found in Figure 1. For each task-specific self-concept, a nine-item scale was developed using the design process. The first item asked for the participant’sself-percept towards conducting engineering design as a whole (giving the engineering designscore) while the other eight items reflected each step of the engineering design process (averagedto be the engineering design process score)2. Page 23.30.3 Figure 1. Steps of the engineering design process12.Self-efficacy affects a person’s behavior towards an activity, and their self-percepts can affectthe thought patterns and neurophysiological reactions13. Those with high self
-audio.Guiding Theory: Identity and agency in figured worldsThe overarching framework guiding the A4I Project is Identity and Agency in Figured Worlds.Holland and colleagues [8] introduced this conceptual framework to elucidate the intricatedynamics between social systems and individuals. They define it as the realized capacity of anindividual to deliberately and reflectively engage in activities situated within "socially-produced,culturally-constructed" contexts (i.e., figured worlds, [8], p. 40-41). In this project, we use thisframework to conceptualize engineering education as figured world in addition to others, such asrace and gender, that overlap and influence students’ experiences in their engineering programs.As students iteratively interact
by Chinese-American,Anglo-Indian, or Latino writers [15]. Code-switching can take on various forms, but in this paper,we define it as the use of both Spanish and English in bilingual communication. This showcasesthe intricate linguistic dance that bilingual speakers engage in, which reflects a blend of linguis-tic choice and cultural narrative. This phenomenon is especially prominent in communities whereboth languages are woven into the social and cultural fabric, allowing individuals to fluidly navigatetheir bilingual identities [16], [17]. Beyond simple language mixing, code-switching incorporatesa sophisticated amalgamation of grammatical structures, cultural cues, and contextual relevance,highlighting the cognitive dexterity of bilingual
Engineering Technology, the careeris Engineering” trademarked by the American Society for Engineering Education reflected thetypical experience of ET graduates. However, despite these and other efforts to assert that ETis a separate but equal, less mathematically rigorous, more practical pathway to a traditionalengineering career, this messaging is often inconsistent with the reality of opportunities andadvancement in college and after graduation. Many employers do not hire ET graduates forengineering positions for a variety of reasons, including a lack of familiarity with the preparation 1and qualifications of ET graduates, and the tendency for many employers to still associate ETwith a two-year
, microcontrollers,and robotics to prototype a variety of mechatronics projects. These activities illustrated real-world applications of fundamentals covered in introductory lectures to reinforce and impart agreater sense of understanding. Such a curriculum and instruction strategy exposed teachers tofundamental mechatronics design principles as they learned the core concepts through activitieswherein they built practical devices that integrated and illustrated their learning. The discussionportion of each session provided participants with an opportunity to reflect on the session’s workand to brainstorm ways of integrating these activities in K-12 STEM learning. On the last two days of guided training, an entrepreneurship module—consisting
the Fall of 2018. Eachinterview used journey maps to elicit students’ identity trajectories and probed further into theirshort and long-term goals and current educational environments, especially in response to theCOVID-19 global pandemic and its impact on engineering education. In this research, wespecifically use journey maps as a reflective tool for students to document their “high points” and“low points” within a particular semester (i.e., Summer 2019 to Fall 2019 or Winter 2019 to Spring2020). We also used journey maps as an artifact to guide the interviews and operate as an elementof procedural and communicative validation [11]. In alignment with the identity trajectory model,these journey maps allow us to differentiate between the most
incorporate computers only forresearch (Wang et al., 2011). If integrated ETS instruction reflects these narrow views, studentswill not develop an understanding of the breadth of technologies and/or how they support scienceand engineering. Therefore, professional development and teacher preparation is needed toensure teachers have robust understandings and confidence to implement ETS instruction(Brophy et al., 2008; Dare Ellis, & Roehrig, 2014; Roehrig et al., 2012).The ill-defined nature of ETS instruction can also pose unique challenges for teachers. By nature,science instruction that incorporates engineering is student-focused, involves active learning, andemphasizes process rather than a single correct answer. This is a stark contrast with
