mass of the rigid body. Question 15 Figure 2: Question 15 from DCI This question tackles the concept of force acting on a body and how a constant force might affect the path of the body.General Performance ResultsGeneral scoring of student answers to these two questions for before and after a dynamics course areindicated in Figure 3 below. For question 11, about rigid body motion with a force applied, indicates onlyabout one-third of the students answered correctly. The most common distractor answers were B and D. Pre-Course Results Post-Course Results c
to first attain l2 . (a) If l1 andl2 are placed in one course, and l3 and l4 in the other, a prerequisite constraint is created betweencourses v1 and v2 , and the structural complexity of the pattern is 5. (b) If l2 and l3 are placed in onecourse, and l1 and l4 in the other, then all prior required learning is contained within course v1 , nocourse-level prerequisites are required, and the structural complexity of the pattern is 2.complexity of a curriculum. Furthermore, if we consider the same engineering program at differ-ent institutions, we will find there is often significant variation among the structural complexitiesof the curricula offered by these programs. As mentioned previously, those with lower structuralcomplexity will have
maintaining and repairing the machine, the workers must now be familiar with four different automation systems that are likely to use different names and conventions to describe their operation. (Wait vs WAIT vs WAITING vs WAIT_A could be describing the same overall function in the controller programs.) In a troubleshooting scenario, the technician must now learn to connect and translate terms which diverts their effort from repairing the system. b. The topography of the system demonstrates that the conveyor language is being translated for use by the robot, then re-translated and transmitted forward to the outfeed and empty container
Samplemodes during operation [4], the handheld tool will materialaccomplish this by way of removable pieces (the central Strain gaugesteel shaft and pins) and interlocking elements (slots and areaholes in the central steel shaft and keyed features in the Handleshandles). The removable central steel shaft with a machinedslot and removable pin are shown in Figure 4(a). Figure 4(b)shows the other end of the central steel shaft with amachined hole and another removable pin. The pins couplethe handle and sample material to the central steel shaft. Thekeyed rectangular feature shown in Figure 4(c) couples thehandles to the sample material.When the
student’s answers were recorded in a dichotomous format,meaning that answers were recorded as either correct or incorrect. Correct answers from eachstudent were summed to form a raw score and converted to a percentage form. Of the 111students who took the TMCT, 108 completed all 12 items, including 63 who completed subtestA and 45 who completed subtest B. Missing data were assumed incorrect. Independent samples ttests were performed between groups to assess equivalence of means. All calculations wereperformed using Microsoft Excel 2019 or Jamovi 2.3.21 [37].Internal consistency of the TMCT with a sighted population was assessed using both Cronbach’salpha and McDonald’s Omega. Cronbach’s alpha is a widely used measure of internalconsistency for
problem. The scoring rubric is: a – complete and correct, b – minor calculation error, c –minor conceptual error, d - major conceptual error, and e – no evidence shown. The total numberof assessment opportunities include five problems during the semester, one at the end of eachmodule, and three additional problems on the final exam making a total of eight problems thestudents are tested on throughout the course. Over the eight assessment opportunities, eachstudent’s demonstration of mastery for each objective is recorded and accumulated. Mastery ofan objective is awarded to a student once they have shown that they can do an objective correctlyfour times. This means that they must do the objective correctly on four different problemsthroughout the
electronics education.Figure 2 shows the comparison of the workstations from both the real physical lab and the virtuallab. (a) (b) Figure 2. (a) A workstation in the real physical lab. (b) A workstation in the virtual lab.3. MethodologiesA. Multi-Model RepresentationIn the process of developing a 3D virtual laboratory, a key consideration is the variety of modelsneeded to simulate instruments and circuit components authentically. This necessity stems fromthe multifaceted nature of virtual lab environments, where objects must not only appear realisticbut also behave and function as they would in a physical lab. To address this, we haveconceptualized three fundamental model types
