observations 1. What was the most important thing with students from another country about your interactions with your you learned from this collaborative might impact what you learn in this partner(s) as you work with them in experience? course? the online environment. 2. Please describe how doing this 2. How do you think the way you see 2. Describe how your course has been experience with international and understand the world might impacted by connecting with a class partners impacted your learning change by connecting with students from another country. experience. in another country
/energy/community-energy-planning/[16] “Community Energy and Emissions Reduction Plan.” Accessed: May 2, 2025. [Online].Available: https://www.brampton.ca/EN/residents/GrowGreen/Community-Energy-and-Emissions-Reduction[17] “College sets global best-practice energy standard through IEMP | Henry Ford College.”Accessed: May 2, 2025. [Online]. Available: https://www.hfcc.edu/iemp[18] Cortes, A., Dos Muchangos, L., Tabornal, K. J., & Tolabing, H. D. (2022). Impact of theCOVID-19 pandemic on the carbon footprint of a Philippine university. Environmental Research:Infrastructure and Sustainability, 2(4), 045012. https://doi.org/10.1088/2634-4505/acaa52[19] Da Silva, L. A., De Aguiar Dutra, A. R., & De Andrade Guerra, J. B. S. O. (2023
informed by our literature review and included questions aboutparticipants’ advisor(s), perceptions of their advisors’ work-life balance, research group climate,and department climate [4]. This paper focuses on responses to two questions from the largerstudy’s interview protocol: 1) What advice does your PhD advisor give you about your suitability and preparation for your desired career path? 2) Are there some aspects of your plans you don’t feel like you can openly discuss with your PhD advisor?3.3 | Data analysis We completed two rounds of inductive coding using transcripts from the interviews [29].In the first round of coding, we identified the five major themes of participant-advisorrelationship, participant's
advisor with my own needs, Overall, my relationship with my advisor isgood. Participants indicated their agreement with the items on a scale from Strongly Disagree (1)to Strongly Agree (5) on a series of questions on advisor relationships. The mean of these itemsis used as the advisor relationship variable. The scale demonstrated strong internal reliability(Cronbach’s alpha = .94).The demographic questions included: "How do you describe your gender identity?" with theoptions: Woman, Man, Genderqueer, Agender, Transgender, Cisgender, Non-binary/third gender,Prefer not to say, and a text write-in option. Race/ethnicity was collected with the question,“With which racial and ethnic group(s) do you identify?" The options included American Indianor
tested in Borrego et al.’s study, canhelp faculty systematically measure individual students’ progress toward culminating designoutcomes, particularly in multidisciplinary settings where knowledge integration is crucial. Bytailoring these rubrics to emphasize remote design considerations and sponsor constraints,instructors could better satisfy ABET’s requirement for robust assessment of outcomes liketeamwork, communication, and multidisciplinary solution strategies.2.4 Supporting Student Motivation and Well-BeingThough remote courses offer scheduling freedom, they also risk isolation and decreasedengagement if students rarely see each other beyond official project calls [2], [11]. Chou et al.[17] suggest that instructors can mitigate this by
quizzes and exams. • The LLM always gives itself a perfect self-assessment score. This could have disastrous consequences for students who blindly use LLMs without verifying the veracity of the presented solution(s), especially if the students trust that the self-assessment by the LLM.After the LLM completed all quizzes and exams, the LLM was determined to have earned an Ffor the course, as shown in Table 1. However, if we were to assume that a student only used anLLM on their assessments and completed all labs, that student may achieve an average grade inthe class. An average student is expected to earn 90% in the lab portion of the class. Looking atTable 2, an average lab grade of 90% would allow an average student using only
. Colab Number 49 Stocking 3.306 Parameters Normala, b Deviation 0.664 Estd. Absolute 0.088 More Positive 0.078 Extreme Difference Negative -0.088 s Test Statistics 0.088 Asim. Sig (2
and Engineering, 27(1).[2] Markle, R. S., Williams, T. M., Williams, K. S., deGravelles, K. H., Bagayoko, D., & Warner,I. M. (2022, May). Supporting historically underrepresented groups in STEM higher education:The promise of structured mentoring networks. In Frontiers in Education (Vol. 7, p. 674669).Frontiers Media SA.[3] Zambrana, R. E., Ray, R., Espino, M. M., Castro, C., Douthirt Cohen, B., & Eliason, J.(2015). “Don’t leave us behind” The importance of mentoring for underrepresented minorityfaculty. American Educational Research Journal, 52(1), 40-72.[4] Griffin, K. A. (2019). Institutional barriers, strategies, and benefits to increasing therepresentation of women and men of color in the professoriate: Looking beyond thepipeline
