indicate their level of satisfaction with their assigned project, where 5 = extremely satisfied and 1 = extremely dissatisfied. Despite not having available comparison data for the instructor-assigned cohort, the authors chose to present the self-assigned student cohort survey responses to this question in this paper.(2) Student Satisfaction with Assigned Teammates: CATME peer evaluation data [5, 9] collected in Weeks 5 and 10 out of 30 were used to assess student level of satisfaction with teammates. We compared the prevalence of underperforming team members and of teams with at least one underperforming member. Because underperformance was identified with CATME survey data, this measure reflects students’ perceptions of their
Science Foundation underGrant No. 2045519. 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.The authors would like to thank Vincent Paglioni from the University of Maryland, JamesStemm from the National Museum of Nuclear Science and History, and Lauren Addario, RianneTrujillo, Jonathan Lee, Becca Sharp, and Dion Boyer from New Mexico Highlands Universityfor their work toward this project.References[1] S. Allen, “Designs for learning: Studying science museum exhibits that do more than entertain,” Sci. Educ., vol. 88, no. S1, pp. S17–S33, 2004, doi: 10.1002/sce.20016.[2] C. Tisdal, “Phase 2 Summative
) and reopening it rectified this. Participants mentioned severalchanges they would implement in the app, such as moving the location of buttons to allow formore streamlined use, adding an axis system, including a scale to illustrate how deformationscompared to the predeformed structure, changing the contour map to reflect compression andtension more accurately, and dynamically increasing the load magnitude and observing how thechange in magnitude impacts results.ConclusionStudents often struggle with conceptualizing complex three-dimensional behavior in traditionalmechanics-oriented classes. Although structural analysis software is often introduced and taughtin these classes to explain these concepts, fundamental behaviors such as elastic
, and institutionalagendas might affect their applicability.The recommendations outlined in the study reflect the synthesis of the literature review andinsights contributed by both the writers and experts involved in the research process. Therefore,the selection of AI applications, curricular components, and cooperation methodologies may beinfluenced by biases or subjectivity, potentially affecting the comprehensiveness and success ofthe proposed initiatives. The study primarily focuses on urgent recommendations forincorporating AI into construction management education. Nevertheless, the long-term impactsof these interventions on student learning outcomes, industry-academia collaborations, and thebroader construction sector remain unclear
. This lab is equipped with cutting-edge technology, including the Gigabot3+ Material Extrusion 3D printer, Raise3D E2, Sovol 3D printer, Einscan Pro 3D scanner forreverse engineering, FLIR thermal imaging camera, and other relevant equipment and tools asshown in figure 2. This lab offers students a conducive environment to work on materialsextrusion and materials jetting based AM and prototyping. Students gain practical experience indesigning, creating, and analyzing components using extrusion-based AM techniques by activeengagement in the semester projects and research. The establishment of this lab was madepossible through support from state and federal research grants, reflecting a commitment toadvancing STEM education and research at the
to create a video presentation knowledge that explains the objective of the project, the proposed solution, and an analysis of the results. Think critically The video should include a comparative and critical analysis of the and reflectively expected results with the theoretical model and the experimental results obtained. Demonstrate Furthermore, the project must be related to the application of physicalEngineering skills concepts in engineering problems.In the laboratory classes, the students were divided into teams of four members. Each teamhad the opportunity to choose a scientific
-reported levels of stress (students with latersubmissions generally report higher levels of stress) [5].The final decision we made was to have no penalty for late work, as long as it was submittedbefore sample solutions published within the LMS. This was helpful for making sure thatproblem set grades reflected only student learning, and not time of submission. Since allassignments were scored to the same rubric with no penalties applied for late submission,individual problem performance could more easily be reviewed and analyzed for continuingimprovement and direct assessment needs for accreditation.Other faculty and our department advisory board expressed surprise and curiosity at theimplementation of the above policy, especially for the entry
