constructioneducation: Case studies and best practices," Int. J. Construction Education and Research, vol. 19,no. 3, pp. 278-294, 2023.[3] M. Awada, B. Becerik-Gerber, and S. White, "Understanding the impact of COVID-19 onsustainable building design principles," Building and Environment, vol. 204, art. no. 108182, 2022.[4] J. T. Brooks, "Human-centered design in post-pandemic construction education," ConstructionManagement and Economics, vol. 41, no. 5, pp. 489-503, 2023.[5] M. Celadyn, "Indoor environmental quality in sustainable building design: Post-pandemicperspectives," Sustainable Cities and Society, vol. 89, art. no. 104267, 2023.[6] L. Chang and S. Lee, "Global trends in sustainable construction education: A comparativeanalysis," J. Engineering
, this case study has beenprovided to inform the broader community of an effective framework for student empowermentand leadership training within the context of a research group, and has provided an exampleassessment of student leadership development within this framework.AcknowledgmentThe authors would like to thank all current and former members of the research group for theirinvaluable contributions and insights, which were instrumental in this study. Your dedication tocollaboration, mentorship, and innovation has greatly advanced the lab’s mission and impact.Thanks also to the ASEE reviewers and to others (Prof. Tyler Ray, UH-Mānoa; Nanosystemsgroup members) who provided feedback on this manuscript.References[1]B. A. Burt, “Learning
: crafting the speculation,” Digit. Creat., vol. 24, no. 1, pp. 11–35, Mar. 2013, doi: 10.1080/14626268.2013.767276.[16] M. S. Shaw, J. J. Coleman, E. E. Thomas, and Y. B. Kafai, “Restorying a Black girl’s future: Using womanist storytelling methodologies to reimagine dominant narratives in computing education,” J. Learn. Sci., vol. 32, no. 1, pp. 52–75, Jan. 2023, doi: 10.1080/10508406.2023.2179847.[17] G. Smith, “Crafting Gender/Crafting Boundaries: Reimagining ‘Authentic’ Gender Performance in Feminized Activities,” University of Virginia, 2015. doi: 10.18130/V3PQ3W.[18] J. Buolamwini, “Algorithmic Justice League.” [Online]. Available: https://www.ajl.org/[19] J. Buolamwini, “Get Ready to Drag
Challenges for Engineering: Imperatives, Prospects, and Priorities: Summary of a Forum," National Academy of Engineering, The National Academies Press, Washington, DC, 2016.[3] "TUEE Transforming Undergraduate Education in Engineering Phase IV: Views of Faculty and Professional Societies," ASEE, Arlington, VA, 2017.[4] D. Grasso and M. B. Burkins, "Beyond Technology: The Holistic Advantage," in Holistic Engineering Education, New York, NY, Springer, 2010, pp. 1-10.[5] S. Abraham, M. Vurkaç, A. Miguel, D. M. Takach, E. Ferré, S. Singh and H. Louie, "Work in Progress: Reimagining the ECE Curriculum: Bridging Technical," in ASEE Annual Conference and Exposition, Portland, OR, 2024.[6] "Oh My Git!," [Online]. Available: Available: https
Paper ID #45691WIP: Implementing Backward Design Approach in Integrated Business andEngineering Capstone Project: A NASA Tech Transfer Case StudyMs. Mandana Ashouripashaki, The Ohio State University Mandana Ashouripashaki is a PhD student in Engineering Education at The Ohio State University and also serves as the Associate Director of Licensing and Business Development at OSU’s Innovation and Commercialization Office. Her responsibilities encompass strategic outreach, key account management, advancing deal quality and velocity, as well as overseeing entrepreneurial training and initiatives. Before her tenure at Ohio
Paper ID #46058Forward Fellows: An extended onboarding program to foster a sense of belongingand research self-efficacy in incoming graduate studentsDr. Anne Lynn Gillian-Daniel, University of Wisconsin - Madison Anne Lynn Gillian-Daniel has been the Education Director for the Wisconsin Materials Research Science and Engineering Center (MRSEC) since 2012 and the Wisconsin Education lead for the Wisconsin-Puerto Rico Partnership in Research and Education and Materials (WiPR2EM) since 2017. In these roles, Anne Lynn collaborates with researchers to broaden participation of historically underrepresented groups in materials
