; Formative • Opportunities for evidence of understanding Assessment through performance tasks Moore, T. J., Guzey, S. S., Hynes, M. M., Douglas, K. A., & Strimel, G. J. (2024). Microelectronics Integration Curriculum Development Framework. https://nanohub.org/resources/39164 SCALE K-12 Curriculum 1 Trekking Through the Periodic Table (8th – 10th, Science) ME Fuse: semiconductors, materials used in microchips, circuits using breadboards and
Inclusion in Higher Education, vol. 3, no. 1, Nov. 2021, Available: https://digitalcommons.wcupa.edu/jarihe/vol3/iss1/4[7] S. Y. Yoon and S. A. Sorby, “Rescaling the Longitudinal Assessment of Engineering Self- Efficacy V3.0 for Undergraduate Engineering Students,” Journal of Psychoeducational Assessment, vol. 38, no. 2, pp. 209–221, Apr. 2020, doi: 10.1177/0734282919830564. Available: https://journals.sagepub.com/doi/10.1177/0734282919830564.
. We intend to use the feedback given in these interviews to begin institutionalimplementation to improve support, inclusivity, and accommodations for neurodivergent studentsin STEM programs. References[1] Cleveland Clinic, “Neurodivergent: What It Is, Symptoms & Types,” Cleveland Clinic,Jun. 02, 2022. https://my.clevelandclinic.org/health/symptoms/23154-neurodivergent[2] S. Salvatore, C. White, and S. Podowitz-Thomas, “‘Not a cookie cutter situation’: Howneurodivergent students experience group work in their stem courses - International Journal ofSTEM Education,” SpringerLink, https://link.springer.com/article/10.1186/s40594-024-00508-0(accessed Feb. 20, 2025).[3] M. Sharma, “Neurodiversity in
effort to learn in the course.Throughout this project, students learned a multitude of technical and soft skills (3D printing,working with CT scans, the engineering design process, teamwork, project planning, and timemanagement). Student feedback regarding the project has been incredibly positive after the firstyear. The second iteration with a new student group just started in Fall 2024, with the list ofaddressed organs/anatomy continuing to grow.References[1] “ Nordic Thingy:52,” Accessed Jan 17, 2024. [online] https://www.nordicsemi.com/Products/Development-hardware/Nordic-Thingy-52.[2] Warren, K. N., & Carlson, C., & Warren, S. (2020, June), A Survey of Biomedical Design Projects to Inform Skill Development in a New
. 2003, doi: 10.1080/00220970309602059.[3] C. E. Wieman, G. W. Rieger, and C. E. Heiner, “Physics Exams that Promote CollaborativeLearning,” The Physics Teacher, vol. 52, no. 1, pp. 51–53, Dec. 2013, doi: 10.1119/1.4849159.[4] H. Jang, N. Lasry, K. Miller, and E. Mazur, “Collaborative exams: Cheating? Orlearning?,” American Journal of Physics, vol. 85, no. 3, pp. 223–227, Feb. 2017,doi: 10.1119/1.4974744.[5] M. Jollands, L. Jolly, and T. Molyneaux, “Project-based learning as a contributing factor tograduates’ work readiness,” European Journal of Engineering Education, vol. 37, no. 2, pp. 143–154, Mar. 2012, doi: 10.1080/03043797.2012.665848.[6] A. S. Palincsar, “SOCIAL CONSTRUCTIVIST PERSPECTIVES ON TEACHING ANDLEARNING,” Annual Review of
-Guided Learning Approach Using Computer-Aided Learning Packages: Evaluation of Learning Outcomes in a Cooling Tower Experiment in the Unit Operations Lab. Chemical Engineering Education, 2022. 56(3): p. 190-198.14. Pisani, S. and M.D. Haw, Learner agency in a chemical engineering curriculum: Perceptions and critical thinking. Education for Chemical Engineers, 2023. 44: p. 200- 215.15. Mataka, L.M. and M.G. Kowalske, The influence of PBL on students' self-efficacy beliefs in chemistry. Chemistry Education Research and Practice, 2015. 16(4): p. 929-938.16. Kolil, V.K., S. Muthupalani, and K. Achuthan, Virtual experimental platforms in chemistry laboratory education and its impact on experimental self-efficacy
. K. Miller, and D. R. Simmons, “Exploring the theoretical social capital ‘deficit’ of first generation college students: Implications for engineering education,” Int. J. Eng. Educ., vol. 30, no. 4, pp. 822-836, 2014.[6] J. P. Martin, D. R. Simmons, and S. L. Yu, “Family roles in engineering undergraduates’ academic and career choices: Does parental educational attainment matter?,” Int. J. Eng. Educ., vol. 30, no. 1, pp. 136-149, 2014.[7] J. P. Martin, S. K. Stefl, L. W. Cain, and A. L. Pfirman, “Understanding first- generation undergraduate engineering students’ entry and persistence through social capital theory,” Int. J. STEM Educ., vol. 7, no. 1, 2020. [Online]. Available: https://doi.org