Miller, Sarah Rodriguez, Christine Harrington, JeanieTietjen, Courtney DeGeorge, and Clarissa Codrington. Thanks as well to Rebecca Zarch andStacey Sexton for their work on the faculty survey and feedback on our project.This material is based upon work supported by the National Science Foundation under Grant No.2110684. 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.References[1] National Science Board (NSB), National Science Foundation. (2020). Science and Engineering Indicators 2020. NSB-2020-1. Alexandria, VA. Available at https://ncses.nsf .gov/pubs/nsb20201/ Accessed January 4, 2022.[2] A. K
with their faculty mentors. Students’ research self-efficacy increased, gainedvaluable research skills and experience, and had positive perceptions about going to graduateschool.AcknowledgementThis material is based upon work supported by the National Science Foundation under Grant No.2243722.References[1] A. L. Zydney, J. S. Bennett, A. Shahid, and K. W. Bauer, “Impact of Undergraduate Research Experience in Engineering,” J. Eng. Educ., vol. 91, no. 2, pp. 151–157, Apr. 2002, doi: 10.1002/J.2168-9830.2002.TB00687.X.[2] D. S. Raicu and J. D. Furst, “Enhancing undergraduate education,” ACM SIGCSE Bull., vol. 41, no. 1, pp. 468–472, Mar. 2009, doi: 10.1145/1539024.1509027.[3] M. G. Norton and D. F. Bahr, “How to run a
://peer.asee.org/54094 9. Ramalingam, V., & Wiedenbeck, S. (1998). Development and validation of scores on a computer programming self-efficacy scale. J. Educational Computing Research, 19(4), 367381. https://doi.org/10.2190/4U0A-3WEG-R874-6PYD 10.Yoon, S. Y., & Sorby, S. A. (2020). Rescaling the Longitudinal Assessment of Engineering Self-Efficacy V3.0 for Undergraduate Engineering Students. Journal of Psychoeducational Assessment, 38(2), 209-221. https://doi-org.services.lib.mtu.edu/10.1177/0734282919830564 11.ABET (2023). Criteria for Accrediting Engineering Programs, 2024 – 2025. Accessed Jan 11, 2024: https://www.abet.org/accreditation/accreditation-criteria/criteria-for-accrediting-engineeri
. Jennifer Nicole Wilburn, California University of PennsylvaniaBrenda Fredette, California University of Pennsylvania ©American Society for Engineering Education, 2025 Aligning Career & Campus Experiences for Student Success (ACCESS): An NSF S-STEM InitiativeIntroductionFormed in 2022 through the integration of California, Clarion, and Edinboro universities,Pennsylvania Western University (PennWest) is a public institution with campuses spanning[redacted]. The university is recognized for its 175-year legacy of academic excellence,nationally accredited programs, and commitment to career-focused education. PennWest is aPredominantly Undergraduate Institution (PUI) that serves as
) Implementation Step Linked Artefact Produced Assessment Tag Variant(s) Calculate δ threshold for Iterated Formal proof appendix Cognitive - TFT Prudence Design stake-slashing One-shot Solidity/Python script Cognitive - contract Incentive Build graceful-degradation Noise API gateway module Affective - wrapper Resilience Normalise rewards via Pay-off Asym. Federated-learning Professional - Shapley
Accessibility and Universal Design for Learning. He was the recipient of the Foundation Excellence Award, David S. Taylor Service to Students Award and Golden Apple Award from Boise State University. He was also the recipient of 2023 National Outstanding Teacher Award, ASEE PNW Outstanding Teaching Award, ASEE Mechanical Engineering division’s Outstanding New Educator Award and several course design awards. He serves as the campus representative and was the past-Chair for the ASEE PNW Section. His academic research interests include innovative teaching and learning strategies, use of emerging technologies, and mobile teaching and learning strategies.Dr. Angela Minichiello PE, Utah State University Angela (Angie) Minichiello
(0.5/5 score) Inaccurate; student |0.1-1|=0.9 Student was 10% sure of the correctness of the was underconfident: solution and the problem was 100% correct Greater than 0.5 (perfect score of 5/5 score)Figure 1 illustrates some of these scenarios in terms of accuracy of judgement.Figure 1. Students’ confidence of judgement. The maximum score was 3 points.To further explain the process used to evaluate students’ judgement of confidence, severalexamples of mathematical problems are presented:Problem 1: A model rocket is fired in a vertical plane and the velocity v(t) is measured as shownin the following figure: V(t) [m/s] t [s
