problem often reflected the presuppositions, preferences, and expectations of others in thegroup, along with the acceptable procedures and structures constituting the organization. Themethods participants followed for working on a problem or project depended on instruction andguidance from coworkers and managers reflecting the preferences and expectations of others inthe organization. The complexity and ambiguity of some of the problems reported by the newengineers in this study agrees with the descriptions of ill-structured problems provided byJonasson, Strobel, and Lee46. They characterized the everyday problems of engineering as ill-structured, having multiple, often conflicting goals and multiple solutions. Furthermore, non-engineering
3preparedness. As such, the primary research question guiding this paper is: How can wemeasure the global preparedness of graduate and undergraduate engineering students? In designing my instrument I used the same subscales of the teacher instrument andaltered individual survey items within the subscales to reflect specific engineering foci asrecommended by the National Academy of Engineering. This paper presents the pilot researchresults from implementation of the global preparedness index that I designed for engineeringstudents. The following seven subscales were utilized in creation of this global preparednessindex. Ethic of Responsibility: Deep personal and care concern for people in all parts of the world; sees moral
Page 11.602.3session and review the videotape. The consultant showed portions of the videotape (forstimulated recall) and encouraged the faculty member to reflect upon the experience, a protocolthat has also been shown to be effective in improving teaching11. As with Cohorts 0 and 2,faculty in this cohort received details about the midterm and end-of-term student ratings onlyafter the term was over.1.2. Approaches for evaluating teaching improvementTo compare and evaluate the methods to improve teaching, data analysis from three separatesources was conducted. These include student ratings of teaching surveys administered atmidterm and again at the end of the term, an online faculty survey, and focus group discussionswith the consultants who
and Lucas [15]. The study will be exploratory and the intervieweeswill be asked to give their personal perceptions of how they see the phenomenon and alsoregarding how and why they have developed those viewpoints.One week before the interview, the interviewees will receive the interview protocol, includingthe questions and short texts presenting the three contemporary challenges the informants aresupposed to reflect upon. The following questions will form the basis for the interview. 1. How do you think these challenges affect the development of your discipline and the educational program(s) you are involved in? 2. What do you expect the situation to be 10 years from now? 3. How do you prepare your students for the future with
, “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
, Innovation, and Hands-on Learning", International Perspectives on Engineering Education, ed. S. Christensen et al.,Springer International Publishing Switzerland, 2015.[7] K. D. Strang, "Improving standardised university exam scores through problem-basedlearning, " International Journal of Management in Education, vol. 8, no. 3, p. 281, 2014.[8] A. G. Pereira, M. Woods, A. P. Olson, S. V. D. Hoogenhof, B. L. Duffy, and R. Englander,"Criterion-Based Assessment in a Norm-Based World, " Academic Medicine, vol. 93, no. 4, pp.560-564, 2018.[9] W. Ray and H. Cole, "EEG alpha activity reflects attentional demands, and beta activityreflects emotional and cognitive processes, " Science, vol. 228, no. 4700, pp. 750-752, Oct. 1985.[10] C. Demanuele, S. J. Broyd
assessment in multiple large-enrollment engineering science courses,allowing for quantitative and qualitative comparisons across these courses. These results willdemonstrate ways in which instructors effectively implement formative assessment and changetheir teaching based on the feedback they receive, and they will also suggest ways in whichformative assessment can be improved in traditionally lecture-based engineering science courses.AcknowledgementsThis material is based upon work supported by the National Science Foundation under Grant No.DUE-1711533. 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.References
with a familiar group of peers, whichseems to lead to a greater sense of community, based on reflection by course instructors whonoticed particularly close-knit groups. Administrators from each department worked to developinitial outlines and structures that would facilitate curricular overlap and connection across eachintegrated “trio” of classes. Instructors in each “trio” were expected to collaboratively exploreand implement effective ways of reinforcing and integrating concepts and curriculum from thecourse they were paired with in their own courses. The program was implemented for sixsections of each course during the Fall 2016 semester. Another six “non-integrated” sections ofthe introductory Design Thinking course were taught with the
and I like to do other things besides math.”The above excerpt, at a first glance, seems to contradict the value that Rebecca earlier expressedregarding intellectual performances. But we found the distance Rebecca sought to achieve from beingcategorized as an engineer reflected more of a desire for her individual agency rather than any disdain forengineering. This desire for agency was particularly heightened in light of her participation in engineeringas a woman. She described how others’ perception of her, in particular as a woman in engineering,invaded her individual sense of control of her choice to exist as an engineering major: I’m a girl so I think a lot of people [will say], “Good for you.” Sometimes it makes me feel
acknowledge that these groupings are narrow basedon the available data. Uneven population sizes from the resulting separation is due in part to themany students who had a neighborhood socioeconomic that was the same value as the quartilemedians. This challenge in data analysis alone emphasizes the need for study of low-socioeconomic students and their relatively few pathways into engineering. Students who attendcollege in engineering majors are surprisingly homogeneous in their neighborhood socioeconomicstatus. These groupings reflect the engineering student population, and thus provide informationon the types of attitudes toward and experiences with STEM that engineering students in a college-going population have by socioeconomic status in
