–61, Jul. 2019, doi: 10.1145/3330794.[3] R. T. Javed et al., “Get out of the BAG! Silos in AI Ethics Education: Unsupervised Topic Modeling Analysis of Global AI Curricula,” J. Artif. Intell. Res., vol. 73, pp. 933–965, Mar. 2022, doi: 10.1613/jair.1.13550.[4] L. Tuovinen and A. Rohunen, “Teaching AI Ethics to Engineering Students: Reflections on Syllabus Design and Teaching Methods,” 2021.[5] J. Lönngren, “Exploring the discursive construction of ethics in an introductory engineering course,” J. Eng. Educ., vol. 110, no. 1, pp. 44–69, 2021, doi: 10.1002/jee.20367.[6] R. F. Clancy, Q. Zhu, and Philosophy Documentation Center, “Why Should Ethical Behaviors Be the Ultimate Goal of Engineering Ethics Education?,” Bus. Prof
of D), failed (grade of F), or withdrew (either with a gradeof Q for students remaining at the institution, or W for students leaving the institution) in aneffort to understand how their performance in computational thinking affected their careertrajectories. In addition, we are also completing the longitudinal study of computational thinkingdevelopment in our student cohorts.IntroductionDuring the last period, the major achievements of this project were the validation of theEngineering Computational Thinking Diagnostic (ECTD) and its dissemination. The validationof the instrument afforded the opportunity to identify its predictive characteristics, strengtheningour rationale that this diagnostic can be a powerful tool in assessing entry
outcomeswere measured as dispositions, including interest, aspiration, motivation, confidence, and self-efficacy. A smaller number of studies also assessed knowledge in specific STEM careers.Overall, a small to moderate level of positive effect was observed (effect size mean = 0.379, SE= 0.064, 95%CI = 0.252 – 0.505, p < .001), with significant heterogeneity (Q (167) = 2418.355,p < .001), suggesting the need to explore potential moderator variables.Intervention characteristics revealed that 58% targeted underrepresented and/or underservedpopulations, 41% included explicit career development, and interdisciplinary content wascommon. Additionally, 56% of studies took place in informal settings. The study also consideredintervention format
profiled assomeone who was going to rob the store or steal items without paying. That really just cementedfor me, like these types of experiences that I'm having today and I'll have in the future, wherethere's no way this “white on the inside” identity that other people try to give to me is going toever be able to be used by me.In terms of other identities, I am a cisgender man. So that comes into play when I have tohesitate to see how aggressive I may come off to somebody from me being Black and then beinga cisgender man specifically. If we are going to go a little bit deeper, I do not fully identify withLGBTQ identity, but if the Q stands for the sense for questioning, I guess it is there. As far asqueerness is involved, I identify with some
; Exposition Proceedings, Atlanta, Georgia: ASEE Conferences, Jun. 2013, p. 23.973.1-23.973.16. doi: 10.18260/1-2--22358.[11] O. García and J. A. Kleifgen, “Translanguaging and Literacies,” Read. Res. Q., vol. 55, no. 4, pp. 553–571, Oct. 2020, doi: 10.1002/rrq.286.[12] O. García and T. Kleyn, Eds., Translanguaging with multilingual students: learning from classroom moments. New York ; London: Routledge, Taylor & Francis Group, 2016.[13] O. García and L. Wei, Translanguaging. London: Palgrave Macmillan UK, 2014. doi: 10.1057/9781137385765.[14] O. García and T. Kleyn, “A TRANSLANGUAGING EDUCATIONAL PROJECT,” in Translanguaging with Multilingual Students, 1st ed., Routledge, 2016, p. 21.[15] O. García and T. Kleyn
question (such as a chapter’s worth of material) to better refine the response to thestudent. We also implement frequent and customized Q&A buttons, such as simplifying aresponse, providing prerequisite information, providing a real-world example, etc. Thecustomization buttons allow the user to provide their own frequently asked questions, such as“Explain it to me like I’m a 5-year-old”.Study impact includes feedback from eNotebook’s usage analytics, where automated personalizedquiz scores will be correlated with tracked study habits, and suggested changes will be offered byeNotebook to improve academic performance. Templates from various study methods will beavailable, as well as shared libraries of student-customized versions of eNotebook
