curated thelesson plan content to directly relate to their specific context, in collaboration with each other and ourresearch team.We built the curriculum leveraging students’ existing conceptions and misconceptions about AI from priorwork while testing the feasibility of addressing AI learning objectives, as well the AI4K12’s Five Big Ideas,in the broader context of middle school science, technology, engineering, mathematics, and computing(STEM+C) education. Our lessons were scaffolded using the iterative machine learning developmentprocess: 1) data collection and preparation; 2) selecting and training the model; 3) evaluating the models’accuracy; 4) tuning model parameters to improve performance. Each stage of the development processconstituted
. 10.18260/p.25933[2] National Science Foundation. Veterans’ education for engineering and science. Report of the NSF Workshop on Enhancing the Post-9/11 Veterans Educational Benefit. McLean, VA, April 13, 2009.[3] F. M. Connelly and D. J. Clandinin, “Stories of experience and narrative inquiry,” Educ. Res., vol. 19, no. 5, pp. 2–14, Jun. 1990.[4] M. Q. Patton, Qualitative Research & Evaluation Methods, 3rd ed. Thousand Oaks, CA: SAGE, 2002.[5] G. A. Phillips and Y. S. Lincoln, “Introducing veteran critical theory,” Int. J. Qual. Stud. Educ., vol. 30, no. 7, pp. 656–668, 2017.[6] T. J. Yosso, “Whose culture has capital? A critical race theory discussion of community cultural wealth,” Race Ethn. Educ., vol. 8, no. 1, pp. 69–91
ofremote/isolated learning cannot be absorbed by their families due to economic pressures andfamily obligations. HBCUs need to move from Covid-19 crisis answers and learn how torecover and make sure that money and arrangements for learning recovery set the foundationsfor more efficient, unbiassed, and strong education systems. References[1]S. BARKER, "CISION PRWEB," Gartner Magic Quadrant for Data Science and MachineLearning (DSML) Platforms, 1 March 2021. [Online]. Available:https://www.prweb.com/releases/rapidminer_named_a_visionary_in_gartner_magic_quadrant_for_data_science_and_machine_learning_platforms/prweb17780545.htm.[2] P. H. England, "Disparities in the risk and outcomes of Covid-19," PHE
future careers thus contributing to building sustainable and resilientdevelopments. The results of this research will be useful for developing SI and advancing therequired professional competencies of the future AEC workforce.References[1] B. Trigunarsyah and M. Skitmore, “The Key to Successful Implementation: Project Management of Sustainable Infrastructure Provision,” in Sustainable Urban and Regional Infrastructure Development: Technologies, Applications and Management, 2010.[2] E. Cooke and A. Bernheim, “Beyond zero: Activating triple zero airports,” J. Airpt. Manag., vol. 16, no. 2, pp. 173–183, 2022.[3] A. M. Raouf and S. G. Al-Ghamdi, “Effectiveness of Project Delivery Systems in Executing Green Buildings,” J
here are approved by the University of Illinois Urbana-ChampaignInstitutional Review Board under NHSR designation 23380. Capstone Innovations at Carle IllinoisCollege of Medicine are supported by The Henry Dale and Betty Smith Family.References[1] DianeR. Bridges, R. A. Davidson, P. Soule Odegard, I. V. Maki, and J. Tomkowiak, “Interprofessional collaboration: three best practice models of interprofessional education,” Medical Education Online, vol. 16, no. 1, p. 6035, Jan. 2011, doi: 10.3402/meo.v16i0.6035.[2] S. Chien, R. Bashir, R. M. Nerem, and R. Pettigrew, “Engineering as a new frontier for translational medicine,” Sci. Transl. Med., vol. 7, no. 281, Apr. 2015, doi: 10.1126/scitranslmed.aaa4325.[3] K. Alder, Engineering the
–855, Jan. 2018, doi: 10.1245/s10434-017-6320-6.[3] S. Chien, R. Bashir, R. M. Nerem, and R. Pettigrew. “Engineering as a new frontier fortranslational medicine,” Science Translational Medicine, vol. 7, no. 281, Apr. 2015, doi:10.1126/scitranslmed.aaa4325.[4] H. Zijlstra, and R. McCullough. “CiteScore: a new metric to help you track journalperformance and make decisions.” Eslevier.com. https://www.elsevier.com/connect/editors-update/citescore-a-new-metric-to-help-you-choose-the-right-journal (accessed Jan. 10, 2023).[5] Elsevier. “Topic prominence in science.” Eslevier.com.https://www.elsevier.com/solutions/scival/features/topic-prominence-in-science (accessed Jan.11, 2023).[6] N. Donthu, S. Kumar, D. Mukherjee, N. Pandey, and W. M. Lim. “How
