Paper ID #46847Pedagogical Choices for Navigating and Teaching Sociotechnical Landscapesin Engineering EducationJenna Tonn, Boston College Dr. Jenna Tonn is a historian of science, technology, and engineering at Boston College. She received her BA and MA from Stanford University and her PhD from Harvard University. Her research focuses on the social and cultural contexts of science, technology, and engineering.Brit Shields, University of PennsylvaniaRyan Hearty, The Johns Hopkins University Ryan Hearty teaches in the Whiting School of Engineering at Johns Hopkins University. He obtained his bachelor’s and master’s in
engineering classroom [2]. However, if we are to train the nextgeneration of engineers, providing a background in NLP could help students better understandthe potential and limitations of these powerful tools [3] . Since many first-year engineeringprograms teach MATLAB, python, or similar programming languages, it is a natural home forexploring the topic of NLP with students to lift the veil of mystery around the technology andprovide practical applications of their coding knowledge.This lesson can be used to guide students through implementing Natural Language Processing inMATLAB. At the end of the lesson, students should be able to (a) articulate the major stepsneeded to create a simple NLP program and the associated terminology as well as (b
motion when successfully grasp- ing an object and moving it from point A to point B. Other analysis related to dynamics, force-based control can also be achieved bringing the regular 3 https://www.fanucamerica.com/products/robots/robot-simulation-software-FANUC-ROBOGUIDE ‘Introduction to Robotics’ course beyond its heavy mathematic framework. • The rapid control prototyping for challenging systems with unstable zero dy- namics. Mobile wheeled pendulum laboratory is a perfect example. Proto- type of MWP has been developed previously [11]. However, special care was given to the design by adding protective torus because this system suffers from unstable zero dynamics and its stabilization is tricky
was offered- inFall 2022 (before the intervention) and in Spring and Summer 2024 (after the intervention). Thegradual release model improved student performance in class and on exams as seen from thegrades (Fig. 3). In the Spring 24 semester, 70% of the students received an A grade of some kindand all the students got a grade of at least a B-. In the Summer 24 semester, 65% of the studentsgot an A while the rest got a B. None got C, D or F grades. This was an improvement over theFall 22 semester, where a similar cohort of students received a range of grades from A to F (6%Fig. 3 Histogram of student grades over the Fall 2022, Spring 2024 and Summer 2024 semesters. Y-axis is percentage ofstudents getting the grades. Indicates improvement in
Chronicle of Higher Education. Accessed: May 01, 2025. [Online]. Available: https://www.chronicle.com/article/here-are-the-states-where- lawmakers-are-seeking-to-ban-colleges-dei-efforts[2] K. B. Follmer, I. E. Sabat, K. P. Jones, and E. King, “Under attack: Why and how I-O psychologists should counteract threats to DEI in education and organizations,” Ind. Organ. Psychol., vol. 17, no. 4, pp. 452–475, Dec. 2024, doi: 10.1017/iop.2024.12.[3] L. M. Leslie, J. E. Bono, Y. (Sophia) Kim, and G. R. Beaver, “On melting pots and salad bowls: A meta-analysis of the effects of identity-blind and identity-conscious diversity ideologies.,” J. Appl. Psychol., vol. 105, no. 5, pp. 453–471, May 2020, doi: 10.1037/apl0000446.[4] J. Yi, H. A
-Generation College Students’ Personal Agency Supports Disciplinary Role Identities and Engineering Agency Beliefs,” p. 5722553 Bytes, 2020, doi: 10.25394/PGS.12472757.V1.[11] C. B. Zoltowski, W. C. Oakes, and M. E. Cardella, “Students’ Ways of Experiencing Human-Centered Design,” Journal of Engineering Education, vol. 101, no. 1, pp. 28–59, Jan. 2012, doi: 10.1002/j.2168-9830.2012.tb00040.x.[12] P. A. Hecker, “Successful Consulting Engineering: A Lifetime of Learning,” J. Manage. Eng., vol. 13, no. 6, pp. 62–65, Nov. 1997, doi: 10.1061/(ASCE)0742-597X(1997)13:6(62).[13] T. J. Weston and S. L. Laursen, “The Undergraduate Research Student Self-Assessment (URSSA): Validation for Use in Program Evaluation,” LSE, vol. 14, no. 3, p
