Undergraduate Engineering Student PopulationIntroductionIt has been previously documented that severe weather events cause a wide range of directmental health concerns, including depression, PTSD and anxiety in individuals living in theaffected community [1]. However, as the urgency around broader climate change has increased,and countries race to meet the 2050 goal of net zero emissions to limit global warming [2], a newphenomenon known as “Climate Anxiety” has emerged [3]. Climate anxiety is a form of anxietyinduced by the existence of climate change and concerns about this change, rather than discreteweather events. Simply being aware of climate change and its negative impacts on our naturaland social systems can cause a severe anxiety response. The
for those implementing it. Hence, it is crucial for teachers to be aware ofthese aspects, allowing them to prepare and optimize the efficiency of PBL implementation.References[1] Christensen, C. M.; Horn, M. B.; Staker, H. 2020. Ensino Híbrido: uma Inovação Disruptiva? Uma introdução à teoria dos híbridos. Boston: Clayton Christensen Institute, 2013. Disponível em https://bit.ly/2Bv5hrg.[2] Fagen, A. P; Crouch, C. H; Mazur, E. 2002. Peer Instruction: Results from a Range of Classrooms. The Physics Teacher, 40(4), 206–209.[3] Gok, T. Gok, O. 2017. Peer instruction: an evaluation of its theory, application, and contribution. Asia-Pacific Forum on Science Learning and Teaching, 18(2), p.2.[4] Oliveira, B. L. C. A. de et al. 2018
. Understanding student behavioral engagement:Importance of student interaction with peers and teachers. Journal of Educational Research,111(2), 163-174.[13] Adams Becker, S., Cummins, M., Davis, A., Freeman, A., Hall Giesinger, C., &Ananthanarayanan, V. 2017. NMC Horizon Report: 2017 Higher Education Edition. The NewMedia Consortium.[14] Graham, C. R., Borup, J., & Smith, N. B. 2012. Using TPACK as a framework tounderstand teacher candidates' technology integration decisions. Journal of Computer AssistedLearning, 28(6), 530-546.[15] Awadhiya, A. K., & Miglani, A. E-learning: Investigating students' acceptance of onlinelearning in hospitality programs. SAGE Open, 6(3), 2158244016664907.[16] Zainuddin, Z., & Halili, S. H 2016. Flipped
theNational Science Foundation. References[1] A. Johri, W.-M. Roth, and B. M. Olds, “The role of representations in engineering practices: Taking a turn towards inscriptions,” J. Eng. Educ., vol. 102, no. 1, pp. 2–19, 2013, doi: 10.1002/jee.20005.[2] R. Kozma, “The material features of multiple representations and their cognitive and social affordances for science understanding,” Learn. Instr., vol. 13, pp. 205–226, 2003, doi: 10.1016/S0959-4752(02)00021-X.[3] R. Kozma, E. Chin, J. Russell, and N. Marx, “The roles of representations and tools in the chemistry laboratory and their implications for chemistry learning,” J. Learn. Sci., vol. 9, no. 2, pp. 105–143, 2000, doi: 10.1207
] What outcome resulted from the method used for studying the biases? [RQ5] What populations were studied?3.2 CriteriaThe criteria for this literature review are shown in Figure 1 and listed here: a) Search all selected databases for keywords Sustainability AND Cognitive Biases for all years including 2022 and 2023. (See section 3.3.1) (retrieved 345 papers) b) Manually remove all duplicated papers. (See section 3.3.2) (excluded 4 papers) c) Screen the titles for relevance within sustainability, civil engineering, and cognitive biases. (See section 3.3.2) (excluded 318 papers) d) Screen abstracts for further relevance within the scope of this literature review. (See section 3.3.2) (included 5 papers) e) Use
applying the procedures depicted in Figure 2 and utilizing an injection molding machine. Table 1. Optimal injection molding processing conditions for selected polymer samples. Material Barrel Mold Injected Trialsd a Temperature (°C) Temperature b c 3 Amount (cm ) Completed (°C) Polypropylene 145 75 6.19 39 Copolymer High-Density 172 70 6.33 19 Polyethylene Polypropylene 180