. “Engaging future engineers is a central topic in everydayconversations on engineering education... It is imperative that the community reflects onprogress and sets a more effective path for the future.” [4] A second motivation was to provide an opportunity for students to begin building self-starting skills earlier in their academic career. The owner of DCOF was highly supportive ofallowing the activities and engagements to be student-led. This gave students the independenceto set their own activity structure and to make decisions in deciding their goals and needs inaccomplishing tasks. There are clear benefits to students; “Without the presence of an organizingfaculty member, students are forced to make decisions in a real-world environment, in
, Reflective Writing in Medicine and Healthcare, Engineering Leadership and Team Building, and Engineers in the Community, among other courses. She believes that education can be a force for liberation and freedom, and through engineering, we can build a more just and equitable world.Sandra Payton Matteucci ©American Society for Engineering Education, 2024 Engagement in Practice: Innovating a Project-Based, Community Engaged Course for Engineering Students that Fosters Ethical ThinkingAbstractThe killing of Michael Brown in Ferguson, Missouri (a suburb of St. Louis) catalyzed the BlackLives Matter movement, underscoring the need for students to explore how privilege andsystemic injustice have physically
51 percent of students from Westlake High School, located in a more affluent area, endedup attending a major university in Texas, where those not included either did not opt into collegereporting, went out of state, or chose not to attend. In contrast, 24 percent of students fromEastside High School, a designated Title I school in the same region, fit into this metric [1]. Ingeneral, most Title I schools have a significantly lower proportion of students who pursue highereducation for various reasons, including insufficient resources, socioeconomic factors, and a lackof exposure to the college process. Reflecting this, a Post-Secondary Executive Summarypublished by Austin Independent School District found that students who submit at least
sustainability are integrated into campus initiatives. 3.8 0.7 0.18 Average 3.8 0.43 0.11When respondents were asked about implementing innovative solutions to environmentalchallenges, they perceived the campus as not very innovative in this regard. The average score of3.8, with a variance of 0.16 and a CV of 0.04, reflects agreement on this sentiment. Similarly, theyfeel the same way about incorporating regional priorities regarding sustainability into campusinitiatives.Moreover, regional priorities were determined based on their regional importance, as identified bythe USGBC regional councils and chapters, and were then shared with the
students intheir learning. [5], [7] As outlined in the principles of good feedback practice, by Nicol, goodfeedback can “facilitate the development of self-assessment and reflection in learning” andmotivate the students to “close the gap between current and desired performance.” Onlineassessments can also provide students with a certain amount of flexibility, which can beadvantageous for those with work responsibilities and family care needs. One challenge inimplementing online assessments is academic dishonesty, as students have increasedopportunities for cheating, especially in poorly proctored assessments. However, measures suchas test-taker verification, plagiarism detection software, and supervised monitoring of testingconditions can
resources such as a chamber of commerce or other connectorgroup familiar with local industry, and communication project progress and accomplishmentsregularly.AcknowledgementThis material is based upon work supported by the National Science Foundation under Grant No.1949454. Any opinions, findings, and conclusions or recommendations expressed in this materialare those of the authors and do not necessarily reflect the views of the National ScienceFoundation.References[1] Allen, P.J., Lewis-Warner, K., & Noam, G.G. (2020). Partnerships to transform STEM learning: A case study of a STEM learning ecosystem. Afterschool Matters, 31, 30-41.[2] Pattison, N. P.(2021). Powerful partnership: An exploration of the benefits of school and industry
messages and instructional content, including graphs of data situating team ratings. Thetool asks students to reflect on the messages and patterns that they see in their team, as well as todescribe behaviors they might try next using strategies from motivational interviewing.The National Science Foundation program for Improving Undergraduate STEM Education(IUSE) awarded the authors a grant to support evaluating the effectiveness of this tool, both interms of its ability to detect inequity and exclusion and in terms of its interventions. In this shortpaper and associated poster we summarize some of this work. Specifically, we will present howwe have operationalized “diverse” and “effective” teams, as well as how statistical measures ofthese
] M. J. Scott and G. Ghinea, “On the domain-specificity of mindsets: The relationship between aptitude beliefs and programming practice,” IEEE Transactions on Education, vol. 57, no. 3, pp. 169–174, 2014.[32] D. A. Fields, Y. B. Kafai, L. Morales-Navarro, and J. T. Walker, “Debugging by design: A constructionist approach to high school students’ crafting and coding of electronic textiles as failure artefacts,” British Journal of Educational Technology, vol. 52, no. 3, pp. 1078–1092, 2021. [Online]. Available: https://bera-journals.onlinelibrary.wiley.com/doi/abs/10.1111/bjet.13079[33] D. A. Fields and Y. B. Kafai, “Debugging by design: Students’ reflections on designing buggy e-textile projects,” Proceedings of
