Engineering”, Alonso [11] studied how engineering identities intersect with other identities. This study brings another element to the framework of Intersectionality - the individual’s perception and a peer’s perception of them being identified as an engineer. To clarify, we are not only observing if the individual identifies as an engineer but how that reflection compares to them feeling they are being portrayed as an engineer within their community. It is a matter of discerning which factors contribute to these identities and which factors dissociate the student with that identity. Through our study, it was apparent that this identity could be solidified by being established prior to attending college. Rincon [5] states [that] “...expressing early
concepts in an incremental manner to helpstudents progress, while still enabling a less-prepared student many opportunities to practice. Anexplanation provides the student feedback, guides the student through the level, and adapts to thegiven question and answer provided.As more classes become virtual and instructors need to cope with larger groups of learners moreefficiently, auto-grading and self-assessment as a result, have become very important.Self-assessment promotes students’ skills of reflective practice and self-monitoring, andincreases students’ motivation and confidence. This homework activity style encouragesself-assessment especially with the use of activities where students receive immediate feedbackon each question. Even when a
. Additionally,because each platform implements rapid development methodologies differently, there can beinconsistencies and some expected feature sets do not always come out-of-the-box (OOTB) [11].RAD is most prevalently used in commercial applications because projects are “schedule intenseand require amalgamate set of team members” [9]. These requirements are the same for capstonedesign courses [2], [3] and research-centric projects. Further research suggests that whenpresented with the same set of independent software variables to examine, student developers’analysis is statistically similar to that of professional industry developers [12], indicating thatstudent behavior is reflective of developer behavior in industry. These parallelisms suggest
topic of interest tothe student. The use of problems framed as technical challenges to report to a supervisor ortechnical peers provides context to inspire students to recognize the independent learning skillsthey will need to be successful engineers.Alignment to Workplace CompetenciesIn addition to the seven defined ABET student learning outcomes, there have been numerousworks to define additional workplace competencies that would be expected by the modern globalengineer [17,24,25]. The National Academy of Engineering (2004) [17] notes that an engineerworking in an interdisciplinary global workforce requires leadership, teamwork, communication,reflective behavior practice, interdisciplinary skills, disciplinary perspective, contextualawareness
wholly inclusive ofthe online learners as legitimate members of the course community. Below we will brieflydiscuss each of these components and how they work to support the program. Notably, what isdescribed here reflects the reality of a pre- (and likely post-) COVID environment whengenerally residential students meet in person and online learners participate in the courseasynchronously. 1. Technology infrastructure. Lecture capture is a relatively common practice in higher education generally [16] and online engineering education specifically [17]. The quality of the recordings are important determinants of distance learners’ experiences [18], [19].Low quality videos marked by things like poor audio and unclear video can
. • I use my personal email more frequently than my school email. Also, update as much and as soon as possible to blackboard. Industrial Robotics • I have taken online classes in the past and I didn’t learn as well as I do in face-to- face lectures. • I hope Blackboard works throughout the semester. The survey results (Table 2) reflect the following facts for each challenge and the possible impact onthe program quality. Table 2. Possible impact on program quality with respect to challenge type Challenge typeFacts Possible impact on the program quality Technology • About 40% percent of students
the living and learningenvironment can easily derail a RedShirt student’s academic progress. Most programs include asecond year in the dorm. While RedShirt students expressed some ambivalence about thisrequirement in the second year, most third year students were grateful for dormitory supportwhen reflecting on their second year. A number of third year students struggled with the impactof moving back home after moving out of the dorm and others struggled with logistics aroundliving in an apartment. These third year struggles were worsened by the pandemic. This seemslike another area where continued engagement with RedShirt staff in the area of intrusiveadvising would be helpful to assist juniors with making their living arrangements when