interviews was designed to understandstudents’ background and pathways into engineering. The second round of interviews involvedasking the students to complete a journey map to guide the interview focused on understandingtheir identity trajectory. This journey map documented the “high points” and “low points” of astudent’s experiences over the previous semester and was used as a reflective tool and datacollection artifact to guide the narrative interviews. The third round of interviews continues to usejourney maps and students’ stories to understand their development in engineering.The interviews were used to develop “restoryed” case summaries. A restoryed case summary is ashort version of each student’s pathway and highlights. In addition to these
mentors, they made more use of officehours when tutoring was not offered or when the hours conflicted with their schedules.Overall, student ratings for tutoring and SI improved from Fall 14 (the first semester in whichCOMPASS students provided feedback) until Fall 15 (see Figure 1). Ratings declined somewhatin Spring16, which appears to correlated with the fact that fewer students were attending tutoringsessions. It also likely reflects the loss of the SI program after the first year.Figure 1. Student Ratings of Tutoring/Supplemental Instruction Tutoring/SI 100% 90% 80% Extremely important 70% Very important
the Entrance to Major process at the beginning of the junioryear (i.e., enrollment in a specific major). Secondary outcome measures are retention in STEMmajors and retention at the University. This research is generously funded by the NationalScience Foundation (NSF IUSE #1525367). Please note that any opinions, findings, andconclusions or recommendations expressed in this material are those of the authors and do notnecessarily reflect the views of the National Science Foundation. The Intellectual Merit of this research is two-fold: examine variation in Engineeringretention for three models of bridge programs and produce a series of workshops on Engineeringbridge leadership, funding, and sustainability strategies for Engineering summer
Thinking. This included interactive lectures in design process, prototyping methods and production. The course textbook, “Making It”19 was used extensively during this por- tion of the course. • Week 13 (11/30/15): Keys to academic success as a Mechanical Engineering student. This motivational lecture is included to promote reflection on the students’ exposure to Mechanical Engineering, as well as provide advice and insight into expectations in the sophomore, junior and senior years
obtain employment outside of academia. In termsof the effect on career outcomes, previous studies found evidence that postdoc training enhancesresearch productivity and increases research output [14], [15]. However, postdoc experiencedoes not significantly influence STEM PhDs’ earnings up to 15 years after PhD graduation [15],[19], [21]. The importance of analyzing the effect of postdoc experiences that vary by field of studyhas been stressed by Horta [14] and Kahn and Ginther [19], for example, in part because thedifferences across fields of study reflect their distinct traditions and identities, especially atadvanced levels of academic training [22]. Since the differences in postdoc experience acrossfields of study exist even within
energy minor, internships, and related activities of the consortium http://liaec.aertc.org/education.htm Co-development and use of templates for electronic portfolios, used by students in the minor program to document evidence of learning, collect reflections, and assess student progress, both in the minor and in internships related to minor program requirements. Several consortium meetings held to assess progress, discuss obstacles, and collect information on cross-registration and course development.Energy Education ModelSeveral learning objectives were established for the minor in energy science, technology andpolicy (ESTeP). The goal is that when students complete the minor, they should be able to: 1. Understand
accountability pressures for reading andmathematics3, 7. Integration of STEM subjects has been suggested as a way to address thechallenges of diminishing instructional time while providing students with the opportunity forengaging in realistic and multidisciplinary contexts that reflect real world problems. With manystates adopting the NGSS8, curricula for integrating engineering with an explicit focus onteaching science are needed.PictureSTEM is a curricular development project aimed at creating STEM integration moduleswith an explicit focus on engineering design, as well as standards-based mathematics andscience, for grades K-5. The PictureSTEM units were developed to meet this need for explicitSTEM integration modules that meaningfully teach each of
uncertain and perhaps even unwilling toembrace sustainability (at least, the environmental pillar) as a valid and valuable part of theirengineering curriculum. Combined with the relatively weak power of ethics (includingsustainability) over personal and business interests,8 students may see sustainability as a noblebut vague and entirely unreachable state of affairs.Previous research studies in engineering education have highlighted the fact that students oftenbring into the classroom views of sustainability that reflect both the broad and confusingdefinitions of sustainability in national and global circles and a narrow view of what engineersare capable of impacting and desiring to contribute to improved sustainability practices
