in engineering.Any opinions, findings, and conclusions or recommendations expressed in this material are thoseof the authors and do not necessarily reflect views of the National Science Foundation. Page 25.1367.17
progresses, the fact those online students have less interaction with the instructor is reflected Page 25.1396.15 by the increase in their time spent on the exercises and their perceived difficulty levels.3. When the difficulty level (NDI) of the lab exercise is high, as seen in Lab 6 (NMR), on- campus students may learn slightly better than the on-line students. Lab 6 is generally considered by students as much more difficult than other labs. Students' behavior in this lab is worth careful study.4. Lab 7 has relatively low NDIs and high PPIs across all semesters. This may have an interesting implication, i.e. students tend to learn
Foundation under Grant No.EEC-1106529, Research Experience for Teachers in Manufacturing for Competitiveness in theUnited States (RETainUS). Any opinions, findings, and conclusions or recommendationsexpressed in this material are those of the author(s) and do not necessarily reflect the views ofthe National Science Foundation.Bibliography1. University of Georgia, River Basin Center (no date). Georgia’s Aquifers. Retrieved January 8, 2012, from http://www.rivercenter.uga.edu/education/summit/general/geology/ aquifers.htm.2. Brain, M., & Lamb, R. (2000, October 9). How Nuclear Power Works. Retrieved July 6, 2011, from http://www.howstuffworks.com/nuclear-power.htm .3. Texas Mining and Reclamation Association [TMRA] (no date). In
questions.The project anticipates expanding the scope of the E3 program by recruiting a higher number ofhigh school teachers and provide them training in developing ethics curriculum for their studentsalong with relevant practical examples so that a larger number of prospective first-generationstudents can receive exposure to the education required to help improve their ethics self-efficacy.Acknowledgement: This work was supported by the National Science Foundation’s Ethical andResponsible Research (ER2) grant (SBE # 2124888). Any opinions, findings, conclusions, orrecommendations presented are those of the authors and do not necessarily reflect the views of theNational Science Foundation.References: 1. R. Thornberg, “The lack of professional
relationships and create connections in thesocial fabric of the makerspace [11], [13]. To have an inclusive makerspace, all studentparticipants must have a strong sense of belonging [11], [14]. Fostering a culture that engendersbelonging in participants requires makerspace leaders and administrators to critically questionhow the environment and culture of the makerspace systematically marginalize certain groupsfrom participating and succeeding in these spaces [15]. To ensure that the makerspace does notreinforce a “closed loop” culture, makerspace designers should reflect on who is not present inthe makerspace and the potential barriers to participation and belonging present in the currentmakerspace design [11]. This can be difficult to achieve because
Conference on Innovation and Technology in Computer Science Education, pp. 325–325, 2019. [6] M. L. Walther, “Matlabta: A style critiquer for novice engineering students,” Master’s thesis, Michigan Techno- logical University, Houghton, MI, 2020. [7] J.-M. Robert and E. Brangier, “What is prospective ergonomics? a reflection and a position on the future of ergonomics,” in Ergonomics and Health Aspects of Work with Computers: International Conference, EHAWC 2009, Held as Part of HCI International 2009, San Diego, CA, USA, July 19-24, 2009. Proceedings, pp. 162–169, Springer, 2009. [8] R. Oshana, “Human factors and user interface design for embedded systems,” in Software Engineering for Em- bedded Systems, pp. 417–440, Elsevier
aspect of the projectis to improve the communication of the broader impacts and societal benefits provided by thecommunity’s research in engineering. The project focuses its mission not only on the engineeringresearch necessary to advance the field, but on the need to educate an engineering workforce thatis a demographic reflection of the current and future nation so we may maximize the impact ofengineering technologies on society. This investigation was undertaken through two approaches.Primarily, we sought to understand to what extent researchers are communicating the broaderimpacts of their work. In addition, we explored the ways in which researchers communicatethose impacts. Theoretical Background
: at-risk or prone-to-risk (grade below B-), and average or outstanding (grade B- or above) • Three types: at-risk or prone-to-risk (grade below B-), average (grade B- or above but below A-), and outstanding (grade A- or above) • Four types: at-risk (grade below C-), prone-to-risk (Grade C- or above but below B-), average (Grade B- or above but below A-), and outstanding (grade A- or above)Addressing RQ2, we delve into the impact of integrating students’ background andnon-cognitive features on the predictive accuracy of LLMs. We hypothesize that a richer featureset, reflecting both the academic and experiential learning trajectories of students, cansignificantly enhance LLM forecasting capabilities.Our contributions are