including studentfamiliarity with the method(s), incoming student skills, student risk tolerance, environmentalconstraints (e.g. class size), perceived risks (e.g. on grades), perceived workload, socialinfluences, and context-specific motivations [3]. Other research has identified that these barriersto student engagement can differ between individual students, or between communities ofstudents. Felder and Brent described the challenges of active learning, where some students arecomfortable whereas others may struggle [1].For specific communities of students like Indigenous students, for example, the importance ofthe experience is critical to many learners. Leddy and Miller stated that “scaffolded experientiallearning is a mainstay in Indigenous
questions. To determine if our collecteddata was normally distributed, we ran Shapiro-Wilk normality tests on all ECCE and IMMS datafrom both the experimental and control groups, both pre- and post-PBLA intervention. The Shapiro-Wilk tests yielded the following:Table 2. Shapiro-Wilk Test Results ECCE-PRE ECCE-POST Control Group S-W = 0.964, df = 71, p = 0.040 S-W = 0.938, df = 71, p = 0.002 Experimental Group S-W = 0.969, df = 120, p = 0.007 S-W = 0.962, df = 120, p = 0.002 IMMS-PRE IMMS-POST Control Group S-W = 0.942, df = 71, p = 0.003 S-W = 0.967, df = 71, p = 0.038 Experimental Group S-W = 0.951, df
through listserv(s) and/or paper postings onbulletin boards with additional information: • Open to graduate students in STEM-related programs • Continue to develop your inclusive teaching skills to support all students in your classes • Attend 3 workshops in [session month/year] • Eligible to earn an Inclusive Teaching for STEM Graduate Students Mini-Course CertificationAll sessions are 90 minutes, including both content delivery (generally 50 minutes total) andsmall group breakout discussions (generally 40 minutes total, broken into 5-10 minute individualbreakout sessions). Please note that while the sessions are titled “classroom,” the instructionalmodality is defined broadly and teaching techniques and strategies for in
behaviors. In the future, this will be taught and reinforced throughout the semester boththrough guided reflection and more traditional assignments and activities with better-designedassessment.references (1) Springer, Leonard, Mary Elizabeth Stanne, and Samuel S. Donovan. "Effects of small- group learning on undergraduates in science, mathematics, engineering, and technology: A meta-analysis." Review of educational research, vol. 69, no.1, pp. 21-51, 1999. (2) ABET, 2025, “Criteria for Accrediting Engineering Technology Programs, 2025-2026.” https://www.abet.org/2025-2026_etac_criteria/ (3) Wolfe, J., Powell, B. A., Schlisserman, S., and Kirshon, A., 2016, “Teamwork in Engineering Undergraduate Classes: What
first three authors).The second study was conducted as a focus group with seven Black faculty mentors speakingabout their experiences mentoring Black Ph.D. students in engineering. A parallel studyexploring the experiences of these Black Ph.D. mentees is underway and will be presented ina future publication.2.2 Research Quality The validation process incorporated multiple rounds of evidence gathering, informed byHall et al.'s perspectives on multidisciplinary approaches to understanding complex socialrelationships [33]. This included peer debriefing sessions, member-checking, and thoroughdocumentation of the research process. The data analysis phase employed systematic codingand theme development, with all team members participating to
Undergraduate Engineering Programs Emphasize? A Systematic Review,” J of Engineering Edu, vol. 106, no. 3, pp. 475– 526, Jul. 2017, doi: 10.1002/jee.20171.[4] C. Young and M. L. Pate, “Compact Power Equipment Troubleshooting Training: Formative Assessment using Think-Aloud Pair Problem Solving,” in 2013 Kansas City, Missouri, July 21-July 24, 2013, American Society of Agricultural and Biological Engineers, 2013, p. 1. Accessed: Sep. 18, 2024. [Online]. Available: https://elibrary.asabe.org/abstract.asp?aid=43359[5] S. Ramachandran, R. Jensen, J. Ludwig, E. Domeshek, and T. Haines, “ITADS: A Real-World Intelligent Tutor to Train Troubleshooting Skills,” in Artificial Intelligence in Education, vol. 10948, C. Penstein Rosé
, and plant biology. R EFERENCES [1] S. Fathalla, S. Vahdati, S. Auer, and C. Lange, “Metadata analysis of scholarly events of computer science, physics, engineering, and mathematics,” in Digital Libraries for Open Knowledge, E. M´endez, F. Crestani, C. Ribeiro, G. David, and J. C. Lopes, Eds. Cham: Springer International Publishing, 2018, pp. 116–128. [2] E. Dagien˙e, “Mapping scholarly books: library metadata and research assessment,” Scientometrics, vol. 129, no. 9, pp. 5689–5714, 2024. [Online]. Available: https://doi.org/10.1007/s11192-024-05120-1 [3] A. Mierzecka, “The role of academic libraries in scholarly communication. a meta-analysis of research,” Studia Medioznawcze