Paper ID #43880Evaluation of LLMs and Other Machine Learning Methods in the Analysis ofQualitative Survey Responses for Accessible Engineering Education ResearchXiuhao Ding, University of Illinois at Urbana - ChampaignMeghana Gopannagari, University of Illinois at Urbana - ChampaignKang Sun, University of Illinois at Urbana - ChampaignAlan Tao, University of Illinois at Urbana - ChampaignDelu Louis ZhaoSujit Varadhan, University of Illinois at Urbana - Champaign Sujit Varadhan is a Junior at the University of Illinois at Urbana-Champaign majoring in Computer Science. He is an undergraduate research assistant as well as a frontend
Updates and Developments in Saudi Arabia and the US,” IJHE, vol. 10, no. 6, p. 57, Jun. 2021, doi: 10.5430/ijhe.v10n6p57.[4] A. Robins, J. Rountree, and N. Rountree, “Learning and teaching programming: A review and discussion,” Computer science education, vol. 13, no. 2, pp. 137–172, 2003.[5] J. Figueiredo and F. J. García-Peñalvo, “Increasing student motivation in computer programming with gamification,” in 2020 IEEE Global Engineering Education Conference (EDUCON), IEEE, 2020, pp. 997–1000.[6] B. D. Jones, “Motivating students to engage in learning: the MUSIC model of academic motivation.,” International Journal of Teaching and Learning in Higher Education, vol. 21, no. 2, pp. 272–285, 2009.[7] J. M. Keller, “Development and
: AnExploratory Study”. International Journal of Artificial Intelligence in Education, 1–35. 2022.[3] B. Akram, S. Yoder, C. Tatar, S. Boorugu, I. Aderemi, and S. Jiang, Towards an AI-InfusedInterdisciplinary Curriculum for Middle-Grade Classrooms. Proceedings of the AAAIConference on Artificial Intelligence, 2022. 36(11) pp 12681–12688.[4] National Research Council, “How people learn: Brain, mind, experience and school”.Behavioral and social science and education, 1999, J. D. Branford, A. L. Brown, and R. R.Cocking, Eds. National Academy Press, Washington, D. C.[5] A. Badura, Social Learning Theory. New York: General Learning press, 1977
be better able to fully explain their report.Given that there was no baseline comparison for this study, it is unclear if the use of a WATTS-trained tutor provided more benefit than one who was not WATTS-trained. However, this studyshows that the WATTS method might be used as a springboard for many potential improvementsin student writing and critical thinking skills.[1] Heard, J., Scoular, C., Duckworth, D., Ramalingam, D. and Teo, I., 2020. Critical thinking: Definition and structure.[2] Bodenhamer, J., & Weissbach, R., & Pflueger, R. C., & Renguette, C. C., & Sorge, B., & Dasgupta, A., & Edinbarough, I. (2023, June), Board 121: Using Tutor-led Support to Enhance Engineering Student Writing for All Paper
, C.J. and Shuman, L.J. (1997), Characteristics of Freshman Engineering Students: Models for Determining Student Attrition in Engineering. Journal of Engineering Education, 86: 139-149. https://doi.org/10.1002/j.2168-9830.1997.tb00277.x[7] Veenstra, C. P., Dey, E.L., Herrin, G.D., "A Model for Freshman Engineering Retention." Advances in Engineering Education 1, no. 3 (2009): n3.[8] Cline, E., & Abraham, M., & Alaei, S., & Dillon, H., & Dinglasan-Panlilio, J., & Heller, J. B., & Kmail, Z., & Lee, S., & Ma, E. Y., & Nahmani, M., & Sesko, A. K., & Yeung, K. Y. (2023, June), Board 207: ACCESS in STEM: An S-STEM Project Supporting Economically Disadvantaged STEM
whoused AI in their water resources classes versus those who did not. This comparison is intendedto realistically denote whether the use of AI influences the improvement of water resourceclasses, thus visualizing whether the use of AI allows for a better overall understanding of thesubject.References [1] George, B., and Wooden, O., 2023, “Managing the Strategic Transformation of Higher Education through Artificial Intelligence,” Adm. Sci., 13(9), p. 196.[2] Sadiku, M. N., Musa, S. M., and Chukwu, U. C., 2022, Artificial Intelligence in Education, iUniverse.[3] Padilla, R. D. M., 2019, “La Llegada de La Inteligencia Artificial a La Educación,” Rev. Investig. En Tecnol. Inf. RITI, 7(14), pp. 260–270.[4] Haleem, A., Javaid, M., and Singh
