of a single point rubric utilizing some of the South CarolinaGrade 2 Mathematics Standards is shown in Table 1. There have been other researchpublications documenting the use of single point rubrics, or similar rubric models, in college orprofessional training settings. [13]–[17]In its purest form, the rubrics are used for formative assessment, either by the instructor or apeer, rather than summative assessment, however some online discussions revolve around settinga “meets expectations” or “standards met” grade at a 3 of 4 allowing work that “exceedsstandards” to earn a 4/4. In this way, a single point rubric can be adapted to a traditional gradingschema (awarding A, B, C, etc.) without requiring the instructor to document each
psychometric characteristics, such as their validity and reliabilityevidence and their item characteristics. Finally, we explored the application of conceptinventories by introducing three different application indexes (Alpha, Beta, and Gamma), whichwere used to quantify the degree to which each inventory has been used in the current literature.Therefore, the following research questions guided this study: (a) What concept inventories havebeen developed for circuits education?; (b) What content/topics in circuits were addressed in theconcept inventories?; (c) What were the psychometric characteristics of each concept inventory?;and (d) To what extent did concept inventories contribute to circuits education and research?II. Background LiteratureA
) VIN GND GND 5V D9 D10(b)Figure 5: The electrical wiring, shown via (a) the connectivity diagram and (b) a photograph of theunderside of the robot.3 GaitsThe robot moves by simultaneously oscillating the angle of each servomotor in offset waves.Specifically, the servo angles θ1 , θ2 are functions of time as 2π θ1 (t) = a cos t + c1 (1) d
up the number of simulated users and capturehow response times, error rates, and system stability deteriorate at various load thresholds.Figures 1b and Figure 1c, shared with students, provide an example analysis. (a) Game Overview (b) Load Time (c) Errors Figure 1: C300 Module4 C400: Cultivating Performance Awareness in Software Metrics and EstimationAt the core of the new module are two related concepts: performance issue reports and return oninvestment (ROI) analysis. Performance issue reports document system inefficiencies such asslow response times, excessive resource consumption, or poor scalability. Zhao et al. proposedthe use of heuristic
recent article about an application of the nanoimprint lithography (NIL) technique. List: a. type of NIL technique used b. what materials are used c. resolution/measured properties d. specific application Hand in a maximum one-page typed summary and a copy of the article. You are expected to present your finding to the class.h) Classroom presentation and discussion includes the results in the lab portion of the NILmodule and the literature search for the NIL application. Students share their findings with therest of the class. This type of activity enhances both writing and oral technical communication.The course activities are well aligned with the ABET general criteria for engineering
life experiences.In this work, the authors describe the implementation of a pilot at University of Detroit Mercy ofthe Science & Engineering Equity Development (SEED) program to emulate these exemplarprograms, but in a more financially sustainable manner. Detroit Mercy is an independent,master’s comprehensive university situated in an urban context that has limited resources inmuch the same manner as other institutions that serve primarily undergraduate studentpopulations. Elements of the SEED program include: (a) thorough integration of three industrialcooperative internships, (b) a 7-week non-residential summer bridge program, (c) bi-weeklygroup counseling sessions for first-year students, (d) and intentional bi-weekly cohort
about their understanding, intended application, and future utility of thecommunication strategies taught in the module. Students answered the following reflectionquestions: 1) What did you learn from the module? 2) How will you apply what you learnedwhile writing survey questions and conducting interviews? 3) How can strategies forcommunication that you learned in this module serve you in a) this course? b) your major? andc) your future personal and professional life?3.3 Data AnalysisDeveloping RubricThe categories of critical reflection, perspective shift, and application of new perspectives wereselected for the rubric because they aligned with the components of Social Perspective Taking(SPT) the cognitive, affective, and motivational
. Table 3: Response generation to programming related questions Query Query Classification Response Write code for nth number of Code Sure! Here is a step-by-step algorithm to find the nth number of the Fibonacci Fibonacci sequence sequence: code 1. Define a function that takes an input `n` which represents the position of the Fibonacci number in the sequence. 2. Initialize two variables, `a` and `b`, to 0 and 1 respectively. These will