Australasian Association Engineering Education Conference (AAEE2019), 2019, pp. 568–574, [Online]. Available: https://aaee.net.au/wp- content/uploads/2020/07/AAEE2019_Annual_Conference_paper_72.pdf.[5] D. Chadha et al., “Are the kids alright? Exploring students’ experiences of support mechanisms to enhance wellbeing on an engineering programme in the UK,” Eur. J. Eng. Educ., pp. 1–16, 2020, doi: 10.1080/03043797.2020.1835828.[6] I. Hilliger, G. Astudillo, and J. Baier, “Lacking time: A case study of student and faculty perceptions of academic workload in the COVID-19 pandemic,” J. Eng. Educ., vol. 112, no. 3, pp. 796–815, 2023, doi: 10.1002/jee.20525.[7] Q. Liu and G. Evans, “Supporting Information for the
difference at =0.05. Several questions were found to be statistically significant, asshown in Table 4 Table 4: Comparing mean values between post-fall and post-spring Q Post Fall 2022 Post Spring 2023 Mean t df p M (SD) M (SD) Difference 16 1.660 (1.205) 2.009 (0.956) -0.349 -2.257 177 .025 34 1.032 (1.589) 1.636 (1.239) -0.604 -2.973 175 .003 37 1.602 (1.595) 2.103 (1.140) -0.501 -2.519 164 .013Discussion & Future WorkAdditional work is needed to better understand the results of the EDVES survey. Initial
, Australian Journal of Psychology, 73:1, 87-102, DOI:10.1080/00049530.2021.1883409[4] Maithreyi Gopalan. “Students’ Sense of Belonging Matters: Evidence from Three Studies”.https://www.google.com/url?q=https://tll.mit.edu/sense-of-belonging-matters/&sa=D&source=docs&ust=1707428553250036&usg=AOvVaw00y7fOXuEVLb49q3Cg-2MA[5] Eccles, J. S., & Midgley, C. (1989). Stage/Environment Fit: Developmentally AppropriateClassrooms for Early Adolescence. In R. E. Ames, & Ames, C. (Eds.), Research on Motivationin Education, 3, 139-186. New York: Academic Press.[6] Eccles, J. S., & Roeser, R. W. (2011). Schools as developmental contexts during adolescence.Journal of Research on Adolescence, 21(1), 225–241. https://doi.org/10.1111/j.1532
, Group Part II: Image of belonging. They used dot voting to identify discussion on space Analysis the most and least significant spaces and impact discussed how these spaces influence their engineering identity and feelings of belonging. Part III: Q- Participants used Q-Methodology to sort Statement sorting, Methodology statements about their engineering education, reflecting on (Statement reflecting diverse views on dominant engineering education Sorting) engineering cultures. They placed these experiences, justifying statements on a Q-Board continuum to
degreepolynomials and their associated End Behavior. It is in this latter part of theircollege algebra course that students start graphing degree 2 and higher 10polynomials. It is at this point that a student can determine the effectiveness of theGraphical Method. Therefore, the survey will be given at the end of each semester.References1. Arsenault, Smith, & Beauchamp, 2006; Krohn, 19912. Friel, Curcio, & Bright, 20013. Ellington, 2006; Wang et al., 20124. Miller & Linn, 2013; Yeh & McTigue, 20095. Friel & Bright, 19966. Ce L., Cheng Z., Zhu H., Wang L., Lv Q., Wang Y., Li N., Sun D.7. Edwards, A. J., Weinstein, C. E., Goetz, E. T., & Alexander, P. A.(2014). Learning and study strategies
higher degreepolynomials and their associated End Behavior. It is in this latter part of theircollege algebra course that students start graphing degree 2 and higher 10polynomials. It is at this point that a student can determine the effectiveness of theGraphical Method. Therefore, the survey will be given at the end of each semester.References1. Arsenault, Smith, & Beauchamp, 2006; Krohn, 19912. Friel, Curcio, & Bright, 20013. Ellington, 2006; Wang et al., 20124. Miller & Linn, 2013; Yeh & McTigue, 20095. Friel & Bright, 19966. Ce L., Cheng Z., Zhu H., Wang L., Lv Q., Wang Y., Li N., Sun D.7. Edwards, A. J., Weinstein, C. E., Goetz, E. T., & Alexander, P. A.(2014). Learning and