interviews to understand the role classroom teachingpractices play in the academic success of engineering students with ADHD. Collectively, thisresearch allows us to explore students’ perceptions of how active learning and lecture-basedclasses influence their classroom experiences, academic adjustment, and sense of belonging.AcknowledgmentsWe would like to acknowledge Cooperative Institutional Research Program (CIRP), the HigherEducation Research Institute (HERI), and the University of California, Los Angeles (UCLA). This research is supported by the U.S. National Science Foundation (2043430). Any opinions,findings, and conclusions, or recommendations expressed in this material are those of theauthor(s) and do not necessarily reflect the views of
• GLC workshop model graduate students Industry Advisory Board Community (GLC) model • GLC small group reflections to work effectively Diversity Advisory Board • Implement & adjust GLC activities • Trainees' ePortfolios in multidisciplinary • Interdisciplinary based on feedback loop • Symposium content teams, Faculty/Mentors Institutional • Hold annual symposium • Professional & communication communicate Support/Infrastructure • Develop ePortfolio structure core competencies matrix effectively with Investigators' • Develop recruiting practices and
curriculum or areas wherestudents may veer off course. Interventions based on the results might entail adjustments tocurricular guidelines, enhanced academic advising, or the implementation of novel programs andinitiatives to bolster student progress. As this project continues to evolve, we expect to delivernew analytical potential to the community and create new strands of inquiry to connect toexisting persistent problems in engineering education. AcknowledgmentsThis material is based upon work supported by the National Science Foundation under Grant No.BPE- 2152441. Any opinions, findings, and conclusions or recommendations expressed in thismaterial are those of the authors and do not necessarily reflect the
, scalability can be achieved byholding the lectures in a large computer lab but usually these labs are set up for open access. As aresult, the flowerpots may need to be set up before each lecture and taken away after. Anotherpossibility is to hold multiple sections of the course with smaller section sizes.AcknowledgmentsThis material is based upon work supported by the National Science Foundation under Grant No.DUE-IUSE-2116226. Any opinions, findings, and conclusions or recommendations expressed inthis material are those of the authors and do not necessarily reflect the views of the NationalScience Foundation.References [1] P. Seeling, “Active learning moves programming students from novice to skilled,” https://www.pearsoned.com/active-learning
prioritize and schedule. We also gathered information about students’ experience of the workshop (the knowledge of the presenter, length of the session). Here we present the most salient results about student learning outcomes related to the workshop’s objectives. Learning Styles and Study Groups Workshop: The learning styles and study groups workshop seeks to increase student’s understanding of their results on the Felder/Solomon Engineering Learning Styles Index by learning about a) the different learning style indexes (e.g. active/reflective, visual/verbal, sensing/intuitive, and sequential/global), b) how these indexes manifest when learning new information, and c) what skills to use to adapt
theory, personalized learningpedagogies address the assumption that learners, especially college students, have an inherentneed to comprehend the purpose behind their learning endeavors, whether revisiting familiarconcepts or exploring new domains.Within the general framework of personalized learning, activities grounded in real-life scenariosenhance student engagement, particularly evident in fields such as robotics and computer science,where problem-solving and scenario-based learning align with adult learning principles. Derivedfrom andragogy, four key principles characterize adult-centered instruction and learning 10,9,11 :relevance to assignments, encouragement of critical and reflective thinking, acknowledgment andutilization of personal
) and do not necessarily reflect the views of the National Science Foundation.DeclarationsThis project is being conducted in accordance with research reviewed by Institutional ReviewBoards for Human Subjects Research at Clarkson University (Protocol 23-31) and the Universityof Colorado Boulder (Protocol 23-0344).References[1] American Academy of Environmental Engineers (AAEE), Environmental Engineering Body of Knowledge, Annapolis MD: AAEE, 2009[2] D. Grasso, Chair; Environmental Engineering for the 21st Century: Addressing Grand Challenges. Consensus Study Report. Washington DC: The National Academies Press, 2018. https://doi.org/10.17226/25121[3] L. Blaney, A. MacKay, D. Rodrigues, K. Nelson, “Results from the 2022-2023 member