Paper ID #41656ASEE 2024 Paper—Examining Cultural Elements to Enable ChangeDr. Marnie Jamieson, University of Alberta Marnie V. Jamieson, M. Sc., P.Eng. is a Teaching Professor in Chemical Process Design in the Department of Chemical and Materials Engineering at the University of Alberta and holds an M.Sc. in Chemical Engineering Education and a PhD in Chemical Engineering. She is currently the William and Elizabeth Magee Chair in Chemical Engineering Design. She leads the process design teaching team. Her current research focuses on engineering design and leadership, engineering culture, the engineering graduate
campuses meet monthly.Speed Mentoring 3 times a year + 1 a) Speed mentoring sessions in Fall, Spring, and Faculty Success Summer, with summer sessions especially for Seminar future faculty and current lecturers b) Faculty from 18 CSU campuses participated c) Faculty success seminar Research 4-5 events (per a) Seed grants (annual) - 4 -5 teams (8-10 faculty) alliance year) from 4-6 CSU campuses. b) Panel discussions / Information seminars on proposal development -2 times/yr- 12-13
County FTES [a] [a,b] [a] Allan Hancock Santa Maria Santa Barbara 9,746 69.8 63.2 Cabrillo Santa Cruz Santa Cruz 8,929 46.8 44.4 Cuesta San Luis Obispo San Luis Obispo 8,169 39.5 35.4 Monterey Peninsula Monterey Monterey 5,879 49.1 42.4 Moorpark Moorpark Ventura 11,875 40.2 35.4 Oxnard Oxnard Ventura 5,398 78.8 73.0 Santa Barbara City
. Savvidis, “Sustainability Components Affecting Decisions for Green Building Projects,” Procedia Econ. Finance, vol. 5, pp. 747–756, Jan. 2013, doi: 10.1016/S2212-5671(13)00087-7.[8] Z. Shen, W. Jensen, B. Fischer, and T. Wentz, “Using BIM to teach design and construction of sustainable buildings,” 2012. doi: 10.18260/1-2--22177.[9] B. Sanchez, R. Ballinas-Gonzalez, M. X. Rodriguez-Paz, and J. A. Nolazco-Flores, “Usage of Building Information Modeling for Sustainable Development Education,” presented at the 2020 ASEE Virtual Annual Conference Content Access, Jun. 2020. Accessed: Jan. 31, 2022. [Online]. Available: https://peer.asee.org/usage-of-building-information-modeling- for-sustainable-development-education[10] J
. 19, no. 1, pp. 91–106, Mar. 2020, doi: 10.1177/1475725719868149.[16] P. Ivie and D. Thain, “Reproducibility in Scientific Computing,” ACM Comput. Surv., vol. 51, no. 3, p. 63:1-63:36, Jul. 2018, doi: 10.1145/3186266.[17] M. Baker and M. Baker, “1,500 scientists lift the lid on reproducibility,” Nature, vol. 533, no. 7604, pp. 452–454, May 2016, doi: 10.1038/533452a.[18] T. M. Errington, A. Denis, N. Perfito, E. Iorns, and B. A. Nosek, “Challenges for assessing replicability in preclinical cancer biology,” eLife, vol. 10, p. e67995, Dec. 2021, doi: 10.7554/eLife.67995.[19] C. G. Begley and L. M. Ellis, “Raise standards for preclinical cancer research,” Nature, vol. 483, no. 7391, Art. no. 7391, Mar. 2012, doi: 10.1038
Lable Range A 𝑠𝑐𝑜𝑟𝑒 90% B 80% 𝑠𝑐𝑜𝑟𝑒 90% C 70% 𝑠𝑐𝑜𝑟𝑒 80% D 60% 𝑠𝑐𝑜𝑟𝑒 70% F 𝑠𝑐𝑜𝑟𝑒 60% ]Figure 11, Students' assignment grades before and after auto-grading implementationProfessors' and Students’ Opinions of the ProgramThe instructors have appreciated the reduced time spent grading, as the courses do not alwayshave a teaching assistant. The program shows the students that they are making a mistake,leading them to ask for help from other students or the professor. The instructors teach theircourses in a flipped manner, where
, “Measuring entrepreneurial self-efficacy to understand the impact of creative activities for learning innovation,” Intl J Mgmt Educ, 12, pp. 456-468, 2014.[9] J.H. Dyer, H. B. Gregersen, and C.M. Christensen, “Entrepreneur Behaviors, Opportunity Recognition, and the Origins of Innovative Ventures,” Strateg. Entrepreneurship J, 2 (4): pp. 317–38, 2008.[10] G. Balau, D. Faems, J. van der Bij, “Individual characteristics and their influence on innovation: A literature review,” Proceedings of the 9th International Conference on Innovation and Management, Nov. 14-16, Eindhoven, The Netherlands. Eds. G. Duysters, A. de Hoyos, K. Kaminishi, Wuhan University Press, pp. 887-901, 2012.[11] A. Bolhari, & S. Tillema
