code for creation and analysis of a cam profile.%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%Program Name: CamAnalysis%%Program Description: Analyzes and Creates Cam Profile%%Inputs: Number of Zones and the Parametersassociated with% each%%Outputs: S,V,A,J Curves, Force, Power, Torque,Pressure Angle,% and Cam Profile Plots. Tabular Data Sets.Max Values.%%Date Created: 11-5-2016%%Revisions:%%0) 11-5-2016 Creation%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%clearclc%Parameters%s_harmonic = @(h,theta,Beta,Beta_time) h/2*(1-cos(pi*theta/Beta));v_harmonic = @(h,theta,Beta,Beta_time)pi*h/2/Beta_time
assessment instruments.III. E XPERIMENTAL S TUDY D ESIGNBuilding on the related research and pedagogical underpinnings in Section II, we consider herethe design of the experimental study. The primary hypothesis of the research study is as follows:“There exists significant improvement in the engagement, student interest, and motivation forsoftware engineering content using an integrated approach of active and deign-based learningcompared to traditional teaching approaches.” Traditional approaches refer to a combinationof lectures, tutorials and lab sessions for a software engineering course.To test this hypothesis, the experimental study included the design of software-engineeringcourse content, coordination of the study’s control (traditional) and
m questionns for the daay; see Sectiion 3.3. Thesequestions provided th he rationale for coveringg the materiaal on a particcular day. When W viewedd atthe end of o the semestter the questtions represeented a frameework withinn which the course wasorchestraated and a means m for the students to frame their Semester S Leearning Essaays.3.1 Courrse organizaationThe relattionship betw ween the teaam organizattion and the course c conteent is displayyed in Figuree 2
questions are presented in Table 4.Table 4 – Survey questions administered to participants. # Survey Questions and their Intended KSBA Model Elements SQ1 What ideas, concepts, knowledge, or facts have you learned? (K) SQ2 What skills have you developed? (S) How have some of your behaviors, habits, or practices changed, and/or what are SQ3 new ones that you have developed or adopted? (B) How have some of your attitudes or beliefs changed, and/or what are new ones SQ4 that you have developed or adopted? (A) Based on what you now know and have studied, how do you understand the idea SQ5 of Sustainability? (K) What
assignment(s). Cheating students would struggle to answer questions abouta paper they did not write, and the teacher would be more easily alerted to deceptive acts. Therefore, Agile educationcould increase student accountability, and perhaps deter cheating. Additionally, the rising use of large-scale, transformer-based models in daily life is apparent: students have and willuse them during the course of their education [16]. It may be possible, however, to ameliorate this seeming dilemma.Students could be required to use GPT or BERT for particular assignments, where they must then edit, revise andannotate the automatically generated assignment through their own effort, showing, with references or sound reasoning,how the model arrived to this
theparticipant to select an answer or multiple answers to a question, which correspond to one of thefour learning styles, each participant’s answers for each learning style were totaled. 1. Difference in Brain ActivationThe brain activations were averaged across all brain waves and across all brain regions for eachDesign Problem. Utilizing a t-test, it was determined that there were significant changes in brainactivations across multiple regions and across the varying waves. To further the conclusions ofthe results, a t-test was applied to each set to the individual brain waves to decisively determinewhich brain wave(s) and brain regions caused these strong correlations. The results of this testindicated that the Beta Low frequency was the most
accommodation does not appear to work witha course structure, the disability office can often help to adapt the accommodation to the course.3) Do not ask students to disclose their disabilities.When a student has obtained accommodations through the university, they have gone throughthe process of providing their official diagnosis(s) and the appropriate paperwork for experts todetermine their accommodations. The information an instructor receives will simply state thatthe student has a disability, and will outline the associated accommodations, but will not revealthe disability diagnosis. While it might seem like a harmless question, an instructor asking astudent to disclose their disability can be a frightening thing.1,28 Students are not obligated