Students Who Have Been There’ workshop. The team decided to utilizethe book The Secrets of College Success, Lynn F. Jacobs and Jeremy S. Hyman and providedspecific assigned and recommended readings.Program CohortsThe initial cohort in 2020 was recruited primarily from incoming first-year CoE students whosubmitted applications tothe traditional residential Table 1. The demographic composition of the BEE program and majorsSummer Scholars in the LSU College of Engineering. BEE BEE BEE All CoEprogram. The 2021 and Cohort 2020 2021 2022 (2021)2022 participants wererecruited from the Number 9
failure using the tensile testing machine. Figure 4. Some examples of the redesigned shapes created by students in week 3 and 3D printed before week 4's sessionDeliverables:Students complete and submit two short deliverables in the first four weeks, a full technical reportin week 10 and an oral presentation in week 13 of the semester. The short deliverables are designedto be included in the full technical report. The first short deliverable is a schematic to show themeasurements made for assessing dimensional accuracy as well as a photograph of the failed shapefor describing what failure looked like and how the location of failure was measured. The secondshort deliverable is a graphdemonstrating the
. Hess, J. Strobel, and R. (Celia) Pan, “Voices from the workplace: practitioners’ perspectives on the role of empathy and care within engineering,” Eng. Stud., vol. 8, no. 3, pp. 212–242, Sep. 2016, doi: 10.1080/19378629.2016.1241787.[2] J. Walther, S. Miller, and N. Kellam, “Exploring the role of empathy in engineering communication through a transdisciplinary dialogue,” in 2012 ASEE Annual Conference & Exposition Proceedings, San Antonio, Texas: ASEE Conferences, Jun. 2012, p. 25.622.1- 25.622.11. doi: 10.18260/1-2--21379.[3] D. Weichert, B. Rauhut, and R. Schmidt, “Educating the engineer for the 21st century: Proceedings of the 3rd workshop on global engineering education.” 2001.[4] H. Burns and K. Lesseig, “Infusing
presentations, and this was not due to differences in anxiety using thesedifferent modes. Student understanding and learning outcomes for both the presenters andthe audience members were significantly higher for in-person presentations. Although itwas not possible with the number of student responses in this course (one undergraduatestudent and eight graduate students), in the future it would be interesting to see if some ofthese results are driven by degree program level or experience with different presentationtypes, as only two students had previous experience with pre-recorded presentations.References[1] S. K. A. Soong, L. K. Chan, C. Cheers, and C. Hu, "Impact of video recorded lectures among students," Who’s learning, pp. 789-793, 2006
Student Experiences at a Minority Serving Institutuin (MSI)," in 2021 ASEE Annual Conference, Virtual conference, 2021.[2] D. R. Walker, Y. Maeda, M. Ohland and L. Tay , "The Impact of Department Diversity on Student Persistance and Success in Engineering," in 2021 ASEE Annual Conference, Virtual Conference, 2021.[3] R. Vivian, K. Falkner and C. Szabo, "Broadening Participation in Computer Science: Key Strategies from International Findings," in Preceedings of the 48th ACM Technical Symposium on Computer Science Education, Seattle, 2017.[4] R. Fall, S. Freeman, R. Greenberg, D. Kaiser and N. Sridhar, "Computer Science through Current Enrollment: A Strategy to Broaden Participation," in Proceeding of the 51st ACM Technical
even tried”). The rubric waspantomimed in class repeatedly for students.Since the project was due just before final exams and grades would need to be turned in shortlyafter, students were aware that detailed point allocation was unlikely but feedback would comein the form of comments about their professionalism and approach, with an overall impression ofwhether they were successful in accomplishing the task without regards to how close theymatched the drag coefficient(s). Within the written feedback to their assignments (via the LMS)comments on their approach and success reinforced the uncertainty inherent in simulations aswell as the uncertainty within published values.ResultsAs seen in Table 1, the majority of students selected SolidWorks
, theirability to identify stakeholders involved in a project scenario and the value engineers can createfor them.While our findings show student ability to create value depends on how they are exposed to theconcept and practice it, we do not argue one method is “better” than the other. Rather, wehighlight the ways in which the structure of these courses and their semester-long design projectsaffects student ability to create value in different ways. Engineering educators can decide whichfacet(s) of creating value they would like to highlight with their students and have them practicemore. In addition, while we used the Creating Value Direct Assessment as a summativeassessment in this work, we anticipate it can be used as a formative assessment by
