connect withone another and reflect on the information they have been exposed to throughout the day.As shown in fig. 6, the majority of teachers have already used, or are intending to use the activitykit provided. Some have even mentioned using activities from the website that were not part of thetrack they attended at the workshop but fit their classroom curriculum. There was a wide breadthin the ways teachers implemented their classroom kits. Some teachers mentioned they use theactivity as an introduction to a new concept, while others used them as hands on reinforcement ofa concept they had already taught in a traditional fashion. Teachers who used the kits mentionedthat they encouraged them to try new teaching strategies in their classrooms
-Technologist [30], [31] and sequencing exercises such as explaining how to put on a coat verbally to another girl. 7. Expand data collection to include reflection, usually in the form of exit slips at the end of class. 8. Design tools specifically targeted at the CT skills and practices relevant in the lesson of the day. 9. Add real-time in-class data collection hardware, such as Swivl video systems to capture conversations at multiple locations in the classroom.Data Analysis. Quantitative data, such as the engagement surveys, will continue to be analyzedby descriptive analysis. The small participant size excludes the application of popular methodsfor affective construct analysis. All qualitative data will continue
have been skewed by thepresentation of the topics in classes and the assignments. However, the data was collected across6-7 sections of the course taught by different instructors in each of the two years during whichdata was collected. Therefore, the data should reflect some averaging. For example, if oneinstructor taught sustainability well and with enthusiasm in one class, while another taught thetopic poorly, then the responses of students from one class should offset the responses from theother class when the data is pooled.Summary and Conclusions A survey-based study of first-year engineering students was conducted at the University ofNew Haven to determine their personality types and interest in topics such as visualization
modernized bachelor-level program at BSU’s MBE Department was developedbased upon a range of stakeholder inspirations, one of the most critical being student feedback.Through course evaluations and direct reflection of learning, undergraduates had requested moreflexibility with class selection, more hands-on engineering, and more themed learning tracks.The faculty recognized these inquiries to be of similar premise to those presented by numerousmechanical engineering education reform initiatives and publications. In these documents, thediscussion of the disassociation between industry needs and what mechanical engineers new totheir careers are prepared to provide is relentless. With the understanding that the presentcurriculum had not been
hands-on immersion experience at FERL (describedpreviously) and co-enrollment in numerous course offerings. This knowledge helps createsbalanced teams which is critical to ensuring healthy competition in the fourth phase. During the competition, teams assume the identity of a design-build firm, dividing upindividual roles by sub-discipline as outlined previously. Team leaders are charged withproviding overall guidance and ensuring the final products reflect a fully coordinated design andconstruction plan between sub-disciplines. Teams compete to “win” the job by having the mosttechnically sound approach and best integrated design. Examining Table 1 highlights a few important similarities between The Crucible and theASC design-build
course ends (e.g., as peer tutors or project mentors), • help improve the course (e.g., by creating new active-learning exercises over the material, or scoping out new technological developments that could be incorporated into the course), and • keep you in contact with current industrial practice (e.g., by serving as a scrum master or training others in the practice).This way of looking at a course reflects a subtle, but important, difference in devising courseprojects. The question is not, How can I specify projects that will familarize students with thecourse content? but rather, How can I design projects that will help students find their role inpromoting their own learning and that of their classmates? This
differentiatedhigher education market. The prevalence of these rankings in the public mind have promptedmany universities to strengthen their enrollment management strategies in order to expandenrollments, maintain better balance across enrollment swings, and to manage their discountrates (amounts offered through financial aid) to keep their institutions solvent—a pressure that islikely only to intensify due to the fiscal impacts of the current COVID-19 pandemic. Manyinstitutions report that the downside of national rankings is that they do not accurately reflect thequality of education offered by their institution, and therefore do not make for an efficientmarket. Indeed, our data point to specific gaming behaviors, often tuned to the algorithmsemployed by