decisions about the project andinterpret the effects those decisions had on the outcomes. The students were asked to come up witha hypothesis after the first day of the project and asked to identify the independent and dependentvariables after completing the second day.Three types of membrane filtration techniques were explored: membrane chromatography, deadend filtration, and tangential flow filtration. The first project modeled tangential flow filtrationusing a cross flow membrane cassette (Vivaflow 50, Sartorius) to separate food dye fromwatercolor pigment [4]. A gel electrophoresis experiment (Flynn Scientific) was performed firstto illustrate the size of dye molecules. The second project used membrane chromatography(Mustang Q Acrodisc, Pall
Benefits and Challenges of Remote Labs for Engineering Students - Engineering Institute of Technology” [Online]. https://www.eit.edu.au/the-benefits- and-challenges-of-remote-labs-for-engineering-students/. (accessed Jul. 17, 2023). © American Society for Engineering Education, 2023 2023 ASEE Midwest Section Conference[3] D. Whitney, E. Rosen, E. J. Phillips, G. Konidaris, and S. Tellex, “Comparing Robot Grasping Teleoperation Across Desktop and Virtual Reality with ROS Reality,” 18th International Symposium on Robotics Research, pp. 335–350, Nov. 2019.[4] T. Zhou, Q. Zhu, J. Du, “Intuitive Robot Teleoperation for Civil Engineering Operations with Virtual Reality and Deep Learning
request or can be more specific such as review for grammar, structure, punctuation, or flow. The decision of how they want ChatGPT to review their essays are carried out by students. The original version and the revised by ChatGPT version of the student essays are shown in Figure 5. Figure 5. Students' Essay and ChatGPT Review of the Students' Essay➢ Phase V – Outcomes Review and Post-Experience Survey: In the last phase, a discussion on the overall experience, and level of incorporation and the outcome quality of the essays are carried out followed by a post-experience survey developed by authors [1] and is a 5-point Likert scale survey as shown in Figure Q. Figure 6. Post-Experience Survey
,modifications and improvements to a syllabus based on comments from the students maydemonstrate a method for syllabus improvement and show a correlation to student success. References:Carbonetto, T. (2024). Early Career Engineers’ Perspectives on Leadership Competency Development in Undergraduate Education (Publication No. 30994836) [Doctoral dissertation, Marshall University]. ProQuest Dissertations & Theses Global.Dann, R. (2014). Assessment as learning: Blurring the boundaries of assessment and learning for theory, policy, and practice. Assessment in Education: Principles, Policy & Practice, 21(2), 149-166.Farmer, W., & Hu, Q. (2018). FCL: A formal language for writing
office, the project team hasidentified the set of available institutional data, developed an inventory of existing academic datasets and dashboards, and explored similar tools developed at other universities (e.g., IndianaUniversity Bloomington, University of California Davis, University of Kansas).During Year 1, over 80 Questions and “I Wonders” (QWs) were developed through the DataTools Co-Design and Inquiry in STEM Success Faculty Communities sessions (prompted byreading papers and national reports on student success and retention in STEM) and visit to ameeting of the STEM department chairs. Members of the Data Tools Co-Design FC categorizedthe generated Q&Ws according to data category, when faculty would use the information, andwhy a
/not-just-for-kids-using- picture-books-with-teens-and-tweens.html#more-22917[3] Wpadminlernerbookscom. (2022a, April 11). How to Use Picture Books with Tweens and Teens: Q&A with Literacy Experts. The Lerner Blog. https://lernerbooks.blog/2021/03/how- to-use-picture-books-with-tweens-and-teens-qa-with-experts.html[4] Fresch, M.J. & Harkins, P. (2009). The power of picture books: Using content area literature in middle schools. Urbana, IL: National Council of Teachers of English.[5] Massey, S.R. (2015). The Multidimensionality of Children’s Picture Books for Upper Grades. English Journal, 104, 45.[6] Chesney, D. Big Fish: The Lost Art of Storytelling in the Engineering Classroom, at the American