the formal introduction of SLRs to the field of engineering education in 2014by Borrego and colleagues, increasing trends in SLR use and impact were observed. While thegoal of SLRs is to answer a clearly formulated (set of) research question(s), the goal of SMRs isto define and describe the broader landscape of existing scholarly research on a topic. In this way,SMRs may be particularly useful for defining the scope of follow-on SLRs in engineeringeducation research.Keywords: literature reviews, systematic maps, systematic mapping reviews, systematic literaturereviews, engineering education Introduction The field of engineering education research (EER) has experienced rapid growth since
from each identified document according to the following criteria:author/s, publication date, document type, purpose, study design/methods/sample, and outcomesor conclusions.Stage 5. Collating, summarizing, reporting results There were 90 papers identified from the first two databases that included “graduateprogram director” and “engineering” as search terms in the title/abstract/subject and 70 identifiedresults in the last database that searched specifically for “graduate program director” in all fields.In the screening phase, a total of 147 were screened and 134 excluded followinginclusion/exclusion criteria which included the title and abstract review and a skim of the fulltext when needed, thus leaving 13 records for analysis
search inquiry keywords were personal narratives, stories, engineering, classroom,university, college, students, STEM, education, intervention, pedagogy, and psychology. Throughiterative searching using these keywords, some new keywords were added (e.g., expressivewriting intervention) and removed (e.g., students). Ultimately, we ended up using the followingkeywords: engineering, education, narrative(s), personal narrative, storytelling, story, stories, 5psychology, STEM, college, university, expressive writing intervention, pedagogy, curriculum.At the same time, our target samples were post-secondary students in higher education, such thatwe
three caregivers enacted over the course of a five-month engineering program conducted in an out-of-school context. Our research question was asfollows: What roles do caregivers enact with/for their child during a family-based engineeringdesign project? Subsequently, we considered the contextual factors of the program that seemedto influence and shape caregivers’ role enactment. Results of our work provide further evidenceof the impact of caregiver inclusion in the process of learning engineering, not only on thestudent(s) involved, but also on caregivers. Findings support the benefit of incorporating familiaradults into the engineering learning process, while providing distinct avenues by whichcaregivers might acknowledge and value their own
culturally heterogeneous process where peopleengage in various repertoires of practices and literacies rooted in different communities [12],[13], [14]. Learning is revealed to be a collective, communal, reciprocal, and agentic activitywhere meaning is created in interaction with others [13], [15], [16], [17]. And because learning issituated and contextual, it does not escape from but is in fact deeply affected by the influence ofpower relationships.Learning happens within and between communities. People grow from being more novice toexperts. In communities of practice, learning is being facilitated through network(s) of cognition[13]. When it comes to learning, the flow of power occurs between people, activities and theenvironment [13], [18]. In
-centered design typepedagogies and the parallels between students’ interdisciplinary learning and faculty learning tonavigate institutional processes to create interdisciplinary courses [20]. Her recent research hasbeen to integrate social, political, and economic contexts into technical engineering courses. Asan actor in engineering education working to integrate broader societal contexts into theengineering curriculum at Tufts University, Ozkan’s positioning as a practitioner and researcherof pedagogical change informs and motivates her to pursue this collaborative research oncontextualization.Human-Centered Design: Contextualization for Better Design(s)Research on engineering design education demonstrates how treatment of design
tofurther define and operationalize our definitions. Table 1 summarizes these themes, which will befurther elaborated in the following sections. (Though an analysis of the role of gender and activitystructure is beyond the scope of the present work, see [16] for a fuller discussion). The focus groupquotes are identified according to their structure and gender composition. US = Unstructured. S =Structured. PM = Predominantly Male. PF = Predominantly Female. B = Balanced.Table 1: Overview of salient themes and associated codes. Theme Operational Definition Associated Codes Challenges Difficulties and areas of stagnation or • Ideation preferences and confusion encountered by
