and URM students.Pre-transfer advising focused on providing students with the information they need to transfer toa specific computing or engineering program within the College. This process helped studentsdiscover how their credits from their previous or current institution(s) would apply to a programas well as a successful pathway for transfer. Students were referred to pre-transfer advisingthrough a variety of different methods such as: transfer fairs (in-person & virtual), communitycollege academic advisor, searching UNIV’s website, referral from UNIV Admissions Advisoror COEIT faculty. During transfer fairs, students were able to obtain copies of COEIT 4-yearplans and program gateway information. Students were also able to complete a
devise a solution(s) to improve the performance of the system. • Devise an inventory policy that minimizes the total annual inventory cost of raw material.For more information about the system and related concepts, the reader is referred to [15].3.2 CourseThe game was implemented in the second course of Operations Research (IE 425: StochasticModeling in Operations Research) in the IE curriculum at Penn State University, The BehrendCollege. The course introduces Poisson processes, Markov chains, queueing theory, inventorytheory, and dynamic programming. The course applies these models to manufacturing andservice systems. It is a required IE course that is taken by the upper-level students in thedepartment. The main topics
mentors and mentees used atleast 50% of the time in their responses on the Pre-SPR; however, only mentors used this codein both their responses to the weaknesses and 200-word justification. Mentors cited fiveadditional codes in common (C-1N, C-2N, C 3N*, M-5N*, and S-2P). Mentees had noadditional shared alignment of codes in the Pre-SPR.At the end of the peer mentoring program, mentors and mentees were more aligned in theirreviews of the Post-SPR manuscript. Both mentors and mentees used three codes (C-2N, C-4N,and E-3P) in at least 50% of their Post-SPR responses. Additionally, mentors and menteesconverged on their use of C-4N in both the weaknesses and the 200-word justification. Mentorshad one additional code (C-3N), and mentees had two
Pakistan, Habib University.Towards this end, the paper first sets the ground for comparing the two frameworks by formallydefining them in the next section, after which the salient differences between the two areidentified across various dimensions. At the end, some recommendations are presented to guidecongruent teaching of the two frameworks to engineering students.2. Definitions2.1. Engineering DesignA few formal definitions of design obtained from various engineering design textbooks arepresented below: ● “Engineering design is a systematic, intelligent process in which engineers generate, evaluate, and specify solutions for devices, systems, or processes whose form(s) and function(s) achieve clients' objectives and users' needs
Engineering Statistics (NCSES), “Diversity and STEM: Women, minorities, and persons with disabilities 2023,” National Science Foundation, Special Report NSF 23- 315, Alexandria, VA, 2023.[4] E. A. Cech and T. J. Waidzunas, “Navigating the heteronormativity of engineering: The experiences of lesbian, gay, and bisexual students,” Engineering Studies, vol. 3, no. 1, pp. 1-24, 2011.[5] E. Cech, “The (mis)framing of social justice: Why ideologies and meritocracy hinder engineers’ ability to think about social justice,” in Engineering Education for Social Justice: Critical Explorations and Opportunities, J. Lucena, Ed. Dordrecht: Springer, 2013, pp. 67 – 84.[6] S. Farrell, A. Godwin, and D. M. Riley, “A
Education at the University of Nevada, Reno. There she completed her Bachelorˆa C™s and is working on her Master of Science in mechanical engi- neering. Her research focuses are on undergraduate engineMs. Rachael Ciara Young Rachael has experience working in kindergarten through college engineering education and is passionate about fostering access and excitement for STEM studies. She graduated with dual bachelor’s degrees in electrical engineering and environmental science in 2022. Rachael currently works in aerospace with an emphasis on avionics and electrical power systems.Ms. Indira Chatterjee, University of Nevada, Reno Indira Chatterjee received her M.S. in Physics from Case Western Reserve University, Cleveland