. Contentious issuesincluded what students thought of the midterm and final exams in these courses, what studentsbelieved to constitute cheating on homework, how students used diverse resources to assist incompletion of homework and course assignments, what unofficial activities students did duringlecture periods, and general student opinions of and reflections on their mathematics experiences.Additional data collection in the third semester included gathering historical artifacts related tothe engineering mathematics curriculum and specifically Calc 3 and Diff Eq. Trips to multiplelibrary archives to collect historical course catalogs, building maps and floor plans, architecturaldrawings, and administrative documentation all helped to shed light on
changes with other members. Despite theimportance of conversation toward meaningful change, written expressions provided significantvalue to the community. Seeing the week’s discussion reflected back in text (in the form of aweekly email summary with references) was highly valued by community members, and allowed Page 26.1128.10absent members to retain ties to the community. Cohort/ Topic Duration/ Cohort Member projects/ Facilitator Incentives
support in higher education is significant, studies of therelationship between faculty support and engagement are notably absent from the highereducation literature, particularly in engineering education research. This work seeks to addressthis gap, in part, by studying the relationship between faculty support (both formal and informal)and behavioral and emotional engagement, because the latter constructs reflect the motivationalstate of the student and motivation is an important predictor of present as well as future behavior.MethodsThis research is part of a larger five-year, multiple institution research study that examinesconnection, community, and engagement in STEM education. In this larger study (describedelsewhere14), patterns of
reflections about their SRLstrategy use. While the intervention may have impacted student self-report of their SRL strategyuse, two benefits occurred: improved rapport with the researcher, who provided the intervention,and a greater fluency of SRL strategies in the reflections and interviews30.The survey distributed at the end of semester included four sections with 86 items. Some itemswere adapted to be applicable to an engineering course from the Motivated Strategies forLearning Questionnaire (MSLQ)31,32. Other survey items were written in three sections16: a 13item goal orientation section, a 28 item FTP section, and 16 items on task and course specificproblem-solving self-efficacy33. The MSLQ31,34,35 has been well-documented, and the MSLQ andMAE
betterunderstanding of racism in the same way sociologists do, for example. However, by not namingracism, we allow racism to persist.Data Driven ResearchData driven research is crucial to elucidate many pathway impediments in engineering, informthe community and move toward strategies for improvement. It is important that this researchtakes multiple forms: large quantitative studies, small qualitative investigations and personalself-reflections. We need to expand the categories of data we collect, where possible, includinggeneration in college status, veteran status, disability, LGBTQA (lesbian, gay, bi-sexual,transgender, queer or questioning, and ally or asexual). We also need to collect demographicvariables aligned with our current understanding of
two suns, four different cultural groups with different resource constraints and industrial needs. Path Finding I Create a step-by-step instruction on drawing lines to create a quilt pattern on a n x n grid and identify similar structures in other teams’ quilt patterns. Path Finding II Use rotation, reflection, and loop to generate a more complex quilt pattern based on simpler base pattern. Marble Maze I Each team member creates a sub-structure allowing a marble to travel at least for n seconds in week 1 and the team puts all sub-structures together to make a super- structure in week 2. Marble Maze II Teams are broken up and now must
interdisciplinary collaboration, design education, communication studies, identity theory and reflective practice. Projects supported by the National Science Foundation include exploring disciplines as cultures, liberatory maker spaces, and a RED grant to increase pathways in ECE for the professional formation of engineers.Prof. Thomas Martin, Virginia Tech Tom Martin is a Professor in the Bradley Department of Electrical and Computer Engineering at Virginia Tech, with courtesy appointments in Computer Science and the School of Architecture + Design. He is the co-director of the Virginia Tech E-textiles Lab and the associate director of the Institute for Creativity, Arts, and Technology. He received his Ph.D. in Electrical and
through undergraduate courses?In this work, we aim to answer this question through a sequential exploratory mixed methodsdesign. Using the Multiple-Institution Database for Investigating Engineering LongitudinalDevelopment (MIDFIELD), we qualitatively coded records of courses offered to engineeringstudents at one public institution between 1989 and 2011 to generate profiles reflecting differentlevels of data analysis preparation. These profiles were then quantitatively clustered into sixdistinct levels. The cluster analysis revealed variable patterns of data analysis preparation acrossdifferent engineering majors. Results from this study also provide a baseline for employers toevaluate the data analysis training of engineers, especially as it
buildingconnections and shared identities between and among stakeholders in a school or department ofengineering; this result suggests that a carefully developed assistant program may go a long wayto support diversity and inclusion efforts. Future research is needed to explore additionalstakeholder experiences with different variations of learning and teaching assistant programs,especially those at institutions with different cultural norms than those sampled for this initialstudy.AcknowledgementsSpecial thanks to the participants who agreed to be interviewed for this project and generouslygave their time and reflections. We would also like to give special thanks to the Louis StokesAlliance for Minority Participation (LSAMP) and the Bridge to Engineering