accessible to instructors is beneficial to facilitate within semester adjustments and more detailed analyses. • Bar Chart: The bar chart shows students' individual scores and progress in learning across each CD. Raw scores from Gradescope are processed further to produce these plots visible in the dashboard that are useful to track individual student’s progress across individual requirements. If the class statistics are useful for overall class adjustments, these bar charts are helpful to identify specific students who need further support and to track the impact of such personalized interventions across the semester. • Radial Plots (A, B, and C): Finally, the radial plots on the bottom part of the
Contexts: Conceptualization, Assessment, and Association With Psychopathology,” Journal of Personality and Social Psychology, 1991. [8] M. W. Enns and B. J. Cox, “The nature and assessment of perfectionism: A critical analysis.” in Perfectionism: Theory, research, and treatment., G. Flett and P. L. Hewitt, Eds. Washington: American Psychological Association, 2002, pp. 33–62. [9] M. Moroz and D. M. Dunkley, “Self-critical perfectionism, experiential avoidance, and de- pressive and anxious symptoms over two years: A three-wave longitudinal study,” Behaviour Research and Therapy, 2019.[10] L. A. Terry-Short, R. G. Owens, P. D. Slade, and M. E. Dewey, “Positive and negative perfectionism,” Personality and Individual
considered period, b) public institutions that had not hada female leader during the considered period and have not had an ADVANCE initiative, and c)public institutions that did not have an initial critical mass but had an ADVANCE initiative [4].From our results, since the paths towards increasing participation included those that did not haveADVANCE initiatives, we interpret that there are additional theoretical considerations that, ifunderstood, could bring a better grasp of alternative strategies, as well as barriers to achieving thegoals of ADVANCE, and other BPIs. In this research we explore such potential.Study DesignThe first stage of our project is this observational and retrospective study, in which we rely mainlyin publicly available
Figure 2 (b) and (c), most of thestudents (64%) had taken a course on sustainability, while only 35% had taken a course oncompressed earthen masonry. Figure 2. Demographic information of students Proceedings of the 2025 ASEE Gulf-Southwest Annual Conference The University of Texas at Arlington, Arlington, TX Copyright © 2025, American Society for Engineering Education 8Sustainability Knowledge, Learning Confidence, and Relevance to CareerThe findings of the study also show that the perception of students’ knowledge and confidence aboutearthen masonry as a sustainable material generally increased while
for effective filtration, a critical function for maintaining normal blood composition. To visualize the way changes in arteriole diameter impacted flow and pressure, the device needed to be manipulatable with some kind of visual representation of changes in pressure throughout the device. Students were given a brief lecture on the fluid dynamics of the kidney, a brief description of what Dr. Price wanted to see in the machine and were then left to create the mechanism with as many features as possible. After extensive research, the team concluded that there is no similar device in existence. 13Appendix B
the squares of the protective grid and resided just downstream of each square of the flow-straightener grid. While obtaining the upstream measurements, the turbine blades were heldstationary to gain access to the flow-straightener grid. Figure 2 shows the point of measurementfor the upstream and downstream locations. (a) (b)Figure 2: Pitot tube at the (a) upstream and (b) downstream locations. The second goal of this work was to measure the rotational power of the blades based onthe torque and rotational speed. The torque is calculated using Equation (3). 𝜏 = 𝐹𝑟 (3)where τ is
constant τ is given by: 𝑎𝑇𝐹 = 𝜏𝑠+1 for a step input of magnitude b,a. Use the final value theorem to determine the steady-state response of the system.b. Determine the complete response of the system using Laplace transformation.c. Calculate how close the system's response is to the steady-state value at times 𝑡=𝜏 and t=4τ. Express the response as a percentage of the steady-state value.In this problem, students engage directly with the mathematical representation of a first-ordersystem without prior lecture-based instruction. Instead of being told the exponential time responseor its key properties in advance, they discover the significance of the time constant (τ) bycomputing the system's response at t = τ (63%) and t = 4τ (98
‘Error,’” presented at the ASEE Annual Conference and Exposition, 2024.[7] Z. del Rosario, J. Ryu, and E. Saur, “Targeting Consequences of Variability as a Data Science Resource,” presented at the IASE Roundtable Conference, Auckland, NZ: IASE, 2024.[8] Z. del Rosario, J. Ryu, and E. Saur, “A Mixed-Methods Study of Statistical Thinking in Engineering Practice,” presented at the ASEE Annual Conference and Exposition, 2024. [Online]. Available: https://peer.asee.org/46755[9] S. H. Kerns and J. B. Wilmer, “Two graphs walk into a bar: Readout-based measurement reveals the Bar-Tip Limit error, a common, categorical misinterpretation of mean bar graphs,” J. Vis., vol. 21, no. 12, p. 17, Nov. 2021, doi: 10.1167/jov.21.12.17.