theory discussion of community cultural wealth," in Critical race theory in education: Routledge, 2020, pp. 114-136.[6] C. C. Samuelson and E. Litzler, "Community cultural wealth: An assets‐based approach to persistence of engineering students of color," Journal of Engineering Education, vol. 105, no. 1, pp. 93-117, 2016.[7] N. Bañuelos, "Community Cultural Wealth Goes to College: A Review of the Literature for Career Services Professionals and Researchers. WCER Working Paper No. 2021-6," Wisconsin Center for Education Research, 2021.[8] S. L. Dika, M. A. Pando, B. Q. Tempest, and M. E. Allen, "Examining the cultural wealth of underrepresented minority engineering persisters," Journal of Professional
. Gilmartin, H.L. Chen, M.E. Besterfield-Sacre, N. Duval-Couetil, A.Shartrand, L. Moore, E. Costache, A.M. Fintoc, Q. Jin, C. Ling, F. Lintel, L. Britos Cavagnaro,H. Fasihuddin, A,K., Breed, “Exploring what we don’t know about entrepreneurship educationfor engineers,” ASEE Annual Conference & Exposition, Seattle, WA, 2015. Available:http://epicenter.stanford.edu/documents/ERS%20-%20ASEE_Summit_Paper_FINAL__040515_.pdf.[5] W.E. Mcmullan and W.A. Long, “Entrepreneurship education in the nineties,” Journal ofBusiness Venturing, 2(3), 261-275, 1987. Available:https://www.sciencedirect.com/science/article/pii/0883902687900139[6] J. Rowley, “What did VCs study in college?”, TechCrunch, April 15, 2018. Available:https://techcrunch.com/2018/04/15/what
sessions.References[1] M. F. Aburdene and R. J. Kozick, “A project-oriented course in probability and statistics for undergraduateelectrical engineering students,” in Proc. IEEE Frontiers in Education 1997 Conference, pp.598 – 603[2] D. Tougaw, “Integration of active learning exercises into a course on probability and statistics,” in Proc. ASEEAnnual Conference & Exposition, Portland, OR, June, 2005.[3] R. A. Budiman, “Using card games for conditional probability, explaining Gamma vs. Poisson Distributions, andWeighing Central Limit Theory,” in Proc. 123rd ASEE Annual Conference & Exposition, New Orleans, LA, June,2016.[4] J. A. Reising, “Lab experiments in probability,” in Proc. ASEE Annual Conference & Exposition, Portland, OR,June, 2005.[5] Q
Value Is that what you got? NA Remember What’s the equation? State Understand So would we do the energy equation to find the Q [heat Recognize transfer]? Apply How did you convert to kilowatts? Solve, Sketch Analyze Why can’t we use enthalpy? Differentiate Evaluate Wait, how do we have an adiabatic turbine? Argue, DefendCategorizing questions depends on more than the initial question. A question like, “How did youconvert to kilowatts?” may not appear to be an application level of learning initially. Followingthe question, the study group went
thein-class exercise to assist you in completing this assignment. 1. So far in our modeling journey, we have used modes to perform ‘what if’ kind of experiments. Models can also be used for system identification. For example, if you have measured pressure and flow data you may interpret the physiological status of the cardiovascular system in terms of resistance and capacitance. The model that you completed in class calculate the arterial pressure, P a (t), given measured volumetric flow rate, Q i (t) and parameter values R and C. As a first step, adapt the code to create a plot of the measured P a (t) and modeled P a (t) using the measured data from Example1.txt file (Patient 1). After you adapt the code, alter
