-is-industry-4-0.html(accessedFebruary8,2024.[9] B.Sakulkueakulsuketal.,"KidsmakingAI:IntegratingMachineLearning, Gamification,andSocialContextinSTEMEducation,"2018IEEEInternational ConferenceonTeaching,Assessment,andLearningforEngineering(TALE), doi:10.1109/TALE.2018.8615249.[10] C.Schelly,G.Anzalone,B.Wijnen,andJ.M.Pearce,"Open-source3-Dprinting technologiesforeducation:Bringingadditivemanufacturingtothe classroom,"JournalofVisualLanguages&Computing,vol.28,pp.226-237, 2015/06/012015,doi:10.1016/j.jvlc.2015.01.004.[11] TeachEngineering."TeachEngineeringDigitalLibrary." https://www.teachengineering.org/(accessed.[12] P.A.Hennelly,J.S.Srai,G.Graham,R.Meriton,andM.Kumar,"Do
datacollection to include several forms of student feedback: (a) pre- and post-survey, (b) end-of-semester interviews, and (c) reflective diary activities. Pre- and Post- Survey. We assessed three key variables of interest: self-concept clarity,awareness of narrative identity, and entrepreneurial mindset. We used an established measurethat were validated in prior work (i.e., self-concept clarity, Campbell et al., 1996; awareness ofnarrative identity, Hallford and Mellor, 2017; entrepreneurial mindset, Brunhaver et al., 2018).Each item on each scale was endorsed using a five-point or 10-point Likert scale. As part of anexploratory approach to identify the effectiveness of story-driven learning on expected learningoutcomes, we collected baseline
includes learning goals, pedagogies, assessment and so on [22]. Curriculum design isthe core of this AI certification program and also a major challenge facing in current AIeducation. Personally speaking, I believe the cultivation of AI talents can be divided into two types: students who are already majoring in AI and students who have never studied AI. Currently, how to educate students who have never learned AI is a challenge. Because the curriculum system for AI majors is relatively mature, while AI education for non-AI majors is mostly in an undeveloped state (Instructor, X).Due to significant differences in academic backgrounds, mathematical foundations, and otheraspects among participating students, the program adopts a
thesecourses and thus satisfying the requirements. One way to assess the progress of the student wouldbe to compare the student’s total accumulated credits to the credits required by the student’sspecific degree program at graduation. Such credits are generally referred to as excess credits inthe higher-education literature [13].This paper seeks to explain the credit efficiency of university students. Not all creditsaccumulated by students are usable towards their degree program of study - a fact that often goesunaccounted for based on the excess credits definitions mentioned above. Even if they are usable,they may not be applicable. In this work, we use a custom-built specialized audit tool todecompose student credits in the following way: unusable
instrument to assess learning or achievement), and engineering researchers (who may use the model or resulting instrument to support their research aims). Thus, we are committed to empathizing with such users and leveraging such empathy to guide model development. 2. Engaging users in appropriate levels of co-design - We are engaging each user group (students, educators, researchers) throughout the development of the model. We have made efforts to reach the variety of potential users in each group, engage with them in ways that are authentic to their empathy-design contexts, and facilitate sufficient agency for each group as they interact with and help refine the model. Through this latter point, we leverage
Engineering IdentityAbstractThis paper is a work in progress (WIP) for an NSF project that explores first-generation students(FGS) in engineering technology (ET); specifically, their academic performance, engineeringidentity development, and use of social capital all compared to continuing generation students(CGS) peers. Despite the growing number of engineering technology degrees awarded annually,there is a scarcity of research focusing on the acquisition of engineering identity, particularlyamong FG students. Overall, this project will utilize a two phase, mixed methods approach. Inthe first phase, we will quantitatively assess academic performance comparisons between firstgeneration and continuing generation engineering students and utilize the
Future Professoriate and from USFQ in Structures for Construction Professionals. MiguelAndres’s research includes Architectural and Civil Engineering Project Management, Sustainable and Resilient Urban Infrastructure, and the development of engineers who not only have strong technical and practical knowledge but the social awareness and agency to address global humanitarian, environmental, and social justice challenges. For him, social justice is a concept that should always be involved in discussions on infrastructure. Related to STEM education, Miguel Andres develops disruptive pedagogies for STEM courses as a tool for innovation, and assessing engineering students’ agency to address climate change. Currently
