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
. 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
]. Additionally, this strong interest inbiomaterials is reflected economically. In 2019, the global market for biomaterials was estimatedto be worth $106.5 billion, and revenues from biomaterials are projected to increase to $348.4billion by 2027 [5]. To ensure these societal and economic demands for novel biomaterials aremet, we must prioritize educating diverse students about designing, engineering, and testingbiomaterials [6], [7].One way to meet this goal is through K-12 outreach. Outreach is an important activity forincreasing the number of students studying science, technology, engineering, and mathematics(STEM) at the university level [8], [9]. This is especially important for increasing therepresentation of individuals who are traditionally
.[5] W. Lee and N. Conklin, “High-altitude radiation detector (HARD): An exemplary means to stimulate electrical and computer engineering undergraduate research,” in Proc. ASEE Annual Conference and Exposition, June 14-18, 2014, Indianapolis, IN, pp. 1-12.[6] K. Arnsdorff, A. Chen, R. McCord, and S. Peuker, “Work in progress - Student description of self-regulated learning: A qualitative investigation of students' reflection on their first semester in engineering,” in Proc. First-Year Experience Conf., August 6-8, 2017, Daytona Beach, FL, pp. 1-5.[7] O. Lawanto and H.B. Santoso, “Development and validation of the engineering design metacognitive questionnaire,” in Proc. ASEE Annual Conference and Exposition, June 15-18, 2014
worked on the project only at home.Less than 1/3 of students had made music using a computer prior to the competition, and fewer(16.4%) had used the EarSketch platform prior to the competition. In terms of their coursework,nearly all students (94.5%) reported being currently enrolled in a computer science or technologyrelated course, and a large portion of students (89.0%) reported that they had previously taken acomputer science or technology related course.Students’ Feedback on the Competition: Students were asked to reflect on various aspects of thecompetition. On eight of these ten items, average student responses fell between the “Agree” and“Strongly Agree” scale points, indicating generally positive feedback about most aspects of
with OMSI, Marcie is a founding member of the Informal Learning Leadership Collaborative (ILLC) and engages with her community as a facilitator for conversations about race and activities for personal reflection. American c Society for Engineering Education, 2021Engineering Awareness at Design Challenge Exhibits (Fundamental)IntroductionEngineering in communitiesAn increasing number of federally funded projects have focused on encouraging youth andfamilies to exercise engineering skills (e.g., GRADIENT [1], Engineering is Elementary [2], andHead Start on Engineering [3]). This trend, paired with the increasing popularity of designchallenge-based
to the local context. They are therefore unable to neither take fulladvantage of local knowledge nor develop city-wide /’at-scale’ responses.”vii “The practice of approaching services’ in an individualized, technocratic form highly reliantupon engineering solutions and expert knowledge reflects institutional and management overlapsand incoherencies between sectors that are not required or in the habit of communicating,whether across governmental ministries, departments or donors, and indeed, is valid across theservices’ spectrum, whether for waste, water, food or energy. … Approaches to municipal wastertend to be fairly technocratic in provision and analysis, ignoring the overlapping effects of wasteon water, sanitation, food and health
of creating an impact in the world, specificallythrough business. (so, it’s a step beyond just innovation)”. Another student expressed, “Findingways to make you/others’ lives better through a product/service/or idea”. As a result, there arestudents who believe creating an impact in the community or in their field is a greater aspect ofentrepreneurship.Self-perceptions of being entrepreneurialWhen engineering students were asked to reflect on their self-perception of entrepreneurship,students’ responses are focused on the general “yes” or “no” question, “Do you see yourself asentrepreneurial? If you answered YES, please indicate why? If you answered NO, please indicatewhy?” Out of the total number of respondents (n=194), 62% (N=121) of the
students along with the resulting output waveform of the amplifieras presented in Figure 2(b2). Students were asked to analyze the given circuit to identify thepossible reason(s) why the output waveform was distorted (the lower half was cut-off).Since the modality, the student population, and the challenge questions were different in the Fall2019 and Spring 2020 semesters due to the ongoing pandemic, a direct comparison of theassessment results cannot be made. However, assessment results for both modes reflect somecommon areas of improvement and provides a qualitative understanding of the student skilllevels in this course. Based on our preliminary assessment results, we plan to develop a rigoroustroubleshooting skill improvement instructional
Niehans, Shelley Lemons, Wright CollegeEngineering Team, Mia Angara and in memoriam: Melissa Mercer-Tachick- MUSE Consulting,NSF-HSI “Building Capacity: Building Bridges into Engineering and Computer Science”evaluator. 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. Wright College IRB protocol # 108007 10REFERENCES[1] C. Adelman, Women and Men of the
ACM Technical Symposium on Computer Science Education, ser. SIGCSE ’18. New York, NY, USA: Association for Computing Machinery, 2018, p. 922–927. [Online]. Available: https://doi.org/10.1145/3159450.3159585 [9] D. Horton, M. Craig, J. Campbell, P. Gries, and D. Zingaro, “Comparing outcomes in inverted and traditional cs1,” in Proceedings of the 2014 Conference on Innovation & Technology in Computer Science Education, ser. ITiCSE ’14. New York, NY, USA: Association for Computing Machinery, 2014, p. 261–266. [Online]. Available: https: //doi.org/10.1145/2591708.2591752[10] M. N. Giannakos, J. Krogstie, and N. Chrisochoides, “Reviewing the flipped classroom research: Reflections for computer science education,” in
profession.Recommendations include focusing on cohort formation, designating space and times for studygroups and encouraging use of campus career resources. Additional focus should be put towardsassisting students in applying for and obtaining internships, co-ops, and undergraduate researchexperiences early in their academic careers.This material is based upon work supported by the National Science Foundation under GrantNo.1644119. Any opinions, findings, and conclusions or recommendations expressed in thismaterial are those of the author(s) and do not necessarily reflect the views of the NationalScience Foundation.6.0 References[1] B. E. Hughes, W. J. Schell, B. Tallman, R. Beigel, E. Annand, and M. Kwapisz, “Do I ThinkI’m an Engineer? Understanding the Impact of