suspect that liberal arts institutions inparticular focus on teaching non-technical knowledge and skills, which are also valued byindustry [1]. A more balanced educational experience might be particularly relevant given thelarge number of folks with engineering degrees who work outside of engineering occupations;the NAE estimated that as of 2013 there were 65% of all degreed engineers who worked inoccupations not considered engineering [41]. The ABET EAC program criteria add additionalcurricular constraints on specialty degrees, with the majority of the identified aspects relating totechnical issues; programs accredited under the general criteria do not face these additionalrestrictions [42]. Previous research quantified the amount of required
(73%) Fall 2022 107 82 (77%)The scores of the engineering calculations assignment between the traditional and generativelearning methods were evaluated with a repeated-measures ANOVA. Although there was a slightdifference between the means of the traditional (1.9 ± 0.2, standard error [s.e.]) and generative(2.6 ± 0.2, s.e.), there was no significant effect of learning method on the performance scores (p= 0.11). There was a significant effect of grader (p < 0.0005). As seen in Figure 1, two of thegraders in the F’21 semester (B and C) graded the calculations assignment significantly lowerthan grader D in the F’22 semester. Within the F’21 semester, a significant difference wasobserved between graders A
interactions. Thislimitation is significant, as it affects the potential depth and effectiveness of human-machineinteractions, especially in scenarios where cooperation and social understanding are key. Ineducation, the integration of generative AI with AEI offers transformative potential. GenerativeAI can be employed to create personalized and dynamic learning content, while AEI enables thesystem to interpret and respond to the emotional states of learners.This work, building upon previous work by the authors[1] ,Recognizing and Responding toHuman Emotions: A Survey of Artificial Emotional Intelligence for Cooperative SocialHuman-Machine Interactions, revolves around a central query: What are the essentialadvancements required in AI to enable it to
experimentscompleted during face-to-face instructional sessions. These experiments involve the generation ofdata through simplistic methodologies, allowing students to quickly gather data for analysis andauthoring short technical reports. The student-driven methodologies and data generation makethese courses less susceptible to plagiarism through copying internet content. However, the courseaims to help students improve their writing techniques, including using active voice, academiclanguage, and use of appropriate grammatical structures. These topics, in addition to graphical 2displays of data are critical for engineers both within their educational setting and in future careerpaths.The methodology for this
assignment learning outcomes. Among other benefits, WATTS has shown statistically significant outcomes towards improvingstudent technical writing [1]. Tutors provide specific, appropriate feedback to the students during thetutoring sessions. However, one area that remains a challenge is engaging students in revising andimplementing that feedback in their writing process. An important next step is to find new ways to engagestudents in the revision process so they can effectively use the feedback they receive from multipleinterdisciplinary audiences and begin to internalize the benefits of the revision process. Here, we begin the work of increasing student engagement with a multi-pronged approach to revision.Students begin by assessing their own
Figure 1 shows the amplitude spectrum|X(f)|of x(t), which can be obtained using the following MATLAB command:abs(fft(x))The result is a vector of discrete samples in the frequency domain with a frequency spacingΔF=FS/N, where N is the number of �me domain samples. The use of the MATLAB commandangle(fft(x))is also discussed, as the students have already been introduced to the concept of phase whentalking about phase distor�ons of amplifiers. Then, the plo�ng of the amplitude spectrum isexplained using the following two steps: 1- Generate the frequency domain vector, x-axis, with N samples from f=0 to f=FS-1 using the MATLAB command f=linspace(0, FS-1, N) 2- Then the spectrum is generated using the following command: plot (f, y). where y
CSCL-tool are considered. However, participants differ in theirinterindividual tool usage, e.g., webcam usage, due to personal or technical reasons. In result, aCSCL-session planned on a web-conferencing platform can unintentionally turn into a session ona spectrum from videoconferencing (all participants use their webcam and microphone) overaudioconferencing (participants refusing webcam usage) to synchronous text-chat (webcam- andmicrophone-refusal). In worst case this can cause misleading conclusions about the didacticmatch between tool and task with negative effect on teaching and learning. To consider theusers’ interindividual tool usage, we conducted an online experiment with 45 undergraduatestudents building 15 three-student groups