student mental health and increasing professional help seeking, especially for studentswho are historically excluded in engineering.Theoretical FrameworkThe IBM is utilized to identify beliefs influencing behavior within a given population [9], whichis grounded in research indicating that intention strongly predicts behavior [10, 11]. In the contextof this project, the IBM asserts that the key driver for help-seeking behavior is the intention to seekhelp (Figure 1). Intention is influenced by three help-seeking mechanisms—attitude, perceivednorm, and personal agency— which are shaped by help-seeking beliefs. Attitude reflects anindividual's overall evaluation (positive or negative) of help-seeking, considering outcome beliefs(anticipated positive
dissatisfied (1).AcknowledgmentThis material is based upon work supported by the National Science Foundation under Grant No.1742496. Any opinions, findings, conclusions, or recommendations expressed in this material arethose of the author(s) and do not necessarily reflect the views of the National Science Foundation.References[1] Rogers, R., & Sun, Y. (2018), Engaging STEM Students from Rural Areas: Emerging Research and Opportunities. IGI Global. DOI: 10.4018/978-1-5225-6341-9.ch003[2] Harris, R. S., & Hodges, C. B. (2018), “STEM Education in Rural Schools: Implications of Untapped Potential.” National Youth-At-Risk Journal, 3(1). https://doi.org/10.20429/nyarj.2018.030102[3] U.S. Department of Agriculture. (2023, November
advisory board need to be recruited.AcknowledgmentThis work was funded in part by the National Science Foundation award 2148138. Any findings, conclusions, orrecommendations expressed in this material are those of the authors and do not necessarily reflect those of theNational Science Foundation.Bibliography[1.] Barger, M, Gilbert, R; Centonze, P; Ajlani, Sam; What’s Next? The Future of Work for Manufacturing Technicians, 2021 ASEE Annual Conference Proceedings (Virtual) (https://peer.asee.org/38053)[2.] Barger, M, M Boyette, R Gilbert - Florida’s Engineering Technology Associate of Science Degree Program: A Model for Technical Workforce STEM Based Education, Journal of Engineering Technology, Spring (2014). - See more at: http
afterexperiencing the AR educational tool. 3.2.Number of rest and achievementsFollowing the AR educational tool experience, there was a substantial reduction in the averagenumber of resets for path-finding layouts among students who gave up on solving the path andattempted new layouts. The average number of resets decreased from 7 to 1.4, reflecting asignificant improvement. Four students notably decreased their number of resets by 10, asillustrated in Figure 2. Additionally, there was an increase in the average number of achievements,rising from 5 to 9 gems. The number of achievements represents the gems students were able tocollect, and all five students achieved more gems, with an increase of up to 4 compared to the pre-test, as shown in Figure 2
journeys.AcknowledgmentThis material is based upon work supported by the National Science Foundation under Grant No.1107015, 1153250, 1643869 (past three grants), and 2221052 (active grant). Any opinions,findings, and conclusions or recommendations expressed in this material are those of the authorsand do not necessarily reflect the views of the National Science Foundation.References[1] Vernaza, K. M., Vitolo, T. M., Steinbrink, S., Brinkman, B. J. (2011). Scholars of Excellence inEngineering and Computer Science Program Phase I: Development and Implementation. Proceedings ofthe 2011 American Society of Engineering Education Annual Conference, June 26-29, Vancouver, BritishColumbia, Canada.[2] Vernaza, K. M., Steinbrink, S., Brinkman, B. J., Vitolo, T. M. (2014
presented the results ofyear 1 work, the background and theoretical underpinning and motivation for the project, and ourresearch and assessment plan in 2023 [3]. This current paper reflects on our experience recruitingand piloting the learning community courses for the first time in Fall 2023 and Winter 2024. Wepresent the demographics of the first cohort in comparison to students in a non-linked version ofour Introduction to Engineering course (ENGR 101). We also describe a few examples ofinterdisciplinary curriculum and projects that we have developed and share some studentfeedback on their experience.Student Recruitment, Demographics, and RetentionWe took the following steps to recruit students for the new learning community. A new page onthe
authors and do not necessarily reflect the views of the National ScienceFoundation.Bibliography[1] J. R. Morelock, “A systematic literature review of engineering identity: definitions, factors, and interventions affecting development, and means of measurement,” Eur. J. Eng. Educ., vol. 42, no. 6, pp. 1240–1262, Nov. 2017, doi: 10.1080/03043797.2017.1287664.[2] A. Godwin, “The Development of a Measure of Engineering Identity,” in 2016 ASEE Annual Conference & Exposition Proceedings, New Orleans, Louisiana: ASEE Conferences, Jun. 2016, p. 26122. doi: 10.18260/p.26122.[3] Z. Hazari, G. Sonnert, P. M. Sadler, and M.-C. Shanahan, “Connecting high school physics experiences, outcome expectations, physics identity, and physics career