need has three statements, and the Figure 1: Plot of Student Ratings for the different Needs in the Hierarchy of Needs, namely Physiological (PN), Safety (SN), Belonging (BN), Self-Esteem (EN), and Self-Actualization value for each of Needs (AN). (A) Course in Fall 2023, (B) Course in Spring 2024, and (C)BME as a major. these is averaged for The box represents the mean of the data, ‘X’ marks the maximum and minimum values, and every student to the whiskers flank the standard deviation. determine their score
given their intensity in mathematicalcalculations. For each course, one exam and one homework assignment were selected. ChatGPTwas then used to solve those problems. The solutions were graded using the same criteria thatinstructors use to evaluate student submissions. The problem statements and evaluation resultsare provided in Tables 2 through 5. Table 2. Thermodynamics homework 6, undergraduate course in Mechanical Engineering Problem 1. An inventor claims to have developed a power cycle operating between hot and cold reservoirs at 1175 K and 295 K, respectively, that provides a steady state power output of (a) 28 kW, (b) 31.2 kW, while receiving energy by heat transfer from the hot reservoir at the rate 150,000 kJ/h. Evaluate each claim
coming to tech!: A history of American engineering education for women. MIT Press, 2014.2. S. Cheryan, S. A. Ziegler, A. K. Montoya, and L. Jiang, “Why are some STEM fields more gender balanced than others?,” Psychol. Bull., vol. 143, no. 1, pp. 1–35, 2017.3. B. L. Yoder, “Engineering by the numbers (2015),” American Society of Engineering Education (ASEE), 2015.4. C. Sarah and L. K. Mona, “Critical mass theory and women’s political representation,” Polit. Stud., vol. 56, no. 3, pp. 725–736, Oct. 2008.5. V. Valian, Why so slow?: The advancement of women. MIT Press, 1999.6. National Science Foundation, & National Center for Science and Engineering Statistics (2019). Women, minorities, and persons with disabilities in
. Estudillo, “Effects of a peer-to-peer mentoring program: Supporting first- year college students’ academic and social integration on campus,” J. Hum. Serv. Train. Res. Pract., vol. 3, no. 2, Oct. 2018, [Online]. Available: https://scholarworks.sfasu.edu/jhstrp/vol3/iss2/3[10] G. Crisp, A. Nora, and A. Taggart, “Student characteristics, pre-college, college, and environmental factors as predictors of majoring in and earning a STEM degree: An analysis of students attending a Hispanic serving institution,” Am. Educ. Res. J., vol. 46, no. 4, pp. 924–942, Dec. 2009, doi: 10.3102/0002831209349460.[11] C. Gattis, B. Hill, and A. Lachowsky, “A successful engineering peer mentoring program,” presented at the 2007 Annual
quality and the document retrieval system onresponse quality. Finally, we compare the performance of the specialist chatbots.4.1 Hallucination and helpfulnessOverall, our RAG-based specialist chatbots demonstrated low rates of hallucination and high ratesof helpfulness. The all-project specialist bot answered 80% of sample questions correctly and70% were helpful to students. Across our one-project specialist bots, 77% of questions wereanswered correctly, and 70% were helpful to students. The generalist bot, ChatGPT, did notperform as well, answering 70% of questions correctly, but only 26% of responses wereconsidered helpful (Figures 3a and 3b).(a) Correctness of chatbot responses by bot type. The (b) Helpfulness of chatbot responses by bot
.tb00832.x.[10] N. F. O. Erbuomwan, S. Sivaloganathan, and A. Jebb, “A survey of design philosophies, models, methods and systems,” Proc. Inst. Mech. Eng. Part B J. Eng. Manuf., vol. 210, no. 4, pp. 301–320, 1996, doi: 10.1243/pime_proc_1996_210_123_02.[11] R. B. Frost, “A Suggested Taxonomy for Engineering Design Problems,” J. Eng. Des., vol. 5, no. 4, pp. 399–410, Jan. 1994, doi: 10.1080/09544829408907897.[12] T. J. Howard, S. J. Culley, and E. Dekoninck, “Describing the creative design process by the integration of engineering design and cognitive psychology literature,” Des. Stud., vol. 29, no. 2, pp. 160–180, Mar. 2008, doi: 10.1016/j.destud.2008.01.001.[13] C. L. Bell-Huff, T. M. Fernandez, K. L. Morgan, and J. M. LeDoux, “WIP