carewithin their state. One participant, B, is a developmental psychologist with a PhD in psychologyand experience as a preschool teacher. She dedicates 50% of her working time to this project and50% of her time to other projects in the College of Social Work. The second participant, J, is aneducational psychologist finishing a PhD in Educational psychology. He also has experience as aK-12 special education teacher. He works on this project full-time. There is an additional full-time member of the research team who did not participate in this project. While these twoparticipants are education researchers working outside engineering education, they representdisciplines which may be involved on engineering education research teams. Initially, I
is also shownin the Figure 6, below.Fig. 5. Skills involved A-Laser cutting, B-Press fitting, C-Machining, D-Basic electronics, E –3D printing, F- Microcontroller programming and Assembly.Fig. 6. Gantt Chart 7Towards the semester end the students were required to present their projects. Hence one mayadd presentation skills to the above list. This module can aid in helping students measure torsionstress (or the shear stress), resulting from the torque. The shaft is ¼ inch in diameter and the 𝑇𝑟torque (T) is being measured. Using, 𝜏 = where r is the shaft radius and J is the polar 𝐽second
-year institution through guaranteed admission.Participant B:Participant B initially attended a four-year university majoring in business for two yearsbefore reverse transferring. This student attended a 4-year institution with scholarship, somoney as a financial barrier was not a factor for reverse transferring. The original decision toenroll and attend a four-year university stemmed from wanting to explore new environmentsand create distance from their family. Realizing that their institution was lacking in diversityand felt disconnected: “I really liked the school, but I really feel being the minority there.” Inaddition, Participant B wanted to switch majors, and their 4-year institution did not have themajor. Participant B reversed transfer
community members who participatedin the workshop. Figure 2: (A) Artist and community member, Christy Robinson in the process of blowing a glass bubble. (B) High school art teacher Alicia English displaying her glass bubble.A survey for the A+E workshop was conducted with a key focus to ask the respondents thefollowing question. Q1. Did the A+E event increase your understanding of the science behind the training activity?This question has become a foundational question for the A+E outreach activities to self-assessour interactions with attendees. For the A+E one day workshop all of the respondents selected thattheir scientific knowledge was increased by the event.We recognize that the impact the A+E program
, students learning towear safety gear and practice melting and pouring techniques and successful pouring ofaluminum alloy billets. (a) (b) (c) Figure 2. Photographs showing (a) the alloying elements weighed out for addition to the melt, (b) students aretrained and practice in full foundry safety gear prior to pouring their molten alloy, and (c) a student pouring molten aluminum into the mold.Thermomechanical process design and execution requires planning and teamwork to completeeverything in the allotted time period of 3 weeks (with the autumn break period built
discussion starts by explaining the relevance ofspectral analysis in real-world engineering applica�ons. Examples from different engineeringfields, such as telecommunica�ons, signal processing, audio processing, nondestruc�ve tes�ng,medical imaging, and vibra�on analysis, were shared with the students. The module consists oftwo parts, each of which takes one lecture.Lecture one: The fast Fourier transform FFT.This lecture starts by asking the following ques�on:“The data or the waveform is now discre�zed and acquired by the computer or microcontroller. How does one find the spectrum of this discrete data?”Figure 1 illustrates that x(t) is the discrete-�me date with a �me domain spacing of T=1/FS,where FS is the sampling frequency in hertz, Hz. Part b of
, T. M., Bira, L., Gastelum, J. B., Weiss, L. T., & Vanderford, N. L. (2018). Evidence for a mental health crisis in graduate education. Nature Biotechnology, 36(3), 282–284.Farra, A., Anantharaman, A., Swanson, S., Wilkins-Yel, K.G., Bekki, J., Yel, N., Randall, A., & Bernstein, B. (2023). Examining the Role of Institutional Support on International Doctoral Women's STEM Persistence and Mental Health. Journal of Women and Minorities in Science and Engineering.García, S. J. (2018). Living a deportation threat: Anticipatory stressors confronted by undocumented Mexican immigrant women. Race and Social Problems, 10, 221-234.Godin, K., Stapleton, J., Kirkpatrick, S. I., Hanning, R. M., & Leatherdale, S. T
change I would make to the design of the thumb is possible a more effective string box to provide tension on the thumb.Student ArtifactsStudents displayed posters and 3D models during the gallery walk. Figure 1 shows four student artifactsalong with 3D models of the designed product. A B D CFigure 1. Student Posters used during the Gallery walk. A. Pencil gripper prototype. B. Deskorganizer. C. Glasses support. D. Prosthetic ThumbThe student teams detailed the design process and the design for additive manufacturingconsiderations used during the development of the products.Future Work and ConclusionFuture development of
