following research question: What kinds of roles andbehaviors do caregivers enact that support their child’s learning and engagement in engineeringactivities at home? We anticipated that caregivers’ roles and behaviors would be influenced bythe home context and reflect caregivers’ trying to balance responsibilities of being aparent/caregiver with their expectations of what it means to support or teach their child about adiscipline with which they may be unfamiliar (e.g., engineering).MethodsStudy ContextThe current study was conducted as part of an NSF-funded project to (1) engage kids and theircaregivers in engineering, (2) increase the awareness of kids and caregivers as to whatengineering is, and (3) increase kids’ interest in engineering. We
majors [3]. This reflects an influence of self-efficacy on career choice. Self-efficacycan influence students at the beginning of their studies in selecting their major and at thecompletion of their studies by increasing their perceived career options [6]. Finally, self-efficacyis also associated with better mental health in students, specifically seen in reduced anxietylevels in students with higher self-efficacy [7].Clearly, the beneficial practices and traits associated with self-efficacy indicate it as a desiredcharacteristic in students. However, self-efficacy is not simply a static personal attribute thatshould be selected for in admissions processes. It is, rather, a dynamic quality, the cultivation ofwhich should be a central aim of
areversed in this and many other tools that are far more advanced?Dr. Watford later comments on how curricular change does not need to happen all at once.Indeed, change an assignment, change a module, do this over time. She also reflects on howstudents do not do their homework. Why? Because faculty do not have the time to grade theassignments. She goes on to suggest the use of digital technologies to not only submit homework,but to grade it. She is certain that the practice of homework and feedback can only help. She alsogave the example of using data analytics to assess student performance. Again, use thetechnology! Dr. Watford also offered that computer science students could take on how todevelop electronic homework, how to grade it, and more
University (OSU), earned a Ph.D. in Bioengineering from the University of Pennsylvania, and an M.S. and B.S. in Biomedical Engineering from OSU.Dr. Monica Farmer Cox, The Ohio State University Monica F. Cox, Ph.D., is Professor and Chair in the Department of Engineering Education at The Ohio State University. Prior to this appointment, she was a Associate Professor in the School of Engineering Education at Purdue University, the Inaugural Direc ©American Society for Engineering Education, 2023 Unexpected Accomplices: Effective Mentoring between a Black and White Woman Despite Historical Issues of Privilege, Power, and PositionalityAbstractIn this reflection
from 30,320 to 149,360, and the proportion of totalstudents in higher education institutions increased from 26.0% to 37.0% (See Table 2).These changes reflected the efforts to align the higher education system with thenational industrialization development strategy.Table 2 Changes in the Proportion of Engineering and Industrial Students before and after the Adjustment of the Faculties (1949-1956) Total Number of Total Number of Number of Industrial Proportion Number Proportion Year Higher Engineering
white and Asian, and 80% identify as men [3]. Usinga sample representative of the discipline would result in an instrument that not only did notaccurately reflect participants who are neither white, Asian, or men, but also would notaccurately reflect the nuance within minoritized groups. For example, Black computingundergraduates attending an HBCU may have differing academic experiences (as part of thedominant racial group on campus) from those attending PWIs (who are part of a non-dominantgroup both in computing and on campus). Students may also be part of a non-dominant group(e.g., race) and dominant group (e.g., gender or ability) based on different parts of their identity.In addition, Cross et al. [1] note that because people from non
Australia – EUR-ACE system Accreditation Washington Accord Duration civil engineering Four years Five years programThis multiple-case design has also been underpinned by a constructivist paradigm, whichacknowledges that the researcher (lead author) has created meaning based on interpretations ofthe educational responses in the civil engineering curriculum. These interpretations are context-dependent and guided by people’s actions under particular contextual settings [14]. Therefore,the findings of this research reflected the subjective construction of knowledge between theresearcher and the interpretation of the data [15].A cross-case analysis explored similarities and
had the occasion or courage to explore.” [1] Before Ibecame chronically ill as a person assigned female at birth, I rarely considered that the decisionsthat engineers made were as much social and political as they were technical. The decline in myhealth coincided with a strong desire and motivation to self-reflect and interrogate how engineersshaped medical realities, realities I dealt with every time I entered a clinic and failed to receive adiagnosis or a regime of care. Autoethnography inspires an analysis of the gaps in technologythat harm populations, how expertise-driven engineering cultures exacerbate these inequities, andwhy critical reflection alongside communities with lived experiences of health injustices canimprove the way we do