respond to the complex ethical, social, political, andenvironmental challenges of today, they may begin to eschew traditional case studies that portrayengineering as objective and apolitical. In this way, they may begin to “transgress” againstdominant views of engineering that can limit students’ critical thinking and engagement withsocio-political issues within engineering contexts. Liberatory pedagogy also disrupts the statusquo of power dynamics and practices in the postsecondary classroom, opening up space for newclassroom activities and assessments that create a more collaborative and equitable learningenvironment [1].In this paper, I explore the redesign of an undergraduate engineering technology and societycourse in relation to the idea of
; Doug®). All parts are shownat the same scale.After completing Part 2, students submitted a written brief that included three components. First,students composed a “standard operating procedure” of the manufacturing steps that they took tomake the part, specifically describing tooling, mill operations, and critical measurements.Second, they included a neatly staged photograph of their final part and a brief assessment of itsquality and functionality. Students were required to comment on whether the critical partdimensions matched the provided engineering drawings. Lastly, students documented a qualityand safety check. For quality, they compared final dimensions of their part to the provideddrawings. The safety check involved performing a sharp
optimizing energy efficiency in office buildings through the strategic placement andsizing of windows. Simulations were conducted to assess different configurations, guiding agenetic algorithm (GA) search towards identifying low-energy solutions. In general, weak AImethodology can be extended to address a diverse array of design challenges, including theselection of construction materials, the design of shading elements, and the optimization oflighting and mechanical systems for buildings. The majority of AI methods currently in use arecategorized as weak AI [10]. However, there has been a recent emergence of the concept of superAI, which denotes software with superior processing and cognitive capabilities compared tohumans, albeit still in its
implementing photovoice as a researchmethod. Some of these benefits include being able to identify and assess the needs and strengthsof participants in a community; sustain participation of the vulnerable, in the context of our studyminoritized, populations in a community; amplify the voices of participants to reach othercommunity members and push for change [1]. The possibility of such positive outcomes has beeninvestigated in relation to women [10–12], disadvantaged groups [13, 14], and largely within theprofessional medicine community [15–17]. Yang has used photovoice, along with portraitphotography and photojournalism, to study whether participatory photography can helpsocio-economically disadvantaged adults develop agency towards pursuing higher
Education and Future Professoriate and from USFQ in Structures for Construction Professionals. MiguelAndres’s research includes Architectural and Civil Engineering Project Management, Sustainable and Resilient Urban Infrastructure, and the development of engineers who not only have strong technical and practical knowledge but the social awareness and agency to address global humanitarian, environmental, and social justice challenges. For him, social justice is a concept that should always be involved in discussions on infrastructure. Related to STEM education, Miguel Andres develops disruptive pedagogies for STEM courses as a tool for innovation, and assessing engineering students’ agency to address climate change
developed various ways of pairing mentors to protégés. Activities such as SpeedMentoring25, personality surveys, and protégé chosen mentors13 have been utilized in forming amore cohesive mentoring pair. Although these pairing mechanisms have assisted programcoordinators in slowly diminishing stated flaws within a program, these flaws are still notcompletely overcome.Myth #2: Informal Mentoring Programs are Always More Effective than Formal MentoringProgramsFormal mentoring is the term used to define a planned mentoring process3. Individuals aregenerally placed together in various mentoring groups and attend scheduled meetings3. Meetingtimes and other scheduled events are logged, and financial costs may be documented to help theinstitution assess
was higher for the FORCES cohort (12.4%) than for theothers.Quantitative and qualitative data collected via surveys are being used to evaluate the Page 22.1047.2effectiveness of FORCES components; a preliminary assessment of some of those components ispresented here. Lessons learned during the first year of FORCES implementation are being usedto modify the program to improve the outcomes for current and future cohorts.IntroductionStudies indicate that a number of parameters, including qualitative skills, social integration andacademic integration impact student retention to varying degrees.1,2 This paper compares firstyear retention and
AC 2011-2209: TEACHING MECHANICS WITH MAPLERadian G Belu, Drexel University (Tech.) Dr. Radian Belu is Assistant Professor within the Engineering Technology (ET) program - Drexel Uni- versity, Philadelphia, USA, and Research Assistant Professor at DRI, Reno, Nevada. Before joining to the Drexel University Dr. Belu hold faculty and research positions at universities and research institutes in Romania, Canada and United States. His research interests included power system stability, control and protection, renewable energy system analysis, assessment and design, power electronics and electric machines for wind energy conversion, radar and remote sensing, wave and turbulence simulation, mea- surement and modeling