Paper ID #46931”What you bring matters”: A Comparative Case Study of Middle SchoolEngineering Teachers’ Pedagogical Content Knowledge (Fundamental)Dr. Jessica D Gale, Georgia Institute of Technology Dr. Jessica Gale is a Research Scientist II at Georgia Tech’s Center for education Integrating Science, Mathematics, and Computing (CEISMC). Her research focuses on project-based learning, STEM/STEAM integration at the elementary and middle grades levels, curriculum development and implementation, and design-based implementation research.Dyanne Baptiste Porter, Georgia Institute of Technology Dyanne Baptiste Porter is a
[1] G. A. Garcia, A.-M. Núñez, and V. A. Sansone, “Toward a Multidimensional ConceptualFramework for Understanding ‘Servingness’ in Hispanic-Serving Institutions: A Synthesis of theResearch,” Review of Educational Research, vol. 89, no. 5, pp. 745–784, Oct. 2019, doi:10.3102/0034654319864591.[2] J. Ritchie, J. Lewis, C. M. Nicholls, and R. Ormston, Eds., Qualitative research practice:a guide for social science students and researchers, 2. ed. Los Angeles, Calif.: Sage, 2013.[3] A. Srivastava and S. B. Thomson, “Framework Analysis: A Qualitative Methodology forApplied Policy Research,” Journal of Administration & Governance, vol. 4, no. 2, pp. 72–79,2009.[4] N. K. Gale, G. Heath, E. Cameron, S. Rashid, and S. Redwood, “Using
National Science Foundation under NSF S-STEMaward DUE-2221250.References[1] B. Leidenfrost, M. Schutz, C. Carbon and A. Schabmann, "The Impact of Peer Mentoring on Mentee Academic Performance: Is Any Mentoring Style Better Than No Mentoring at All?," International Journal of Teaching and Learning in Higher Education, vol. 26.1, pp. 102-111, 2014.[2] A. Ilumoka, I. Milanovic and N. Grant, "An Effective Industry-Based Mentoring Approach for the Recruitment of Women and Minorities in Engineering.," Journal of STEM Education: Innovations and Research, vol. 18.3, 2017.[3] K. Hoffmeister, K. P. Cigularov, J. Sampson, J. C. Rosecrance and P. Y. Chen, "A Perspective on Effective Mentoring in the Construction Industry.," Leadership &
of the literature,” Improving Schools, vol. 19, no. 3, pp. 267–277, Nov. 2016, doi: 10.1177/1365480216659733.[11] B. W. Lilly, L. M. Abrams, M. Neal, K. Srinivasan, and D. Mendelsohn, “DEVELOPING AN EFFECTIVE PLATFORM FOR INTRODUCING MECHANICAL ENGINEERING IN A LARGE PUBLIC UNIVERSITY,” 2012. [Online]. Available: http://asmedigitalcollection.asme.org/IMECE/proceedings- pdf/IMECE2012/45219/517/2479745/517_1.pdf[12] E. Coyle and E. J. Coyle, “2006-2565: THE VERTICALLY-INTEGRATED PROJECTS (VIP) PROGRAM IN ECE AT PURDUE: FULLY INTEGRATING UNDERGRADUATE EDUCATION AND GRADUATE RESEARCH.” [Online]. Available: http://epics.ecn.purdue.edu/.[13] C. B. Zoltowski and E. J. Delp, “Vertically Integrated
engaging Engineering Summer Camp," 2014 ASEE Annual Conference & Exposition, 2014.3. A. H. Nowariak, O. Lang, A. P. Thomas, D. Monson, and D. Besser, "Assessing the Effectiveness of an Engineering Summer Day Camp," 2016 ASEE Annual Conference & Exposition, New Orleans, Louisiana, pp. 1-15, 2016.4. R. Hammack, T. A. Ivey, J. Utley, and K. A. High, "Effect of an engineering camp on students’ perceptions of engineering and technology," J. Pre-College Eng. Educ. Res. (J- PEER), vol. 5, no. 2, Art. no. 2, 2015.5. M. Khalafalla, T. U. Mulay, D. Kobelo, B. Shadravan, and D. Akinsanya, "The role of hands-on engineering technology summer camps in attracting underrepresented high school students to STEM majors," in ASEE Annu. Conf
Course an Inductive and Deductive Learning Experience," Chemical Engineering Education, vol. 44, no. 2, pp. 119-126, 2010.[3] D. E. Clough, "Bringing active learning into the traditional classroom: Teaching process control the right way," in 1998 Annual Conference, 1998, pp. 3.126. 1-3.126. 9.[4] M. Rodriguez, I. Diaz, E. J. Gonzalez, and M. Gonzalez-Miquel, "Motivational active learning: An integrated approach to teaching and learning process control," Education for Chemical Engineers, vol. 24, pp. 7-12, 2018.[5] M. Rodríguez, A. Prada, I. Díaz, E. Gonzalez, and M. González-Miquel, "Active Learning of Process Control," in Computer Aided Chemical Engineering, vol. 43: Elsevier, 2018, pp. 1693-1698.[6] B