use of electronic diagnostic tools. Technical skill: Circuit design. Analysis of electrical and electronic systems. Soft Skill: Attention to detail: Precision in the design and assembly of electronic com- ponents. Diagnostic skills: identify and solve problems in electrical/electronic systems. Key performance Indicator: Quality in the design and assembly of circuits. Ability to identify and solve electrical problems. Analysis report and support of the circuit used.Case in point: Internet of Things(IoT)1. Focus Area: General Learning Objective: Understand IoT/IIoT principles and their application in automated pick-and-place systems for inventory and quality management. Analyze data-driven pro- duction efficiency
aims to help shift its undergraduate engineering education offeringtowards such a balance.5. References 16[1] Marbach-Ad, G., Egan, L. C., and Thompson, K. V., “Concluding thoughts”, In G. Marbach-Ad, L. C. Egan, and K. V. Thompson (Eds.), Cham: Springer, pp. 223-226, 2016.[2] ABET, “General criterion 3. Student outcomes from criteria for Accrediting EngineeringPrograms”, 2019. Retrieved from https://www.abet.org/accreditation/accreditation-criteria/criteria-for-accrediting-engineering-programs-2019-2020/#GC3.[3] Ananiadou, K., and Claro, M., “21st century skills and competences for new millenniumlearners in OECD countries”, Paris: Head of Publication Service, OECD, 2009.[4] Winberg, C
research-based program, defined and structuredtraining in how to write clearly and convincingly is needed for their publication which arerequired for their third- and fourth-year curriculum. What has been observed while teaching international students in the ‘Science andReligion in Japan’ course is that, in general, both our research-based program students andinternational exchange students can express their thoughts logically while speaking, however,in writing, they cannot express their opinions clearly. Below are instructions to complete theirsummary and response paper: Step 1: Choosing two topics from the lecture. Step 2: Deciding the thesis statement for each topic. Step 3: Identifying their opinions and thoughts
period, we also were interested to note thatthe younger graduate spoke more explicitly about these. Our broader study seeks to expand thesepreliminary findings through the analysis of further interviews with the stakeholders in thisparticular program and then to expand our study to an advisory board of another program at thesame institution.References[1] D. Keržič et al., “Academic student satisfaction and perceived performance in the e-learning environment during the COVID-19 pandemic: Evidence across ten countries,” PLoS ONE, vol. 16, no. 10, p. e0258807, Oct. 2021, doi: 10.1371/journal.pone.0258807.[2] M. Menon and J. Poroor, “Grounded Idea Generation: An Analysis Framework for Project- Based Courses,” Procedia Computer Science, vol
are actively using ROS as a tool [1]. These metrics aregrowing steadily year over year. While early adopters of ROS were graduate students or in-dustry users, increasingly, students and instructors are taking an interest in ROS at the under-graduate level [2] [3] [4] as has been explored at the masters level [5] [6]. However, even justinstalling ROS can be a daunting task for the uninitiated. This paper explores options for in-stalling ROS for undergraduate courses, offers recommendations, and points readers towardsadditional guides and resources.2.1 Importance of ROSROS has become a powerful staple of robotics research and development. ROS is a softwaresuite with efficient, modular, and easily customizable software tools [7]. It is free
), AISC (American Institute of SteelConstruction) and/or ISO (International Organization for Standardization) standards are usedextensively for these purposes. However, the significance of standards may not be immediatelyapparent to students in a classroom or laboratory setting. Generally, in laboratory courses,students are asked to follow a given set of procedures without understanding the criteria ormethod by which the procedures were selected. Similarly, mechanical or structural designcourses emphasize code requirements without providing a comprehensive picture of thedevelopment of codes and the relationship to core mechanics of materials concepts. Thispresentation leads to students who can perform calculations without understanding why. Hence
-COVID). A rubric was created, adapting existing rubrics anddefinitions reported by Gin et al. [6] and Stanny et al. [7]. Syllabus elements (i.e., grading policy,general absence policy, general makeup work policy, office hours, instructor contactinformation, important course dates, instructor encourages student contact, general campusresources, grading rubrics, emergency planning, and mental health resources, Table 1) wereevaluated using direct coding [8]. The presence or absence of each syllabus element wasrecorded for all syllabi (i.e., pre-COVID and post-COVID). In addition, the presence ofsubstantial changes between the early and late syllabi were recorded. The syllabi were codedindependently using two coders, and discrepancies were resolved
generator and a voltmeter, which the students can use to better understandchemistry principles and may be adopted in other disciplines and at different levels of academia.Figure 3: pH MeterThere is also an additional function in the ADALM 1000 board that uses an application totransfer function equations to convert voltage and frequency readings from the device into thedesired measurement units.Figure 4: ADALM 1000 Analog DeviceIn this study, the experiment-centric pedagogy module was implemented between fall 2021 tofall 2022 and the Motivated Strategies for Learning Questionnaire (MSLQ) was adopted, whichcomprised of 1-7 Likert scales and has 8 subscales [26]. To measure the curiosity of the students,this study adopted the Litman and Spielberg