already be familiar with (RISC-V), Professor 1’s students couldspend less time learning a new architecture and more time using it. Alternatively, the inclusion ofARM Architecture could allow for everyone to start from the same place to better support newcommunity college transfer students who may not have the prior RISC-V experience. Secondly,many students learn about support resources at Cal Poly through their instructors. Having or nothaving information about the Disability Resource Center and accommodations matters, as doeswhat department/college-specific and university support resources are included, particularly forstudents from minoritized groups, students who would benefit from enhanced academic support,and students experiencing food or
well-roundedknowledge on the subject.”ConclusionsThis study adds to an existing database of studies that indicate some of a variety ofenhancements that may benefit students who are administered authentic oral exam assessments.Such assessments have the potential to improve student understanding, combat growing issuesrelated to violation of academic integrity, and permit deeper instructor engagement with students.AcknowledgementsThe authors acknowledge the participation of the ITFS students surveyed for this study.References[1] S. D. Roney and D. R. Woods, "Ideas to Minimize Exam Anxiety," Journal of Engineering Education, vol. 92, no. 3, pp. 249-256, 2003.[2] S. N. Ullah, "Examples of authentic assessments in engineering education
Latinos (76.5%)live in these counties, with 32.6% residing in Miami-Dade County. Additionally, eight of the 10largest Florida counties are also home to the state's largest Latino communities, including Miami-Dade County, Broward County, Orange County, Hillsborough County, Palm Beach County, PolkCounty, Lee County, and Duval County. Given the fact that [University]'s headquarter is inBroward County, the demographic of Latino students is expected to exponentially increase foryears to come. Most KU students are Pell-eligible. The below table presents the data from the DOEwebsite, the most updated data related to FTIC students at Keiser University. Table 2. Unmet Financial Need of KU First Time-Full Time Students Keiser University
for this disparity are complex andinfluenced by a tremendous number of factors, however, the Society of Women in Engineering’sannual review of literature has identified psychological or cultural factors as the leading cause ofprofessional attrition [13]. A survey by Conrad, Abdallah, and Ross compared the experience of women inuniversity STEM programs, noting that more women in engineering programs experiencedinstitutional/cultural barriers compared to women in STEM programs or male identified students[14]. The responses also emphasized a greater reliance on professors and mentorship programs asa support system than other STEM disciplines or male identified students in engineering. Ong etal.'s study of women of color in STEM found
assignment and a study guide before the final exam.Examples of these materials are provided in the appendix and discussed in the results section ofthe study. The design of this study aimed to explore whether simply informing students about AIand allowing them to use it without specific training or structured guidance could enhance theirunderstanding of the course topics. This approach was particularly relevant as our institution, likemany others, is debating whether to limit student use of AI tools.ResultsWe started the study with the soft introduction phase. Examples are selected from the coursetextbook(s) and are solved using Chat GPT-4o and AP- Microeconomics bot. We created a newpaid account and used it only for the study. This was done since
’s with Alan Turing and the “Turing Test”,officially coined as “Artificial Intelligence” by John McCarthy in 1956 (19). AI is a generalterm for technology that “enables computers and machines to stimulate human learning,comprehension, problem solving, decision making, creativity and autonomy” (19). Under theumbrella of AI are multiple AI-based tools (AI-T) that can assist in the engineering designprocess.The first of these is Machine Learning (ML). According to Radhika Jajkumar, “ML refers to theprocess of training a set of algorithms on large amounts of data to recognize patterns, whichhelps make predictions and decisions” (20). There are three categories that ML is divided into:supervised learning, unsupervised learning, and reinforced