) under one category due to its closeness in definitions [2]; multidisciplinarydiscipline will be referred to as Type II. Specifically, multidisciplinary approach tailors toproblems whose solutions can be analyzed from multiple perspectives (e.g., multiple disciplinaryangles) and can be independently proposed, in part, by the relevant disciplines (e.g., A, B, and Cin Figure 1, bottom left panel). One thing to note is that multidisciplinary collaborations donecessarily draw information and knowledge (hence, exchange of information) from differentdisciplines but do not require an integrated, fused approach [2]. On the other hand, both inter-and trans- disciplinary approaches require an integrated, fused approach that necessitates ashared, well
Lents, N. H., 2016, “Cultivating Minority Scientists: Undergraduate Research Increases Self-Efficacy and Career Ambitions for Underrepresented Students in STEM,” J. Res. Sci. Teach.[8] Watkins-Lewis, K. M., Dillon, H. E., Sliger, R., Becker, B., Cline, E. C., Greengrove, C., James, P. A., Kitali, A., and Scarcella, A., 2023, “Work In Progress: Multiple Mentor Model for Cross-Institutional Collaboration and Undergraduate Research,” American Society for Engineering Education, Baltimore MD.[9] Lopatto, D., Hauser, C., Jones, C. J., Paetkau, D., Chandrasekaran, V., Dunbar, D., MacKinnon, C., Stamm, J., Alvarez, C., Barnard, D., Bedard, J. E. J., Bednarski, A. E., Bhalla, S., Braverman, J. M., Burg, M
:15 am Adaptable Buildings: Designing a Structure for Today and Instructor 1 Tomorrow9:45 am Arrive to Room A Instructor 29:50 am 10 min break Instructor 1, Instructor 210:00 am Costs and benefits of regulating indoor environments Instructure 211:30 am Break for lunch12:45 pm Arrive to Room B/C Instructor 3 and 4 Group A Group B Instructor 3
final circuit, shown in Fig. 1(a).Then, students use a provided kit to house all of their components, which they solder and connectby hand. With a little finagling, everything fits into the box and they have a final product, theinsides of which are shown in Fig. 1(b). (a) (b) Figure 1: (a) Schematic of useless box, (b) physical implementation of useless box.2.1.3 Laboratory Assignment 3: 3 × 3 LED matrixThe third laboratory project involves building a manually-controlled, 3 × 3 LED matrix. This isthe start of the extended project for the term. In this assignment, students learn about persistenceof vision, how large LED matrix displays work, how to use shift registers, and
for which the output is either not known or invalid as “don’tcares.” Don’t cares are highly relevant to both logic design and machine learning.Two common representations of Boolean functions are truth tables and Karnaugh maps, asshown in Figure 1. c d - - - - - 1 0 - a b c d f (a, b, c, d) b 0 1 0 1 1
, and internal pin forces required to calculate the stresses in Phase II. • Phase 2 - Stress Analysis. The stress analysis is carried out using the forces from the equilibrium analysis in Phase I. The stress analysis is limited to pin shear stress, member pull-out shear stress, connection bearing stress, and normal stress in axially loaded members. The pin connection is considered a tight fit with uniform bearing stress and a loose fit with non-uniform bearing stress.We will now summarize Phases I and II, and the detailed solution process can be found inAppendices A and B, respectively.Qualitative AssessmentA qualitative assessment was carried out by using student surveys. We carried out a qualitativeassessment
experimental years.3.2 The Relations of the First-year Students’ Math and Science Preparation and theirPerformance in Statics.The in-depth analysis is conducted to investigate the factors affecting the first-year students’learning in the introductory mechanical engineering course and their relations with theirperformances beyond the course. We have focused on the 62 first-year mechanical engineeringstudents who enrolled and passed MECH 101 in the two experimental years. Based on thestudents’ paths related to Statics, we can group the 62 students into the following four categories: • Group A: Passing Statics with a C or better (n = 35) • Group B: Receiving a C- or DFW in Statics, resulting in a retake (n = 12) • Group C: Planning to take
the multitude of formulas that can describe thesequantities in different situations provide students with a challenging experience of balancingconceptual and procedural knowledge [63], [64]. Thus, we chose these concept questions tounderstand narratives of understanding in short answer responses and provide a large set ofconcepts to train our machine learning algorithms.Figure 1. Student view of CT 1072 (A) and 1073 (B) on the Concept Warehouse. The imageshows the multiple-choice question and the short-answer response field analyzed in this study.The correct answers are in the green boxes.We can visualize the mixing process described in Figure 1 through the representation shown inFigure 2. The enthalpy change in concept question 1072 is zero
