engineering laboratory courses and asked the respondents to answer survey itemsrelated to five research questions: 1. What are the three most important learning outcomes for a laboratory-intensive chemical engineering course? [Open-ended Response] 2. How important are the following learning outcomes for a laboratory-intensive chemical engineering course? [Likert scale for level of importance and Top 5 of importance ranking] 3. What gaps exist in the thirteen learning outcomes identified by Feisel and Rosa? [Open- ended Response] 4. Which learning outcome(s) do you feel you have the most trouble with / are weakest in? [Select 3] 5. Which learning outcome(s) do you feel your overall chemical engineering
methods,” in 2005 IEEE international conference on systems, man and cybernetics, 2005, pp. 86–91.[7] D. DeLaurentis and R. K. Callaway, “A system-of-systems perspective for public policy decisions,” Review of Policy research, vol. 21, no. 6, pp. 829–837, 2004.[8] N. Guarino, D. Oberle, and S. Staab, “What Is an Ontology?,” Handbook on Ontologies, pp. 1–17, 2009, doi: 10.1007/978-3-540-92673-3_0.[9] Oxford English Dictionary, “https://www.oed.com/.”[10] T. R. Gruber, “A translation approach to portable ontology specifications,” Knowledge Acquisition, vol. 5, no. 2, pp. 199–220, Jun. 1993, doi: 10.1006/KNAC.1993.1008.[11] Z. Ming et al., “Ontology-based representation of design decision hierarchies,” J Comput
] Van Veelen, R., Derks, B., & Endedijk, M. D. (2019). Double trouble: How beingoutnumbered and negatively stereotyped threatens career outcomes of women inSTEM. Frontiers in Psychology, 10, 150.[6] Statistics Netherlands (2016). De Arbeidsmarkt in Cijfers 2016. Available at:https://www.cbs.nl/-/media/_pdf/2017/19/de-arbeidsmarkt-in-cijfers2016.pdf[7] Stoeger, H., Duan, X., Schirner, S., Greindl, T., & Ziegler, A. (2013). The effectivenessof a one-year online mentoring program for girls in STEM. Harvard Kennedy SchoolGender Action Portal.[8] Kupersmidt, J., Stelter, R., Garringer, M., & Bourgoin, J. (2018). STEM Mentoring.Supplement to the "Elements of Effective Practice for Mentoring". MENTOR: TheNational Mentoring Partnership
also be explored.AcknowledgementsSupport for this work was provided by the National Science Foundation under Award No.2301341. 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. Research work was conducted under institutional IRB protocols, IRB#1965654. Theauthors would also like to thank Dr. Jenni Buckley for providing copies of her EngineeringStatics class notes for use in this work.References1. ABET, “Criteria for Accrediting Engineering Programs, 2020 – 2021 | ABET,” ABET, 2021. https://www.abet.org/accreditation/accreditation-criteria/criteria-for-accrediting-engineering- programs-2020-2021
session lasted for more than an hour. Session 1’s duration was 86minutes, Session 2 lasted for 78 minutes, and Session 3 lasted for 74 minutes. A total of 238minutes (3 hours 180 minutes) worth of qualitative data was obtained. 3.4. Data AnalysisThe qualitative data was prepared, cleaned, and subjected to the MMCS analytical approachstarting with the thematical analysis [33]. The thematic analysis involved open coding,allowing for the initial identification and labeling of significant concepts within the data [34],[35], [36]. Subsequently, the generated codes were organized into meaningful categories,laying the foundation for the development of coherent themes that encapsulate the essence ofthe data. Next was to develop the teamwork or team
] S. Negash, “Business intelligence,” Communications of the association for information systems, vol. 13, no. 1, p. 15, 2004. [5] S. Siuly and Y. Zhang, “Medical big data: neurological diseases diagnosis through medical data analysis,” Data Science and Engineering, vol. 1, pp. 54–64, 2016. [6] D. A. Jenkins, M. Sperrin, G. P. Martin, and N. Peek, “Dynamic models to predict health outcomes: current status and methodological challenges,” Diagnostic and prognostic research, vol. 2, no. 1, pp. 1–9, 2018. [7] J. Chen, K. Li, H. Rong, K. Bilal, N. Yang, and K. Li, “A disease diagnosis and treatment recommendation system based on big data mining and cloud computing,” Information Sciences, vol. 435, pp. 124–149, 2018. [8] L. Sun, C. Liu
furthest tocompletion, with electrical design being lowest and equal to plumbing. An unexpected result was how manytake their designs to a construction document (CD) level of completeness (Fig. 2b). This could be partiallydue to a team’s ability to go to that level of refinement, or perhaps certain key parts of a discipline’ssystem(s) are developed to that extent while other parts are not. For example, a team may design a singlestructural connection but not all of them in the building. To provide some literature context, most capstoneshave students target a level of completeness of their project somewhere between SD and DD [18-19]. a) covered within the capstone b) completeness of student work