responses compared to thepost-survey responses are presented in some of our prior research [24, 25].AcknowledgementsThis work was made possible by a collaborative research grant from the National ScienceFoundation (DUE 1827392; DUE 1827600; DUE 1827406). Any opinions, findings, andconclusions or recommendations expressed in this material are those of the author and do notnecessarily reflect the views of the National Science Foundation.References 1. J. S. Zawojewski, H. A. Diefes-Dux, and K. J. Bowman, Models and modeling in engineering education: Designing experiences for all students. Sense Publishers, 2008. 2. A. R. Carberry and A. F. McKenna, "Exploring student conceptions of modeling and modeling uses in engineering design
detailed exploration of student perceptions of the questionsacross the two instruments. We will continue to administer both instruments annually tounderstand students’ long-term trajectories and identify which factors have the greatest impact ondevelopment of identity. By better understanding identity development, we can work to improvepersistence in computing programs.AcknowledgmentsThis material is based upon work supported by the National Science Foundation under Grant No.1833718. Any opinions, findings, and conclusions or recommendations expressed in this materialare those of the author(s) and do not necessarily reflect the views of the National ScienceFoundation.References [1] G. Kena, L. Musu-Gillette, J. Robinson, X. Wang, A. Rathbun, J
method for relativeness score for Lab 1 — 3. 9 As for the qualitative analysis, coding method was used to extract keywords from students’10 responses. According to the qualitative questions, four categories were created: benefits of11 participating in Lab 2, challenges of participating in Lab 2, remote working skill, and12 transferable skill. In each category, the authors read reflections sequentially by student and13 identify common keywords. The number of common keywords was counted, and the pie charts14 were created to display the popularity of common keywords in each category. Moreover, some15 student answers to the qualitative questions were used to provide more insights.16 Results and Discussion17 Quantitative Assessment
distanceReferences: 1. The Chronicle of Higher Education. “Covid-19 Has Forced Higher Ed to Pivot to Online Learning. Here Are 7 Takeaways So Far”. https://www.chronicle.com/article/covid-19-has-forced-higher- ed-to-pivot-to-online-learning-here-are-7-takeaways-so-far/. 2. David Christian and Danny McCarthy. “Experiential Education during the COVID-19 Pandemic: A Reflective Process.” Journal of Constructivist Psychology, DOI: 10.1080/10720537.2020.1813666 3. Fiseha M. Guangul, et al. “Challenges of remote assessment in higher education in the context of COVID-19: a case study of Middle East College” Educ Assess Eval Account. 2020 Oct 21 : 1–17. DOI: 10.1007/s11092-020-09340-w 4. Arizona State University, “Teach Online
disciplines. A third exampleinvolves classifying the quality of questions that students generated when using an Englishwriting intelligent tutoring system, once again using a rule-based system [15]. In the area ofanalyzing feedback surveys, Dhanalakshmi et al. [16] used a supervising learning approach topredict the polarity of student responses (a common framing of a sentiment analysis task). Ofcourse, these models also have several potential limitations such as inadvertently introducingbias and reflecting unintentional differences across groups [17], [18].In engineering education, there have been limited applications of NLP on either the research orteaching side. The more modern applications have applied standard statistical and machinelearning
PBL to be effective. Simply giving students a problem to solve in a group does notautomatically confer benefits. Transfer is also aided by reflection, which is often incorporatedinto problem-based learning. In brief it is worth considering that in disciplines like engineeringwhere addressing contingencies in practice is important knowledge matters, but experience maymatter more. Ultimately, we become what we do so techniques such as cases, simulations, andPBL allow students to gain experiences with applying contingent knowledge. If designedeffectively these learning experiences can transfer to practice.Another area that most of these degree programs have in common are some form ofcomprehensive examination before an individual is licensed for
expressed in this material are those of theauthor(s) and do not necessarily reflect the views of the National Science Foundation.References1. Khasawneh, M., Bachnak, R., Goonatilake, R., Lin, R., Biswas, P., Maldonado, S.C.,(2014) “Promoting STEM Education and Careers among Hispanics and Other Minorities throughPrograms, Enrichment, and other Activities.” ASEE Annual Conference and Exposition,Conference Proceedings, 2014.2. Martinez, D., Jacks, J., Jones, D., Faulkner, B. (2010). “Work In Progress – RecruitingInitiatives for Hispanic, First-Generation Students.” 40th ASEE/IEEE Frontiers in EducationConference, 2010.3. Enriquez, A., Langhoff, N., Dunmire, E., Rebold, T., Pong, W. (2018). “Strategies forDeveloping, Expanding, and