://doi.org/10.1007/s40692-019-00147-3[3] J. Miller, "STEM education in the primary years to support mathematical thinking: using coding to identify mathematical structures and patterns," ZDM Mathematics Education, vol. 51, pp. 915-927, 2019. https://doi.org/10.1007/s11858-019-01096-y[4] P. J. Rich, S. F. Browning, M. Perkins, T. Shoop, E. Yoshikawa and O. M. Belikov, "Coding in K-8: International Trends in Teaching Elementary/Primary Computing," TechTrends, vol. 63, pp. 311-329, 2019. https://doi.org/10.1007/s11528-018-0295-4[5] T. Q. Kieu, V. B. Nguyen and A. T. Nguyen, "Micro: bit in Science Education: A Systematic Review," Jurnal Penelitian dan Pembelajaran IPA, vol. 9, pp. 1-14, 2023. http://dx.doi.org/10.30870/jppi.v9i1.19491
classified as matching the content of Quizzes 1 or 2, kinematics and kinetics ofparticles and rigid bodies, respectively. None of the project topics selected by the studentsmatched the content of Quiz 3, which covered vibrations. It should be noted that deepercomparison of the quiz scores between groups may contain significant confounding factors dueto variations in quiz difficulty from semester to semester.Project scores were calculated using a rubric (see Appendix B) and the Cumulative score wascalculated from the total of all points available in the course including quizzes, homework, andthe project. There was no significant difference in the project scores across the groups. In thecumulative score, the Video group had a statistically significant
a survey, theRevised Test Anxiety Online (RTA-O) scale 19 . The RTA-O has been validated, further refines theubiquitous Test Anxiety Inventory 1 , and captures information about the multiple dimensions oftest anxiety. Afterwards, students were randomly split into two groups, groups A and B. Group Atook their first exam in the classroom, while group B took their first exam in the CBTC.Thereafter, the modalities were alternated for each group for each exam. The course had sixexams, meaning that students took three exams in the CBTC and the other three exams under aBYOD setup. The exams were 50 minutes long and consisted mainly of numeric fill-in-the-blankquestions.After each exam, students were sent a survey to collect information regarding
withclients to achieve a working product.” Student B highlights her growth in leadership, stating, “Igained so much confidence in my leadership, initiative, and collaboration abilities.” Student Cadds, “I gained confidence in presenting curriculum to multidisciplinary leadership teams.”These qualitative insights are supported by survey data, which show that confidence inprofessional collaboration increased from a mean of 3.2 before participation in the program to4.3 afterward. By fostering these interpersonal skills, DIFUSE prepares interns to thrive ininterdisciplinary, team-based environments.Strengthening Technical Knowledge Through Applied Learning: Hands-on opportunitiesallow interns to deepen their technical expertise. Projects involving Python
literature review, Computers & Education, Volume 141, 2019, 103612, ISSN 0360-1315, https://doi.org/10.1016/j.compedu.2019.103612.[4] R. Schulz, B. Smaradottir, A. Prinz and T. Hara, "User-Centered Design of a Scenario- Based Serious Game: Game-Based Teaching of Future Healthcare," in IEEE Transactions on Games, vol. 12, no. 4, pp. 376-385, Dec. 2020, doi: 10.1109/TG.2020.3033437.[5] Schwartz, S. H., Cieciuch, J., Vecchione, M., Davidov, E., Fischer, R., Beierlein, C., ... & Konty, M. (2012). Refining the theory of basic individual values. Journal of personality and social psychology, 103(4), 663.[6] Smolen, L. A., Colville-Hall, S., Liang, X., & Mac Donald, S. (2006). An empirical study of
each experiment. Experimental results can then be tracked and analyzed in an oscilloscope,Multi-channel (MCA), or Single-Channel Analyzer (SCA). Fig. 1 (a)-(b) shows snapshots of thevirtual environment. Fig. 2 also depicts snapshots of (a) actual lab equipment and (b) the samevirtual equipment. (a) (b)Fig. 1: Snapshots of the AVR-DML environment. (a) Data Processing Lab and (b) Spectroscopy with a NaI Detector Lab. (a) (b) Fig. 2 Snapshots of (a) a NIM bin module/oscilloscope and a GM detector in the real lab setting and (b) the same devices in the