administered a short pre-survey thatasked about participants’ demographics, major, year in school, current courses, and grade pointaverage. The participant orientation meeting gave students an opportunity to learn more aboutthe study’s aims and to receive the initial prompt for the study (prompts are explained below).We used photovoice methodology [32] as a means of data collection and asked students to takephotographs and reflect on their sources of motivation, success, and struggle during theirengineering journeys, and also to engage with one another via three focus groups throughout thesemester. We encouraged participants to assign hashtags (recognition, interest, or competence) totheir photographs to help them better describe the content of their
axes (i.e. column capacity vs effective length) similar to Fig. 5. Each student was then required to make reasonable assumptions about the test set-up andpredict the failure load for the column with an effective length of 4 ft. During testing, theinstructor occasionally paused the test in order to explain a structural behavior or answer anyquestions from the students. Fig. 8 (c) shows the buckled column and Fig. 8 (d) shows theinstructor pointing out the yielded steel. After the test, the students were required to reflect onthe following questions: 1. Based on your plot, predict the load at which the column will buckle. 2. What assumptions were made about the support conditions of the column? 3. During testing, closely
happen due to unforeseen or unplanned eventthat occurs that the system was not designed for. Under these circumstances it might be difficultfor any quick analysis since tools to analyze chaotic situations may not be available. This iswhere the use of AI technology to analyze becomes an important tool since AI can look at datafrom all phases and make quick predictions. With XAI one can also expect highly influentialfactors and maintenance can relate them to one or more of the SE phases.It is also important to note that in the Figure 2 V-model diagram, there is no relationship orconnection shown from the Operations and Maintenance section to any subsection in thedecomposition and integration cycle. This is also a reflection of no process or tools
impactfindings match what has been stated in early reports–that students have been adversely affected inseveral ways and that schools serving majority BIPOC students were more heavily impacted. Inthis section, we take a deeper, reflective look at the findings.4.1 Observations4.1.1 CapacityWhen asked about the impact the pandemic had on their school’s capacity to offer equitable accessto CS courses over the past 12 months, participants reported that they saw significant increases intheir schools’ funding, policy, and curriculum changes. Specifically, schools increased their plansto add additional CS courses, as well as their strategies to make CS curriculum more equitable,improve CS curriculum, recruit more diverse students into CS, and add CS A or CS
programs. This disparity is especially true in regions in which their richethnic diversity is not reflected in the demographics of students entering STEM degree programsor subsequently joining the STEM workforce. Relevant literature points to the fact that largeproportions of underrepresented students report fear of math and a lack of understanding ofopportunities in the STEM and energy sectors, thus leaving them barred from entry into existingacademic and career pathways in STEM [42], [43].The STEM Core model includes a developed summer bridge opportunity for rising high schoolseniors and dual-credit enrollees, recent high school graduates, and (perhaps) non-traditionalentering community college students to be held on-site at partner community
and belonging. The program worked to reduce the isolation, exclusion, andsilencing of non-majority individuals within the typical academic career progression in additionto adapting to support during pandemic-altered faculty challenges. Key advantages of CIMCsincluded enabling inter-institutional exchanges and reflective learning among committeemembers about similarities and differences in climate and opportunities on different campuses.This paper will review the premise and literature on peer and peer-plus mentoring as well asdescribe the process of forming and supporting the CIMCs. Formative assessments for thisongoing program will also be discussed. This paper can serve as a guide for other institutions toform communities of support for