lack oftransparency about university process; workload; role conflict [34]; the political landscape; andimpostor syndrome [35]. Satterfield et. al [30]. noted that the pool of research on the graduatestudent experience in STEM was limited and compiled a comprehensive literature review in2018 to set the stage for future work. The summary focused on the experiences of graduatestudents during their studies, and how individual factors (the influence of the student’s advisor),programmatic factors (isolation and teaching assistantships), and external factors (work-lifebalance and family influence) influence their persistence in the field [30]. Berdanier et al.’s [36]study of social media forums found that among the factors influencing attrition in
. Participants were then recruited, given consentinformation, and scheduled to participate.During the scheduled interview times, in an initial briefing, the participants were asked torecord verbal consent, given information about the study including instructions on how tothink aloud and respond, and given an opportunity to ask clarifying questions about the CImethod. Then participants were shown the survey and responded aloud to how they wouldanswer survey items. The interviewer(s) asked concurrent probing questions as participantsanswered these questions aloud, and at the end of each section of related items, theinterviewers asked broader retrospective questions. These questions included assessing theoverall clarity and design of the study, the
experiences of faculty of color pursuing tenure in the academy. Urban Review, 41(4), 312–333. https://doi.org/10.1007/s11256-008-0113-yDowdy, J. K., Givens, G., Murillo, E. G., Jr., Shenoy, D., & Villenas, S. (2000). Noises in the attic: The legacy of expectations in the academy. Qualitative Studies in Education, 13(5), 429–446. https://doi.org/10.1080/09518390050156396Goldberg, C. E., & Baldwin, R. G. (2018). Win-win: Benefits of expanding retirement options and increasing the engagement of retired faculty and staff. New Directions for Higher Education, 182, 69–74. https://doi.org/10.1002/he.20281Guramatunhu-Mudiwa, P., & Angel, R. B. (2017). Women mentoring in the academe: A faculty cross-racial
://www.canadianconsultingengineer.com/features/status-of-the-canadian-consulting- engineering-industry/ (accessed Mar. 12, 2023).[17] N. Malhotra, “The Nature of Knowledge and the Entry Mode Decision,” Organization Studies, vol. 24, no. 6, pp. 935–959, Jul. 2003, doi: 10.1177/0170840603024006006.[18] N. Malhotra and T. Morris, “Heterogeneity in Professional Service Firms,” Journal of Management Studies, vol. 46, no. 6, pp. 895–922, 2009, doi: 10.1111/j.1467- 6486.2009.00826.x.[19] S. Pantic-Dragisic and E. Borg, “Creating the mobile engineer: a study of a training program for engineering consultants,” EJTD, vol. 42, no. 7/8, pp. 381–399, Oct. 2018, doi: 10.1108/EJTD-12-2017-0117.[20] S. Pantic-Dragisic and J. Söderlund, “Swift transition and knowledge
justpartially agreeing that an official document distributed by the Ohio Department of Taxation wasrealistic, when in fact the specified procedures listed in such government documents serve as a“gold standard” that all corporate entities operating within the state must adhere to. To obtainadditional information from students regarding this aspect of the programming assignment, twoqualitative questions were included with the survey. For the question, “in what way(s) do youbelieve that learning to correctly compute sales tax is important?” 29 (out of 33) responses werereceived. Most students responded in similar ways, in that such computations are “used everysingle day” as “it is a necessary part of any business’s functions, so its accuracy is
. Mehta, “Sustainability Across the Curriculum,” Int. J. Eng. Educ., vol. 23, no. 2, 2007.[2] J. S. Cooper, “Evolution of an interdisciplinary course in sustainability and design for environment,” Int. J. Eng. Educ., vol. 23, no. 2, pp. 294–300, 2007.[3] C. I. Davidson, C. T. Hendrickson, and H. S. Matthews, “Sustainable engineering: A sequence of courses at Carnegie Mellon,” Int. J. Eng. Educ., vol. 23, no. 2, pp. 287–293, 2007.[4] M. K. Watson, J. Pelkey, C. Noyes, and M. O. Rodgers, “Using Kolb’s Learning Cycle to Improve Student Sustainability Knowledge,” Sustainability, vol. 11, no. 17, p. 4602, Aug. 2019, doi: 10.3390/su11174602.[5] A. S. Lau, “Green design in first-year engineering,” Int. J. Eng