data, making direct comparisons at each time point more difficult.However, quantitative data and qualitative data demonstrate gains in program objectives forcohort members. Students, despite a pandemic, showed growth in professional skills and careernetworks through the support of their S-STEM mentor, program guidance, tutoring, andinternship opportunities.IV AcknowledgementsThis material is based upon work supported by the National Science Foundation (NSF) underGrant No. 1833769. 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. The authors would like to acknowledge Eric Brown, Yoojin Choi, ReneeCox
development of more inclusive and culturallyrelevant practices tailored to meet the unique needs of Latinx students. We anticipate that ourfindings will offer valuable insights for engineering and computing programs at HSIs, benefitingfaculty, administrators, and professionals dedicated to serving Latinx and other BIPOC students. AcknowledgementsThis project received support from the United States National Science Foundation under theImproving Undergraduate STEM Education: Hispanic Serving Institutions (HSI) program,Award #2122917. Any opinions, findings, and conclusions or recommendations expressed in thismaterial are those of the authors and do not necessarily reflect the views of the National ScienceFoundation
, physics, and upper engineering labs Figure 3. Distribution of credit hours for labs and electives. Credit hours are normalized to 128 total hours.The two outliers for the general education credits both have multiple types of credits. The first isthe standard social study requirements, while the other is an unrestricted elective. So, the largeamount of general education credits required reflects more freedom in the curriculum rather thanan emphasis on social studies.MS/BS program:Out of the 35 schools examined in this study, 30 (86%) had a chemical engineering master’sdegree program. All statistics from this section will be in reference to those 30 schools.50% of schools with a MS program offer a MS/BS program. However, out of those 15 schools
cybersecurity research, counseling students, assisting with open days for new students, contributing to curriculum enhancements, and proposing a new club to support women in the industry, SWCSI (Supporting Women in the Computer Security Industry). He excels at guiding students in subject choices based on interest, ability and skills. His continual quest for knowledge and broadening his skills has proven beneficial to his students and his professional evaluations reflect this in perfect teaching scores. Additional awards, societies and honor groups include: 2018 Expert Level Instructor Excellence Award – Cisco Networking Academy. 2017 Instructor 5 Years of Service Award – Cisco Networking Academy. 2017 Excellence in CCNA
conclusions or recommendations expressed in thismaterial are those of the authors and do not necessarily reflect the views of the National ScienceFoundation. The authors thank our project evaluator, Dr. Liz Litzler. We thank advisory boardmember Diana Gonzalez for her support with recruitment on this project. The authors also thankthe year 2 and year 3 participants for supporting this work by sharing their experiences in oursurveys. References[1] T. M. Evans, L. Bira, J. Beltran-Gastelum, L. T. Weiss, and N. L. Vanderford, Evidence for a mental health crisis in graduate education, The FASEB Journal, vol. 36, pp. 282- 284, 2018.[2] J. L. Lott, S. Gardner, and D. A. Powers, Doctoral student
the GPDs to reflect on thelived experiences of graduate students in their program. As part of these questions, we inquiredabout the extent to which students were experiencing trauma during the time in graduate schooland the actions taken by the GPD when a student was experiencing trauma. The interview alsoincluded questions about the role of the department and institution in handling traumatic events.All the interview audio was transcribed by Rev.com for analysis purposes.Preliminary Data AnalysisLeveraging trauma-informed frameworks of care and systems analysis techniques, the dataanalysis has focused on the first two research questions noted in the Project Overview section.To this end, the initial data analysis process involved examining
analyzedalong with data from the other survey instruments to explore the relationships between cognitive,motivational, and emotional processes on self-efficacy as it relates to academic persistence.6. AcknowledgementsThis material is based upon work supported by the National Science Foundation under Grant No.2204892. Any opinions, findings, and conclusions or recommendations expressed in thismaterial are those of the author(s) and do not necessarily reflect the views of the NationalScience Foundation.7. References[1] H. N. Haron and A. M. Shaharoun, "Self-regulated learning, students' understanding and performance in engineering statics," presented at the IEEE