their ability to learn the ma-terial, apply the material they have learned, and how well they believe they will perform in the Figure 5: User testing flow chart.learning activity. The full list of questions in the affective assessment is provided in Appendix B.The cognitive assessment consists of five multiple-choice questions focusing on technical aspectsof AFM imaging and identifying sources of common image artifacts.In the lab session, once it was confirmed that each student had completed the pre-lab, they wererandomly assigned to either the simulation cohort or the traditional paper (control) cohort. Stu-dents in the paper cohort did not have access to the simulation and were instead provided withimage(s
behaviors.The foundation of the MBTI lies in four fundamental dimensions, each represented by a pair ofopposing traits: • Extraversion (E) – Introversion (I): This dimension focuses on where individuals direct their attention and energy. Extraverts gain their energy from external sources and thrive on social interaction, while introverts find solace in their inner world and prefer reflection. • Sensing (S) – Intuition (N): This aspect relates to how individuals process information. Sensing types rely on concrete details and present realities, while intuitive types prioritize abstract concepts and future possibilities. • Thinking (T) – Feeling (F): This dimension highlights decision-making styles. Thinkers
Services at Utah State University. Her research centers the intersection identity formation, engineering culture, and disability studies. Her work has received several awards including best paper awards from the Journal of Engineering Education and the Australasian Journal of Engineering Education. She holds a Ph.D. in Engineering Education from Virginia Tech as well as M.S. and B.S. degrees in civil engineering from the South Dakota School of Mines and Technology.Dr. Bruk T Berhane, Florida International University Dr. Bruk T. Berhane received his bachelorˆa C™s degree in electrical engineering from the University of Maryland in 2003. He then completed a masterˆa C™s degree in engineering management at George
with the question, four in-context examples of answers, and the corresponding codes and instructed it to generate thecode(s) for the new answer instance. The in-context examples for GPT-4 prompt are drawn fromthe training split of the manually-coded dataset. We finetuned the Mixtral of Experts (MoE) [30]model using input and target pairs derived from the manually-coded training datasets. Thistrained model was then prompted with new test inputs, and the model-generated coded sequencewas evaluated against the manually coded target sequence. We evaluated both models on a testset of around 140 samples for each thermodynamics question. Using manual and languagemodel-based coding, we aim to answer two research questions: 1. What aspects of student
caring that includes both comfortwith faculty and empathetic faculty understanding from the same author.Discrimination (25 items)Discrimination is an active process that influences belonging in engineering (McGee, 2020). Toaccount for this potential, we adapted and included five items across five different identity-axes(race/ethnicity, gender, sexual orientation, (dis)ability, and socioeconomic status) from Bahnsonet al.’s (2022) work on discrimination in engineering graduate student experiences.Comfort and Team Inclusion (19 items)We believe feelings of discrimination and differences in belonging are also seen through students’comfort and inclusion on their team. As such, we included items based on these topics. Like othersabove, these scales
console panel is used to toggle thefan power and adjust the wind speed. The other gauges on the console panel are unused (they arefor a force balance from the manufacturer). A Dwyer Mark II Manometer is used to measure thewind speed by reading the pressure change due to the flow. Assuming a temperature of 25 ◦ C anda pressure of 1 atm, using the datasheet [13] gives the conversion to wind speed in m/s as p v = 20.4952 Pv (4)where v is the wind speed in m/s and Pv is the pressure reading in inches of water.5.1 Benchmarking Drag on a SphereThe drag on a sphere is a well-studied quantity in fluid mechanics, so we
science) are partnered with healthprofessionals (e.g., physicians, nurses, dentists, therapists, pharmacists) to solve unmet healthchallenges. In the first quarter, teams of 3–5 students work closely with the health professional(s)who originally proposed the unmet health challenge to develop a deep understanding of theunmet health need, including potential markets, stakeholder psychologies, prior solutions,intellectual property considerations, regulatory requirements, and reimbursement strategies. Inthe second and third quarters, the teams continue to refine and iterate upon their understanding ofthe unmet need and develop a series of functional prototypes (which are quantitatively evaluated)and an early-stage business plan.The program faculty