Outcomes Bloom's ABET Activity 1 2 3 4 5 6 7 8 9 Taxonomy Outcomes 1) Buoyancy K, App, A, E 2) Mass Flow Determination K, C, App, A a, b, c, d, e, 3) Pressure Drop K, C, App, A, S, E f, g 4) Time to Empty Tank K, C, A, E 5
at Howard University and a Carnegie Scholar. She served as a Co-Principal Investigator of the Center for the Advancement of Engineering Education (CAEE). Dr. Fleming earned her Ph.D. in civil engineering from the University of California at Berkeley and holds a Master of Science and Bachelor of Science degree in civil engineering from George Washing- ton University and Howard University, respectively. Dr. Fleming’s research interest is concentrated on the reform of engineering education, broadening participation in engineering and the scholarship of teaching and learning.Robin Adams, Purdue University, West Lafayette Robin S. Adams is an Assistant Professor in the School of Engineering Education at Purdue
543 4.42manage the materials for each lesson.The facilitators described what in theactivities students are likely to strugglewith (either conceptually or with 546 4.37manipulating the materials) and how toaddress these when implementing theunit.The facilitators shared how to lead thevarious activities in the unit(s), including 545 4.48questioning throughout the activity(before, during, and after). Page 25.503.12I was given opportunities to consider and 543
experience in developing programs for student professional development and broadening participation (co-PI and PI on three NSF S-STEM grants). He has led a number of undergraduate training and summer research programs focussed on supporting first-generation and underrepresented minority students.Dr. Dustin B. Thoman, San Diego State University Dr. Dustin Thoman is a Professor in the Department of Psychology and the Center for Research in Mathematics and Science Education at San Diego State University. His scholarship is grounded in social psychology, diversity science, and a social contextual framework of motivation. He studies how motivation can be supported or disrupted by the social and cultural contexts in which
is the relationship brokerand mediator between university, military, and government partners. As an example of howCMI2’s facilitation supports success, this paper’s Appendix includes an example Customer NeedsStatement for the LMTV camouflage deployer project carried out by UF ME. Developing thisdocument required several iterations between UF and 3ID to settle on parameters that met theArmy’s need to reduce vehicle camouflage deployment time while aligning with UF’s budget,resource, and experience constraints.Camo deployer development through UF ME and GT ME Capstone proceeded in three steps acrossmultiple semesters. First, given a Customer Needs Statement created in advance of the courses,undergraduate senior Capstone students developed
StudiesOur main objective was to find the interventions in circuits education and how they influencedundergraduate students in circuits courses, extracted information could be beneficial to determinewhich papers could be included in the study and which were not relevant or did not offer anyinterventions to students. The information was gathered from reading the title of the paper, theabstract, and the content with a particular focus on methods, discussions, and conclusions of thestudies. In summary, our closed coding scheme was as follows: author(s) and publication year,whether they were used before, during, or after COVID-19, intervention category, interventionsub-category, teaching mode, duration of intervention, and research method. We also
fields [26].Ultimately, the STEM workforce should reflect the population it serves. However, research bythe National Science Foundation finds “Hispanic, Black, and American Indian or Alaska Nativepersons collectively account for 37% of the U.S. population ages 18–34 years in 2021, and 26%of S&E bachelor’s, 24% of S&E master’s, and 16% of S&E doctoral degrees earned by U.S.citizens and permanent residents in 2020” [27]. In addition, women earned 51% of S&Ebachelor’s, 51% of S&E master’s, and 47% of S&E doctoral degrees in the U.S. in 2020, butdespite women’s high levels of representation in S&E (which includes the life sciences andsocial sciences), women of color earned only 14.9% of all S&E bachelor’s degrees [27
; Morris, M. W. (2010). Negotiating gender roles: Gender differences inassertive negotiating are mediated by women’s fear of backlash and attenuated when negotiatingon behalf of others. Journal of Social and Personality Psychology, 98, 256-267.Ameri, M., Schur, L., Adya, M., Bentley, S., McKay, P., & Kruse, D. (2015). The disabilityemployment puzzle: A field experiment on employer hiring behavior. The National Bureau ofEconomic Research. doi: 10.3386/w21560.Baker, P., & Copp, M. (1997). Gender matters most: The interaction of Gendered Expectations,Feminist Course Content, and pregnancy in student course evaluation. Teaching Sociology, 25,29-43.Barnum, P., Liden, R. C., & Ditomaso, N. (1995). Double jeopardy for women and minorities:Pay