responses used for training grows. Whether theevaluation is done by a human or via an NLP-based algorithm as described, there is oftenambiguity for the very reason that students were often found to fail to adequately justify theirresponses to the considered conceptual writing quiz. This is where a Directed Line of Reasoningapproach to providing feedback would be most useful.AcknowledgementsThis material is based upon work supported of the National Science Foundation under Grant No.1504880. Any opinions, findings, and conclusions or recommendations expressed in thismaterial are those of the authors and do not necessarily reflect the views of the National ScienceFoundation.Works Cited[1] Writing to Develop Mathematical Understanding, David K. Pugalee
, Kim,& McDermott [57]. To recap key aspects of the discussions and opinions appearing in the precedingpages, I offer Table 4, in which I have listed my subjective rankings of various factorsthat help women’s participation and achievement in STEM fields, based on my personalobservations and experiences in the US and Iran over a 48-year academic career. I couldhave listed inhibiting factors, but perhaps accentuating the positive is preferable as wellas more intuitive (higher scores reflect greater desirability). The total score should betaken with a grain of salt, as not all factor have the same importance.Table 4. A comparative summary of factors helping women’s participation/achievementin STEM educational programs and careers (on
39.52 compared to 36.45 from UPRM. Therefore UPRM participantsexhibited characteristics of a collectivist society in which people are born into groups that providesupport and help to others in exchange for loyalty. Thus, the UPRM student population reflects amore ingrained sense of collectivism. Meanwhile, the mainland score of 91 represents anindividualist society, where people expect to take care of themselves. On the contrary, MSUstudent population scores align with the characteristics of a more collectivist culture.The analysis by gender revealed that female students reported a score lower than the generalpopulation at both institutions, with 33.98 for MSU and 36.31 for UPRM. For male students, weobtained a higher score of 46.40 and 37.18
to have high totals when the impacts weresummed. The authors’ reasoning of these hypotheses comes from observations seen in actualstudent teams within the IBL class. Teams in which students have similar end goals and worktogether on their projects often progress further in their learning and achieve project outcomeswith high impact. Teams that lacked innovative goals and did not work well together often hadlearning outcomes with low impact. As shown in Table 1, there is a moderate correlationbetween the team’s innovative impact and the team’s progress across all group sizes. Theseresults reflect the author’s hypotheses, suggesting that multiple students on the team need to havesimilar innovative impact inputs to reach higher progression
woman (she/her) Engineering Yes Dr. O Black woman (she/her) Engineering Yes Dr. Wu Black woman (she/her) Natural Science YesData AnalysisThe data was analyzed using a general inductive analytic plan, meaning we analyzed theinterviews in line with the conceptual framework and study’s objectives [63], [64]. The first stepof the data analysis involved reading through the transcripts so the lead researcher couldfamiliarize themselves with the data. Next, the lead researcher identified significant statements ineach of the interviews pertaining to codes reflective of the Collins’ [11] domains of powerframework. The interpersonal domain code was created to describe when a participantmentioned
. Unlike prior years, when the semester ended with acelebration of each student group’s learning and accomplishments, this semester concluded withboth students and instructors mentally exhausted by the crush of last-minute token reviews andrevisions.Action Steps: Revising Peer ReviewBased on reflections within the instructional team and student input, the token and PR processhas been revised in several ways. These are shared as both principles (see italicized headings)and specific actions.Keep It SimplePR is valuable, but it also requires time and mental energy. Our first change was to eliminate thePeer Review Definition stage. Very few tokens repeated this step, and its removal has theimmediate benefit of eliminating 50% of all PRs. Furthermore
DEI efforts and larger DEI efforts. As part of the plan we haveengaged with constituents and discussed ways to implement the following levels for the Call toAction by addressing the following questions and then reflecting on the levels in Figure 4. ● How do we make the initiatives actionable? ● How do we make the actions sustainable? ● How do we measure success of the actions? ● How do we manage accountability for the initiatives? ● What did we miss? What have we not considered? ● What are the strengths, weaknesses, threats and opportunities? Figure 4. Call To Action Levels of ActionNext StepsThe BIE Call to Action offered a solid foundation for the launching of other BIE strategicinitiatives. Among
my protégé. And she started getting a masters in nursing. So we were like going, who's gonna finish first?”Nathan’s wife encouraged him to pursue an advanced degree as she said, “…hey look, you should go forward to great opportunities. So I decided to do it and never looked back since then. It was a great experience. Great professors and yeah, that's pretty much it.”Alex reflected on who had a role in directing him toward the engineering field and mentioned hismother: “It was maybe, her, pushing me to do something else [other than her profession], you know, turned me more toward engineering.”Another participant said it like this “... they [my family] don't truly understand what I go through as a PhD