increasing diversity in designteams.Research on teams has shown that diversity, including gender diversity, leads to an increase in the qualityof work by improving collective intelligence of groups, encouraging equitable contributions in teamsettings, and adding new perspectives to groups [5]. Gender diversity, specifically within engineering, hasbeen investigated for many years, as it is widely accepted that the representation of women in engineeringneeds to be increased. This is reflected in efforts such as Engineers Canada’s 30 by 30 initiative, whichdirectly targets this goal by working with regulators, higher-education institutions, and other keystakeholders to increase the percentage of women in engineering [6]. These efforts appear to be
framework, mentioning existing codes of ethics or less formalstandards within professional organizations or conferences. A few, however, offered moreimplicit examples. One participant from mathematics reflected on their program, explaining: Then you know I think for me it's more like you know, because you get PhDs or you follow your supervisors, you know, I mean your supervisor is a good model. So, you just follow the style in some way, so….you cannot cheat, that’s basic, right. So, and I mean, you have to do the math. Not to do anything else right. So, I mean just that's something I think. What you’re supposed to do, I think you know I just stay in sync….Here, the participant offers a less formal way to know what
time investment when first creating these problems is about one to two hours. Afterthey are created, they can be reused for subsequent classes with usually only minor updates (e.g.,adding clarity to the problem statement). The automated grading does save time but can generatea substantial increase in student questions. The quantity of these questions can be managed bythe following guidelines: • Provide students with a “MATLAB Grader Q & A” worksheet that contains answers to commonly asked questions regarding MATLAB Grader. • Insist that students come prepared with neatly written work describing their process instead of just their code. • Update the feedback within MATLAB Grader tests to reflect common errors or
collaboration between the groups? (How many meetings/timing) What type of knowledge have you shared among the groups? (Difficulties in understanding each other) Can you try to tell us how (and if) the process has been different from your ordinary semester projects? Retrospective reflections Could you have done this project within the other groups? (Your contribution/contributions from the other groups) Have you gained a better understanding of your own disciplinary contributions? What have you learned being part of leadENG? Did it make sense being part of leadENG already in second semester? (Pros and cons) What do you think should be done to improve leadENG further?Data were transcribed and coded using the software NVivo. The coding was data-driven
questions one by one, such that if participants do not answer the first question,the second question will not send, and it has delay between two distributions. Participants have awindow until 12 am on the next survey day to answer the question, so that multiple surveys arenot taken reflecting the same day. On Fridays, there are an additional six questions: Given that ASMS 2-way survey including more than five questions is highly likely to reduce the participationfor a long period of a longitudinal survey, we chose to send a separate one-way SMS message witha link to the weekly survey that directs them to a Qualtrics browser window. The Monthly surveysare conducted in the same way.At the end of each week, the PhD student overseeing this project
suchjustifications based on my positionality. In addition, I identify as an Asian man who was bornand raised in Malaysia, and I have experienced certain forms of privilege as an engineeringstudent because of my identity. I constantly acknowledged the privilege that shaped myexperiences with tests, such as high school learning experiences that have prepared me as a goodtest taker, during the research process. These positionalities shape how I see tests, and as areflexive researcher, I reflect and acknowledge them in my research.Results This paper illuminates Charlie’s case to answer the research question of exploring whatCharlie’s test usage beliefs and behaviors are. While presenting these beliefs and behaviors, Ialso explored how the beliefs and
can help researchers betterunderstand the needs of today’s students, including the challenges they face and the educationalresources and support systems they now expect to be available. Furthermore, criticallyexamining what worked better online can help advance the community’s understanding of whatconstitutes a successful learning environment. In summary, this avenue of study would bevaluable for understanding the future of education in the post-pandemic world.In the quest to address this research challenge, this paper reflects on our experience teaching anintroductory computer networks course, titled Computer Networks I, from the Fall 2020 semesterthrough the Fall 2021 semester. The course is typically taken by electrical and
make significant strides. In a report from the NationalAcademy of Sciences, they describe this challenge as “Despite the demonstrated advantages todiversity in the workforce, it remains an unfortunate truth that the current composition of theSTEM workforce does not reflect the current or future demographic realities of the UnitedStates” [3]. As it stands, Black students are less than 5% of undergraduate engineering graduates,and Black faculty represent less than 3% of engineering faculty [1]. Even the solutions to bothproblems in engineering education are parallel. Blosser [4] describes a need for a critical mass ofBlack engineering faculty to address the problem of representation. Rottmann et al. [5] describe aneed for a “critical mass of