75th percentiles,respectively, and the whiskers extend to data points not considered to be outliers. Outliers areplotted as red +’s. If there are no boxes, then all responses besides the median response areconsidered to be outliers.Figure 1: Statistics for responses to survey question 1: How would you rate your study habits whilelearning remotely as compared to learning in person? 1=better in person, 7=better remotelyFigure 2: Statistics for responses to survey question 2: How would you rate your access to re-quired technology (e.g., computer and internet) while learning remotely as compared to learningin person? 1=better in person, 7=better remotelyAs shown in Figure 1, students generally reported a significant negative impact of
survey. Most of them are from Texas. Our next study willcertainly sample a large number of participants that better represent the population of the USA inthe warehousing and industrial distribution industry. For example, we could choose some areasin the country that have the greatest number of warehousing and distribution centers. These areashave vastly different cultures and environments. This way, the results of the study would includea better reflection of how the future of work would impact varying cultures, thus providing abetter insight into how employees and managers would be willing to accept the changes neededto incorporate new technologies into the work environment.References:[1] S. S. Bhattacharyya and S. Nair, "Explicating the
]. Available: http://arxiv.org/abs/1904.09408.[9] T. Mikolov, K. Chen, G. Corrado, and J. Dean, “Efficient Estimation of Word Representations in Vector Space,” arXiv:1301.3781 [cs], Sep. 2013, Accessed: Nov. 06, 2020. [Online]. Available: http://arxiv.org/abs/1301.3781.[10] J. Pennington, R. Socher, and C. Manning, “GloVe: Global Vectors for Word Representation,” in Proceedings of the 2014 Conference on Empirical Methods in Natural Language Processing (EMNLP), Doha, Qatar, Oct. 2014, pp. 1532–1543, doi: 10.3115/v1/D14-1162.[11] J. Firth, A synopsis of linguistic analysis. Oxford, UK: Blackwell, 1957.[12] S. Crossley, J. Ocumpaugh, M. Labrum, F. Bradfield, M. Dascalu, and R. S. Baker, “Modeling math identity and
askedparticipants to describe ways to improve entrepreneurship education programs, with specificattention to women faculty experiences.Table 1. Description of Participants Participant Race and Gender Discipline STEM Entrepreneurship Positionality Education Programming Participation Status (Yes/No) Dr. J Black woman (she/her) Engineering No Dr. Sh Black woman Engineering No (she/they) Dr. C Black woman (she/her) Engineering No Dr. W Black woman (she/her) Engineering Yes Dr. S Black
, the course, or the specific faculty member. This study aimed tounderstand the needs of engineering faculty members, especially those who had not workeddirectly with the engineering librarian for library resource instruction. The study was modeledafter a similar multi-site study conceived and organized by Ithaka S+R, a not-for-profitorganization that provides guidance and support for academic and cultural communities, thatexplored the teaching needs of business faculty members [3]. Interviews were conducted withfaculty members from the departments of Mechanical & Aerospace Engineering and Industrial &Systems Engineering in the summer of 2020. This paper examines the main teaching themes thatemanated from the analysis of the interview
dynamics in requirementsengineering will be underexplored, yet important for the practical use of this body of knowledge.This paper will support future work on the impact of requirements engineering education at theundergraduate level, as well as informing frameworks for understanding professionalrequirements engineering work.References[1] C. L. Dym, A. M. Agogino, O. Eris, D. D. Frey, and L. J. Leifer, “Engineering design thinking, teaching, and learning,” J. Eng. Educ., vol. 34, no. 1, pp. 65–65, 2006.[2] D. P. Crismond and R. S. Adams, “The informed design teaching and learning matrix,” J. Eng. Educ., vol. 101, no. 4, pp. 738–797, Oct. 2012.[3] C. J. Atman et al., “Engineering Design Processes: A Comparison of Students and