case studies, reflections, portfolios and projects.” [6].The U.S. Military Academy at West Point ended its second chance program, returning to a policywhere cheating results in expulsion from the Academy [7]. Even video game companies aretrying to find ways to stop non-academic cheating. Call of Duty recently banning 60,000 userswho were cheating in its online gaming platform [8]. Cheating, and specifically cheating withChegg, was significant enough to warrant an extensive article in Forbes Magazine titled, “This$12 Billion Company is Getting Rich Off Students Cheating Their way Through COVID” [9].Solutions to the problem of cheating can be daunting. Research suggests that the best cure forcheating is building a culture of strong academic
recommendations expressed in thismaterial are those of the author(s) and do not necessarily reflect the views of the NationalScience Foundation. The authors would like to thank Xin Wang for his assistance in organizingand analyzing data.References[1] J. P. K. Gross, D. Hossler, M. Ziskin, M. S. Berry, “Institutional merit-based aid and student departure: A longitudinal analysis,” Review of Higher Education, vol. 38, no. 2, pp. 221-250, 2015.[2] J. L. Hieb, K. B. Lyle, P. A. S. Ralston, and J. Chariker, “Predicting performance in a first engineering calculus course: Implications for interventions,” International Journal of Mathematical Education in Science and Technology, vol. 46, no. 1, pp. 40-55, 2015[3] K. B. Coletti, E. O
page for this class was not great. o The projects need to be clearer. There was a lack of direction and the professor basically said to figure it out even though this is an introduction course to the software. o This course would be much better to teach in person but other than that the course was very well done considering it is online. o Better instruction o How things are submitted o In class rather than online.8. ConclusionThis class structure and format provided a rich learning environment for students to understandhow to interface the world to computers. The experiments offer ample opportunity for studentsto learn through open-ended examples. Student comments reflect
activitiespromoted ‘connectedness’ among SCOAM students and motivated students to work hard andcomplete their coursework.Small Group Activities and Monthly MeetingsStudents were asked to participate in 3 small group activities each semester. In cross-generational groups (i.e., freshman, upper classman, graduate student), students were asked toseek out and attend activities on campus or create their own social event. The purpose ofattendance at these activities was to encourage relationships between members of the cohort andto foster a sense of ‘belonging.’ After attending an activity, students were required to postpictures and a reflection on SCOAM’s online learning management platform. At least one ofthese activities had to focus on a social issue
literature review, the researcher developed a study to understand the current state of the CEMcurriculum at the middle and high school levels by assessing course offerings in North Carolinafor the 2019 – 2020 academic year. The researcher hopes to learn the course names, coursetopics, and the CEM curriculum within a school. For this study, the data gathered will reflect thetop five populated counties in North Carolina, representing 33% of the overall population.IntroductionThe size of the available workforce in the construction industry decreases for both managementand skilled professionals [1]. According to the National Center for Construction Education andResearch (NCCER), 40% of today’s construction workforce will retire by 2030 [2].Unfortunately
,recommendation, or favoring by the United States Government or any agency thereof. The viewsand opinions of authors expressed herein do not necessarily state or reflect those of the UnitedStates Government or any agency thereof.References[1] P. Maxigas, "Hacklabs and hackerspaces:Tracing two genealogies," Journal of Peer Production, no.2, Jul. 2012, Accessed: Jun. 29, 2020. [Online]. Available: https://eprints.lancs.ac.uk/id/eprint/88024/.[2] S. Mersand, "The State of Makerspace Research: a Review of the Literature," TechTrends, vol. 65, no. 2, pp. 174–186, Mar. 2021.[3] R. Dattakumar and R. Jagadeesh, "A review of literature on benchmarking," Benchmarking: An International Journal, vol. 10, no. 3, pp. 176–209, Jan. 2003.[4] R. M. Epper
engineering. This activity alsohas similarities to work presented by ASEE colleagues [7]. Students chose an existing part andobserved the process while the course instructor scanned their parts. The scan data was providedto the students who were then challenged to convert this scan data to a solid model and then (ifsuccessful), edit the solid model. This activity was designed to fail; the success of this activitywas very dependent on what the students chose to try to scan. Transparent surfaces cause gaps inthe scan, reflective surfaces skew data, and flat horizontal surfaces are impossible to capture in ascanner that does not have the capabilities to adjust the angle of the laser. Students who capture agood scan struggle to convert their scans to a