andidentity, and encouraging career-related reflection. This review provides insight into the nuance ofthe breadth of students’ experiences in student organizations to inform future work examining thecontextual influence of experiential learning on engineering students’ professional development.IntroductionEngineering education programs aim to prepare graduates to transition into the 21st centuryworkforce as professional engineers with a breadth of technical and interpersonal skills and a senseof professional responsibility. Multiple competing influences have contributed to engineeringeducation’s current overcrowded curriculum, which largely focuses on technical knowledge [1].This technical focus is increasingly being questioned amidst calls for
course learningoutcomes) rather than direct measures (e.g., work produced by students evaluated against criteriathat reflect the learning outcomes). While beyond the scope of the present study, examiningdirect evidence of students’ learning and development in this course context would be a usefulnext step. Our future work also seeks to understand how students identify their own and others’strengths and their conceptions of the design process. Individual student interviews along withanalysis of student free responses around design and project management will be used to furtherinvestigate these questions. In the present study, researchers hoped for a higher survey responserate to allow for group comparisons across various identities (i.e., race
2014 called Repos (an acronym for Oswaldo Sevá Grassroots Engineering Network).Repos’ intended proposals are: to technically support social movements across the country;provide formative experiences for those interested in GE practices; and reflect on Brazilianengineering syllabuses so as to be able to lobby for an engineering education compatible with theformation of grassroots engineers, and assist universities and/or governments in theimplementation of such formation processes [3], [13].From within Repos, it has been consolidated an understanding – or definition – of whatgrassroots engineering is. That is, “a practice that, through university extension, develops socialtechnology along with solidarity enterprises, based on participatory
engineering macroethics. Even more discouraging is the fact thatthere is insufficient amount of work on integrated approaches to address both micro and macroissues in engineering, that is, linking personal and professional ethics as well as linkingprofessional and social ethics [1]. The micro-macro distinction, however, is not always clear andone might find it difficult to encourage ethical reflection at a micro level without taking macroaspects into account [4]. To understand how microethics and macroethics are related, we will nowdiscuss each in detail.Sensitivity to MicroethicsMicroethics focuses on issues for the most part internal to engineering practice, such as therelationship between individual engineers, or between the engineers and their
: Learning Objectives and Core Activities for Introduction Section Learning Objective Core Activities 1. Learn about other members in the group and 1. Introductions begin building a learning community 2. Reflect on group dynamics and ways to 2. Examining constructive and make the group functional destructive group behaviors 3. Establish ground rules for participation 3. Generate ground rulesThe introductory activities are particularly important because they help participants identifydeeper connections (beyond major or home department) and begin building trust and a learningcommunity. The list of suggested introduction activities that is provided as part of the
education, including how to support engineering students in reflecting on experience, how to help engineering educators make effective teach- ing decisions, and the application of ideas from complexity science to the challenges of engineering education. ©American Society for Engineering Education, 2020 A Look Into the Lived Experiences of Incorporating Inclusive Teaching Practices in Engineering Education AbstractThis research paper contributes to the field's understanding on how to support educators increating a diverse and inclusive engineering education environment. Even with manyconversations around diversity and inclusion, recruitment
2012, S-STEM projects were required to dedicate 85% of budgets to scholarships.Starting in 2012, the NSF solicitation changed to allow increased expenditures for programmatic,evaluation and knowledge generation efforts. S-STEM teams are challenged to implementprograms that reflect best practices and generate evidence regarding successful interventions.1.2 Institutional ContextAugsburg University is a private Lutheran institution with an enrollment of about 3,000 students,approximately two thirds of whom are undergraduates. Founded in 1869, Augsburg has a strongcommitment to providing broad access to a quality education and supporting students fromdiverse backgrounds. As of Fall 2019, 45% of the full-time undergraduates were students ofcolor
based on our past experiences, cultural perspectives, innocuous misconceptions, orsubjective biases. Measuring these different mental models poses a unique challenge sinceconceptualizations are held in the mind and any description of them is simply a representation ofthe mental model and not the mental model itself; in other words, we are seeing a reflection ofthe mental model through a dirty mirror. In this work, the previously published instruments usedto elicit undergraduate students’ mental models [1-3] are deployed without intervention to makeprogress on validation of the instruments for future research studies, therefore cleaning thatmetaphorical mirror. Despite the impossibility of perfectly representing a mental model, thiswork takes a
