distributions, normality, separability,and strong correlations within the dataset. For this module, students were shown the process ofEDA using the canonical “Iris Setosa” dataset, and were then encouraged to explore the conceptusing a dataset of concrete mix designs (Figure 2). (A) (B)Figure 2. Interactive exploratory data analysis on the properties of concrete, and their correlationwith concrete compressive strength. A) histograms showing admixture quantities in kg/m3 on thex-axis against their frequency of occurrence on the y-axis. The number of bins is controllable by the user to allow visualization of distribution parameters. B) User driven visualization of the
metacognitive strategy use during problem-solving. The research questions,with a focus on both student learning and evaluation of the project, are as follows: 1) What do engineering students learn in relation to problem-solving and metacognitive skills through a think-aloud and peer review project in an introductory engineering course? a) What problem-solving strategies do students use when conducting a think-aloud in an introductory engineering class? b) What strategies are students learning from the peer review process of a think-aloud recording? 2) In what ways can the multi-week peer review problem-solving project be strengthened? a) What benefits are students
hardware and software (Are they ready?) b) Student attitudes toward using Tinkercad (Was it helpful?) c) Instructor observations and experiences (Is implementation hard? Do students benefit?) d) Any differences between the two institutions in terms of student preparedness and attitudesIn our previous report [9], we have shown that most students have little background in eithercircuit design, hardware, or programming. However, there is a good number of students who arevery confident in their abilities in these areas, which means that we have to accommodate a widerange of backgrounds and preparation to be sure to keep all students engaged. We have alsofound that students liked the Tinkercad software, but the sample was small. In this
-cognitive engagement patterns, likely due to its token-wisebidirectional processing, which enables richer contextual representation of input features.(a) Performance of BERT-base and Llama 3.1 (b) Performance of BERT-base and Llama 3.18B on Non-Cognitive Data. 8B on Non-Cognitive + Background Data.Figure 1: Comparison of performance on Non-Cognitive Data (left) and Non-Cognitive + Back-ground Data (right) using BERT-base and Llama 3.1 8B.[RQ2]: To what extent does incorporating student background data alongside non-cognitivefeatures in students’ LE data enhance the accuracy of forecasting their lecture-basedengagement? To address RQ2, we evaluated the impact of integrating background data (NC+B)on the
which force components do and do not cause a moment about the given point. a. Ability to recognize vertical forces that cause moment. b. Ability to recognize horizontal forces that cause moment. 2. Find the moment arm distance for each force component. 3. Determine the direction of each moment of force. 4. Add to find the resultant moment. Figure 1. Exam 1 problem on moments of forces.The errors identified for each of the above skills are summarized in Table 1 below. Minorcalculation errors were not included in the analysis. Table 1. Errors identified for Exam 1 problem on moments of forces. Fundamental Skill Errors Identified
Paper ID #47606Problem-Based and Project-Based Robotics Engineering Program: An IntegratedApproachDr. Franc¸ois Michaud, Universite de Sherbrooke Franc¸ois Michaud, Ph.D., is an engineer and full professor in the Department of Electrical and Computer Engineering at the Universit´e de Sherbrooke, in Qu´ebec Canada. He is the founding director of the Bachelor of Robotics Engineering Program (2017 - 2022) at the Universit´e de Sherbrooke, the first and only one in Canada. He is also a co-founder of Robotique FIRST Quebec (2010 - ).´Elise Richard-B´edard, Universite de Sherbrooke ´ Elise Richard-B´edard is an engineer and
two main steps.First, the registered point cloud data from RealWorks is exported to Recap Pro. This step iscrucial as it converts the point cloud data into a format compatible with Revit. Figure 4 illustratesthe (a) exterior view and (b) interior view of the scan in Recap Pro. Second, the point cloud datafrom Recap Pro is imported into Revit, where it can be viewed in different perspectives, such asplan view, elevation view, and cross-section view. (a) Exterior View (b) Interior View Figure 4 Imported Point Cloud in RecapFigure 5 presents four distinct perspectives: (a) a plan view, (b) an elevation view, (c) crosssection A, and (d) cross section B. These views can
