internal Medicine, vol. 173,no. 6, p. 442, Feb. 2013, doi: 10.1001/jamainternmed.2013.19.[6] O. L. Lanier, M. D. Green, G. A. Barabino, and E. Cosgriff-Hernandez, “Ten simple rules inbiomedical engineering to improve healthcare equity,” PLoS Computational Biology, vol. 18, no.10, p. e1010525, Oct. 2022, doi: 10.1371/journal.pcbi.1010525.[7] M. Whitehead
them. The following instructions regarding AI usagewere provided: a) No AI Assistance: If no AI assistance was used, students were required to indicate in their reports that they were written independently. b) AI Assistance: If AI assistance was used, students were asked to include the following information in the Appendix of their reports for this study: i. The prompt(s) used. ii. Details on how the AI-assisted content was incorporated or revised.This information was collected to ensure the accuracy of the report content and the authenticityof references. In addition, it is worthy to note that students were not given any training ongenerative AI use or crafting prompts. They self-selected the
the end of semester anonymousstudent evaluations conducted by the university using the IDEA Student Ratings Systems. Thefollowing survey questions were selected for examination.Survey Questions- Likert ScaleStudent Ratings of Learning on Relevant Objectives(1- Strongly Disagree, 2- Disagree, 3- Neutral, 4-Agree, 5- Strongly Agree) A. Gaining a basic understanding of the subject (e.g. factual knowledge, methods, principles, generalizations, theories) B. Learning to apply course material (to improve thinking, problem solving, and decisions) C. Developing specific skills, competencies, and points of view needed by professional in the filed most closely related to this course D. Developing creative capacities (inventing
additive manufacturing workshop.Results3D ModelThe model for teaching and student learning is defined according to University of Sheffieldfacilities. Here, Chichén Itzá pyramid is chosen as the prototype to be manufactured, Figure 2 a).Thus, the scan of the sculpture is done, and the *.stl archive is obtained, with enough resolutionand detail, Figure 2 b). The dimension of the model is rescaled to 20×20 cm of base and 10 cm ofheight. Then, using the software Autodesk Slicer for Fusion, the archive *.dxf is created, and themodel is divided into 17 layers; this, considering that it is sliced vertically with a thickness of 5mm. Hence, the pyramid model can be built using recycled material, Figure 2 c), where thecharacteristic of the architecture is