/?id=EJ854930[5] P. Marshall, “How much, how often?” College and Research Libraries, vol. 35, no. 6, pp. 453, 1974[6] C. M. Burchfield and T. Sappington, “Compliance with required reading assignments,” Teaching of Psychology, vol. 27, no. 1, pp. 58, 2000.[7] T. Berry, L. Cook, N. Hill, and K. Stevens, “An Exploratory Analysis of Textbook Usage and Study Habits: Misperceptions and Barriers to Success,” College Teaching, vol. 59, no. 1, pp. 31–39, Dec. 2010, doi: https://doi.org/10.1080/87567555.2010.509376.[8] A. Bovtruk, I. Slipukhina, S. Mieniailov, P. Chernega, and N. Kurylenko, "Development of an electronic multimedia interactive textbook for physics study at technical universities," 16th
/education-oer/ (accessed Feb. 09, 2023).[3] N. B. Colvard, C. E. Watson, and H. Park, “The Impact of Open Educational Resources on Various Student Success Metrics,” International Journal of Teaching and Learning in Higher Education, vol. 30, no. 2, pp. 262–276, 2018.[4] B. Khan, C. Robbins, and A. Okrent, “The State of U.S. Science and Engineering 2020 | National Science Foundation,” 2020. Accessed: Feb. 09, 2023. [Online]. Available: https://ncses.nsf.gov/pubs/nsb20201/u-s-s-e-workforce[5] E. Litzler and J. Young, “Understanding the Risk of Attrition in Undergraduate Engineering: Results from the Project to Assess Climate in Engineering,” Journal of Engineering Education, vol. 101, no. 2, pp. 319–345, 2012, doi: 10.1002/j.2168
correlated with curricular progressionthrough the major, and degree of exposure to military culture and/or service members.References[1] Syracuse University, D’Aniello Institute for Veterans & Military Families. [Accessed Feb 20, 2023.] [Online]. Available: https://ivmf.syracuse.edu/[2] Forbes: P. A. Dillon, “Memo To Employers: Veterans Aren't PTSD Basketcases; They're Disciplined And Committed,” Forbes, September 29, 2014; assessed online September 11, 2017 at https://www.forbes.com/sites/realspin/2014/09/29/memo-to-employers-veterans- arent-ptsdbasketcases-theyre-disciplined-and-committed/[3] S. E. Kerr (Ed.), Examining Gun Regulations, Warning Behaviors, and Policies to Prevent Mass Shootings. IGI Global, 2021.[4] A
requires anencrypted connection to the server.Apart from issues with defective components, some groups, initially, were provided withRaspberry Pi 3’s instead of Raspberry Pi 4’s which resulted in slow response and irregular drivingby the RC cars. Through testing, it was seen that there were significant differences in drivingperformance on Raspberry Pi 3’s because they had only 1GB RAM. As latency increases, the carcan oscillate more. At high speeds, this can cause the car to drive off the track. This is why it isrecommended that a Raspberry Pi 4 with at least 4GB of RAM be used. In addition to running thedriving code, the Raspberry Pi is responsible for sending the sensor data and camera feed to theserver and receiving driving requests from a
derive the first lawefficiency (thermal efficiency) for a Carnot engine, Eq. 7. The expression for the Carnotefficiency is again derived when the concept of entropy is well understood and the processescomprising the cycle are presented on a T-s diagram. 𝑄𝑄 𝑇𝑇𝐻𝐻 � 𝑄𝑄𝐻𝐻� = ………………………………….(6) 𝐿𝐿 𝑟𝑟𝑟𝑟𝑟𝑟 𝑇𝑇𝐿𝐿 𝑇𝑇 𝜂𝜂𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐 = 1 − 𝑇𝑇 𝐿𝐿 …………………………………(7) 𝐻𝐻To ensure that the second law is enforced through quantification, the concept of entropy isintroduced and discussed both qualitatively and quantitatively. Published
unresponsive for several seconds. This could be due tothe network connectivity of the microcontrollers/dashboard users or the way the microcontrollersare programmed to publish data to the server. Troubleshooting is needed to find the exact reason.References[1] A. Sadik, T. Ortelt, C. Pleul, C. Becker, S. Chatti and A. Tekkaya, "The challenge of specimen handling in remote laboratories for Engineering Education", in 12th International Conference on Remote Engineering and Virtual Instrumentation, Bangkok, Thailand, 2015, pp. 180-185.[2] M. Sierra Apel, F. Odebrett, C. Paz and N. Perozo, "Multi-phase flowloop remote laboratory", in 17th International Conference on Remote Engineering and Virtual Instrumentation, University of
