asked to predict an outcome from ascenario and in the other to evaluate an existing outcome.All seven participants attended a private southwestern university and majored in aerospaceengineering. The majority of participants were White and male (Table 1). A small fraction of theparticipants reported a military status and most were in their final year. Pseudonyms were givento the participants to maintain confidentiality and safeguard their identities. All participantsreported having received either an A or B in their statics class (taken at least a year prior); Adamnoted receiving a B after the second time taking the course. Participants noted a variety of priorprofessional engineering experience, including work experience associated with the
situations: the proposed topic is (a) better reformulation of another proposedtopic; (b) a subtopic of another proposed topic; (c) a super-topic of another proposed topic; (d)overlapped (related) with another proposed topic; or (e) a new topic (not related with theprevious proposed topics); 4 – Other expert crowd participants are then asked to confirm thecategorization of the proposed topic (similar with the options in step 3); 5 – If a crowdacceptance level was obtained, the topic is proposed for global validation; If not, the topic ismaintained in the proposed topics list but not included in the global validation list.Consensus building methodWe created a dynamic crowdsourcing method to elicit curriculum elements using a collectiveintelligence
Breathing exercises, body scan, gratitude Instructor A 1 minutes Daily activities Breathing exercise coupled with a theme like Instructor B 30 seconds Daily gratitude or intention-setting Box breathing, active listening activities (2), Instructor C 10 - 30 minutes Bi-Weekly gratitude activities (2), body scan 2-3 minutes daily, Box breathing, active listening
, either 2D or 3D, for which a dragcoefficient is published and attempt to match that value using the CFD simulation code of theirchoice. They were also required to explore the effect of grid refinement on their results, and to“do something else” and discuss what they think the results mean. The assignment sheet isincluded in its entirety in Appendix B. There were additional oral instructions and some CFDdemonstrations given during class to better express the expectations. Several aspects of thisassignment were purposefully left vague so the students had to make choices and be somewhatcreative in how they approached it. Drag coefficient diagrams and tables excerpts from severaltextbooks were provided for the students to choose from [6]–[9], and
television in early developmental stages. Looking at a flatscreen exposes children to a two-dimensional environment and reduces their playing time withphysical 3D objects, missing the opportunity to develop hand-eye coordination that is thefoundation of spatial skills.Continuous efforts have been made to create training methods and exercises that increase spatialvisualization skills. In 2003 Sorby, S., A., Wysocki, A. F., and Baartmans B. J., published amultimedia software-workbook package which contained the course “Introduction to 3D SpatialVisualization” [11], now used for engineering graphics education throughout the nation. In 2009Sorby, S.A. identified several strategies that can be effective in developing 3‐D spatial skills andin contributing
Paper ID #38901Student-led program to improve equity in Ph.D. oral qualifying examsMeredith Leigh Hooper, California Institute of Technology This author was an equal first author contributor to this work. Meredith Hooper is an Aeronautics PhD student studying under Professor Mory Gharib in the Graduate Aerospace Laboratories of the California Institute of Technology (GALCIT). Meredith is a National Science Foundation Graduate Research Fellow, leader within the GALCIT Graduate Student Council, and Co-Director of the Caltech Project for Effective Teaching (CPET). Her PhD research uses a combination of machine learning and
terms and six work terms (Table 1). The BME is a design-centered program curriculumdivided in four years, each year with two terms, term A and term B, consisting of 40 core courses,7 of which are design focused and another 7 of which are engineering science-based courses withintegrated design components. Following the shift to online, instructors needed to modify theirdelivery and assessments, as traditional lecture, tutorial and in person exams were no longerfeasible. As the pandemic restrictions eased, course delivery shifted to hybrid approach, wherecourses were required to offer 1-1.5 hrs/week in-person and remaining weekly hours weredelivered online. This allowed a transition to in person teaching, exam assessments, teamwork forproject…etc