the assignment.The first efforts to utilize the method are described in the paper, complete with assessments ofstudent learning and satisfaction. It is of particular interest to determine if learning styles anddemographics of the students influence performance under the new class method. Courseassignment and exam scores, compared to previous offerings of the course, will be used to assessperformance. Surveys of the students will used to assess their time commitment, comfort level,perception of fairness, and overall satisfaction. Since the method can be thought of as shiftingmore of the learning burden to the students themselves, a survey will assess motivation and itseffect on involvement and performance. An estimate is also made of
custom laser tag modules deployed on-board each vehiclethat make possible a wide variety of one-on-one and multiplayer competitions that increase bothstudent motivation and spectator interest.The overall structure of the course is discussed, including a project management frameworkshared with other technical projects offered concurrently. The paper details the coursecompetencies – specific, measurable skills and knowledge connected to learning outcomes forour degree programs – associated with the senior project course, and it includes an assessment ofhow well the robotic laser tag project meets these expectations. The organization of the projectand supporting infrastructure is described in detail, as are the experiences of the first year of
colleges of engineeringfrom four participating universities. Student respondents filled out a 20-minute survey, amongwhich were assessments of the three forms of self-efficacy. The analysis of the data revealedthat social support in the first year from friends, family, college support services, and facultyfurnishes a powerful and independent impact on efficacy over and above demographic qualities.The only demographic characteristic that preceded social support as an explanation of self-efficacy was the impact of academic performance on academic self-efficacy. Otherwise, socialsupport furnished the most significant explanation of work, career, and academic self-efficacyupon completing the first year in undergraduate engineering
) requires a ‘meshing’ of human expressive modalities. Nathan& Johnson19 argue modes are in service of each other, for example the use of gesturingaccompanied with speech helps students organize their ideas in meaningful ways. Oftenphenomena is being imagined in 3-dimensions, and the use of gestures can compliment student-generated graphic models that are often in 2-dimensions. Finally, combining modalitiesfacilitates an understanding of phenomena that varies in scale, temporality and causality. The useof multiple modes to express ideas highlights gaps in reasoning often not identified if only onemode of thinking is used. It is difficult to assess student drawings without written work, andanalysis of these drawings often requires student verbal
across engineering disciplines to predict interdisciplinary skills. At most, they predict 41% of the variance for industrial engineers; at least, they predict 16% of the variance for electrical engineers.8. For all engineering subdisciplines except industrial and general engineering (and engineering Page 22.519.12 seniors in aggregate), a student’s SAT critical reading score is a good predictor of their senior-year, self-reported interdisciplinary skills. Since the critical reading test is partly designed to assess analogical reasoning59, it stands to reason that students exhibiting this ability before matriculation would
]. Thispractice is done at nearly all institutions, however, the format that is followed varies widely. Thisinclusion is, typically, done through experiential learning techniques [4,5]. Two modes ofexperiential learning situations which are frequently used include internships and appliedresearch problems within the curriculum. The College o Engineering and EngineeringTechnology at Northern Illinois University deals has developed one mode of project and real-world integration through large-scale cross-disciplinary projects.Objectives and outcomes developed for each program detail what skills and knowledge eachgraduate will possess at the end of their studies. It is these objectives and outcomes which are atthe heart of the assessment process and also at
operations; heat transferoperations; mass transfer operations; and chemical reactor design. Over the three-year CCLIproject, activities/modules will be developed and incorporated into each of these courses, witheach activity/module focusing on a particular element from the process intensification spectrumand designed to also enhance vertical concept integration. This poster presentation focuses onthe activities and modules developed in Year 2. The preliminary assessment data collected fromYear 1 implementation are also presented.IntroductionThe chemical industry faces numerous challenges in the coming years due to decreasingavailability of raw material and energy resources. Thus, existing processes must operate in anefficient manner, with maximum