Level ABET 1. Technical Core an ability to apply knowledge of Ability (3) a mathematics, science, and engineering 2. Experiment an ability to design and conduct Ability (3) b experiments, as well as analyze and interpret results 3. Design an ability to design a system, component, Ability (3) c or process to meet desired needs 4. Multidisciplinary an ability to function on multi- Ability (3) d disciplinary teams 5. Engineering an ability to identify, formulate, and solve Ability (3) e Problems
collaborative entrepreneurship competencies should be integratedinto the curriculum. Incorporating specific subjects that target these competencies within variouscourses will enhance students' knowledge, while ensuring lathat entrepreneurship skills aredeveloped throughout their education.BIBLIOGRAPHY[1] Moscoso, B. E., and Fernández, C. J., 2023, “Modelo pedagógico para desarrollar competencias colaborativas de emprendimiento en estudiantes de administración de empresas en una universidad del Ecuador, 2022,” Ciencia Latina Revista Científica Multidisciplinar, 7(1), pp. 479–499. https://doi.org/10.37811/cl_rcm.v7i1.4405.[2] Moscoso, B. E., and Guerra, M. A., 2024, “WIP: Developing Collaborative Entrepreneurship Competencies for
pertinentto broaden the scope to examine the extent to which short-cycle programs in othernational contexts can be relevant.LimitationsLimitations of the work reported in this study include (a) the volunteer or conveniencenature of the sample, wherein students with certain characteristics (e.g., courage,curiosity, time) were more likely to volunteer than others, and (b) the language barriersthat necessitated having multiple interviewers and transcribers and led to someinconsistency in probing and/or depth of conversation from one interview to the next.This variance in interview procedures rendered a data set viable for thematic coding butweakly suited to phenomenological analyses (d) as one author had taught ten of theparticipants, this previous
shows a student preparing for the competition where the drone was controlled by aphone app. Figure 3 Student preparing drone (left) for the competition with a phone-app controller (right).Figure 4 shows photos of drones during the competition just after taking off. The first day ofcompetition was the last day of class on a Thursday afternoon on a clear but cold day. Figure 4 Drones just after takeoff.Figure 5a shows an example of a drone in flight and Figure 5b shows an example of a dronegetting ready to drop its payload. Figure 6 is a photo of students attaching a new payload on thebottom of their drone, just after dropping a payload. (a) (b
limited to the students enrolled into 3-credit hour College Algebra in Fall 2021, Fall 2022,and Fall 2023. This included 1194 students who used MLM in Fall 2021, 1432 students whoused MLM in Fall 2022, and 1608 students who used ALEKS in Fall 2023.To assess the impact of transitioning to ALEKS, we analyzed pass/fail rates across differentdatasets (Fall 2021, Fall 2022, and Fall 2023). A passing grade was defined as earning an A, B,or C, while a failing grade included D, F, or W. Additionally, we examined pass rates and gradedistributions of students who advanced to Precalculus and University Chemistry I in thefollowing Spring semester. This analysis helped determine whether differences in their algebraonline platform influenced performance in
\textit{Decision and Game Theory for Security: 8th International Conference, GameSec 2017, Vienna, Austria, October 23-25, 2017, Proceedings} (pp. 213-233). Springer International Publishing. [7] Seo, S. H., Lee, B. H., Im, S. H., \& Jee, G. I. (2015). Effect of spoofing on unmanned aerial vehicle using counterfeited GPS signal. \textit{Journal of Positioning, Navigation, and Timing}, \textit{4}(2), 57-65. [8] Khan, S. Z., Mohsin, M., \& Iqbal, W. (2021). On GPS spoofing of aerial platforms: a review of threats, challenges, methodologies, and future research directions. \textit{PeerJ Computer Science}, \textit{7}, e507. [9] Gaspar, J., Ferreira, R., Sebastião, P., \& Souto, N. (2018
Xiaoye Michael Wanga, Jackie Liub, Timothy N. Welsha, Ariel W Chanb,* Faculty of Kinesiology & Physical Education, University of Toronto a b Department of Chemical Engineering and Applied Chemistry, Faculty of Applied Science and Engineering *corresponding author: ariel.chan@utoronto.ca AbstractThe Unit Operations Laboratory (UOL) provides chemical engineering students with hands-onexperience by applying engineering and science concepts to industry-scale equipment. The traditionalphysical lab environment has several limitations that hinder its effectiveness as a comprehensiveteaching tool
, subjective, differential hiring / Adjunct, Lecturer, Assistant Prof C, E promotion guidance Take credit for others work Adjunct C, E Control, interrupt, micromanage Assistant Prof C Ignore / exclude Lecturer, Assistant Prof C, D Insult / disrespect Research center dir, Assistant Prof B, D, E Treat differently based on position Research center dir, Adjunct B, C, D Insult / surprise at smartness PhD student, Lecturer, Assistant Prof A, C, E Misrecognition of others