unanswered. Initial questions on the survey asked the students declared major(ARCH, ARCHE, dual major, or undeclared), and a second question asked their year in ourprograms. Table 1(a) gives a breakdown of the responses, with none of the respondentsindicating undeclared as their current major. Table 1(b) provides a similar breakdown ofresponses from the follow-up survey. There were no respondents indicating a dual major orundeclared as their current major in the follow-up survey.It is important to the understanding of this survey that since the curriculum has the Introductionto Architecture course as a prerequisite to the first architecture design studio, the benefits of thiscourse should be considered within this research. In the fall 2022 semester
summary of the structure ispresented in Figure 1. Figure 1 Structure of academic distraction method testDetails of Individual tests and Examples of distraction questions:In test 1, there were 22 curriculum questions (1 point each) and the type 2 group received 3additional questions as given below.1. A monkey, a squirrel, and a bird are racing to the top of a coconut tree. Who will get the banana first, the monkey, the squirrel, or the bird? A. Monkey B. Bird C. Squirrel *D. None *None, because there are no bananas on a coconut tree.2. If I say "Everything I tell you is a lie", am I telling you the truth or a lie? A. Truth *B. Lie C. It can be
/validation is gradedout of 30%. This project accounted for 20% of the total weight of the “Design Methodologies”course. Appendix B shows the five stages of the PCB project along with some explanation of howstudents’ work is assessed at every stage. Appendix C shows one anonymous sample of studentsubmission for each of the project stages.Project Outcomes and OrganizationThe PCB project is designed in such a way that if a student drops the “Circuits, Signals andMeasurements” class, they will still be able to continue taking “Design Methodologies”. In otherwords, a student’s grade in one class would not impact their performance in the other. Courseinstructors advised students who were off-cycle or had to drop “Circuits, Signals andMeasurements” that
group; and (b) whether career self-concept wasinfluenced by learning modality. The pedagogical changes brought on by the COVID-19pandemic served as a natural experiment for the latter.Over the course of six contiguous semesters spanning Fall 2019 to Fall 2021 we measuredabsolute and relative self-concept (engineer versus clinician) from 333 students via explicitdeclaration, and via an implicit attitudes test (IAT). The IAT is a psychological test that relies onrepeated measures of response latency in a subject’s association of two concepts – in this case,between the concepts of self and other, and the concepts of clinician and engineer. Weinterpreted the resulting measure of implicit bias as a measure of career self-concept.The data suggest
performing a murder mystery based on hidden-profile-paradigm. The murder mystery task simulated a typical CSCL-session task in higher education,where an ad-hoc small-group of three students collaborate by pooling shared and unsharedknowledge into a common solution. This data-driven approach targeted to evaluate potentialdifferences in (a) task performance, (b) interaction-process quality, and (c) mental workloadbetween CSCL-sessions intentionally planned to be performed on a web-conferencing platformby the lecturer for didactic reasons but participants refuse to use webcam or microphone. Thegained insights should serve to define CSCL related policies and practices, which are conduciveto learning. Despite from theory and prior empirical findings
) C+ E2: Identify common op-amp circuits, find the output voltage (or gain) for several cascaded amplifiers. 1/3 of a B- E3: Find the analytical solution describing the voltage (and current) in a RC grade or RL circuit as a function of time. increase for E4: Use Mesh analysis to find V, I and/or P in complex circuits with multiple B each sources. additional E5: Use source transformation to simplify and then analyze a circuit to find skill passed B+ the V, I, P or a R. A1: Design an op-amp circuit project to transform input signal to meet A- specified output
room experience were not told beforearriving to class that they would be executing an escape room. The sections were broken downinto three teams consisting of six students. Throughout the semester the students worked inthree-person lab groups. Two lab groups were combined to form six-person teams that wouldexecute the escape room. The students were authorized to use the textbook and class notes tocomplete the puzzles but were given everything that was required to solve the puzzles in theprovided folder and backpack. An image of the students participating in the MC364 escape roomare shown in Figure 1d and 1e. (a) (b) (c
(22) studentsparticipated in the initial baseline survey. The intervention plans designed for buildingenvironmental behavior were implemented in Spring 2022. In the post and pre-surveys of theintervention semester, 25 and 22 students responded from a senior-level mechanical engineeringcourse.A pool of survey questions was developed to understand the following: a) Knowledge of sustainability, b) Attitudes and intended behavior towards sustainability, c) Willingness to pursue a sustainability career, and d) Perceived preparedness for a sustainability career. The essential goal of the intervention is to understand the role that the instructional approachplays in changing undergraduate students' knowledge, attitudes