on research [18] [19] [20].Women also are more likely to use student-centered teachingpractices [21] [22]. Moreover, women show greater commitment to community service in theirfaculty roles [23] and are more likely to pursue service as scholarship [24] [25] [26]. Park notesthat some responses to this gendered division of labor problematize women [17]. For example,women are often advised to become better at saying no to service requests in order to prioritizeresearch. She argues that such advice reflects sexist attitudes pervasive in our society thatundervalue nurturing tasks (child rearing, teaching, advising, mentoring) and communal servicetasks (departmental and institutional service) often undertaken by females. Moreover, Parkargues that
scalesrepresenting academic challenge (higher order learning, reflective and integrative learning,learning strategies, and quantitative reasoning) and two scales representing experiences withfaculty (student-faculty interactions and effective teaching practices). The subscales associatedwith the latter set of indicators (experiences with faculty) are similar to faculty support andstudent-faculty interaction scales used in other research efforts. In contrast, the four subscalesassociated with academic challenge reflect what students actually do in their academic endeavorsby measuring time on task associated with the various skills that students use and develop duringtheir college experience [15].Studies which focus on the emotional aspects of engagement are
and BackgroundDespite decades of targeted effort and resources, women remain dramatically underrepresentedin engineering fields (Yoder, 2012) and this underrepresentation can lead to a number ormarginalizing experiences. Researchers have demonstrated the ways in which masculine normsand values are reflected in engineering practice and therefore code the discipline as male(Dryburgh, 1999; Secules, 2019). At the same time, technical/social dualisms map intomale/female binaries in ways that inform and support beliefs about what counts as engineeringwork and what is peripheral to the practice (Faulkner, 2000, 2007). These factors combine towhat amounts for an unwelcoming or chilly climate for women in most engineering fields(Ambrose, Bridges
qualities they havethat are not reflected in quantitative measures like SAT scores or high school GPA.Next, we review the applications and look for other signs of academic potential and leadership.To us, leadership potential is signaled by significant participation in a student organization or asports team or a volunteer effort. Admittedly, this is not simple to determine, but generally, weare looking for signs of initiative, growth mindset, and working effectively on a team as we readthe applications.Finally, after the application stage we make a short list and interview those selected applicants.Most of these interviews are done on a campus visit day for prospective students. This interviewis not designed to determine if the applicants deeply
-profile with the advent of the spaceprogram starting in late 1950s. DBER combines expert knowledge of a science or engineeringdiscipline with the challenges of learning and teaching in that discipline, and the science oflearning and teaching generally to address discipline-specific problems and challenges. A widelyrecognized definition of DBER comes from the National Research Council [15], “DBER isgrounded in the science and engineering disciplines and addresses questions of teaching andlearning within those disciplines… DBER investigates learning and teaching in a discipline froma perspective that reflects the discipline’s priorities, worldview, knowledge, and practices. DBERis informed by and complementary to general [educational] research on
NTP analogy, the telnet protocol offers a network administrator aquick way to set up a text-based console connection between a computer and a network deviceuses port 23. It can be shown visually as an individual (I) being able to establish a quick andconvenient connection with a network hardware device. The Network News Transfer Protocol(NNTP) uses port 119. It would seem like a problematic port number to memorize; however, ifone imagines looking at this number reflected in the mirror, it would be “911” -- which forreasons yet unclear to the author -- is what most news these days is. An open newspaper showsthe 119 port number with images and text regarding the news of the day. Email is an extensiveglobe-spanning system which can be shown by a
. Nextwe incorporate sklearn 40 so students can execute and explore the results of machine learningalgorithms. To prepare for machine learning content students watch bots videos 14 and they arealso assigned some ethics reflection prompts in response to Cathy O’Neil’s TED Talk 35 .The common thread across topics is the problem-solving heuristics shown in Figure 1. Weintroduce these early on and revisit them with each topic and explicitly point out when we areusing a strategy, or trying several of them, to solve a problem. For example we point out the useof concrete examples for solving encoding problems, developing algorithms, and initially usinghard-coded values in incremental web development. Another example is how students areexposed to