who provide engineering services which have a potential impacton the public health, safety and welfare. To accomplish that purpose, licensure laws stipulateminimum levels of engineering education and experience, and require that applicants passexaminations intended to assess technical competence. The state laws and rules also provide Page 22.598.4codes of professional conduct, requiring among other things that engineers hold paramount theprotection of the public health, safety and welfare, and stipulate disciplinary processes for thoselicensed professional engineers who are determined, following due process, to have not compliedwith the
international competitions, students are asked to complete surveys. Thesurvey covers a variety of topics, including the following: awareness and interest in ocean STEM Page 22.648.7careers, increased desire to take STEM courses due to involvement in the program,awards/honors received as a result of competition experience, and self-assessment of change inSTEM knowledge.Most of the regional competition surveys are conducted via paper forms later entered into SurveyMonkey. The international competition surveys are conducted in computer labs with directaccess to the web survey in Survey Monkey. Data is then extracted from the web system andanalyzed with
) Collaboration is essential (v) What students learn during their self-directed learning must be applied back to the problem with reanalysis and resolution (vi) A closing analysis of what has been learned from work with the problem and a discussion of what concepts and principles have been learned are essential (vii) Self and peer assessment should be carried out at the completion of each problem and at the end of every curricular unit (viii) The activities carried out in PBL must be those valued in the real world (ix) Student examinations must measure student progress towards the goals of PBL (x) PBL must be the pedagogical base in the curriculum and not part of a didactic curriculum (pp. 12-14
of assessment,analysis, and adjustment. Facilitating this process is an additional benefit for students that comesfrom the formal recognition by the Compact of the sequence of courses (shown above) through2 The full list of courses, course descriptions, learning objectives, the Memorandum of Understanding signed by Page 22.700.9participating institutions, and the list of signatory institutions in the Voluntary Mechanical Engineering TransferCompact can be found here: www.thecb.state.tx.us/mechanicalengineeringtransfercompact.the freshman and sophomore years. The consistent sequence of courses will make it possible totrack and
damping. ii Compute the natural frequency and predict the response for a one-degree-of- freedom system undergoing torsion vibrations, with or without damping. iii Compute the natural frequency and predict the response for a machine with a rotating unbalance.2. Students will have the ability to design and conduct experiments, as well as to analyzeand interpret data. (ABET Criterion b)Performance Criteria iv Practice vibration measurements on a structure using state-of-the-art equipment, rigor and documentation. v Analyze the data from an experiment appropriately. vi Assess the validity of the experimental results and compare with theoretical results when
faculty and research positions at universities across the country.The U.S. National Science Foundation created the ADVANCE program in 2001 to focus on developingcenters to increase the participation and advancement of Women in academic Science and Engineering(see http://www.nsf.gov/funding/pgm_summ.jsp?pims_id=5383). The ADVANCE program has 3funding areas: 1. Institutional Transformation (IT) – support systemic organizational approaches in higher education that will result in increasing the participation and advancement of women in STEM academic careers, 2. Institutional Transformation Catalyst (IT-Catalyst) – support organizational self-assessment activities that will result in issue identification and resolution of
the firstyear of implementing the corrective action program in the fall of 2008, the numbers roseby 18%. Student surveys and interviews are used to qualitatively assess the program andOU-ECE enrollment numbers are used as a quantitative assessment. I. Introduction:This paper has resulted from the need to correct the problem of reduced enrollments in Page 22.285.2Electrical & Computer Engineering (ECE) at the University of Oklahoma (OU). Afterstudying the situation in more depth it was noticed that our problems are similar to whatis occurring across the U.S. in engineering. A trend was noticed from the latest “Digestof Education Statistics
AC 2011-1050: COMPUTATIONAL EXPERTISE IN ENGINEERING: ALIGN-ING WORKFORCE COMPUTING NEEDS WITH COMPUTER SCIENCECONCEPTS.Claudia Elena Vergara, Michigan State University Claudia Elena Vergara. PhD Purdue University. Fields of expertise: Plant Biology and STEM Education Research. Dr. Vergara is a Postdoctoral Fellow at the Center for Engineering Education Research (CEER) at Michigan State University. Her research interest is in STEM education through research projects on instructional design, implementation and assessment of student learning, aimed to improve science, engi- neering and technology education.Mark Urban-Lurain, Michigan State University Director of Instructional Technology Research & Development