. Therefore, we use actual circuits to help students learnBoolean algebra and provide a concrete, hands-on approach to the abstract concepts introduced inlogic gates and Boolean algebra.At the beginning, when introducing students the concepts of AND, OR, and NOT, we usecircuits to show the associated operations in Boolean algebra as depicted in Fig. 1. (a) Y= A x B (b) Y = A + B (c) Y = A’ Fig. 1 Circuits showing three basic operations in Boolean algebra.Take Fig. 1 (a), the AND operation as an example. With the help of the circuit, students can easilyunderstand that the two switches are controlling the status of Y. When and only when both A andB are closed (status 1), the status of Y is on
impact on deep learning andperceived advantages or disadvantages of participating in them. 2. MethodsIn this study, we investigate two courses for which we designed and implemented explanatorylearning activities for Mechanical and Aerospace Engineering (MAE) students: Course A(Statics and Introduction to Dynamics) and Course B (Solid Mechanics I). The two courses weretaught by the same instructor. There are three types of explanatory learning activities designedand implemented among the two courses: written homework prompt, group video assignment,and oral exams with descriptions as following:2A. Written Guidance prompts on homeworkWritten guidance prompt questions refer to guidance prompt text questions in addition to thetraditional homework
student work presented, theiteration row vector average is [3.0 4.3 3.5 4.3]. The average total number of steps, includingwithin multiple block-step iterations is 15.0. Collectively and qualitatively, not many iterations arerequired for what appears to be very good curve fitting, that implies numerical answers to thesystem ID problem directly within MATLAB. As a side story, one positive effect that often occursin this lab is a fun and friendly competition amongst the teams to see which team’s result overlapstheir experimental data the most. All in the name of oscillator dynamics, where students learnpractically about concepts like natural frequency and the damping ratio! a. Student team A with [1 3 1 3]. b. Student team B
havevariable input numbers such as voltage sources and resistors. Students are asked to solve forvoltage, current and/or power in circuits, and the numbers change for each question. Figure 1shows and example problem using automated assessments for this course. The quizzes arestructured this way so students can focus on mathematical modeling and evaluation processrather than getting the correct numerical results for one set of input values. Fig. 1 illustrates anexample of this quiz structure. (a) (b) (c)Figure 1: Analog circuit assessment, (a) circuit schematic with variable inputs, (b) question oneusing
4.57 4.4 5.4 a a 4.2 5.2 (a) (b) 4.0 5.0 Pre-Camp Pre-Sophomore
methods in STEM education assessment topromote inclusivity, engage learners, and empower underrepresented and marginalizedcommunities. Such research can then inform future pedagogical practices, curriculum design,evaluation plans, and resource allocation to contribute to a more inclusive and diverse STEMlearning environment and resultantly, the future STEM workforce.ReferencesBattel, K., Foster, N., Barroso, L. V., Bhaduri, S., Mandala, K., & Erickson, L. (2021, October).“We Make the Village”-Inspiring STEM Among Young Girls and the Power of CreativeEngineering Education in Action. In 2021 IEEE Frontiers in Education Conference (FIE) (pp. 1-7). IEEE.Bevan, B. B., Barton, A. C., & Garibay, C. (2018). Why broaden perspectives on
]. Another, theSurvey of Engineering Ethical Development (SEED), measures ethical knowledge (e.g.,knowledge of the NSPE code of ethics) [17]. Other examples include the EERI, the ESIT, DIT-2,and the Survey of Ethical Reasoning (SER) which measure ethical judgment [18]–[21]. Whilethese quantitative measurement instruments can be useful, such measures can be challenging toimplement [13]. Specifically, the measurements are (a) inflexible in that they cannot be adjustedto account for one’s learning context, (b) purely quantitative and thus fail to elicit students’views in their own words, and (c) prime students to focus on certain ideas, thus activating extantschema [22] while foreclosing other possible responses. For example, if an instructor aimed
claims are better established throughnon-empirical methods such as reviews of literature on the instrument’s development, which occurred aspart of the instruments’ development, or evaluation of the measured constructs against the learningobjectives of our course. To evaluate evidence supporting our three claims for each instrument, weorganized the paper around the following research questions, with the related claim in italics: 1. How well does our data fit with prior CSSE results and characteristics of good measurement? (a) How well do our data align with the established factor structure? (fit) (b) How well do our data show appropriate measurement range? (reliable) (c) To what extent do demographic variables affect fit and