knowledge gains, interest in the degreeprogram, and ability to function as a professional engineer. The mobile boards have also beenutilized in other disciplines such as mechanical engineering using two experiments developedand tested in a class. [5-12].Connor et. al. observed that to successfully adopt and incorporate innovative educational devicesinto curricula within and across multiple institutions, understanding the potential advantages isessential, but understanding the barriers that can occur is just as important to ensure theeffectiveness of implementation. For the Mobile Studio project, they identified barriers as: (i)reflected experience of both students and instructor, (ii) the use and the development ofsupporting resources to the device
institution, in a student’s decision toremain there. However, culture and student perspective should also be valued and considered.Institutions that are more agile in doing this may be more successful at maximizing retention andsuccess for wider numbers of students, with a range of backgrounds related to race, ethnicity,socioeconomic status, environment, and/or the intersectionality of these and others. For example,students from backgrounds that reflect first-generation college attendance can also face a rangeof similar (though not identical) challenges. While there can be various approaches to enhancingretention for students of all backgrounds, first-semester GPA may help better predict andencourage graduation for students [11-13].STRIDE: A Cohort
improvement process. Student learning outcomes are developed with the consultation of the graduate faculty committee, Industry Advisory Board (IAB) and alumni, who are the constituents of the program. Data are collected every three years to assess the attainment of the learning outcomes. Analyzed data are presented to the graduate faculty committee to identify improvement needs. Approved improvements are implemented and assessed. The learning outcomes are periodically reviewed by the constituents to ensure that learning outcomes are still valid and relevant to reflect the needs of the industry. Student learning outcomes are developed with the consultation of the graduate faculty committee, Industry Advisory Board (IAB) and alumni, who
., 2016, p. 6). However, this dichotomy does not reflect the heterogeneity and blendof real engineering practice in industry, thus there is a tension that arises within the division oflabour. Women and minoritized individuals will assimilate valued forms of technical masculinityin the workplace in order to build positive professional identities. This techno-social dualism isused as a framework for analyzing engineering design discourses to deconstruct invisiblemessaging that may unintentionally create spaces that are not inclusive.MethodThis paper uses discourse analysis to review highly cited engineering education literature onengineering design and observe themes. The discourse analysis methodology and the datasetselection method are both
]. Similarly,the faculty of the pilot sections prepared a pre and post survey that all students taking EASC1107would be asked to complete. IRB approval was obtained, and students were asked to consentbefore completing surveys. The surveys had students create an anonymous identifier by whichwe were able to match their pre and post surveys while retaining student anonymity. Due to thechallenges of having all students complete the pre/post survey, as well as one faculty member notpassing out the post survey in time, the analysis is presented for 3 sections of makerspacecourses with 22 paired responses, and two sections of the traditional course model reflecting 25paired responses.The pre survey was passed out in the middle of the semester, just prior to
others interested in the project to discuss skill sets and to make ageneral determination of their compatibility as teammates.During each lab time, up to 75 students mingled and placed sticky notes on up to 25 posters. Weallocated about 45 minutes for this mingling process. Students were encouraged to monitor thenumber of sticky notes, colors, and names on a particular project poster in order to gage the levelof interest and note which other students were interested in the project. Based on thisinformation, they had the opportunity to adjust their choices. Pictures of the activity as itprogressed are shown in Figure 5.After this first 45-minute round, we asked the students to stop and reflect: Did their first-choiceproject include people with
activities we will increasestudents mindset in the three C’s as compared to a control group. The assessment includescuriosity scale pre & post survey and three reflection assignments.MethodsParticipants - This research project was approved by Vanderbilt’s IRB # 191344. Participants inthis research were broken into two major groups, intervention and control. The interventiongroup are students who enrolled in the new introductory chemical engineering module. Thecontrol group are students who enrolled in the historical model of the chemical engineeringsection. Table 1 below, summarizes the number of students in the control and interventiongroups.Table 1. Enrollment data for Control and Intervention Modules Control
that fallunder 1-3 of the learning outcome categories. Figure 3 presents the number of students who havehighlighted each of the learning outcome categories, from 2017 to 2019. Since one student coulddescribe up to three learning outcomes of the same category, the counts do not reflect the totalnumber of mentions per category.Combining all data from 2017 to 2019 (Fig. 3), the responses were categorized according to theiralignment to the five key learning objectives of the course (Appendix I): Reactor Physics Theory(11 of 29 students), Nuclear Fuel Life Cycle (9 of 29), Reactor Technology (12 of 29), NuclearSafety (8 of 29), and finally the Connection between the Nuclear Sector and Society/Public (15 of29). The societal aspect of nuclear