also shows the application ofeach major construct. Applications vary from minimizing error and bias in evaluation systems,designing evaluation systems and evaluation settings. Moreover, the theory sets the guidelines onhow to test the reliability of evaluations and how to remove bias and error components from theevaluation results. The following sections will refer to and discuss the theory constructs,hypotheses, theory applications, how to apply the theory in teaching evaluation and how thetheory principles compare to the current teaching evaluation standards.Figure 1: ToR constructs and applicationsRatees’ control and their relationship with ratersThis major theory construct is covered by theorems 1, 3 and 4 and hypotheses 1.a, 1.b, 1.c, 3.a
reported thatbeing a STEM major at graduation was positively correlated with extra credit accumulation [15],indicating that STEM students are more likely to graduate with extra credits. This result can beextended by a quantitative analysis of the rate, and composition, factors influencing extra creditsaccumulated by STEM students in comparison to campus-wide (all) students. As mentioned inSection 1, we pursue this direction through investigation of the accumulation hypothesis.3 MethodologyThe audit tool solves an optimization problem that matches classes to degree requirements in away that maximizes the number of applied credits, subject to the constraints that a) each class ismatched to at most one requirement and b) no excess credits are
errors, in turn, resulted inusers obtaining inaccurate responses. Examples of successful and unsuccessful problem solutionsare included below. Full solutions from ChatGPT are included in Appendix B.• Example problems for which ChatGPT provided correct responses: o Statics ➢ The bending moment on a beam is given by 𝑀 = −4𝑥 3 + 3𝑥 2 − 23𝑥 + 5 N.m, calculate the shear force at 𝑥 = 3 m. (Correct Answer: V = 113 N; ChatGPT answer: 113 units [whatever the units of the bending moment are]) o Dynamics ➢ The position of a particle is given by 𝑠[𝑡] = 𝑡 3 − 12𝑡 2 + 44𝑡 + 11 m, calculate the acceleration value at 𝑡 = 5 s. (Correct Answer: a = 6 m/s2; ChatGPT answer: acceleration at t=5s
courses offers a promising approach to equipfuture engineers with these crucial skills and the necessary mindset to develop sustainable andequitable solutions for the future. By engaging in projects, engineering students learn to grapplewith real-world, multidimensional challenges, to adapt and innovate—a crucial mindset foraddressing the multifaceted issues faced by engineers [18].One of the early definitions for PBL [19] involves five distinct aspects: a) student-drivenproblem-solving where they propose their problems or choose from options, fostering ownershipand engagement, b) integration of a range of educational activities, c) a tangible deliverableoutcome, such as a presentation, prototype, or research report, demonstrating
active learning," CBE—Life Sciences Education, vol. 14, no. 1, p. ar5, 2018.[7] B. B. Morrison, L. E. Margulieux, B. J. Ericson, and M. Guzdial, "Subgoals help students solve Parsons problems," Learning and Instruction, vol. 34, pp. 63-71, 2015.[8] T. Naps, G. Rößling, V. Almstrum, W. Dann, R. Fleischer, C. Hundhausen, A. Korhonen, L. Malmi, M. McNally, S. Rodger, & J. Á. Velázquez-Iturbide, "Exploring the role of visualization and engagement in computer science education," SIGCSE Bulletin, vol. 35, no. 2, pp. 131-152, 2002.[9] H. G. Sigarchian, S. Logghe, R. Verborgh, W. de Neve, F. Salliau, and E. Mannens, "Hybrid e-TextBooks as comprehensive interactive learning environments," Interactive Learning Environments
plan.”Data AnalysisFirst, we individually coded each episode per family for one or more of the 16 epistemicpractices [6]. Cunningham and Kelly [6] classified the 16 epistemic practices into four broadcategories: (a) engineering in social contexts (e.g., consider problems in context, persist in theface of failure); (b) uses of data and evidence to make decisions; (c) tools and strategies forproblem solving (e.g., consider materials and their properties); and (d) finding solutions throughcreativity and innovation (e.g., innovating processes, systems, and objects). As an example ofour coding process, the following event from the Soccer Bot kit was coded as envision multiplesolutions and consider materials and their properties because Ashley
correct/incorrect steps are noted. The incorrect steps must be corrected before further operation can be carried out. In the game environment, students can also see the control system and operate it (Figure 1c-d). The control system and output stream information are generated to mimic real-life operations. Students can use the data to solve some problems encountered in the game. They can practice and repeat the experience at their own pace and time. These two steps help students remember a valve's location and how to complete the operating procedures. The immersive 3D works similarly but requires a VR-enabled headset (Figure 2a-b). (3) Additionally, students can also use VR walkthrough (Figure 3)to gain