. Accedido: 29 de abril de 2025. [En línea]. Disponible en: https://peer.asee.org/wip-using-real-materials-scale-modeled-for-learning- about-construction[5] J. M. Bonilla, M. S. Valarezo, B. D. Villacrés, y M. A. Guerra, «Board 44A: Work in Progress: Unannounced Frequent Examinations to contribute student learning and building academic integrity», en 2023 ASEE Annual Conference & Exposition, 2023. Accedido: 29 de abril de 2025. [En línea]. Disponible en: https://peer.asee.org/board-44a-work-in-progress-unannounced-frequent- examinations-to-contribute-student-learning-and-building-academic-integrity[6] J. M. Bonilla, M. S. Valarezo, y M. A. Guerra, «WIP: Unannounced Tests and Examinations to
maps as a tool for making connections than for knowledgeapplication across the levels of courses.Finally, the text data from the survey were analyzed using the GPT-4 model. The studentcomments were predominantly positive, which was also reflected in the quantitative responsesfrom the survey discussed earlier. The GPT model was utilized to generate suggestions forimproving the assignment based on the open-ended comments from the students. The suggestionsincluded the following: • Introducing concept maps as in-class, group activity to help students better understand the (a) (b)Figure 2: Progression of the students’ concept maps throughout the semester. (a
of the author and do not purport to stateor reflect the position of the United States Government or any agency thereof, including the UnitedStates Military Academy, the Department of the Army, or the Department of Defense.References 1. L. T. Eby, T. D. Allen, S. C. Evans, T. Ng, and D. Dubois, “Does Mentoring Matter? A Multidisciplinary Meta-Analysis Comparing Mentored and Non-Mentored Individuals”. Journal of Vocational Behavior, 72(2), 254-267, 2008. https://doi.org/10.1016/j.jvb.2007.04.005 2. W. B. Johnson, L. L. Behling, P. Miller, and M. Vandermaas-Peeler, “Undergraduate Research Mentoring: Obstacles and Opportunities”, Mentoring & Tutoring: Partnership in Learning, 23(5), 441
acknowledge meaningful program contributions from Drs. Jaclyn Duerr, Joel Brown,David Artis, Dmitriy Kalantarov, Octavio Ortiz, Truong Nguyen, and Olivia Graeve.References[1] M. H. Duggan and J. W. Pickering, “Barriers to Transfer Student Academic Success and Retention,” J. Coll. Stud. Retent. Res. Theory Pract., vol. 9, no. 4, pp. 437–459, Feb. 2008, doi: 10.2190/CS.9.4.c.[2] J. G. Mikell and W. J. Davis, “Personal support and its impact on the mental health of first‐generation and transfer students,” New Dir. Teach. Learn., vol. 2022, no. 171, pp. 37–45, Sep. 2022, doi: 10.1002/tl.20515.[3] C. J. Matyas, K. A. Stofer, H. J. L. Lannon, J. Judge, B. Hom, and B. A. Lanman, “Despite challenges, 2-year college students benefit
. United States’ ProgramsIn the United States, study abroad programs are dependent on individual universities, and are notpublicly funded. Universities can choose what they are willing to offer, and what universitiesabroad they partner with. In the 2021-2022 academic year, 188,753 students participated in a studyabroad program [9]. Out of all students, more than two-thirds of students chose to study abroad inEurope, followed by Asia and Latin America. Over 83,000 students study in just five Europeancountries: Spain, Italy, the United Kingdom, France, and Ireland [10]. b. Europe and the United StatesEurope has developed a formidable study abroad program through the Erasmus+ coalition, whichhas allowed many European students to undergo
]. Available: https://ncses.nsf.gov.[2] C. Riegle-Crumb, B. King, and Y. Irizarry, “Does STEM Stand Out? Examining Racial/Ethnic Gaps in Persistence Across Postsecondary Fields,” Educational Researcher, vol. 48, no. 3, pp. 133–144, 2019. Doi: https://doi.org/10.3102/0013189X19831006.[3] G. A. Garcia, A.-M. Núñez, and V. A. Sansone, “Toward a multidimensional conceptual framework for understanding ‘servingness’ in Hispanic-serving institutions: A synthesis of the research,” Review of Educational Research, vol. 89, no. 5, pp. 745-784, 2019. Doi: https://doi.org/10.3102/0034654319866265.[4] F. M. Connelly and D. J. Clandinin, “Narrative Inquiry,” in Handbook of Complementary Methods in Education Research, 3rd ed., Routledge, 2006