Details a. Identify the loan length. b. Identify the frequency of payments (usually monthly) c. Identify the disbursed date. d. What is currency loss, and how is it covered by the partner.5. Click on Field Partner (the agency on site, making the loan, collecting interest) a. Search for them on the web and add their mission statement. b. Identify the Average cost to borrower (for this Field Partner) Explain what PY (portfolio yield) and APR (Annual percentage rate) mean, depending on which one is listed for this loan. c. Explain what is meant by return on assets, and identify ROA for this organization.You can just edit this file and turn it in. EGR 461
them.They have not given them the recognition due, as for example, studies in the US by L. B.Barnes [4], Scotland by T. Burns and G. Stalker [5], and England by M. B. Youngman, R.Oxtoby, J. D. Monk and J. Heywood [6]. It is argued that the story (case study) that Binghamand Hames tell lends strong support to this view [7]At the same time, such models challenge the idea that technological literacy is a subject thatought to be in the curriculum since they ask the question “what does it mean to be literate intechnology? Technological literacy as conceived here is not a particular discipline of studybut a skill that enables a learner to bring together different components of knowledge andskill in the solution of technological and scientific problems
graduatein six-years, and we view this as a positive and important finding. Regardless of when a studentwas admitted to a program, the likelihood of graduating in six-years did not change. Thisindicates that college administrators might be able to use programs like the one described in thispaper to help manage college enrollments without impacting graduation rates. Moreover, therewas no ill-effect noted based on URM status or gender. Researchers could scale up a similartype of study and investigate program matriculation timing across numerous institutions to see ifa similar type of pattern is observed.References1. B. L. Yoder, Engineering by the numbers: ASEE Retention and Time-Graduation Benchmarks for Undergraduate Engineering Schools
Colab file that covers the “continue” keyword in Python. Thisshould closely match the delivery of content in the lecture slides and videos, as seen in Figure 2. Fig. 1. Colab content on the "continue" keyword Fig. 2. Lecture slide content on the "continue" keywordIn the self-paced version of the course, an instructional Colab notebook was shared with thestudents two times each week (available in Appendix B). In the instructor-led version of thecourse, lectures were delivered two times each week via Google Meet, recorded, and shared withthe students along with the slides (slides and recordings available in Appendix B). Both courseshad live Q&A sessions at the end of each week.5
. Figure 1: diagram (A) and photo (B) of the holography apparatus.After successfully teaching this lab for the first time, we wanted to further investigate thesystem’s sensitivity to torsions and rotations. A few different experiments were tried and aresummarized here. First, as shown in the middle panel of Figure 2, we introduced only a verticalrotation of the metal beam by clamping it in the middle and applying a point load to the end.Rotation is not something a strain gauge can sense, since it uses the deformation of a metal foilto generate its signal (namely, a changed electrical resistance). In this setup, the small rotation isreadily determined, and produces evenly spaced and perfectly vertical fringes. With 4 fringesacross the 10 mm of beam
, no. 3, pp. 471–493, Sep. 2013, doi: 10.1007/s11218-013-9222-x.[8] E. Seymour and N. M. Hewitt, Talking about leaving, vol. 34. Westview Press, Boulder, CO, 1997.[9] K. L. Tonso, “Engineering Identity,” in Cambridge Handbook of Engineering Education Research, A. Johri and B. M. Olds, Eds., Cambridge: Cambridge University Press, 2014, pp. 267–282. doi: 10.1017/CBO9781139013451.019.[10] E. S. Abes, S. R. Jones, and M. K. McEwen, “Reconceptualizing the model of multiple dimensions of identity: The role of meaning-making capacity in the construction of multiple identities,” Journal of college student development, vol. 48, no. 1, pp. 1–22, 2007.[11] G. L. Downey and J. C. Lucena, “Knowledge and professional identity in engineering
and Arts students’ search processes. We mayexpect that undergraduate students experience cognitive complexity with more advanced searchtechniques, like proximity searching, truncation, wildcards, or Boolean expressions, for example.However, analysis reveals that undergraduate students experience cognitive complexity in basicelements of library research: a) deciding which terms to use, b) knowing if they are searching inthe right place, c) examining each article to weed out less relevant articles, and d) evaluating thequality of a source. Our findings reveal a sizable disconnect between what librarians may expectare basic elements of the search process and what students experience as cognitively complex.Introduction As public internet