potential of industrial ‘E-mentoring’ as a retention strategy for women in science and engineering,” in Proceedings of the Frontiers in Education Conference, Pittsburgh, PA, Nov. 1997.[5] C. Slater, W. Edmister , B. Watford, and J. Kampe, “Lessons learned: Implementing a largescale peer mentoring program,” in Proceedings of the ASEE Annual Conference and Exposition, Chicago, IL, June 2006. https://peer.asee.org/1118[6] E. Hart, A. Mott, and S. Furterer, “Piloting an undergraduate engineering mentoring program to enhance gender diversity,” in Proceedings of the ASEE Annual Conference and Exposition, Virtual, June 2020. https://peer.asee.org/35058[7] V. Washington and J. Mondisa, “A need for engagement opportunities and
, Evelina Dineva, Francesco Maurelli, and Andreas Nabor. A robotics course during covid-19: Lessons learned and best practices for online teaching beyond the pandemic. Robotics, 10(1):5, 2021. [2] Amanda B Click. International graduate students in the united states: Research processes and challenges. Library & Information Science Research, 40(2):153–162, 2018. [3] Elena V Frolova, Olga V Rogach, Alexander G Tyurikov, and Pavel V Razov. Online student education in a pandemic: New challenges and risks. European Journal of Contemporary Education, 10(1):43–52, 2021. [4] Curtis J Bonk. Pandemic ponderings, 30 years to today: Synchronous signals, saviors, or survivors? Distance Education, 41(4):589–599, 2020. [5] Tamer Sari and Funda
observation protocol (appendix A) to follow, whichalso contains an observation notes section to document what happened during the game.Additionally, observers completed a reflective summary immediately following the exercise,documenting key inflection points, tactics used, the role of the facilitator, and the activity of theparties within the game.Participants also completed surveys pre- and post-exercise, which were administered viaQuestionPro (attached as appendix B). The participants were asked to complete the consentprocess and pre-survey two days in advance to the game, and the period for submissions wasopen until the game started. Participants were then sent a post-survey via email four days later,which contained the same questions as the pre
. [6] J. Brickell, D. Porter, M. Reynolds, and R. Cosgrove, “Assigning Students to Groups for Engineering Design Projects: A Comparison of Five Methods,” Journal of Engineering Education, vol. 83, no. 3, pp. 259–262, Jul. 1994. [7] M. W. Steiner, “A Case Study Approach for Understanding the Impact of Team Selection on the Effectiveness of Multidisciplinary Capstone Teams,” in American Society for Engineering Education, 2017. [8] B. M. Aller, D. M. Lyth, and L. A. Mallak, “TEACHING BRIEF Capstone Project Team Formation: Mingling Increases Performance and Motivation,” 2008. [9] M. D. Lane, “Effective Student Teams: A Faux Hiring And Peer Evaluation
1 (Disagree) to 5 (Agree), with option 3 (Neither agree nor disagree) beingneutral.There are also the following evaluations underway, where a more comprehensive analyseswill be submitted in the full paper.(b) The Basic Psychological Need Satisfaction and Frustration Scale (BPNSFS), providedbefore the intervention, measures students’ self-perceived characteristics and motivation inrelation to their levels of autonomy, relatedness, and competence [19].(c) The Problems in School (PIS) Questionnaire [20], provided before the intervention,measures their orientation towards decision-making, either being more controlling or moreautonomous.(d) An Ill-Structured Problem Validation Tool (ISPVT) [21], provided after the intervention,allow students to