developing since the 1970’s, led largely by Dr. David Kolb; this theory is based “ona learning cycle driven by the resolution of the dual dialectics of action/reflection and ex-perience/abstraction” 43 . The importance of experiential learning has been discussed for themedical field 1;3;9;15;18;33;61 , engineering 2;19;76;84;85 , leadership roles 16;29;32;34 , and general edu-cation 7;58;86;87 . For further reading on broad applications of the experiential approach, Kolbhas compiled bibliographies containing numerous works spanning decades 44;45;46;47 . Burger found that experience with actual work is one of the strongest factors affectingcareer choice 22 while Tuss concludes that “experiential education strategies will strengthenschool science
for Engineering Education, 2020 Spatial Visualization Skills Training at Texas State University to Enhance STEM Students Academic SuccessAbstractA diagnostic of thirty questions administered to incoming STEM students in Fall 2013 and Fall2015 - Fall 2018 reflects that their spatial visualization skills (SVS) need to be improved.Previous studies in the SVS subject [1], [2], [3] report that well-developed SVS skills lead tostudents’ success in Engineering and Technology, Computer Science, Chemistry, ComputerAided Design and Mathematics. Authors [4], [5] mention that aptitude in spatial skills isgradually becoming a standard assessment of an individual’s likelihood to succeed as anengineer.This research reports the
Enhancement (FIRE), is supportedby the National Science Foundation under Grant No. 0969382. Any opinions, findings, andconclusions or recommendations expressed in this material are those of the authors and do notnecessarily reflect the views of the National Science Foundation.1.0 Project Activities1.1 Overall Goal Page 23.551.2The most specific and immediate goal of this project is to increase the School of Engineering andEngineering Technology (SEET) graduation rate from its 2009 five-year average of 42% to animproved five-year average of 65%.1 To achieve this target, 1-year retention of new studentsmust be increased to 85% from its 2009 level of 68
of Learning Styles25 as shown inTable 1 is composed of four dimensions: active/reflective, sensing/intuitive, visual/verbal, andsequential/global. Active learning tools are designed to meet the needs of students with a rangeof learning styles. Particular approaches to teaching often favor a certain learning preference.Therefore, it is important to incorporate a variety of teaching approaches. This index can assistinstructors in creating active learning modules that impact all student learning styles effectively. Page 25.752.7 Table 1. Learning styles categories.Myers Briggs Type Indicator (MBTI) Personality
NSFGraduate Research Fellowship. Some of these experiences were directly facilitated by the effortsof STEM CONNECT. For example, one Scholar applied and accepted an internship to Hudl aftera local tour, and other Scholars have received extensive feedback on application materials andletters of recommendation from project leaders. A total of twenty university Scholars havegraduated in computing and mathematics-related majors, with an average GPA of 3.66. Ten ofthese Scholars graduated with distinction. Further, 85% were either first-generation, women,and/or URM.The project consistently positioned Scholars as worth investing in. One community collegeScholar reflected on the importance of this positioning: I find it very encouraging knowing that
survey on students' online collaborative experience are shown in Table 8. They demonstrate that the students in the groups (B, C, and D) with scaffolding generally had higher level of perception or collaboration activities than those in the control group (A) without scaffolding on online collaborative learning. However, students in the cognitive cooperation-scaffolding group (C) showed lower levels when they were asked “the members in my group collaborate with each other effectively, ” “It motivates me to learn through the use of online discussion,” and “Team online discussion makes me reflect on the course content in a deeper level”. This result is in accordance to the finding by Weinberger 24, i.e., students following the cognitive scaffolding
reflect the views of the National ScienceFoundation.References[1] B. Donovan, D. M. Mateos, J. F. Osborne, and D. J. Bisacco, “Revising the Economic Imperative for US STEM Education,” PLOS Biology. Jan. 2014. [Online]. Available: https://doi.org/10.1371/journal.pbio.1001760[2] M. Smith and L.N. Willison, “Stem Obstacles In The Collegiate Setting,” Journal of STEM Education: Innovations & Research, vol. 22, no. 4. Oct. 2021. [Online]. Available: https://www.jstem.org/jstem/index.php/JSTEM/article/view/2532[3] A. Zilouchian, N. Romance, A. L. Myers, and D. Hamadeh, “A Collaborative Framework to Advance Student Degree Completion in STEM,” 2020 ASEE Virtual Annual Conference Content Access. July 2020.[4
)College-Student identity, or (c) Future-Engineer identity. Next, adapting Kaplan and Garner(2017) coding scheme to reflect our context of low-income college engineering students, scholarresponses were further broken down into the four components of the DSMRI model (1)ontological and epistemological beliefs, (2) purpose and goals, (3) self-perceptions and self-definitions, or (4) perceived-action possibilities. Examples of this coding are shown in Table 2.Table 2. DSMRI example codes from scholar interviews (adapted from Kaplan & Garner, 2017) DSMRI Component Description of Component Example Scholar Statements Ontological & Scholar knowledge and Ontological: “Low-income Epistemological emotion from