significantlydifferent to assess the effect size of the difference and a descriptive analysis was conducted tostudy the means and variances of these groups [15]. The tests used above were used keeping inmind the nature of data to be ordinal and non-parametric. The details of the group differences areshown in Fig A.1 of Appendix.Inferences based on the Group Differences Analysis: 1. Participants who attended communication skills related workshops have reported higher averages than participants of technical skills related workshops on five aspects: Intent of application, Confidence in application, Change in relevance, Physical load and workshop’s role in teaching the application of the concept in decreasing order of effect but still
attended the onsite sessions at Institut Teknologi SepuluhNopember (ITS) Indonesia, engaging in face-to-face lectures and local community field studies.Those unable to travel continued participation online.Through an interdisciplinary approach [2], the programs and courses aligned with the 21stCentury Imperative [3] as well as the Washington Accord 11 Global Attribute Profiles(WA11GAP) defined by The International Engineering Alliance (IEA) [4]. This article exploresstrategies for encouraging engineering students to participate in mobility programs fosteringglobal competence and Asian pride. In addition, the learning outcomes are assessed based onWA11GAP criteria.1. Background to start of Virtual/Hybrid programs, and program outlinesMobility
plausibledistractors, all aimed at testing students' understanding and application of strain hardeningprinciples. Figure 1 shows the prompt given to GPT4 to generate the MCQs, after feeding it [9].Figures 2 and 3 display the output of the prompt. Figure 1: Prompt to Chat GPT 4 to generate an MCQ of 5 questions. Figure 2: First 3 MCQs. Figure 3: Last 2 MCQs.It should be noted that, in Figures 2 and 3, the AI's approach to generating MCQs was overly directin addressing the LOs. This level of directness, while beneficial for clarity, potentially underminesthe development of analytical skills by not fully challenging students to apply their understandingin
familiarity with LLMssuch as ChatGPT, we will look for differences in student response based on their level ofexposure to and familiarity of use with LLMs.References[1] I. Asimov, "Runaround," Astounding science fiction, vol. 29, no. 1, pp. 94-103, 1942.[2] M. Haenlein and A. Kaplan, "A brief history of artificial intelligence: On the past, present, and future of artificial intelligence," California management review, vol. 61, no. 4, pp. 5-14, 2019.[3] P. Wang, "On defining artificial intelligence," Journal of Artificial General Intelligence, vol. 10, no. 2, pp. 1-37, 2019.[4] M. Javaid, A. Haleem, R. P. Singh, S. Khan, and I. H. Khan, "Unlocking the opportunities through ChatGPT Tool towards ameliorating the
(see Table 1) It is evident from theresults that institutions have different approaches first year requirements. Universities that offergeneral first year engineering courses offer a broad curriculum to all incoming students. Incontrast, universities that offer non-general first year courses offer a set of courses specific toeach engineering major.Table 1: General first year and non-general first year universities General First Year Non- General First Year Carleton University British Columbia Institute of Technology Concordia University Lakehead University Dalhousie University McGill University McMaster University
, and its capacity to combine expertise andcompetencies from various disciplines, including computer science, electrical engineering,mechanical engineering, and mathematics. Robotics covers a wide range of fields and promotesthe development of critical thinking skills such as problem solving, systematic reasoning,abstraction and generalization, as well as collaboration and communication [1, 2]. This growinginterest in robotics has been accompanied by the development of accessible open-sourceplatforms, such as Arduino and Raspberry Pi, which enable both novice and expert users to createelectronic projects, from simple LED displays to complex robotic systems. This has resulted inthe creation of several commercially available educational robotic
between the Quiz two sessions, but the questions were different. Amont the five Quiz (5 quizzes quizzes, Quiz 0 was designed to evaluate students’ (5 quizzes were knowledge background from prerequisites. Quiz 1-4 were assigned) assigned) evaluated students’ learning outcomes of general accounting equation, mass balance, charge balance, and energy balance. Final Exam Final Exam (Two parts (Two parts and and accumulative The format of the final exam
variation in units representing courses (credithours, credit points, etc.) would make comparisons of raw totals difficult. An intuitive similaritymetric would be 0 for students in completely unrelated majors, and 1 for students in the samemajor. Subtracting a 0-1 similarity measure from 1 would yield disciplinary distances of d = 0for students in the same major, and d = 1 for students in entirely unrelated majors.Relationships between student degree programs can be observed in two general areas: curricularoverlap and cross-listings. The two measures of similarity were calculated for each pair ofmajors, scaled to a range of 0-1 (not similar to very similar), and averaged for each majorpairing. The single scaled similarity measure for each pair of