Lessons 8 through 13 reflected noticeably lower student study times. The averagescores for Quiz 1 through 4 were 76.6%, 80.4%, 78.3%, and 77.4%, respectively. The weightedaverage of all four quizzes was 78.25%. However, with respect to the two exams, studentsstudied an average of 93 minutes for Exam 1 and 167 minutes for Exam 2. The course-wideaverages for Exam 1 and Exam 2 were 83.1% and 88.5%, respectively. Thus, the average for thetwo exams was 85.8% (i.e., a “B”). This is nearly 3% lower than the single exam (88.6% or“B+”) administered during the 2024 Spring Semester which covered the same material, albeit inless depth, breadth, and contextual emphasis.Figure 4. Course 1 Student Time Survey by Lesson, 2024 Fall SemesterCourse 1 conducted a
Paper ID #49490What makes a competent nuclear engineer?Tina Baradaran Ms. Tina Baradaran is a physicist, higher education educator and a PhD candidate in Nuclear Engineering Education at the University of New South Wales (UNSW), Australia. Collaborating with the Australian Nuclear Science and Technology Organization (ANSTO), Tina explores the core competencies, essential knowledge, and skills and attributes needed in nuclear engineering and the role of on-the-job training in developing these competencies. As one of the pioneering PhD scholars in engineering education at UNSW Engineering, this research aims to create and
Paper ID #47945Toward the Use of LLMs to Support Curriculum Mapping to EstablishedFrameworksMr. Eric L Brown, Tennessee Technological University Eric L. Brown is an education leader with over 28 years of experience in higher education, currently serving as the Associate Director of Workforce Development for the Cybersecurity, Education, Research, and Outreach Center at Tennessee Tech University. As a senior lecturer in the Computer Science department, Eric teaches various cybersecurity courses and agile-focused software engineering. His prior experiences include serving as a District Solutions Advocate for the Tennessee
Annual Conference & Exposition, Jun. 2018. Accessed: Jan. 02, 2025. [Online]. Available: https://peer.asee.org/active-learning-model- as-a-way-to-prepare-students-for-knowledge-integration[8] S. Acharya, B. R. Maxim, and J. J. Yackley, “Applied Knowledge Retention – Are Active Learning Tools the Solution?,” presented at the 2019 ASEE Annual Conference & Exposition, Jun. 2019. Accessed: Jan. 02, 2025. [Online]. Available: https://peer.asee.org/applied-knowledge-retention-are-active-learning-tools-the-solution[9] J. M. Gregory, D. Wilson, and L. Stephenson, The Seven Laws of Teaching: Foreword by Douglas Wilson & Evaluation Tools by Dr. Larry Stephenson, First Edition. Canon Press, 2014.[10] L. W
employs a hybrid format1, facilitating theconvergence of research in diverse areas of engineering. It boasts a history spanning more than15 consecutive events and attracts over 1,500 authors. For this study, works published from 2017to 2024 were extracted from Event A. Event B was an international congress aimed atdisseminating research on entrepreneurship, innovation, education, and technology inengineering. The event was established in 2021 in an exclusively virtual format. For this article,publications from 2021 to 2024 were examined.Table 1 shows the topics of both events in which we collected a total of 4530 articles, of which3796 correspond to event A and 734 to event B.1 Event A was held in person from its inception until 2020. In 2020 it
college student status, traditional versus non-traditional enrollment, and first-time-in-college (FTIC) status. It also assesses students’ initialproficiency with hands-on engineering skills and their access to tools or workspaces. Thisinformation establishes a foundation for analyzing changes in self-efficacy and project-spaceusage over time while identifying key variables, such as demographic or proficiency disparities,that may influence the study’s outcomes.Survey B: Engineering Skills Self-Efficacy ScaleDeveloped by [1], this 14-question Likert-scale survey measures self-efficacy in three areas:experimental (five questions), tinkering (five questions), and design (four questions). The scalewas adapted from a variety of sources [15], [16], [10