sports prosthetics. Prosthesis, vol. 5, no. 1, pp. 13-34, 2023. 7. C. Gentile, F. Cordella, and L. Zollo, “Hierarchical human-inspired control strategies for prosthetic hands,” Sensors, vol. 22, no. 7, pp. 2521, 2022. 8. A. C. Etoundi, C. L. Semasinghe, S. Agrawal, A. Dobner, A. Jafari, “Bio-inspired knee joint: trends in the hardware systems development,” Frontiers in Robotics and AI, vol. 8, no. 613574, 2021. 9. M. Asano, P. Rushton, W. C. Miller, and B. A. Deathe, “Predictors of quality of life among individuals who have a lower limb amputation. Prosthetics and Orthotics International, vol. 32, no. 2, pp. 231-243, 2008. 10. M. C. Carozza, G. Cappiello, G. Stellin, F. Zaccone, F., Vecchi, S. Micera
read and approved by all named authors and that there160 are no other persons who satisfied the criteria for authorship but are not listed. We further confirm161 that the order of authors listed in the manuscript has been approved by all of us. Thanks for the162 support from the National Science Foundation (NSF S-STEM #2029907; NSF Implementation163 Project #2306341). Any opinions, findings, conclusions, or recommendations expressed in this164 material are those of the authors.165166 References167 [1] E. Rivers, “Women, minorities, and persons with disabilities in science and168 engineering”, National Science Foundation, 2017.169 [2] S. Livingstone, & M. Bovill, “Children and their changing media environment: A170
for the technical interview(s)1 week or less before their interview [8].While ideally the industry would find alternative approaches to assessing candidates, currenthiring practices are so widespread that they are unlikely to be changed anytime soon. So what canbe done to help students excel in technical interviews and aid in their transition to the workforce?How can higher education institutions foster the knowledge, capabilities, skills, and dispositionsrequired for students to succeed in the workplace and enhance their employability?In this study, we sought to explore the opportunities to integrate such awareness and training intocurricula. To better understand where it may be feasible to do so within existing academic andprogrammatic
tovalidate and improve laboratory practices, contributing to the broader goal of sustainability in highereducation. The future work involves trying out modified enzymes for bioethanol production with increasedconversion rates for different feedstock and measuring its carbon footprint with the available setup in unitoperation labs.References1. Aroonsrimorakot S, Yuwaree C, Arunlertaree C, Hutajareorn R, Buadit T. Carbon footprint of facultyof environment and resource studies, mahidol university, salaya campus, thailand. APCBEE Procedia.2013;5:175. doi: 10.1016/j.apcbee.2013.05.031.2. Finkbeiner M, Inaba A, Tan RBH, Christiansen K, Klüppel H. The new international standards for lifecycle assessment: ISO 14040 and ISO 14044. Int J Life Cycle Assessment
second chance to provetheir knowledge increased their motivation to learn. This highlighted to them that the class wasabout increasing their knowledge rather than penalizing them for their mistakes.3.2 Do students find oral exams play a positive role in their learning? D. How did oral exams impact students' understanding of the subject matter?In the end-of-quarter survey, students were asked whether they believe the oral exams increasedtheir understanding of the subject matter. Overall, the majority of students found the oralassessment(s) increased their understanding of the subject matter. 72.1% of the valid responsesanswered “agree/strongly agree” to the prompt, while nearly 21.4% answered neutral, and only6.4% answered, “disagree/strongly
this materialare those of the authors and do not necessarily reflect the views of the National ScienceFoundation.References[1] M. M. Chemers, E. L. Zurbriggen, M. Syed, B. K. Goza, and S. Bearman, "The role of efficacy and identity in science career commitment among underrepresented minority students," Journal of Social Issues, vol. 67, no. 3, pp. 469-491, 2011, doi: 10.1111/j.1540-4560.2011.01710.x.[2] D. I. Hanauer, M. J. Graham, and G. F. Hatfull, "A measure of college student persistence in the sciences (PITS)," CBE-Life Sciences Education, vol. 15, no. 4, pp. 59- 82, 2016 2016, doi: 10.1187/cbe.15-09-0185.[3] T. Ju and J. Zhu, "Exploring senior engineering students’ engineering identity: the impact
of Engineering.Our study is guided by Allen et al.'s integrated framework for understanding sense of belonging,specifically focusing on opportunities to belong. Through in-depth qualitative interviews withfaculty and students, we aim to address two research questions: (RQ1) How are the differentfirst-year seminars at our institution understood and conducted? (RQ2) What aspects of theseseminars contribute to students' sense of belonging? As the university reshapes its engineeringcurriculum, this research provides insights into enhancing the transition experience and fosteringa supportive academic community for first-year undergraduate engineering students. The resultsmay also provide insights for other institutions in what works towards the