algorithm is a flexibleend-to-end approach for information transcription.Transcribing slides to EnglishFor further accessibility, translating LaTeX into English through spoken Math systems wasexplored with the Speech Rule Engine [11] and MathJax [9]. These models can translate LaTex totwo different spoken Math systems: MathSpeak and ClearSpeak. MathSpeak focuses on conciselanguage while ClearSpeak focuses on more natural language. For example the LaTex of abwould give the output "a Superscript b" with the MathSpeak domain and "a to the b-th power"with the ClearSpeak domain. This enables further accessibility to Mathematical material throughverbal methods.We also looked into using Large Language Models (LLMs) to transcribe diagrams and
with guidance and feedback from theirproject sponsor, faculty advisor, and the capstone instructor. At the end of the spring term,project teams present their results, write a report, and participate in a poster session. B. CornerstoneAs discussed in the introduction, students frequently were unprepared for this complex teamproject, having had little to no team project experience. For this reason, we introduced thecornerstone project in 2018 to provide intermediate project experience before their senior year[2],[3]. The cornerstone sequence consists of two classes (ECE 211 and 212), preferably takenfall and winter terms of the sophomore year, but also offered in compressed form in summerterm for transfer students. These classes have two
session. This schedule gave studentsmany opportunities to find an office hour session that worked within their schedule.MethodologyA two-part approach was used in this study to observe the impact of teaching fellows: recordingstudent attendance at TF office hours and performing an end-of-course anonymous survey. Forthis study, two professors with two sections of EGR 1301 were observed. Professors 1 and 2required the “A” section of the class to attend at least two TF office hours, one before each of thecourse’s two midterm exams, and did not require the “B” section to attend office hours. Classes1A and 1B had 28 students (n=28), 2A had 27 students (n=27), and 2B had 29 students (n=29),yielding a total sample of 112 students. The “A” Sections were
justice-oriented design process in the future.Overall, the pedagogical technique shifted mindsets towards justice. Table 4 summarizes themeasures to evaluate the efficacy for each participant that have been presented in this section,including participants’ preference, and demonstrated mindset shifts. Twelve of the participants(63%) have at least five of the seven measures, and only 1 participant (5%) has less than two. Table 4: Summary of reflective pedagogical technique ParticipantDoes the participant: a b c d e f g h i j k 1 m n o p q r s1. Demonstrate understanding of justice mindset2. Revise any
,” 2024.[4] A. A. D. BIA, “A creativity based goal modeling approach for accessibility of neurodivergent individuals,” 2023.[5] E. Kokinda, M. Moster, P. Rodeghero, and D. M. Boyer, “Informal learning opportunities: Neurodiversity, self-efficacy, motivation for programming interest.,” in CSEDU (2), pp. 413–426, 2024.[6] C. Bourke, “Introduction to git,” 2015.[7] B. K. Ashinoff and A. Abu-Akel, “Hyperfocus: The forgotten frontier of attention,” Psychological research, vol. 85, no. 1, pp. 1–19, 2021. 5
. Thiry, “Advising from community college to university: What it takes for underrepresented transfer students in STEM to succeed,” Community Coll. J. Res. Pract., vol. 47, no. 9, pp. 582–601, 2023.[2] B. W.-L. Packard, J. L. Gagnon, O. LaBelle, K. Jeffers, and E. Lynn, “Women’s experiences in the STEM community college transfer pathway,” J. Women Minor. Sci. Eng., vol. 17, no. 2, 2011.[3] E. Dunmire, A. Enriquez, and K. Disney, “The Dismantling of the Engineering Education Pipeline,” in 2011 ASEE Annual Conference & Exposition Proceedings, Vancouver, BC: ASEE Conferences, Jun. 2011, p. 22.1443.1-22.1443.17. doi: 10.18260/1-2--18945.[4] M. Ford, A. Dhanji, K. G. King, J. Sheng, S. Roth, and E. Hadnagy
. Our graduate-level certificates are designed tobe completed 100% online, with both asynchronous and synchronous (remote) time, so studentsget the benefit of individual learning and class interactions without having to be on campus.2. Prioritizing high-quality and relevant program designWe prioritize program quality and relevance by (a) engaging our world-renowned faculty expertsto design and teach the courses (the “who”) and (b) focusing the curriculum on cutting-edgeknowledge and skills that are sought after by employers and/or hard to obtain (the “what”).The faculty involved in our online programs are the same faculty who design and teach in ourin-person, full-degree programs. They are often designing online certificate courses based on