. Hinings, D. Logue, and C. Zietsma, “Fields, institutional infrastructure and gov- ernance,” The Sage handbook of organizational institutionalism, pp. 163–189, 2017. [5] E. Chenoweth, Civil resistance: What everyone needs to know®. Oxford University Press, 2021. [6] A. Reuel, B. Bucknall, S. Casper, T. Fist, L. Soder, O. Aarne, L. Hammond, L. Ibrahim, A. Chan, P. Wills et al., “Open problems in technical ai governance,” arXiv preprint arXiv:2407.14981, 2024. [7] R. Søraa, AI for diversity. CRC Press, 2023. [8] T. Gebru and É. P. Torres, “The tescreal bundle: Eugenics and the promise of utopia through artificial general intelligence,” First Monday, 2024. 6
throughout the theoretical model.When it is cited, the influence of time primarily relates to (a) the students’ ability to manage theirtime when they are in college, (b) the time it takes to emotionally and physically make thesecondary-tertiary transition, and (c) time to develop mathematics skills. TABLE III NUMBER OF CITATIONS ASSOCIATED WITH THEMES Citations Theme Codes Percentage Rite of Passage 61 24.4 Affective 15 6.0 Student Autonomy 19 7.6
understanding of the course material. 4.4 4.2 4.1 27 L.) Having the notes and other materials available in advance of class helped me to better use the class-time. 3.9 3.9 3.9 28 Q.) The way this course was taught helped me gain a deep understanding of the material. 4.1 4.0 3.2 16 B.) I preferred the video lectures as compared to live lectures. 1.7 1.9 2.0 20 H.) I preferred the use of the in-class discussion questions as a supplement to a lecture when compared to a lecture without formal discussion questions
more gender balanced than others?," Psychological Bulletin, pp. 1-35, 2017.[3] L. Debs and B. R. Kota, "Gender Differences in Construction Management Students’ Sense of Belonging," Virtual Meeting, 2021.[4] L. Dickson, "Race and Gender Differences in College Major Choice," The ANNALS of the American Academy of Political and Social Science, pp. 108-124, 2010.[5] B. Rapoport and C. Thibout, "Why do boys and girls make different educational choices? The influence of expected earnings and test scores," Economics of Education Review, pp. 205-229, 2018.[6] A. V. Maltese and C. S. Cooper, "STEM Pathways: Do Men and Women Differ in Why They Enter and Exit?," AERA Open, 2017.[7] B. F. Bigelow, A. Saseendran and J. W. Elliot
technology in classes or class projects.LLMs have demonstrated promising performance in code-based tasks. Thus, papers have beenpublished about using LLMs in code-centric classes [6, 7, 8]. Other subjects where LLMs havebeen frequently used in higher education are social sciences, business and management, andSTEM [20]. We are interested in the application of LLMs in an engineering course. In thispaper, since the LLM is answering questions like a teaching assistant (TA) does during officehours, we will refer to it as the AI TA. An AI TA could be useful to students who a) have aconflict with normal office hours or b) are uncomfortable asking questions in office hours or c)are doing homework late at night, when the class instructor and TA are not
://cft.vanderbilt.edu/guides-sub-pages/teaching-outside-the-classroom/.10. Insorio, A. O., & Macandog, D. M. (2022). YouTube Video Playlist as Mathematics Supplementary Learning Material for Blended Learning. European Journal of Interactive Multimedia and Education, 3(2), e02212. https://doi.org/10.30935/ejimed/1249011. How long should a YouTube video be? A complete guide. Teleprompter. (n.d.). https://www.teleprompter.com/blog/how-long-should-a-youtube-video-be12. Phillips, P. B. T. (2024, February 23). Filming a documentary. Rock Creek Productions. https://rock-creek.com/how-long-should-a-documentary-be/13. Sarosh, : Aliya. (2024, December 11). Improve your youtube watch time: Flintzy. Youtube Hacks | Learn & Grow. https