engineering, who are particularlyvulnerable to dropping out of engineering careers.Career commitment reflects students’ intention to work in the field of engineering. Measures ofstudents’ self-reported commitment to career have primarily been used by others as outcomevariables [10], [11]. In our analysis, we model the possibility that commitment to an engineeringcareer may serve as a motivator to obtain the knowledge and credential often necessary forstudents to obtain their occupational goals. Because these are early career students, we expectthem to have relatively low commitment to the field of engineering in this baseline data, butmodeling their expressions of commitment throughout their undergraduate education may helpus better understand their
, “Students’ agency beliefs involve how students see andthink about STEM as a way to better themselves and the world along with being a critic ofthemselves and science in general [20, p. 939]. The critical thinking perspective is intimately tiedto engineering agency beliefs, where students become “evaluator[s] of STEM as well as becomecritics of themselves and the world around them through self-reflection” [39, p. 13]. In essence,agency beliefs in this framework are based on a spectrum of how students view engineering as away to change their world or the world at large.Most agentic frameworks in engineering education used qualitative research methods. However,Godwin and colleagues [40] and Verdín and Godwin [41] used quantitative measures to
‘COSMOSEducational Toolkit’.Initially, several teachers stated that the lecture and lab phase (weeks 1-2) of the program couldhave been shorter, rather than full-day activities because there was a lot of material to absorb. Inaddition, teachers also noted that they especially enjoyed the lecture topics that coincided directlywith lab experiments, as this gave them a sense of how-to best design lessons for their own studentsby being able to actively take on a learner’s perspective. These comments were made immediatelyafter the first 2-weeks of the PD program. At the end of the PD program teachers reflected andstated that the rigorous lecture and lab phase supported their conceptualization of wirelesscommunications in order to best create lessons in the
reflective stagesof learning, preparing them for success in future research and professional design engagement.As a bridge between academic and professional worlds, it can provide the initiating sense oflegitimately belonging to a profession, a crucial step toward long-term productivity within theprofession [11].The application of the impacts of SBL and of the exploration of developing trans-disciplinarystudy firmly rooted in a process acknowledging inherent conflicts between methods and modelsembedded within each participating discipline should provide useful data, insights, andreplicable models for programs seeking to improve minority persistence and success in STEMresearch and professional practice.In addition to the program’s potential to more
quilombolas (that is, communities of descendants of runaway slaves)), building up cultural and economic empowerment.All projects count with undergraduate and graduate students and a project coordinator, who maybe of Soltec’s permanent staff or a volunteer collaborator.Project training is usually provided in four ways: i) on the teams’ study sessions, which are runevery two weeks or monthly, and are meant to offer space, time, and opportunities to acquiringtheoretical tools for the support of the assisted groups and to reflect and evaluate about theprovided support achievements; ii) on general educative activities offered to all of the Soltec’steams on issues such as solidarity economy, popular education, racism, sexism, LGBTQ-phobia,etc.; iii) on
modelingrelated questions at the end of the semester. In addition, they provided longer responses andmore specific words related to modeling types at the end of the semester. Further analysis isneeded to understand the extent of their knowledge gain during the semester.AcknowledgementsThis work was made possible by a grant from the National Science Foundation (IUSE 1827406).Any opinions, findings, and conclusions or recommendations expressed in this material are thoseof the author and do not necessarily reflect the views of the National Science Foundation.Table 6 – Word cloud representation of student responses. Course Pre Post Publi c Scho ol Priva te Scho ol Cour se 1 Priva
the course, after a key milestone;and the third interview set was between 1-3 months after the end of the course project. Thisspread allowed data collection which would capture temporal and situational contexts toinfluence the data, as well as allow the liaisons to regularly reflect on the value of the project,enabling rich data.The interview methodology used followed the semi-structured, intensive interviewingapproach, where the premise is to create a directed conversation with individuals who haverelevant experiences, which – with the help of the interviewer – are reflected upon in-depth ina way that is rare in everyday life [36]. Broad open-ended questions were devised toencourage interviewees to explore the notion of value for themselves