or recommendations expressed inthis material are those of the authors and do not necessarily reflect the views of NSF.References[1] L. Farrell, “Science DMZ: The fast path for science data,” Sci. Node, May 2016. [Online]. Available: https://sciencenode.org/feature/sciencedmz-a-data-highway-system.php[2] E. Dart, L. Rotman, B. Tierney, M. Hester, J. Zurawski, “The science dmz: a network design pattern for data-intensive science,” in Proceedings of the International Conference on High Performance Computing, Networking, Storage and Analysis, Nov. 2013.[3] “NSF 2017 PI Workshop CI Engineer Breakout Survey.” [Online]. Available: http://www.thequilt.net/wp-content/uploads/NSF-2017-PI-Workshop-CI-Engineer- Survey_v4.pdf[4
about. In contrast,amongst women born overseas, more explanation was needed, both on their part and mine. Thiswas reflected in their opening narratives as well.Here is Kalpana, a young engineer who was educated in India and came to the United States forgraduate school: Me: How did you become interested in engineering as a career? Kalpana: So I think the main reason goes back to my family, and what my parents, even my grandfather, what they did, how they thought about things. That’s what got me into physics or math or engineering in general. My grandfather was a schoolteacher and eventually the principal of the school. He never got to study more than a bachelor’s level. In spite of that, the amount of
storage spaces, build spaces, andworkbenches. High-resolution tool-use data collection is set to begin spring of 2020 at TexasA&M, including details that will remove some of these limitations.Because of these limitations a hypothetical dataset was created to reflect student-toolinteractions. This hypothetical dataset is guided by current data and engineering curriculum forTexas A&M, so the results are reasonable. These results present a picture of the design advicemodularity analyses will be able to provide once additional data is available.Hypothetical student-tool network creation © American Society for Engineering Education, 2020 2020 ASEE ConferenceA hypothetical-realistic
demonstration; come to a consensus on their interpretations of the concepts; orcomplete a quick example of each concept. A key component of the interactive lecture is that no“solution” slides are provided. The teams must work through the calculations or reflections togain a complete set of slides. This forces all students to engage in the lecture. Answers are sharedout in the larger group and the instructor guides the discussion of the answers so as to ensure acommon understanding of the concepts.Our initial assessment shows a marked improvement in student understanding of the relevanthydrodynamics concepts necessary to designing an underwater vehicle. Students are able toconverse more knowledgeably on hydrodynamics, and the ROV designs are more
and the breakdown of each assignment in the project (i.e. market analysis, business model…) • It was cool • The project was interesting and realistic data collection process was good to experience • Let’s you reflect on what I’ve learned • I liked the real world applications and going over data analysis techniques • It was well rounded, showed another side to research • I liked how we went through the whole process in regards to creating and running a study • Benefited senior project exploration, technical writing and formatting skills • Working on real world problems • Project based class • I liked how we had freedom to decide what we wanted to do for our human performance project, it
completion of the group project proves untrue. Though this is the case, it is worth noticing that team dynamics in Section 1 deteriorates in a statistically significant manner (see Table 7 where t = 1.38, nu = 29, and p<0.05) whereas there is no statistically significant difference when comparing answers to Question 2 (Q2) for pre- and post-project survey results in Section 2—see Table 12 where t = 0.83, nu = 41, and p>0.05. This is also reflected in the respective median score as that of Section 1 decreases from 9 (pre-project) to 8 (post-project), while that in Section 2 stays constant at 8. Put differently, the answers to
community colleges that can supportand facilitate their transition into community college faculty positons.9 AcknowledgmentsThis material is based upon work supported by the National Science Foundation under Grants No.1723209 and 1723245. Any opinions, findings, and conclusions or recommendations expressed inthis material are those of the author(s) and do not necessarily reflect the views of the NationalScience Foundation.10 References[1] R. W. Fairlie, F. Hoffmann and P. Oreopoulos, "A Community College Instructor Like Me: Race and Ethnicity Interactions in the Classroom," The American Economic Review, vol. 104, no. 8, pp. 2567-2591, August 2014.[2] A. Perrakis and L. S. Hagedorn, "Latino/a Student Success in Community Colleges and