𝑊 = ∫ 𝑝𝑑𝑉 𝑉𝑖 The interview protocol was broken up into three separate stages (Figure 2) thatprogressively investigated students’ interpretations of the first law and the provided interviewprompts. To start, participants were asked open-ended questions about the first law ofthermodynamics to better understand how they conceptualized the first law prior to any furtherprompting. Afterwards, students proceeded to separately address one in-discipline and one out-of-discipline interview prompt. Interview questions during the second stage were modeled afterthe dynamic transfer framework [22] by first asking questions that primed students to identifyrelevant target tools and to reflect on their
material are those of theauthor(s) and do not necessarily reflect the views of the National Science Foundation.References[1] Museum of Science. (2021). Engineering is elementary. Available: http://www.eie.org/. [Accessed January 25, 2021].[2] Tufts University, About us: Center for engineering education and outreach. Available: http://ceeo.tufts.edu/about/. [Accessed February 15, 2021].[3] E. R. Banilower, P. S. Smith, K. A. Malzahn, C. L. Plumley, E. M. Gordon, and M. L. Hayes, Report of the 2018 NSSME+. Chapel Hill, NC: Horizon Research, Inc., 2018.[4] S. Brophy, S. Klein, M. Prtsmore, and C. Rogers, “Advancing engineering education in P-12 classrooms,” Journal of Engineering Education, vol. 97, no. 3, pp. 369-387, 2008.[5] M. W
own words.This instrument was developed to measure indicators of impact on the SCCT constructs ofoutcome expectations and self-efficacy. Figure 2: Outcomes and Subscales of the Pre/Post Test. Note: * indicates significant differences favoring Academy Cadets.To supplement the pre/post assessment we collected qualitative data through interviews andstudent reflection journals. At the end of each day of the Academy, students were givenreflection prompts about the day’s activities. Students kept an electronic journal which captureda record of all their responses to each prompt. These journals were analyzed and comparedagainst the findings from the pre/post survey to better understand student attitudes towardSTEM, big ideas students took
with COVID by setting up a designated study area that is only mine.” • “Adaptability, one of my strengths, has allowed me to accept the situation and work with what has happened.” • “I have adapted and modified my life to use connectedness in new ways. I am able to talk and reach out to others by other means rather than face to face during these times by the use of technology such as zoom.”Ongoing Research: Strengths, Social Identity, and Social NetworksSurveys and interviews by the external evaluator have not explicitly asked students to reflect onthe “strengths from a social justice perspective in engineering and computer science as context”model of mentoring and advising – instead, the evaluator has focused, to date
first-year studentswho were interested in pursuing mechanical engineering at a research-intensive university inNorth America. The participants are a subset of a sample from our team’s ongoing multi-methods study, which focuses on the curricular messaging about the nature of engineering workin core courses in two disciplines and how these curricular messages align with students’ ownengineering interests and career ambitions. The three interviews were chosen from the larger dataset to reflect a diversity of practices emphasized.The participants included in the present study varied in their interests, pre-college experiences,and self described social identities. Participant 1 identified as a South Asian woman; Participant2 self-identified as a
learned certain tools, or whichtools they had used prior to this semester and their college entry. Given the time between whentools were used and when students completed the surveys in question, their answers may nothave perfectly reflected their experiences. This difficulty in recalling the timeline of tool usageand when tools were learned is compounded particularly with simple tools and features of themakerspace, such as hand tools, whiteboards, or even a desk. Given that such tools and featureshave particularly interesting ramifications for makerspaces efficacy and their outcomes, theinformation lost from this could be considerable.While the information gathered does not perfectly capture how makerspaces are being used andthe motivations
expertise of the team. Coordinated iterative cycles of reflection and action were usedfor instrument development [30-31]. The instrument currently has seven baseline categories thatcould be applied to all ERC population groups and will be used to conduct cross-ERCcomparisons. Table 1 documents the baseline categories (excluding demographics):understanding of the ERC, impact on skills, culture of inclusion, mentorship experience, futureplans, and program satisfaction. These six categories were extracted from the NSF ERC BestPractices Manual [3] and ERC program solicitation [32] as cross-cutting categories that NSFrecommends evaluating to monitor ERC progress and impact around workforce development andculture of inclusion initiatives. Comparisons