, no. 2, pp. 82-87, 2020.[3] S. Sahin, "An Application of Peer Assessment in Higher Education," Turkish Online Journal of Educational Technology, vol. 7, no. 2, pp. 5-10, 2008.[4] S. Öncü, "Online Peer Evaluation for Assessing Perceived Academic Engagement in Higher Education," EURASIA J Math Sci Tech Ed, vol. 11, no. 3, pp. 535-549, 2015.[5] T. Issa, "Promoting Learning Skills through Teamwork Assessment and Self/Peer Evaluation in Higher Education," International Association for the Development of the Information Society, 2012.[6] K. S. Double, J. A. McGrane and T. N. Hopfenbeck, "The Impact of Peer Assessment on Academic Performance: A Meta-analysis of Control Group Studies," Educational Psychology Review, vol. 32, pp. 481
, “Aeronautical Information Manual (AIM),” US Department of Transportation, June, 2021. https://www.faa.gov/air_traffic/publications/media/aim_chg_1_dtd_12-2-21.pdf[9] Federal Aviation Administration. “FAA Form 7110–2 PIREP Form - OMB,” OMB.report, 2022. https://omb.report/icr/202007-2120-006/doc/102821000[10] Johnson, I., Blickensderfer, B., Whitehurst, G., Brown, L. J., Ahlstrom, U., & Johnson, M. E. (2019). Weather Hazards in General Aviation: Human Factors Research to Understand and Mitigate the Problem. 20th International Symposium on Aviation Psychology, 421-425. https://corescholar.libraries.wright.edu/isap_2019/71[11] Gupta, S., Deo, M., Johnson, M. E., Pitts, B. J. & Caldwell, B. S. (2021). Exploratory Study of
recognizable and relevant to the student’s major(s) [12,13]. 2). Students could predict performance of a proposed design with their current level of knowledge [4,14] 3). Prediction of the behavior of the system to be built is within the scope of the course content in concurrent math and science courses. 4). The project lends itself to supporting the engineering process rather than trial and error/guess work. 5). Material presented to the students to help predict behavior of the system to be analyzed must prepare students for follow on courses in the students’ chosen major(s). 6). Success does not rely on the fabrication ability of the students, 7). The project must be conducted within a suitable time period and
recognizable and relevant to the student’s major(s) [12,13]. 2). Students could predict performance of a proposed design with their current level of knowledge [4,14] 3). Prediction of the behavior of the system to be built is within the scope of the course content in concurrent math and science courses. 4). The project lends itself to supporting the engineering process rather than trial and error/guess work. 5). Material presented to the students to help predict behavior of the system to be analyzed must prepare students for follow on courses in the students’ chosen major(s). 6). Success does not rely on the fabrication ability of the students, 7). The project must be conducted within a suitable time period and
of this study also taught the course understudy.Ethics approval: Research conducted retrospectively under IRB approval through Texas A&MUniversity.Consent to participate: Not applicable (exempted through IRB approval)Consent for publication: Publication was approved by IRB board.Availability of data and material: All student record data were de-identified and approved forFERPA compliance by Texas A&M University’s Office of the Registrar.References[1] M. Itani, S. Kaddoura, & F. al Husseiny. “The impact of the Covid-19 pandemic on on-line examination: challenges and opportunities,” Global Journal of Engineering Education, 24(2), 105–120, 2022.[2] B. Ives, & A.-M. Cazan. “Did the COVID-19 pandemic lead to an increase in
] G. Conole and B. Warburton, “A review of computer-assisted assessment”, Research in Learning Technology, vol. 13, no. 1, Mar. 2005, doi: 10.1080/0968776042000339772[2] S. N. Ikwumelu, Ogene A. Oyibe, and E. C. Oketa, “Adaptive teaching: an invaluable pedagogic practice in social studies education”, Journal of Education and Practice, vol. 6, no.33, 2015.[3] B. Balakrishnan, “Motivating engineering students learning via monitoring in personalized learning environment with tagging system”, COMPUTER APPLICATIONS IN ENGINEERING EDUCATION, vol. 26, no. 3, pp. 700–710, Feb. 2018, doi: /10.1002/cae.21924.[4] K. Soria, I. Chirikov, and D. Jones-White, “The obstacles to remote learning for undergraduate
characterization of biological systems,” Int. J. Appl. Electromagn. Mech., vol. 50, pp. 353– 363, 2016.[4] R. T. Sheldon, “Radiofrequency and capacitive sensors for dielectric characterization of low- conductivity media,” 2015.[5] M. D. Janezic and D. F. Williams, “Permittivity characterization from transmission line measurement,” in Microwave Symposium Digest, 1997., IEEE MTT-S International, vol. 3, pp. 1343–1346, 1997.[6] Massa, R., Caprio, E., De Santis, M., Griffo, R., Migliore, M.D., Panariello, G., Pinchera, D. and Spigno, P., Microwave treatment for pest control: the case of Rhynchophorus ferrugineus in Phoenix canariensis. EPPO Bulletin, 41(2), pp.128-135, 2011.