mentorship program for underrepresented minorities (URM). She was a founding member of a STEAM Innovation Program at an urban vocational technical school servicing URM in STEM, where she taught Biology, Chemistry, and Biotechnology. Hilderbrand-Chae has a Masters’ De- gree in Genetics from Tufts University Medical School and now focuses research on epigenetic regulation influenced by substrate stiffness.Shalain Iqbal SiddiquiDr. Chiara E. Ghezzi Chiara Ghezzi, PhD is assistant professor in the department of biomedical engineering at University of Massachusetts Lowell. She received her undergraduate and masterˆa C™s degrees in biomedical engineer- ing from Politecnico di Milano, in Italy. During her dBryan Black
,” Soc. Psychol. Q., vol. 63, no. 3, pp. 224–237, 2000.[7] D. Collins, A. E. Bayer, and D. A. Hirschfield, “Engineering Education For Women : A Chilly Climate,” Women in Engineering Conference : Capitalizing on Today’s Challenges - 1996 WEPAN National Conference. pp. 323–328, 1996.[8] L. K. Morris and L. G. Daniel, “Perceptions of a chilly climate: Differences in traditional and non-traditional majors for women,” Res. High. Educ., vol. 49, no. 3, pp. 256–273, 2008, doi: 10.1007/s11162-007-9078-z.[9] K. F. Trenshaw, “Half as likely: The underrepresentation of LGBTQ+ students in engineering,” CoNECD 2018 - Collab. Netw. Eng. Comput. Divers. Conf., no. 2011, 2018.[10] J. Jorstad, S. S. Starobin, Y. (April) Chen
environmentmanagement.Consequently, the control of the effect that emotional self-regulation could have on therelationship between mental well-being and self-regulated learning remains open, so future workshould incorporate other dimensions of self-regulation learning into the proposed model,analyzing how these are impacted by the two dimensions of mental well-being. Future work isalso expected to estimate the indirect effect of the gaps in social integration of specific groups ontheir mental well-being and on the self-regulation of their learning.AcknowledgementsReserved for blind review.References[1] S. J. Bork and J. L. Mondisa, “Science, Engineering, and Mathematics Graduate Student Mental Health: Insights from the Healthy Minds Network Dataset,” in 2019 ASEE
. Ofthe undergraduate students, 82% are white, 5.9% are Hispanic, 4.2% are African Americans, and0.3% are American Indian or Alaska Native. At the graduate level, these numbers are 80.6%,3.2%, 3.5%, and 0.4%, respectively. In comparison, the statewide demographics are: 79.2%white, 5.3% Hispanic, and 14.1% African American. Efforts to focus on inclusion and equity atthe university level have a long history. In the 1970’s, the university established the MulticulturalCenter that supported a wide range of cultural activities as well as academic and supportprogramming to the Minority Education Cohorts: Minority Science Education Cohort, MinorityTeacher Education Cohort, and Minority Business Education Cohort. This was the primaryapproach at the
disambiguation framework consists of fouriterative stages to create a “best-guess” of a completely resolved network data set and provides ageneral structure for future algorithmic methods. Results of this work will better enableresearchers to study larger, more holistic educational networks. BackgroundStudents benefit from social interactions in a variety of ways. For example, Kalaian et al.’s [5]meta-analysis identified that across 18 studies, formal small group settings enhance student’sabilities to succeed academically—especially among first-year engineering students (d = 0.84).Studying students’ online social media interactions, Su and Huang [6] found that students whofrequently use social media for academic
demographic information.Table 1. Participant information Child Caregiver(s) Child Child Caregiver Ethnicity Pseudonym Pseudonym Age/Grade Gender Information Jennifer worked in an Billy Jennifer 9/4th Male White elementary school as an art teacher. Edward 12/7th Male John worked in a John African
structured according toLind et al.’s [15] Indicators of Ethical Sensitivity (i.e., story characteristics, stakeholders,consequences, and ethical issues). (Note that the terms “ethical sensitivity” and “moral sensitivity”can be used interchangeably; in this paper, we primarily use Rest’s term “moral sensitivity” exceptwhen specifically referring to Lind’s framework.) The story includes story characteristics (e.g., acurfew was instituted in New Orleans), stakeholders (e.g., elderly residents), and consequences(e.g., drinking water was unsafe). The interview questions were designed to encourage participantsto discuss the fourth indicator, ethical issues. Using a qualitative content analysis, we found thatall participants focused on one major