HealthDisparities within Undergraduate Biomedical Engineering Education,” Ann. Biomed. Eng., vol.45, no. 11, pp. 2703–2715, Nov. 2017, doi: 10.1007/s10439-017-1903-8.[4] “A Student Guide to Biodesign: Justice, Equity, Diversity, and Inculsion in Design.”Accessed: Mar. 28, 2023. [Online]. Available: https://biodesignguide.stanford.edu/toolkit/justice-equity-diversity-and-inclusion-in-design/[5] S. Canali, V. Schiaffonati, and A. Aliverti, “Challenges and recommendations for wearabledevices in digital health: Data quality, interoperability, health equity, fairness,” PLOS Digit.Health, vol. 1, no. 10, p. e0000104, Oct. 2022, doi: 10.1371/journal.pdig.0000104.[6] S. Burgstahler, “A Framework for Inclusive Practices,” Creating inclusive learningopportunities in
Contact: What Can It Henry Debord: h-debord@onu.edu Do? Dr. Coffman-Wolph: CONTROL STUDENT s-coffman-wolph@onu.edu PROGRAMMED GAMES CONTROL DIGITAL TO Dr. Ammar: PHYSICAL DEVICES a-ammar@onu.edu PRACTICE SOLDERING
. L IMITATIONS OF THE S TUDY While the study’s approach offers innovative methods to analyze and provide health recommendations basedon HRV data, it was limited to a small number of participants within a selected dataset. Incorporating additional 2 https://github.com/datasci888/ASEE June 2024methodologies, especially the application of neural networks, holds promise for improving accuracy, particularlywhen dealing with larger datasets. Further expansion in demographics, such as including participants from diverseage groups, skin colors, and geographical locations, could provide a more comprehensive understanding of themodel’s effectiveness across various populations. F UTURE D
throughout the demonstration)produced desired product D (yellow), and the other where C formed undesired byproduct B(blue) (Figure 1). The demonstration allows users to manipulate up to five variables: the molarflow rate of reactant C, the single-pass fractional conversion of C, the fractional selectivity, theseparator temperature, and the recycle ratio.The block flow diagram labels streams and units. The purge Stream 6 (brown) and the recycleStream 7 (green) arrows grow and shrink in size to visualize the recycle ratio, e.g. with a lowrecycle ratio, Stream 6’s arrow would be large and Stream 7’s arrow would be small. Below theblock flow diagram are visual representations of the system variables that can be manipulated.Single-pass fractional
who might not have had other chances to learn aboutengineering. One female counselor noticed that girl campers were less confident speaking if boycampers were present and worked with another female counselor to “all show each other girlscan do it”. Two counselors were interested in applying for the job as a means of challenginginjustice by providing the camp opportunity to “students like them”. Participants spoke about nothaving such camps available when they were in middle and high school, and how they wouldhave benefited from such programs. One shared that she chose to be a counselor to be a “spark ofinspiration” for “underrepresented kids” because she “really like[s] the message”. Anothershared what it meant to him to be able to be a
ASEE Annual Conference & Exposition Proceedings, Atlanta, Georgia: ASEE Conferences, Jun. 2013, p. 23.120.1-23.120.13. doi: 10.18260/1-2--19134.[2] K. J. Reid, D. Reeping, T. Hertenstein, G. Fennel, and E. Spingola, “Development of a Classification Scheme for ‘Introduction to Engineering’Courses,” in 2013 IEEE Frontiers in Education Conference (FIE), Oklahoma City, OK, USA: IEEE, Oct. 2013, pp. 1564– 1570. doi: 10.1109/FIE.2013.6685101.[3] B. D. Jones, M. C. Paretti, S. F. Hein, and T. W. Knott, “An Analysis of Motivation Constructs with First-Year Engineering Students: Relationships Among Expectancies, Values, Achievement, and Career Plans,” J. Eng. Educ., vol. 99, no. 4, pp. 319–336, Oct. 2010, doi: 10.1002/j
(Engeström), Daiute [48],[49] recognizes the social, dynamic nature of narratives to inform data collection and analysismethods. According to these theories, it is important to consider the interdependence inherent inthe broader context of experience and narration. This perspective aligns with this research as oursurvey reinforced the complexity of individual experiences of lifelong learning.In narrative research, the researcher needs to make plausible interpretations within the bounds ofthe narrative(s) because they capture complex experiences that are not aligned with hypothesistesting paradigms [50]. To bring forward meaningful evidence in interview approaches involvinghomogenous groups, 12 participants are typically sufficient for thematic