industries are the anticipated factors to trigger the high demand for theDigital Twin platform over the forecast period.References[1] F. Tao, J. Cheng, Q. Qi, M. Zhang, H. Zhang, F. Sui, “Digital twin-driven product design,manufacturing, and service with big data,” Int. J. Adv. Manuf. Technol, vol. 94, pp. 3563–3576,2018.[2] X. Ma, J. Cheng, Q. Qi, F. Tao, “Artificial intelligence enhanced interaction in digital twinshop-floor,” Procedia CIRP, vol. 100, pp. 858–863, 2021.[3] T.K. Ren, Y. Chew, Y.F. Zhang, J.Y.H. Fuh, G.J. Bi, “Thermal field prediction for laserscanning paths in laser aided additive manufacturing by physics-based machine learning,”Comput. Methods Appl. Mech. Eng, vol. 362, 112734, 2020.[4] R. Stark, C. Fresemann, K. Lindow
tutoring and grading to maintain fairness.2.3 Student Engagement and active learning methodsNew faculty member should utilize evidence-based learning approaches to enrich the educationalexperience for students and aim to optimize learning outcomes and foster a more engaging andeffective classroom environment[2][6]. There are several approaches can be used in classes: • Multi-source teaching: Encompass a combination of slides, whiteboard illustrations, short videos, and dedicated Q&A sessions within the lecture. This varied presentation style aims to prevent students from experiencing a lack of concentration. • In-class exerices: Each class can incorporate diverse in-class exercises, including multiple- choice
attention differently in examining physics diagrams? A study of change detection using the flicker technique,” Physical Review Physics Education Research, 11(2), 020104, 2015. https://doi.org/10.1103/PhysRevSTPER.11.020104 [36] J. W. Morphew, E. P. Kuo, Q. King-Shepard, P. Kwon, R. Lin, T. J. Nokes-Malach, and J. P. Mestre, “Seeing and doing are not believing: Investigating when and how conceptual knowledge impinges on observation and recall of physical motion,” Journal of Experimental Psychology: Applied, 27(2), 307-323, 2022. https://doi.org/10.1037/xap0000338[37] M. Perry, R. Breckinridge Church, and S. Goldin-Meadow, “Transitional knowledge in the acquisition of concepts,” Cogn. Dev., vol. 3, no. 4, pp. 359–400, Oct. 1988
stem. CBE Life Sciences Education, 15(3), 1–. https://doi.org/10.1187/cbe.16-01-0038Freeman, R., Huang, W. (2014) Collaboration: Strength in diversity. Nature 513(305). https://doi.org/10.1038/513305aMiller, P. H., Rosser, S.V., Benigno, J.P., Zieseniss, M. (2000). A desire to help others:goals of high achieving female science undergraduates. Women Stud Q, 28(1–2), 128–142.National Science Foundation. (2024). Diversity and STEM: Women, Minorities, and Persons with Disabilities. U.S. National Science Foundation. https://ncses.nsf.gov/pubs/nsf23315/faqsOgbogu, U., & Ahmed, N. (2022). Ethical, legal, and social implications (ELSI) research: Methods and approaches. Current Protocols, 2, e354. doi: 10.1002
. Zhao, R. R. Issa, and N. Singh, “BIM for improved project communication212 networks: Empirical evidence from email logs,” J. Comput. Civ. Eng., vol. 34, no. 5, p.213 04020027, 2020.214 [4] T. Liu, H.-Y. Chong, W. Zhang, C.-Y. Lee, and X. Tang, “Effects of contractual and215 relational governances on BIM collaboration and implementation for project performance216 improvement,” J. Constr. Eng. Manag., vol. 148, no. 6, p. 04022029, 2022.217 [5] R. Samimpay and E. Saghatforoush, “Benefits of implementing building information218 modeling (BIM) in infrastructure projects,” J. Eng. Proj. Prod. Manag., vol. 10, no. 2, pp.219 123–140, 2020.220 [6] G. Chen, J. Chen, Y. Tang, Y. Ning, and Q. Li, “Collaboration
Arabia and the effect of gender bias in student evaluations.7,8 In other applications, topicmodeling has been used to construct recommendation systems in Q&A sites, analyze developerdiscussions on Stack Overflow, explore posts on Twitter and Instagram, and understand the diningexperience of tourists.9-13Similar to numeric clustering methods, topic models discover patterns in unlabeled data. To findword clusters, various techniques can be used. In this paper, we study four topic models that usedifferent implementation methods: (1) Latent Dirichlet Allocation, (2) Nonnegative MatrixFactorization, (3) BERTopic, and (4) Top2Vec.2.3.1. Latent Dirichlet AllocationLatent Dirichlet Allocation (LDA) is a generative probabilistic model for collections