importance of the voice of thecommunity when developing a technical solution: “Because if some people think the problem tobe solved is ‘A’ and I show up with a great technical solution to ‘B,’ guess what? The folks whoare looking for ‘A’ are going to say ‘What?”’ (00:22:49–00:23:04) This identification ofstakeholders and the solution environment illustrates problem definition.Leo went on to describe one of the things that attracted him to the university in the first place:institutional support of leadership positions related to things like “social innovation”(00:34:20–00:34:27). Leo actively suggested revisions for such positions, again illustrating hisproblem-solving mindset.Finally, Leo spent a sizeable amount of time discussing how innovation
--8653.[3] M. Wagner, B. Christe, and E. Fernandez, “Comparing First-year Engineering Technology Persisters and Non-persisters,” in 2012 ASEE Annual Conference & Exposition Proceedings, San Antonio, Texas: ASEE Conferences, Jun. 2012, p. 25.331.1-25.331.9. doi: 10.18260/1-2--21089.[4] M. J. Khan and C. A. Aji, “Development of Engineering Identity,” 2020.[5] D. Dougherty, “The Maker Movement,” Innov. Technol. Gov. Glob., vol. 7, no. 3, pp. 11– 14, Jul. 2012, doi: 10.1162/INOV_a_00135.[6] S. Weiner, M. Lande, and S. Jordan, “Making Identities: Understanding the Factors that Lead Young Adults to Identify with the Maker Movement,” in 2017 ASEE Annual Conference & Exposition Proceedings
implementations will be integrated and tested in a future pilot studybefore classroom integration in the Fall of 2024.AcknowledgementThis material is based upon work supported by the National Science Foundation under Grant No.2396230 - “Collaborative Research: Research Initiation: Formation of the Foundations forEngineering Intuition in Structural Engineering with Mixed Reality.References [1] J. Huang, S. Ong, and A. Nee, “Real-time finite element structural analysis in augmented reality,” Advances in Engineering Software, vol. 87, pp. 43–56, Sept. 2015. [2] W. M. K. Roddis and A. B. Matamoros, “Web-Enhanced Teaching of Steel Design: From Case Study to CD,” pp. 1–4, June 2012. Publisher: American Society of Civil Engineers. [3] Y. Turkan, R
create assignments and projects. This paper discusses fourteaching strategies integrated with G-AI; a) AI-assisted learning, b) Students evaluating AIgenerated solutions, c) Research-based learning with AI, and d) Open-ended project-basedlearning. Implementation of these strategies in electrical and robotics engineering technologycourses such as circuits analysis, signal processing, and robotics systems is explored. Thesecourses often require assignments that involve theoretical analysis and coding, solutions forwhich can easily be generated with AI. Therefore, employing these strategies in these courses ismore important to effectively address plagiarism and enhance learning. An analysis comparinggrade point average scores showed that student
Gandhi, and L. Ding, “Curriculum Design for Sustainability of Globally IntegratedManufacturing,” Jul. 2015, doi: https://doi.org/10.18260/p.23770.[4] E. Paravizo, O. C. Chaim, D. Braatz, B. Muschard, and H. Rozenfeld, “Exploring gamification tosupport manufacturing education on industry 4.0 as an enabler for innovation and sustainability,” ProcediaManufacturing, vol. 21, pp. 438–445, 2018, doi: https://doi.org/10.1016/j.promfg.2018.02.142.[5] K. Raoufi and K. Haapala, “Manufacturing Process and System Sustainability Analysis Tool: A Proof-of-Concept for Teaching Sustainable Product Design and Manufacturing Engineering,” doi:https://doi.org/10.1115/1.4064071%5D.[6] I. Roeder, M. Severengiz, R. Stark, and G. Seliger, “Open Educational Resources as
thing orientation,” in 2022 IEEE Frontiers in Education Conference (FIE). IEEE, 2022, pp. 1–6.[11] J. B. Main, T. Dang, B. Johnson, Q. Shi, C. Guariniello, and D. Delaurentis, “Why students choose STEM: A study of high school factors that influence college STEM major choice,” in 2023 ASEE Annual Conference & Exposition, 2023.[12] L. W. Perna, “Studying college access and choice: A proposed conceptual model,” in Higher education: Handbook of theory and research. Springer, 2006, pp. 99–157.[13] M. J. Grant and A. Booth, “A typology of reviews: an analysis of 14 review types and associated methodologies,” Health information & libraries journal, vol. 26, no. 2, pp. 91–108, 2009.[14] R. W. Lent, S. D. Brown, G. Hackett et