knowledge of use in engineering education.Finally, the presence or absence of explicit "designing for X" framing reveals its potential value forfocusing RtD work. While Shroyer's explicit use clarified her focus, its absence in Coppola's worksuggests opportunities for more intentional framing in future RtD efforts in engineering education.Even this limited sample reveals how the approach can generate structured insights about educationaldesign work while accommodating different scales of innovation. As we continue to examineadditional examples of RtD in engineering education, these initial insights provide a foundation forunderstanding the approach's potential contributions.ReferencesCoppola, S. M., & Turns, J. A. (2023, June). Developing a
graduateresearch assistant, and the REU mentor.Research FundingThis study was funded by the National Science Foundation Division of Engineering Educationand Centers (ENG/EEC) program under Grant Number #2244293. 4References[1] S. Sampath et al., "Pandemics Throughout the History," (in eng), Cureus, vol. 13, no. 9, p. e18136, Sep 2021, doi: 10.7759/cureus.18136.[2] World Health Organization. "WHO COVID-19 Dashboard." https://data.who.int/dashboards/covid19/deaths (accessed April 28, 2025).[3] J. Howard et al., "An Evidence Review of Face Masks Against COVID-19," Proceedings of the National Academy of Sciences, vol. 118, no. 4, p
team gratefully acknowledges the joint support of the National Science Foundationand the Department of Defense, administered through the NSF Division of Engineering Educationand Centers (Award Nos. 1852130 and 2244324). The authors are thankful for the support fromthe UCF Office of Research and Office of Undergraduate Research.References[1] M. Ragab, F. M. Cheatwood, S. Hughes, J. DiNonno, R. Bodkin, A. Lowry, J. Kelly, and J. G. Reed, “Performance Efficient Launch Vehicle Recovery and Reuse,” AIAA SPACE 2016, AIAA 2016-5321, 2016. doi: 10.2514/6.2016-5321[2] E. J. Tuegel, A. R. Ingraffea, T. G. Eason, and S. M. Spottswood, “Reengineering Aircraft Structural Life Prediction Using a Digital Twin,” International Journal of Aerospace
the National Science Foundation under Grant No.(2236075). 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] D. Ebert-May, T.L. Derting, T.P. Henkel, J.M. Maher, J.L. Momsen, B. Arnold, H.A. Passmore, Breaking the cycle: Future faculty begin teaching with learner-centered strategies after professional development, CBE Life Sci. Educ. 14 (2015) 1–12. doi:10.1187/cbe.14-12- 0222.[2] S. Bernstein-Sierra, A. Kezar, Identifying and Overcoming Challenges in STEM Reform: a Study of four National STEM Reform Communities of Practice, Innov. High. Educ. 42 (2017) 407–420. doi:10.1007/s10755
with a wind speed of 7 mph ‘3.13 Over the WiFi data that was transferred to the raspberry pi m/s’, a revised decay constant k=2.47s/m is needed to accurately5 using the flask server. Sensor data was updated every second. calculate the observed PM2.5 concentration which is 2.90The IP address identified during the Arduino code to match the µg/m³.Flask server as well as its port. A combination of sensor This suggests that natural wind patterns and environmentalreadings was sent simultaneously while containing the factors significantly affect PM dispersion, and the decayparticulate
important to note that this research is still in progress, with plans for additional surveys tofurther explore students' preferences. Given ChatGPT 4.0's strong proofreading abilities, it wasemployed to correct grammatical and spelling errors and enhance the clarity of the text [10].ConclusionsThe findings from this study demonstrate that ChatGPT 4.0 has considerable promise as asupportive educational tool for enhancing MATLAB programming skills. A significant majorityof students (77.2%) indicated that ChatGPT effectively improved their coding comprehension andproblem-solving abilities through real-time feedback and the clarification of complex concepts.The use of ChatGPT also substantially reduced debugging time for most students (81.8%),although