DiscussionBy fall 2019 semester, about 260 students had participated in the online survey, 68.92% male,and 30.28% female and 0.8% identified as other. The online survey addressed pre-college,family background, campus life and faculty interaction, peer interaction, extra-curricularactivities, internship experience, and social life. Charts reflecting this data can be seen inAppendix C. Of those surveyed, 41.67% were Mechanical Engineering students, 13.33% wereBiomedical Engineering, 18.33% Civil Engineering, 16.67% Chemical Engineering, 8.33%Electrical Engineering, and 1.67% Engineering Entrepreneurship.When surveyed about family background, almost 29.49% of the participants responded that theyhad an immediate family member in the engineering field. As
% 39% Yes No No 52% 61% 78% Figure 3: Association with minority groups of the 23 study participantsWith the demographic context provided by Figure 2 and 3 in mind, the main result of our studyso far is the master codebook itself, as shown in Table 2. The codebook follows the hierarchicalstructure depicted in Figure 1, and is divided into six topics: engineering discipline, engineeringexperience, engineering connection, support for success (during college), obstacles anddeterrents (during college), and reflection on engineering identity. Within this
plugging the resistors into ablinking LED circuit to determine the relationship between LED brightness and resistorstrength. The weak resistor showed a bright LED, while the strongest resistor displayed nolight. Each lesson in the MMC was designed to highlight the microcontroller's software forspecific CT skills. Students trained to read circuit diagrams by plugging the expected pins onthe Arduino board; most circuit activities in MMC are comprised of LED lights and buttons.Ultrasonic sensors were introduced within the Arduino IDE, and text-based programminglanguage was used to teach students how to reflect the Scratch structure. As a result, studentslearned to correlate how the blocks programming corresponds to real-world coding. On
between the ages of three to five years acquire these skills. The second development stagereferenced by Piaget is visualizing objects in three-dimensional forms and being able to perceivethese objects from different dimensions via mental rotation. Students typically acquire this skill byadolescence for objects they are familiar with [24]. He cautions, however, that if the object is notfamiliar, students may have difficulty in visualizing the object even while in college. Piagetclassified projection skills as the third stage, where students can visualize different measurementsand combine them such as distance, rotation, volume, translation, and reflection [24].Theoretical PerspectiveThis study evaluates the literature through the lens of a social
choice of major was correct shouldreduce the likelihood that the student will change majors, which can extend the time tograduation.Results of pre- and post-bootcamp surveys demonstrated improved self-confidence regardingskills important to their majors, particularly in their ability to learn and apply math concepts, aswell as an increased sense of belonging in the major. The authors also assessed the ALEKSmathematics learning tool as a means to improve students’ math skills. Evaluation of the impactthat PBL modules had in helping students recognize the importance and application ofmathematics in their chosen fields and the faculty reflections on the bootcamp are still inprogress. Data on participants’ success in Fall 2019 math courses and
without fear of repercussions [18]. When groups lack voice safety, the benefitsof incorporating diverse perspectives cannot be realized [19].Voice safety is an important aspect of good group decision making, and it is related to thehierarchical decision making described above. An individual might perceive a lack of voicesafety for a variety of reasons, including actual enforcement of power differences within a groupbut also including differences in expectations regarding conversational rituals [20]–[22]. Items inthe survey were based on validated items from [18], though language was changed to reflect theproject team context.Sense of Belonging and CommunityA sense of belonging is when a student feels as if they fit in and belong to a community
career following the REU experience.Acknowledgement: This research was supported by a REU Site grant from the National ScienceFoundation (# EEC 1757882). Any opinions, findings, conclusions, or recommendationspresented are those of the authors and do not necessarily reflect the views of the National ScienceFoundation.References 1. Aggies Invent : Solving Problems in 48 Hours, Engineering Entrepreneurship program, College of Engineering, Texas A&M University, https://engineering.tamu.edu/student- life/aggies-invent/index.html (accessed, May1, 2020). 2. Nepal, B., Pagilla, P. R., Srinivasa, A., Bukkapatnam, S., Moturu, P., 2019, “Preparing Next Generation of Manufacturing Leaders: A case of REU site in Cybermanufacturing