Adaptive Expertise. Educational Research and Reviews, Vol. 12, pp.14–29.Bransford, J. and B. Stein (1984). The IDEAL Problem Solver. New York: W. H. Freeman.Bransford, J., A. Brown & R. Cocking, Eds. (1999). How People Learn: Brain, Mind, Experience, and School.National Academy Press: Washington, DC.Bransford, J., Stevens, R., Schwartz, D., Meltzoff, A., Pea, R., Roschelle, J., Vye, N., Kuhl, P., Bell, P., Barron, B.,Reeves, B., & Sabelli, N. (2006). Learning Theories and Education: Toward a Decade of Synergy, in P. A.Alexander & P. H. Winne (Eds.), Handbook of Educational Psychology, pp. 209–244. Lawrence Erlbaum AssociatesPublishers.Brophy, S., Hodge, L., & Bransford, J. (2004). Work in Progress - Adaptive Expertise: Beyond Apply
stereotypes regarding AfricanAmericans academic capabilities, their numerical majority status within the HBCU context actsas a buffer enabling them to perceive their racial and professional identity as compatible andintegrated. On the contrary, the numerical minority status of African American engineeringstudents in PWI exacerbates their vulnerability to feel threatened by the negative stereotypesabout their group. Even as they struggle to maintain a positive ethnic identity, they question thecompatibility between their ethnic and professional identities. As Du Bois states, it is the tensionthat impedes “fluid participation in Black world(s) and white world(s)”. It is for this reason thatAfrican American engineering students in PWIs may struggle more
2007 ASEE Summer School, Pullman, WA. 2. E. Seymor and N. Hewitt, Talking about Leaving: Why Undergraduates Leave the Sciences, Westview Press, Boulder, CO, 1997. 3. K. Solen and J. Harb, “An Introductory ChE Course for First-Year Students”, Chem Eng. Ed., 32 (1), 52 (1998). 4. D. Visco and P. Arce, “A Freshman Course in Chemical Engineering: Merging First-Year Experiences with Discipline-Specific Needs” Proceedings of the American Society for Engineering Education, 2006. 5. S. G. Sauer, “Freshman Design in Chemical Engineering at Rose-Hulman Institute of Technology” Chem. Eng. Ed., 38 (3), 222 (2004) 6. C. Coronella, “Project-Based Learning in a First-year Chemical Engineering Course: Evaporative Cooling”, Proceedings of the
and experiments in fluidmechanics, they generally do not possess the capabilities to perform hydrodynamic testing. Thispaper will present the work by the authors to develop a water flume that would allowhydrodynamic testing at velocities up to 2.0 m/s. The flume was constructed by anundergraduate and at a cost lower than commonly available commercial units. Both thefabrication process and the potential experiments that the flume could house are designed toimprove student learning in the area of fluid mechanics. The design is developed to be relativelycompact, with a 7’x3.5’ footprint and utilizes a commonly available single-stage centrifugalpump. Flow velocities in the test section can be varied passively by changing the insertcontaining the
, skills, and ability to solve complexproblems and to produce excellent solution(s) within the structure of the team. This concept wasfurther developed to include defining team and task, team climate, communication, and reflection(for a detailed description, please see Table 1)23-26.Design competence focused on finding and evaluating variants and recognizing and solvingcomplex design problems. These were further defined as having the ability to discover and designmultiple solutions to a given problem and to effectively evaluate those solutions to determine thebest solution, and having the ability to see the overall picture of a complex design problem, thenbreaking it into smaller, more manageable parts to solve while keeping the overall problem
wish to thank T.J. Nguyen for his work on the CyberAmbassadors project. We alsoappreciate the support and engagement of the many organizations partnering with theCyberAmbassadors project, including Tau Beta Pi, ACI-REF, CaRRC, the Carpentries, NRMNand CIMER. This material is based upon work supported by the National Science Foundationunder Grant No. 1730137. Any opinions, findings, and conclusions or recommendationsexpressed in this material are those of the author(s) and do not necessarily reflect the views ofthe National Science Foundation.References[1] H. Neeman et al., “The Advanced Cyberinfrastructure Research and Education Facilitators Virtual Residency: Toward a National Cyberinfrastructure Workforce,” in Proceedings of the