’ responsesincreased from 2.84 to 2.89. Even though the increase for males is marginal, the analysisdemonstrates the differential impacts of this STEM-focused program on students’ likelihood ofstudying STEM in college by gender. Second, students whose parents/guardians or relatives do not work in the field of STEMwere separated from the rest (who have at least one parent/guardian or relative working in aSTEM field). The weighted average using the four-point scale dropped from 3.08 to 2.68 forstudents whose parents and relative(s) are not STEM workers; these students are generally notexposed to STEM career perspectives at home or family events. In contrast, the weightedaverage increased from 2.82 to 2.94 for students who have at least one parent
without. This experiment will measure the tool’s direct impact oncollaborative learning outcomes and its ability to promote equitable and effective teamdynamics.7 AcknowledgmentThis material is based upon work supported by the National Science Foundation under Grant No.DUE 21-21412.References [1] M. M. Fong, S. Huang, A. Alawini, M. Silva, and G. L. Herman, “Exploring computing students’ sense of belonging before and after a collaborative learning course,” in Proceedings of the 55th ACM Technical Symposium on Computer Science Education V. 1, ser. SIGCSE 2024. New York, NY, USA: Association for Computing Machinery, 2024, p. 359–365. [Online]. Available: https://doi.org/10.1145/3626252.3630850 [2] W. W. M. Lam, H. Xie, D. Y. W. Liu
Cited[1] C. Luchs and W. Smith, “An Examination of the Use of Service in the Promotion and Tenure Process,” 2004.[2] J. S. Filetti, “Assessing service in faculty reviews: Mentoring faculty and developing transparency,” Mentoring and Tutoring: Partnership in Learning, vol. 17, no. 4, pp. 343– 352, 2009, doi: 10.1080/13611260903284416.[3] J. C. Schweitzer and J. C. Hudson, “Evaluating faculty service to student organizations,” The Journalism Educator, vol. 44, no. 4, pp. 60–63, 1989.[4] R. M. Diamond, Aligning Faculty Rewards with Institutional Mission. Statements, Policies, and Guidelines. ERIC, 1999.[5] P. Seldin, “Changing practices in evaluating teaching,” 1999.[6] A. L. Antonio, H. S. Astin, and C. M. Cress
://infrastructurereportcard.org[3] American Society of Civil Engineers. (2019). Civil Engineering Body of Knowledge:Preparing the Future Civil Engineer (3rd ed.). ASCE[4] Bae, H., Polmear, M., & Simmons, D. R. (2022). Bridging the Gap between IndustryExpectations and Academic Preparation: Civil Engineering Students’ Employability. Journal ofCivil Engineering Education, 148(3). https://doi.org/10.1061/(ASCE)EI.2643-9115.0000062[5] Brunhaver S., Korte R., Barley S., Sheppard S. Bridging the Gaps between EngineeringEducation and Practice. In: U.S. Engineering in a Global Economy. University of Chicago Press;2019:129-164. doi:10.7208/9780226468471-006.[6] Congress.gov. H.R.3684 - Infrastructure Investment and JobsAct. https://www.congress.gov/bill/117th-congress/house
assumptions have to be made to proceed. Unknowns Solution No indication of how the problem should or can be Structure and 0 solved. EquationsIn contrast, a problem with all 2’s would be equivalent to a free body diagram of the scenario withall necessary elements for calculation explicitly listed. In this case, all that would be left to do isthe calculation, evaluation, solution communication and self-reflection, or the “CESS pool” of thePROCESS rubric.The ratings of the homework problems in the course were conducted by two members of theresearch team, the course instructor and graduate research assistant with disciplinary expertise inmechanical engineering. For the correlation
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, “Stage-based challenges and strategies for support in doctoral education: A practical guide for students, faculty members, and program administrators,” Int. J. Dr. Stud., vol. 11, p. 15, 2016.[3] J. W. Anastas and E. P. Congress, “Philosophical Issues in Doctoral Education in Social Work: A Survey of Doctoral Program Directors,” J. Soc. Work Educ., vol. 35, no. 1, pp. 143–153, Jan. 1999, doi: 10.1080/10437797.1999.10778953.[4] A. Johri, A. S. Katz, J. Qadir, and A. Hingle, “Generative artificial intelligence and engineering education.,” J. Eng. Educ., vol. 112, no. 3, 2023, Accessed: Jan. 15, 2025. [Online]. Available: https://search.ebscohost.com/login.aspx?direct=true&profile=ehost&scope=site&authtype