scholarly production: How great is the impact?" Scientometrics, vol. 105, pp. 1809–1831, 2015.7. R. Thomopoulos, S. Destercke, B. Charnomordic, I. Johnson, and J. Abécassis, "An iterative approach to build relevant ontology-aware data-driven models," Information Sciences, vol. 221, pp. 452-472, 2013.8. N.F. Noy and D.L. McGuinness, "Ontology development 101: A guide to creating your first ontology," Stanford University, 2001. [Online]. Available: https://corais.org/sites/default/files/ontology_development_101_aguide_to_creating_your_fir st_ontology.pdf9. A.L.A. Menolli, H.S. Pinto, S.S. Reinehr, and A. Malucelli, "An incremental and iterative process for ontology building," in ONTOBRAS, Proceedings of the 6th Seminar on Ontology
tasks. This camerauses IFM Vision Assistant software for setting parameters and logic.5. Experimental Setup and ResultsFigure 8 demonstrates the layout of the work cell designed in SOLIDWORKS and the finishedwork cell. All the wiring and other connections are safely set up under the platform for safety andpresentation. Based on the limits provided by ISO standard 15066 guidelines, a protection cagethat could be easily set up and taken down would be a cheap viable option to satisfy safetyrequirements. (a) (b) Figure 8. (a) the layout of the designed work cell and (b) the finished work cell.Cooling time of the part on the printer is critical to the timing of lab
novel capstonedesign projects derived from a summer clinical immersion experience [2], [3]. Przestrzelski, B.,et al., paired a clinical needs-finding immersion rotation with an internship at a technologytransfer office [4]. Pal, S., et al., reported on a program focused on Rehabilitation Engineeringand incorporated a Summer Immersion term for students between their 3rd and 4th years [5]. Byfar the most common method of connecting to engineering practice was the exercise of “needsfinding.” This function is an essential part of the Biodesign and innovation cycle, and we electedto focus our program development here, as well.In an effort to improve the impact of the “needs finding” exercise during clinical immersion,programs take a variety of
increased concern around disclosing raceamong applicants after the ban of affirmative action.2 Race notations: A – Asian, B – Black, C – Caucasian, H – Hispanic, I – American Indian, P – Pacific Islander orAlaskan NativeWe also examined the race composition of the two graduate computer science degrees offered bythe university. Among the underrepresented minority groups (URMs), we observe a decline inthe percentage of applicants who reported race as Black by 12.8% and Hispanic by 17.9% for theMS degree. However, for the PhD degree, the increasing trend of students reporting race asBlack continues, with the percentage increase changing from 11.3% to 13% in the 2022-23 and2023-24 application cycles, whereas there is a decline in Hispanic. When
growing department has made it impossible forany individual instructor to teach all the students we have. As more instructors were added to theteaching rota, we had the unique opportunity to examine how different teaching styles impactedstudent outcomes.During Fall 2024, three people taught Statics: instructor A (Anna Howard) who had been teachingall the sections fall-and-spring during 2008 - 2022, instructor B (Greg Watkins) who was new to NCState University but with 29 years of prior teaching experience, and instructor C (Nicholas Garcia)who was a graduate student and a teaching mentee for instructor A with significant familiarity withthe flipped class and materials.All instructors agreed to use the same weekly quizzes and exams. These exams
, incorrectly identifying thecircuit as a series RLC circuit. (ChatGPT-4o had similar errors of treating parallel circuits asseries circuits for multiple times in this study.) All the rest of calculations were followed withthe incorrect circuit analysis. 6 Figure 5: ChatGPT interpreted the circuit as LRC in series, and calculated the equivalent impedance in series by substituting numerical values with appropriate unit conversions (See A and B). The error in circuit analysis was propagated down throughout the calculations.Category 5. Accuracy in the use of equations and numerical calculations.Table 1 shows the performance of ChatGPT-40 measured by the