. Variational were used to validate the model's ability to detect pneumoniaAutoencoder fills in the gaps of incomplete records. DAG + efficiently. Future work will proceed with improving data lossBayesian models aid in avoiding overfitting solely based on concealment and extending dataset validation for clinicalimage data. Finally, considering all these Model 2 is more applicability and robustness in a hospital environment.reliable with the problem. V. FUTURE DIRECTIONS REFERENCES Future advancements will focus on refining VAE and BN [1] Rajpurkar, P., Irvin, J., Zhu, K., Yang, B., Mehta, H., Duan, T., Ding, D.,components with
studies could also address the impacts of team dynamics such assize, communication and leadership on the application of requirements tools and evolution [18],[19]. These studies would enable further assessment of the impact of QFD on requirementsevolution in capstone product design.References[1] D. G. Ullman, The Mechanical Design Process, 6th ed. Independence, Oregon: David G. Ullman, 2018.[2] G. Pahl and W. Beitz, Engineering Design: A Systematic Approach, 2nd ed. London: Springer, 1995.[3] B. Morkos, S. Joshi, and J. D. Summers, “Investigating the impact of requirements elicitation and evolution on course performance in a pre-capstone design course,” Journal of Engineering Design, vol. 30, no. 4–5, pp. 155–179
. Plate fin Aluminum Base plate Heating element Superwool insulation Figure 1: Simplified schematics of the setup A B C DFigure 2: Natural convection setup: A. DC power supply B
Paper ID #45756The Case for a Separate FE Exam for Construction Engineering: AddressingCurriculum Discrepancies and Student PerformanceDr. Nahid Vesali, The Citadel Dr. Nahid Vesali is an Assistant Professor in the Department of Engineering Leadership and Program Management (ELPM) in the School of Engineering (SOE) at The Citadel. She joined the program in Aug 2020. She teaches project management, technical planningDr. Mostafa Batouli, The Citadel Dr. Mostafa Batouli is an Assistant Professor of Construction Engineering in the department of Civil and Environmental Engineering at The Citadel. Dr. Batouli received his PhD in
2025 ASEE Northeast Section Conference, March 22, 2025, University of Bridgeport, Bridgpeort, CT, USA. Pedagogy of Artificial Intelligence with Machine Learning and Computer Vision in a Community College Setting Sunil Dehipawala, Guozhen An, Arkadiy Portnoy, Tak Cheung Physics Department CUNY Queensborough Community College New York City USA Abstract—A deployment of artificial intelligence-based (AI- environment would expedite the student research progress. Thebased) examples was
. dynamics within the team. Example sub-questions: Prompt reflection of their role within the a) What’s (not) working well in the mentoring relationship? overall mentoring team. b) What can you do better as a mentee/mentor? Identify strengths and areas of improvement c) What was not helpful or constructive? within the context of team interactions. Document progress and What has the mentee learned or accomplished since the last personal/professional successes with reflection? What helped them learn or accomplish
italicized names are the individuals that were leading that part module or activity.Throughout the morning the student’s had the opportunity to engage in the all the rotating modules,see Figure 2. The students had a unique opportunity to work on a Scanning Electron Microscope(see Figure 2a), Near Infrared Spectroscopy (see Figure 2d), and a Transmission ElectronMicroscope (TEM). The students also had a guided tour through the Arbegast Material Processing& Joining facility (see Figure 2b). A B C D Figure 2: (a) Students viewing the
accessible and enriching opportunity for aspiring young engineers.This work was funded through the NSF Division on Research in Learning Grant Number DRL#1850116. References 1. M. F. Bugallo and A. M. Kelly, "Engineering Outreach: Yesterday, Today, and Tomorrow [SP Education]," IEEE Signal Processing Magazine, vol. 34, no. 3, pp. 69- 100, May 2017, doi: 10.1109/MSP.2017.2673018. 2. M. F. Bugallo, K. Sheppard, and R. D. Bynum, "Educating engineers of the future," 2012 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Kyoto, Japan, 2012, pp. 2749-2752, doi: 10.1109/ICASSP.2012.6288486.3. H. Wang, K. Dinota, and M. B. Bugallo, "Traffic lights engineering