., vol. 95, no. 2, pp. 139–151, Apr. 2006, doi: 10.1002/j.2168-9830.2006.tb00885.x.[3] J. Trevelyan, The Making of an Expert Engineer, 0 ed. CRC Press, 2014. doi: 10.1201/b17434.[4] ABET, “Criteria for accrediting engineering programs,” Baltimore, MD, 2024. Accessed: Oct. 27, 2024. [Online]. Available: https://www.abet.org/accreditation/accreditation-criteria/criteria- for-accrediting-engineering-programs-2024-2025/[5] H. Chaibate, A. Hadek, S. Ajana, S. Bakkali, and K. Faraj, “A Comparative Study of the Engineering Soft Skills Required by Moroccan Job Market,” Int. J. High. Educ., vol. 9, no. 1, p. 142, Dec. 2019, doi: 10.5430/ijhe.v9n1p142.[6] M. S. Rao, “Enhancing employability in engineering and
21st, 2025.[4] Cervone, G., Franzese, P., Ezber, Y., and Boybeyi, Z. “Risk assessment of atmospheric emissions using machine learning”, Nat. Hazards Earth Syst. Sci., 2009, 8, 991–1000.[5] Chen, J., Kong, H., Su, Y., and Zhang, H. “Indoor air quality monitoring system for smart buildings: A comprehensive review”. Building and Environment, 2021, 196, 107786.[6] Cuesta-Mosquera, A., Močnik, G., Drinovec, L., Müller, T., Pfeifer, S., Minguillón, M. C., Briel, B., Buckley, P., Dudoitis, V., Fernández-García, J., Fernández-Amado, M., Ferreira De Brito, J., Riffault, V., Flentje, H., Heffernan, E., Kalivitis, N., Kalogridis, A.-C., Keernik, H., Marmureanu, L., Luoma, K., Marinoni, A., Pikridas, M., Schauer, G., Serfozo, N
their evidence-based practices. Theanalysis is ongoing and will be presented in a future paper to highlight how they are used toupdate our change framework and activities.AcknowledgementsThis material is based upon work supported by the National Science Foundation under AwardDUE- 2021532. 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.References[1] Chan Hilton, A.B. (2024). Board 429: Work in Progress: Capacity-Building for Change Through Faculty Communities Exploring Data and Sharing Their Stories. ASEE 2024 Annual Conference and Exhibition, NSF Grantees Poster Session, Portland, OR, June 2024
specimen, the process of loading the brass specimen can ANDWILL STRETCH THE SPECIMEN. To safely load the brass specimen, follow the processdescribed in step 6 but for the lower jaws, grab the test rod and lightly tap the joystick. Havesomeone monitor the load on the laptop and ensure the load does not exceed 100 lbs. This canhappen very quickly. 6. Once the test rod has been mounted in the jaws, connect the strain gage to the cord, see Figure 6a, by plugging in the data cord to the test rod, see Figure 6b. To connect the cord to the box, with the black locking switches in the up position, see Figure 7a, insert the white wire into the D120 port on Channel 1 Input. Then insert the black wire into the S- port and the red wire
the perceived challenges of live streaming as an informal learning opportunity forcomputer science students?Through this work, we aim to understand and evaluate whether or not live streaming impacts anundergraduate student’s perceived self-efficacy in software or game development, RQ1 . Toquantitatively measure self-efficacy, we have adapted questions from Ramalingam andWiedenbeck’s Computer Programming Self-Efficacy Scale and Hiranrat et al.’s surveymeasurements for software development career [41, 42]. As we allow the students to choose theirown projects and set their own goals, we expect there to be some division among the participantson how quickly they believe themselves to be improved based on the gravity of the goals they setfor
from merely reacting tochallenges to actively learning and growing from them. Ultimately, this approach shifts themindset from reactive problem-solving to personal development and continuous learning. Beyond these alignments, in terms of connection to industry and leadership, personalmastery does have a presence in industry. Literature noting that current engineering education isnot producing leadership qualities in engineers [30] suggests that something must be done tomeet the U.S.’s leadership needs. With many of the traditional organizations within industrytransitioning to learning organizations, likely to meet the demands of the Fourth IndustrialRevolution as learning is the “currency of survival” [8, p.1], lifelong learning remains
of universities is another task al-together that’s equally important. By building upon continued efforts, future directions can drivemeaningful progress toward equity in STEM education. Such efforts will ensure that STEM fieldsaccurately reflect the overall diversity of the population as a whole, as well as create innovationand excellence for every student engaging in STEM curriculum.AcknowledgeThis work is supported in part by the National Science Foundation (NSF) under Grant No. 2301868and the National Institute of Food and Agriculture (USDA NIFA) Grant No. 2023-70020-40570 .References [1] S. R. Howe, “Culture at work: A comparative analysis of advertising for