semester of writing tutoring are eligible for WATTS training.Eligible tutors are invited to participate and can decline. Since the beginning of project, nine WATTStutors were humanities majors, six were engineering majors, four were science majors, three werebusiness majors and one was a social science major. Only three of the 23 tutors were male. With theexception of two, all of the tutors stayed with the project until they graduated.Methodology:In each year of the study, the same assignment (the “analysis” report) was collected. In the first year ofthe study, the students had no tutor interaction. In the second year, (the control year) the studentsinteracted with “generic” tutors. In the final year, the tutors were given a training session by
), Electrical & Computer Engineering(ECE), Industrial & Systems Engineering (ISE), and Transportation & Urban Infrastructure Stud-ies (TUIS). Figure 1 shows the adoption of tools in each department. Overall, four tools were uti-lized: Microsoft Excel, Google Forms, SearchLight Performance Assessment, and Canvas Learn-ing Management System.Figure 1 shows the timeline of tool adoption for each department. All departments began usingExcel. The ECE department transitioned to SearchLight in 2014. SearchLight Performance As-sessment is a flexible performance assessment engine designed to help educational institutionseffectively utilize data to drive decision-making. The software is an assessment tool that allowsdepartments to enter, generate, and
what specific technicalknowledge our students should have, ie not running a paper manufacturing course. We are usingthese partners to find out what skills they value and where they see the next generation ofengineers succeeding and struggling. Consistently, the multi-disciplinary team of industrypartners speak of the need to communicate clearly to a range of audiences, in both writing andpresenting. The college has an extensive writing requirement and oral communicationrequirement, which supports our expectation of the value of the broader whole-person approachof the liberal arts environment with the technical aspects of an engineering degree.The advisory circle also spoke to needing employees willing to take ownership of their worksuch that
received scholarships from the grantprogram. In the third section, academic performance of STEM Ambassador and Non-STEMAmbassador scholars are compared. The last section presents the impacts of the Urban STEMproject on personal and academic life of the scholars.3-1. Demographic comparison of Scholars and Non-scholarsOverall, the project has been successful in attracting a diverse group of scholars in terms of gender,first-generation, and URM statuses. Figure 6 compares representation of female students amongscholars in the Urban STEM Collaboratory project and non-scholar (but with the same academicand financial eligibility) students. In all years, female representation is significantly higher amongscholars than non-scholars. In years 2019 and 2020
this project, a deeplearning system has been developed to determine if a bottle cap on a small plastic bottle is a)installed properly, b) misaligned, c) open, or d) missing. Examples for each case or category aredisplayed in the table below (figure 1). The task for the students is to develop and test an imageclassification CNN using transfer learning and MATLAB to distinguish and identify the variousbottle cap orientations. A training set can be developed by the student teams, or they can utilizean existing bottle image dataset developed by a previous class (30 images per category). The useof existing image datasets can reduce the time required to complete laboratories. Other objectscan be optionally chosen by the students in the general area
technologies, they need people with particular kindsof competencies (Aldrich, 1979). In this paper, we draw from our experiences to provide an1 Authors listed in alphabetical order with equal contribution. Corresponding author: Marina Dias mvbdias@amazon.com2 All authors are affiliated with Amazon.com, Inc.example of a multi-disciplinary team conducting talent management research within the techworkforce of the 21st century, and describe some of the typical roles one may find at similar techteams that engineers and engineering educators may join.Talent management research refers to research on the people that make up organizations. Atypical employee life cycle is illustrated in Figure 1 below. An employee journey begins whenthey are recruited and
was successful, with 15 of the 17 students successfully completing courseactivities and passing the course. Analysis and reflection from the course is available in theAnalysis section.Fall 2022 [ENGR 35]The Fall 2022 cohort enrolled 11 students and 11 students persisted past the withdrawal deadline.Class sessions were all held in-person with Zoom optional for students who were unable toattend due to illness or other excuse. Class attendance was regularly 10 students, with 1-2students attending via Zoom.Students in this cohort were a higher percentage of sophomores as we specifically targeted newsophomores in our advertising for the course. Figure 3 shows the F2022 student cohort by year. Figure 3: The year-in-school of the