learningopportunities. It discusses how participants were encouraged to explore their identity formationand its impact on STEM career development while fostering a sense of belonging and self-efficacy in their fields. Using a mixed methods evaluation and assessment approach, findingssuggest several implications: (a) an increase in participants' awareness and skills within STEMfields, potentially enhancing interest in these areas; (b) a greater understanding of social changepartnerships and their integration into higher education research; and (c) transformed practicesthat could prepare more students for STEM careers. Emphasizing educational research inengineering and community engagement, this paper discusses the critical importance ofpromoting access, respect
. Retain our most valuable resources—students, faculty and staff—by cultivating an inclusive environment and developing opportunities for advancement, recognition, and support. Initiatives: a. Recognize and celebrate cultural differences within the School. b. Encourage continuing education of faculty and staff by incentivizing professional development that is beneficial to the employee and School operations. d. Promote a school culture that values collaboration and contributions of our people. B: Improve access to financial resources and enhance opportunities to support the needs of the School and the financial wellbeing of the CEE community.Student Experience
unable todemonstrate the basic concepts of these courses in later courses. The mastery-based assessmentforces students to demonstrate mastery of each learning outcome rather than just achieving asatisfactory score on a time limited exam. This significantly improves the students’ ability tomaster the essential concepts of Statics and Dynamics [5], [6].DescriptionThe mastery-based assessment structure used in Statics at Angelo State University is adaptedfrom the model developed by Papadopoulos et al. [5]. The most current version of this structureis outlined in Table 2, which details the mastery levels, associated topics, homeworkassignments, and prerequisites for each level. The mastery system is organized into four levels:D, C, B, and A. For
in a model that might be better forus all to understand. Generally, the definitions of intelligence, education, learning, and what ourbrains do are extremely complex, and the wide variety of scientific fields (Cognitive Psychology,Neuropsychology, Educational Psychology, Artificial Intelligence, etc.) that work in this spaceprovides a broad glimpse of the complexity of the questions and includes many definitions.Therefore, we will provide starting points based on models and definitions to create acurriculum/course benchmark.2.1 Educable - a definition of intelligence?First, we use Valiant’s “Educable” definition [8]: (a) “learning from experience.” (b) “acquiring theories through instruction.” (c) “applying what one has acquired
tomake metal contact/via onto doped regions in thesubstrate and to interconnect devices with metal layer. Aphysical vapor deposition (PVD) system is used todeposit the aluminum contacts. The resulting wafer isshown in Fig. 10.Lab Session 10: In this lab session, the objectives are to Figure 10. Wafer status after Lab 8.remove remaining photoresists, perform plasma cleaningand anneal to achieve good ohmic contacts. This is the last lab for fabrication, The final devicestructure and a photograph of the wafer with fabricated CMOS chips/die are shown in Fig 11below. (a) (b) Figure 11. (a) Wafer status after Lab 10, (b
recommendation by Kline[37], we report a set of three fit indices for each iteration of the model: (a) the goodness of fitindex (GFI) which represents an absolute fit index that indicates information analogous to theproportion of explained variance of the data; (b) the comparative fit index (CFI) which capturesthe model fit comparative to the fit of an independent, or null (no causal relationships betweenany variables), model; and (c) the root mean square error of approximation (RMSEA) which is aparsimony-adjusted index capturing model misfit (‘errors’) per model degree freedom. Althoughthere are several different interpretation guidelines for what value is considered a good fit foreach fit index, a common set of interpretation guidelines for good fit