. These results are presented in Figures 1-4 below. FIGURE 1: Results for survey items 1-5.FIGURE 2. Results for survey items 6-10.FIGURE 3. Results for survey items 11-15. FIGURE 4. Results for survey items 16-20.DiscussionSTEM Identity, Self-Efficacy, Mindset, and Major/Career IntentionsOverall, participation in the VIP program did not seem to impact engineering identity, self-efficacy, mindset, or intentions to remain in the engineering major or pursue an engineeringcareer. Most participants scored highly on these measures, perhaps reflecting a selection bias,with the VIP program attracting students who already have strong sense of themselves as “STEMpeople.” It may also be the case that
No.DUE-TUES-0941035. Any opinions, findings, and conclusions or recommendations expressed inthis material are those of the authors and do not necessarily reflect the views of the NationalScience Foundation.References[1] Gurocak, H., “Mechatronics course with a two-tiered project approach,” 2007 ASEE Annual Conference and Exposition.[2] Giurgiutiu, V. and Mouzon, B., “Functional Modules for Teaching Mechatronics to non-EE Engineering Students,” 2005 ASEE Annual Conference and Exposition.[3] Pourboghrat, F., et. Al., “Enhancing mechatronics education using model- based techniques and Mathworks tools,” 2011 ASEE Annual Conference and Exposition.[4] Rogers, J., Rabb, R., Korpela, C. and Ebel, R. “Learning mechatronics
to assess the impact of case-based instruction on conceptual understanding andtheir attitudes towards case studies.VI. Acknowledgements This research is funded by the National Science Foundation (Grant # DUE 1140109.Statements made in this paper are the opinions of the authors and may or may not reflect theviews of the National Science Foundation. We would also like to thank our graduate students,Verrol McLeary and Niya King, for their assistance during the lab courses.VII. References1. Howe, N. and W. Strauss, Millennials Rising: The Next Generation. 2000, New York: Vintage Books.2. Elam, C.L., T.D. Stratton, and D.D. Gibson, Welcoming a New Generation To College: The Millennial Students. Journal of College
any two of the selection criteria. These letters must reflect academic, employment or community experiences that relate to the energy technology field and highlight leadership and teamwork abilities of the representative. These letters must accompany the application package, not be sent separately.Part E: Certification Page 23.934.13 12 Applicant's Certification I certify that the information I have provided in this document is accurate. I understand that if I am chosen to participate in the CREATE US – Australia Renewable Energy Learning Exchange and Network, I will be representing both my organization
as to what is contained at more detailed levels. Cross-Course Effects on Learning: The power of the Adaptive Map tool is its emphasis on connections. So far, the tool has been limited to a single course, but by developing content for related courses (e.g., Dynamics, Strength of Materials, etc.) researchers could explore how this tool could help students develop knowledge that crosses course boundaries.6. AcknowledgmentsThis material is based upon work supported by the National Science Foundation under Grant No.NSF TUES-1044790. Any opinions, findings, and conclusions or recommendations expressed inthis material are those of the authors and do not necessarily reflect the views of the NationalScience
reflect functional capacity.Water Utility Management and Human Intended to provide the learner with anRelations overview of the management and human relations aspects of water and wastewater utilities. A learner in this course will gain industry-based insight into the special operations and management functions of a water or wastewater utility with emphasis on the human relations activity.Modern Technology & Water
. University of California, Santa Barbara Jaman Mohit Texas Tech University Montana Montez Texas Tech University Alyson Garcia Midwestern UniversityAcknowledgement:This material is based upon work supported by the National Science Foundation under Grant No.(1930037). Any opinions, findings, and conclusions or recommendations expressed in this materialare those of the author(s) and do not necessarily reflect the views of the National Science Foundation.Correspondence concerning this manuscript should be addressed to
similarpattern to the ToSLS, so there is no reason to suggest that the decline is due to the ToSLS itself.In addition, grades for students in these classes serve as an objective measure that most studentsare learning this material, they are just not translating this learning to their performance on post-tests.5. CONCLUSIONWe conclude that students, both STEM and non-STEM, indicate that their scientific skills andknowledge increase over the course of a semester in which they participate in a CAB project.This is reflected in the high pass rates of students enrolled in all of these classes, whichobjectively assess (through a variety of means) that students have learned the assigned material.The anomalous findings from the ToSLS and the Alternative SL