, 2006.[13] M. D. Koretsky et al., "For Systematic Development of Conceptests for Active Learning," in EDULEARN19 Proceedings, 2019: IATED, pp. 8882-8892.[14] A. S. Bowen, D. R. Reid, and M. Koretsky, "Development of interactive virtual laboratories to help students learn difficult concepts in thermodynamics," in 2014 ASEE annual conference & exposition, 2014, pp. 24.426. 1-24.426. 26.[15] M. A. Vigeant, M. J. Prince, K. E. Nottis, M. Koretsky, and T. W. Ekstedt, "Hands-on, screens-on, and brains-on activities for important concepts in heat transfer," in 2016 ASEE Annual Conference & Exposition, 2016.[16] J. Cook, T. Ekstedt, B. Self, and M. Koretsky, "Bridging the Gap: Computer Simulations and
% (fall 2024) and 54% (fall 2023) of students stronglyagreed or agreed. No students (fall 2024) and 21% (fall 2023) of students strongly disagreed ordisagreed. These results indicate that the implemented adjustments in the difficulty and format ofthe SGAs lead to a considerable improvement in students’ perception of the SGAs.Appendix B lists students’ responses to three open-ended questions: (1) “what did you like bestabout grading your own homework?” Most of the students listed positive comments regardingfinding their own mistakes, knowing the answers beforehand, trying to correctly solve theproblem with their classmates. One student’s comment summarizes the benefit of the adjustmentimplemented in fall 2024 by stating “I really love these self
Anisotropic Composite Structures Under Extreme Multi-Axial Mechanical and Thermal LoadsParticipants spend the bulk of their time conducting research, but 4-8 hours each week are reservedfor professional develop activities, additional training on multiphysics software, and industry sitevisits, for example as seen in Figure 1. UCF hosts several REU sites, so participants also engagein social activities with the other students conducting summer research experiences to provide astronger social bond beyond the HYPER cohort. Other groups at UCF, like the Office of a) b) c) d) e) Figure 1: Students participate in social activities like escape rooms (a
-improve-communicating-science-in-engineering-students[2] J. L. Klosky, S. M. Katalenich, B. Spittka, y S. F. Freyne, «Inspiring Student Engagement through Two-Minute Follies», presentado en 2014 ASEE Annual Conference & Exposition, jun. 2014, p. 24.762.1-24.762.29. Accedido: 26 de noviembre de 2024. [En línea]. Disponible en: https://peer.asee.org/inspiring-student-engagement-through-two-minute- follies[3] R. B. Cassin, «Leadership and Communications in Civil Engineering: Past, Present, and Future», Leadersh. Manag. Eng., vol. 3, n.o 3, pp. 145-147, jul. 2003, doi: 10.1061/(ASCE)1532-6748(2003)3:3(145).[4] R. Toscano, M. A. Guerra, S. Durán-Ballén, y B. M. Valarezo, «WIP-Development of Critical Thinking in AEC
Q Quest B 7 C 5: toki pona Translator 8 R Collections of Data 6: Genetics Analysis Retake Quest A / B 9 Q Quest C 10 C 7: Movies I: Pre-Processing 11 R Files & More Movies II: Structured Data Retake Quest A / B / C 12 Q Quest D 13 C 9: Movies III: Data Visualization 14
space, it cannot be fully describedby any single process. Gajary et al. aimed to broaden the scope of convergence research (as anobject of study) by framing it as a systemic phenomenon that itself emerges from semi-autonomous systems-level interactions and transformations across different knowledge domains.Specifically, their formulation includes three ancillary systems that are each linked by processesof “inter-system feedback and synthesis” [5 p.10]. These systems are (a) collaboration systems, 4(b) inquiry systems, and (c) contextual systems—representing the interactions of (a) people, (b)research conduct, and (c) the social and physical
% 37 2.60 100.% 94.7 11.56 10.00 100 15 100 100 A 1 35% 27 06RL 1.00 81.5% 85.2 10.01 5.88 100 13 100 100 A 2 100% 5 1 91% 60 07BM 1.85 99.8% 56.9 5.97 5.69 100 28 100 77.03 A 2 100% 8 08AP 1 96% 60 1.15 73.4% 118.9 13.42 19.19 80 39 91.04 84.03 B 09LT 1 61% 60 1.25 62.4% 179.6 17.72 15.69 85 28 0 0 F 10MT 1 90% 12 2.05 100.% 23.9 3.30 4.38 100
. https://doi.org/10.1080/03043797.2024.2303023 Baura, G., & Kallemeyn, L. (2019). An integrated social justice engineering curriculum at Loyola University Chicago. Bielefeldt, A. R. (2023). Integration of Diversity, Equity, and Inclusion Topics into a First-Year Introduction to Civil Engineering Course. Bielefeldt, A. R., & Silverstein, J. (2021). Environmental Justice and Equity Issues: In Our Backyards and Beyond. Bilgin, B. (2024). Fostering Diversity, Equity, and Inclusion in Engineering Education: A Case Study of UIC Chemical Engineering Department. Brit Shields. (2023). Justice