ethicsand data bias as learning goals arose from only a rudimentary understanding of how machineslearn. We do not believe that critical perspectives about machine bias would have been possiblewithout a basic mechanistic explanation of the processes involved in machine learning.AcknowledgementsThe authors are grateful to the teacher candidates who creatively engaged in this work and toMehrdad Mahdavi and Swaroop Ghosh for inviting us to think together about machine learningsystems in drug discovery contexts. This work is partially supported by the National ScienceFoundation NSF OIA-2040667. References[1] Bolger, M. S., Kobiela, M., Weinberg, P. J., & Lehrer, R. (2012). Children's mechanistic reasoning
- DMvm_VaJv8ne89rurfCXMNPwWxk9sUz5ioQ5zGD9lqnGko7wxuYAWq5jgEhpcdWA2XvIXbl3 2d_JHXJYoCIb-ivm2neGRQyBqKVuokhinC6U7rvA9eAtwLyfG10Mn8mMX-pPnafYyqGm- K8rMnYCQkH4YRz1o59rMXm286K24AiydNVFMat3OsSE7EsaQRJ0UD- yEsMpr6Jw66ub0ch_Ovd-orxvcwtlmXfOdBuTex-YHnD16iw 2. S. Olson, D. G. Riordan and Executive Office of the President. Engage to excel: Producing one million additional college graduates with degrees in science, technology, engineering, and mathematics. report to the president. Executive Office of the President. 2012 Available: http://uc.summon.ssc.uc.idm.oclc.org/2.0.0/link/0/eLvHCXMwjV1LSwMxEB6qeBA8KFZ8VJ kfsC3bbLK23ord1ovowXuZTbJSkCh1F_w1_tZOkq0vFLwEMixLMjCZB998A5CJQdr_8SYMq7 wyhoy0eUmcAdicSqVJkaxyfhD19-k-sBnq-F
, 44(8), 1187–1218. • Cheryan, S., Master, A., & Meltzoff, A. N. (2015). Cultural stereotypes as gatekeepers: Increasing girls’ interest in computer science and engineering by diversifying stereotypes. Frontiers in Psychology, 6(49), 1–8. • Collins, K. H. (2018). Confronting color‐blind STEM talent development: Toward a contextual model for Black student STEM identity. Journal of Advanced Academics, 29(2), 143–168. • Kricorian, K., Seu, M., Lopez, D., Ureta, E., & Equils, O. (2020). Factors influencing participation of underrepresented students in STEM fields: Matched mentors and mindsets. International Journal of STEM Education, 7(16), 1–9. Key references are included on this slide
for Multicultural Education 11(2), 149- 159.32 32 References Fifolt, M., Engler, J., & Abbott, G. (2014). Bridging STEM Professions for McNair Scholars through Faculty Mentoring and Academic Preparation. American Association of Collegiate Registrars and Admissions Officers. Griffin, K. A. (2019). Institutional barriers, strategies, and benefits to increasing the representation of Women and Men of Color in the Professoriate: Looking beyond the pipeline. Higher Education: Handbook of Theory and Research: Volume 35, 1-73. Hurtado, S., Eagan, M. K., Tran, M. C., New man, C. B., Chang, M