these face-to-face strategies should be translated into a web-based environment[24, 25].We have implemented collaborative learning activities in our courses using the group features inPrairieLearn while encouraging students to use the POGIL roles of Recorder, Manager, andReflector. The Recorder is the main “driver” who enters most of the answers in PrairieLearn. TheReflector completes a survey at the end of each activity, reflecting on the group’s interaction andhow the activity itself helped their learning. The Manager coordinates team’s efforts, making sureeveryone is contributing and following along. Currently these roles are encouraged, but notenforced by the system. Members of each group are required to alternate in these roles such
receivingscholarship through the NSF award and through the CARA donor, which currently have GPArequirements of 2.5/4.0 and 3.0/4.0, respectively. A main goal of the Spring 2022 semester willalso be to create more group cohesion between the 22 scholars and to engage scholars to be moreactive participants in the workshops, events, and on campus.AcknowledgementsPartial support for this work was provided by the National Science Foundation Scholarships inScience, Technology, Engineering, and Mathematics (S STEM) program under Award No.2028340. Any opinions, findings, and conclusions or recommendations expressed in this materialare those of the author(s) and do not necessarily reflect the views of the National ScienceFoundation.References1. Bailey, T.R., K.L
program based on the continuous collection of data from a variety ofsources. These sources included interviews from a mixture of stakeholders (instructors, administrators,students, alumni, and advisors), pre-post-retrospective surveys from students within the program, studentwork, and reflections from an embedded ethnographer. The analyzed data includes interviews from 30students, 20 alumni, and 14 faculty/administrators/advisors as well as over 241 pre/post/retrospectivesurvey responses. The data from these sources were analyzed and reviewed by the cross-college facultyfor refinements to the model at the end of each academic year as well as for identifying institutionalbarriers toward, and strategies for, transdisciplinary programming. As a
thestudy groups, and three of the five achieved the required C to continue on to the next course in the EEsequence. However, for the Scholars who did not achieve a C, the PI ran a mini-course after the semesterended, to raise their skill levels to C level. Out of the two, one was able to continue to the next course,while it was recommended to the other, that he change his major to a two-year electrical technologymajor, which he eventually did. It should be noted that the student who did not achieve the skills neededto continue in the major, also scored very poorly on our department’s math pre-Calculus assessment tests,even though he scored at least a C in Pre-Calculus, Calculus I and Calculus II, which indicates that gradesdo not always reflect
glaze that solely used materials from the Black Hills, as it added additional creative andtechnical challenges to overcome.The scientific and creativity rubric that was used to for the MET 352 competition can be seen inTable 2. The students were evaluated by program faculty and the AIR. The students also receiveddirect feedback (comments) from the evaluators.Spring 2022 MET 352– Results and Lessons LearnedThe A+E team goal for the MET 352 course was to have the student teams design and produce(formulate, fire, glaze) a unique ceramic body. In that regard, the design goal for MET 352 was asuccess as all teams successfully designed and fabricated prototypes. One point of reflection forthe PIs after the term was complete was the reproducibility or
with less difficulty and workload, even though they were told all choiceshad similar workload and difficulty. Understanding what groups of students feel stressed whenchoosing from multiple options can help design strategies to minimize such negative effects ofassignment choice.We hope that the findings presented in this paper help educators with proper implementation ofISBL and decision-making related to offering context choice to their students.AcknowledgementsThis material is based upon work supported by the National Science Foundation under Grant No.2000599 (ECR program). Any opinions, findings, and conclusions, or recommendations expressedin this material are those of the authors and do not necessarily reflect the views of the
necessarily reflect the views of the NationalScience Foundation.References [1] Sonnert, G., & Sadler, P. M. (2014). The impact of taking a college pre-calculus course on students’ college calculus performance. International Journal of Mathematical Education in Science and Technology, 45(8), 1188-1207. [2] Bressoud, D. M. (2014). Attracting and Retaining Students to Complete Two-and Four- Year Undergraduate Degrees in STEM: The Role of Undergraduate Mathematics Education. National Academy of Sciences.[3] Wade, C., Sonnert, G., Sadler, P. M., & Hazari, Z. (2017). Instructional Experiences that Align with Conceptual Understanding in the Transition from High School Mathematics to College Calculus