]. New SCCT models were developed to explain vocational satisfaction and well-being [10,11], and career management [9]. At the core of the original SCCT model, and most of the SCCTmodels that followed, are self-efficacy (i.e., confidence in the ability to successfully perform adomain-specific task, like a specific engineering skill), outcome expectations (i.e., anticipatedoutcomes of a particular behavior), interests (i.e., patterns of likes/dislikes for career activities),and goals (i.e., determination for a particular outcome). Taking this one step further, Lent etal.’s [9] integrative social cognitive model of academic adjustment, derived from both SCCT [1,2] and the social cognitive model of academic satisfaction [10, 11], explains how
appropriate realistic constraints, including consideration of health, safety, etc., to the engineering problem for the capstone design. Measure: Evaluated in final CPEN 3850 report • Competency: Students demonstrate ability to generate effective solution(s) to the capstone design problem formulated in CPEN 3850, including identified constraints. Measure: Evaluated in final CPEN 4850 report [1]Thus, in order to determine whether students can both identify and apply appropriate standardsand constraints, and apply these in an engineering design, it was decided that it was necessary toevaluate students continuously working on a project; therefore, measuring in sequentialsemesters was specified. Other required
Career Guidance Short- & Long-Term Goals Parent & Family STUDENT-SPECIFIC BELIEFS Encouragement of activities Activity Choice & Expectations for Student s Opportunities to learn various Engagement Achievement skills Performance Specific Socialization Goals Reinforcement Patterns Perceptions of: Other Communications of Beliefs -- Student s Abilities -- Value of Various Skills -- Student s interest
), white board(s),projector(s), and printer(s). The author was the professor of record and independently designedthe course based on Purdue University CLOOs. In course planning and preparation, theinstructor adopted a learning-centered paradigm, while using a Learning Management System(LMS) (i.e., Blackboard) for course organization, file sharing, assignment posting/submission,grading, and testing. The instructor’s goal was to create a learning environment in which studentscould learn to restructure the new information and their prior knowledge into new knowledgeabout the content, and practice using it. Course design included a combination of mini/bridginglectures (as needed), readings, group discussions, exams, assignments, and a team project
Group 2 identified by applying the separation criteria RV249 and RV242). Note that while eachof these separation criteria identifies distinct groups, the group characteristics are very different. (a) (b) (c) Figure 3: For course 1’s top two separation criteria (RV249 and RV242 shown in (a) and (c), respectively), the response pattern statistics for the applied science course result in distinct response groups (labeled Group 1 and Group 2, matching the labels from Figure 2). The dimensions that are unaffected by the criteria (i.e., personal interest and university application for RV249; fit with lifestyle for RV242) remain consistent (within
and Their Pedagogical AssessmentAbstractImparting real world experiences in the classroom for a software verification and validation(S/W V&V) course is typically a challenge due to lack of effective Active Learning Tools(ALTs). At Robert Morris University (RMU, the author’s institution), this educational resourcegap has been addressed by developing several ALTs in the form of class exercises, case studies,and case study videos that were created by collaborating with the academia and industrialprofessionals. Through this three-year work 20 delivery hours of case studies, 18 delivery hoursof exercises and 6 delivery hours of role play videos totaling 44 delivery hours of Software V&Vcourse materials have been developed. The developed