Scale MyMathLab Average 90% - 100% 80% - 89% 70% - 79% 60% - 69% < 60% 22 – 25 A B B B C # Standards 19 – 21 B B C C D Mastered 16 – 18 C C C D D 13 – 15 D D D D F < 13 F F F F FStudents were given in-class assessments five times throughout the course
–20.[4] A. L. Pawley, “Universalized Narratives: Patterns in How Faculty Members Define ‘Engineering,’” Journal of Engineering Education, vol. 98, no. 4, pp. 309–319, 2009, doi: 10.1002/j.2168-9830.2009.tb01029.x.[5] C. Seron, S. S. Silbey, E. Cech, and B. Rubineau, “Persistence Is Cultural: Professional Socialization and the Reproduction of Sex Segregation,” Work and Occupations, vol. 43, no. 2, pp. 178–214, May 2016, doi: 10.1177/0730888415618728.[6] P. Robbins, “The reflexive engineer: Perceptions of integrated development,” Journal of International Development, vol. 19, pp. 99–110, Jan. 2007, doi: 10.1002/jid.1351.[7] J. Saldaña, The coding manual for qualitative researchers, 2. ed. Los Angeles, Calif.: SAGE Publ, 2013
significantly contributed to the success of this initiative.References[1] M. Heirwegh, D. C. Rees, and L. Malcom-Piqueux, Postdoctoral Scholar Recruitment and Hiring Practices in STEM: A Pilot Study. 2024.[2] S. C. McConnell, E. L. Westerman, J. F. Pierre, E. J. Heckler, and N. B. Schwartz, “United States National Postdoc Survey results and the interaction of gender, career choice and mentor impact,” Elife, vol. 7, p. 40189, 2018.[3] B. Cantwell and B. J. Taylor, “Rise of the science and engineering postdoctorate and the restructuring of academic research,” The Journal of Higher Education, vol. 86, no. 5, pp. 667–696, 2015.[4] M. Denton, M. Borrego, and D. B. Knight, “US postdoctoral careers in life sciences, physical
Operating Systems: A Frameworkfor Understanding Identity Development for Undergraduate Latina Students in Computing. InE.M. Gonzalez, F. Fernandez, & M. Wilson (Eds.), An Asset-Based Approach to AdvancingLatina Students in STEM: Increasing Resilience, Participation, and Success. Research in STEMEducation Series. London, UK: Routledge.Sáenz, V. B., García-Louis, C., De Las Mercédez, C., & Rodriguez, S. L. (2020). Mujeressupporting: How female family members influence the educational success of Latino males inpostsecondary education. Journal of Hispanic Higher Education, 19(2), 169-194.
below.The online surveys in Qualtrics were based on iREDS Pre-Post Survey [2]. This pre-post surveyis designed to evaluate the efficacy of scientific research ethics education and training. Drawingupon the literature in fields of research ethics, communication, and survey design as well asconsultation with Principal Investigators, its survey questions aim to assess (a) student-levelpractices in labs (i.e., ethical understanding and ethical behavior) and (b) general lab culture andclimate (i.e., choice architecture), such as faculty’s behavior. In this study, we used 55 questionsfrom iREDS Pre-Post Survey: five-point Likert scale questions (35 questions) and binaryquestions (6 questions) for general statistical data analysis, and “select all that
both surveys.Figure 1: (A) Failure tolerance assessment scores showed no difference between pre-course (n = 169)and post-course (n = 125) surveys. (B) For both datasets, the majority of students scored as failuretolerant with scores ranging from 22-32. p = 0.96; student’s T-testTracking and comparing individual responses at ONU revealed a slight average decrease in failuretolerance following MBL course completion: −0.93 ± 3.95 (Fig. 2A; p < 0.05, paired t-test). The majorityof students (n = 42; 58.7%) recorded changes within one standard deviation of no change, indicatingtheir scores shifted only slightly, either toward more or less tolerant (Fig. 2B). Overall, 25 students(34.7%) improved their failure tolerance scores, while 43 students