eagerness to program the robots. Besidesbeing exposed to advanced mathematical material, the teachers were able to use this to bridge intoother academic areas. To help their students learn to identify angles, teachers used sentence wordgaps (shown in Figure 2), a technique commonly used in teaching language arts.Figure 2: A first-grade teacher at an elementary school, using the sentence word gaps to teach earlyelementary students the angles they need to program the direction of the robots.BOTS consisted of a series of progressive PD sessions held for three hours on a Saturday morningalmost monthly throughout the academic year. Each session built upon the previous and gave theteachers the opportunity to reflect and receive feedback on their
reading more and more. This class has opened my eyes to what I want to do. It allows a person to really self-reflect on their opinions and career goals. I learned how much work takes to make a research paper, and the time to make sure you understand the main goals of the experiment. I learned how to breakdown a scientific paper, and I was interested to … research opportunities that I wouldn’t have known of otherwise. Breaking down the research process and explaining how it’s done. Then being able to examine research that has been conducted helped to understand the process better. Learning to actively look for jobs in detail and make sure
asked to reflect on their choice ofuniversity and major, as well as their experiences with courses and assessment. Furthermore,participants were asked to speak about various aspects of their social experience thus far in theiruniversity career, including the disciplinary makeup of their friend group and their participationin disciplinary professional societies and other extracurricular activities. Interviews lastedapproximately one hour each. The recordings were sent to a professional transcription serviceand were checked once more by the research team to ensure the accuracy of the transcript.AnalysisThe process for this analysis began with familiarization with each of the individual participant’sinterview transcript. Each was read first for
important factor in a potential faculty member’s decision to join.Additionally, PhD students play a vital role in mentorship of undergraduate students, serving asteaching assistants in courses and as mentors in the laboratory. Graduate students can beparticularly influential role models for undergraduates considering research careers. Finally,graduate students that go on to successful careers in a variety of sectors plays a crucial part inexpanding the reputation of the School. Their success is a direct reflection of the laboratoriesand faculty that mentored them.Just as important as the number of graduate students is the diversity of the student body. TheNational Science Foundation (NSF), other members of the National Academies, and the USCongress
elementary students, and in discussing possible pathways intoengineering with the elementary students. Perhaps these changes could improve the impact of theWP on college students, and provide further evidence for positive impacts on the elementarystudents.AcknowledgementThis research received no specific grant from any funding agency in the public, commercial, ornot-for-profit sectors. Any opinions, findings, conclusions, and recommendations expressed inthis paper are those of the authors and do not necessarily reflect the views of the university.ReferencesBielefeldt, A. R., & Canney, N. (2014). Impacts of service-learning on the professional social responsibility attitudes of engineering students. International Journal for Service
inFigure 8a and b, respectively. Students in Group B were substantially more confident inunderstanding the project geometry compared to Group A, which was reflected in theirrespective scores on the problems. A total of 79% of students in Group B noted they eitheragreed or strongly agreed that it was easy for them to understand the geometric parameters. Only37% of students from Group A found it easy (agreed or strongly agreed) to comprehend theproblem by having access to 2D model. The survey also showed that Group B participants werequite confident in their understanding, despite many of the students making minor errors inunderstanding the nailing details in the problem. (a) (b)Figure
students to reflect on how useful ClassTranscribe was for learning, preparing examsand working on assignments. Students reported favorable and similar utility in all threecategories (see the Lickert results presented in Fig. 5). Only one respondent chose “Not at alluseful.” Figure 5. Survey responses to the utility of ClassTranscribe for learning, preparing for exams and working on assignments in a bioengineering sophomore required laboratory course. Note for comparative visualization purposes, we conservatively represent “moderately useful” as a neutral response.These results are congruent with the survey results from earlier surveys in ECE and CS coursesthat have larger sample sizes which we report in the next section.The
Center 5. Continue the engineering specific tutoring and provide the engineering cohort leadership opportunities and a community in which they feel they can belong. 6. Create a programmatic pre-engineering track. This material is based upon work supported by the National Science Foundation under Grant No. DUE-1832553. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation. Approved by the City Colleges of Chicago IRB (IRB2018007). 11[1] T. D. Holmlund, K. Lesseig, and D. Slavit