mentorship for students in hybrid orfully virtual situations. Reflections were made to consider the potential differences in theperceptions of EHL and IP-EHL students. The results and implications garnered from this deeperdive allowed us to provide recommendations for future efforts in hybrid or fully virtual peermentorship in engineering.Research QuestionThe research motivation for this analysis emerged from the frequent participant responses inChristensen’s study [31] related to the impossibility or difficulty in receiving peer mentorship invirtual or distance learning scenarios. As such, the research question for this study is: What arethe unique priority student communicated needs that should be considered with relation tofully or hybrid virtual
these marvels firsthand during the final two weeks of the term. This paper providesan overview of the Engineering Marvels course, including a list of topics covered, types ofassignments, a travel itinerary, and a cost breakdown for students, faculty, and the university.Lessons learned throughout the planning and execution of the course are also provided to helpfuture educators wishing to implement similar courses into their curriculum.Pedagogical MotivationExperiential learning is a type of active learning where students perform an activity [1], andadditional learning takes place when reflecting on the experience [2]. Field trips have beenshown to improve student motivation and lead to the development of personal connections withengineering [3
definition QUAN & QUAL of self-advocacy and identified their willingness to ignite an action on behalf of themselves and others around issues of HC. They provided a personal example highlighting what they have self-advocated for in engineering. (9) Wrap-Up These questions inquired about the QUAL major lessons learned about HC through this survey and asked participants to reflect
asking students to complete a journey map to depict the highs andlows since their previous interview. During the interview, we asked the students to describe theirexperiences over the past approximately six months using the journey map elicitation tool. Thisprocess allowed the students to reflect on their curricular and co-curricular experiences whilenavigating engineering. Following the journey mapping activity, the interviewer asked clarifyingquestions to bring out more details about the students’ experiences. Then, the researcherfollowed up with standardized questions from the interview protocol that probe into students’classroom experiences, interactions with faculty in engineering, as well as how they navigatedthe highs and lows of their
designed to address this training gap and transcendcommunication barriers between disciplines while promoting team science through creation ofan integrated inter-disciplinary educational model that reflects rapid advances in microbiomeresearch and the need for both interdisciplinary research and professional skills to address thesechallenges [6]. This paper reports on the evaluation of this project over five years with a focuson challenges identified in training graduate students with different entry level skills and acrossdisciplines. Strategies and training elements implemented to successfully address thesechallenges were made possible through close collaboration between the evaluation team andproject leadership who were highly responsive to
training project realization would be part of the moreall-encompassing scope of ITL as discussed in the section “ITL future work and applicability toscalability” . As with any cultural change to how students understand learning, it is advisable that instructorswho are adopting Inquiry over Transmission spend time explaining the method to students, sharing thevisual diagram of the different stages of Inquiry, and providing scaffolds, such as graphic organizers thatprompt students to reflect while engaging in what may be a very new and foreign approach to learning.The more explicit instructors can be about the value they place on learning through Inquiry, how thishappens, challenges students face initially, and other factors, the better
helping the research goals of a sponsor or the teaching needs ofthe university. Of course, these three sets of goals are not mutually exclusive. The P3 modelattempts to coordinate what is best for the student while assuring that the support system alsobenefits sufficiently to provide resources for the student’s training.The third consideration for designing the P3 model reflects changes in the employment sectors,which would determine realization of students’ career plans. The data in Fig. 2 show growth ofcareers in industry at the expense of academe. The absolute numbers as well as change in demandin favor of industry are particularly strong in STEM fields, most notably in engineering andphysical+earth sciences; mathematics+computer sciences and