completed in preparationfor each class, as well as guiding questions for students to consider as they studied.Unfortunately, it was not possible to track the extent to which students engaged with the content.Students were required (via a participation grade) to submit responses to reflection questionsprior to class asking them to identify: i) the main concepts covered, and, ii) any specificquestions they would like addressed in class. Understanding of concepts covered online wasassessed in class using iClickers, with the remainder of class-time focusing on problem solving.3. Study Design Total enrolment for the course was approximately 1400 students in twelve lecture sectionsranging in size from 80–160 students, depending on program. Based on
equations or other solution methods.3 To capture thischaracteristic, we examined two facets of student performance on the innovation test. The first werefer to as innovation. The innovation score reflects how effectively students are able apply theirknowledge base and analysis tools to devise a wise strategy for solving a difficult open endedproblem they have now encountered previously. The second facet we refer to as efficiency. Thisscore examines whether students applied appropriate governing principles and constitutive equationsto model the process. A high score on these two categories indicates that a student is approaching theproblem similarly to an expert in the area who was considering how to solve the problem for the firsttime. These coding
in the Journal of Engineering Education, engineering education researchcan and should contribute to learning theory, not only be informed by it [7,12]. Reflecting onepistemology helps researchers to situate research questions in the big picture. For example, inthis study, we want to know why and how traditional academic structures persist in light of newlearning theories that reflect increasingly dynamic and active views of knowledge and learning.It is our hope that studying methods of group assessment will contribute to solving thisepistemological problem.Contemporary theories of learning reflect a shift from a teaching-centered approach, focused onknowledge transfer from teacher to student, to a learning-centered approach, focused
the language used in each article to explain therationale for using mixed methods are included in the table, along with the category name. Only2 of the 16 articles contained no statement that could be identified to reflect a rationale foremploying mixed methods. Page 24.68.8 Table 1: Articles Using Qualitative and Quantitative Methods and Mixing PaperJournal Paper Title Year Why Collect Qual and Quant Data? Category
. Page 25.864.2social and cognitive psychology, sociology, education, and other STEM education disciplines) tobring valuable research skills and perspectives5. However, like many interdisciplinary fields,engineering education has the difficulty to identify what constitutes ‘interdisciplinary’ work dueto lack of appropriate indicators to measure the degree of knowledge integration. It is thusworthwhile exploring current initiatives to lead the formation of interdisciplinary networks ofengineering education researchers and the changes of interdisciplinarity over time usingbibliometric indicators. To date, interdisciplinarity of engineering education research has beenconceptualized in various ways; for example, by reflecting the international
entering he course have:1) algebraic skills to be able to find slope and use equations for lines, 2) geometry skills to beable to use a coordinate grid, understand the concept of similar figures and the area-diameterrelationship of circles, and 3) physics knowledge of light reflection and how light travels instraight lines. While these concepts are considered pre-requisite knowledge, the concepts arereviewed within the first few lessons of the unit. The unit consists of 11 lessons and was taughtover the course of 9 3-hour workshops. The lessons were organized into lesson sets groupingtogether broader learning episodes; these lesson sets are described in greater detail in table 2
Huberman’s contact summary form to capture immediate reflections on the interview and toprepare for the next interview. These reflection questions are reproduced in Table 4. Table 4: Post-interview reflection (memo). From Miles & Huberman’s46 contact summary form (p. 53) 1. What were the main issues that struck you in this interview? 2. Summarize the information you got (or failed to get) on each of the target interview areas you had. 3. Anything else that struck you as salient, interesting, illuminating or important in this interview? Any patterns? 4. What new (or remaining) questions do you have in considering next interview with another subject
mentor, I persisted.” — Female post-doctoral associateiThe need to increase the numbers of traditionally underrepresented minorities (URMs) in engineeringcareers and research is well documented. Underrepresented minorities (African Americans,Hispanics or Latinos/as, and American Indians/Alaska Natives) make up approximately 31% ofthe population1, but account for just 11.6% of the science and engineering workforce2. Thisdisparity is also reflected in the demographics of students earning degrees in engineering. In2008, just 12.4% of the Bachelor‘s degrees in engineering were earned by underrepresentedminorities3. Looking at graduate degrees for the same year, 19% of the Master‘s degrees and3.5% of the doctoral degrees granted in engineering fields
, students spend less time inreflection over the course material, which is unfortunate because reflection is more likely to lead todepth in conceptual understanding and critical thinking about the material2, 3.Evidence that the traditional collegiate-level strategies are not successful in developing deep, criticalthinking in college students has been making national headlines. The recently published“Academically Adrift” by Arum and Roksa4 concluded that colleges and universities graduate studentswith no significant increase in critical thinking. Meanwhile, over the past few decades, the author citesthat average GPAs are on the rise. Albeit critical thinking isn’t the only lens to view success (nor isthe Collegiate Learning Assessment used in “Adrift
Education9 identifies theprinciples of research which include questions for education research to be posed such thatquestions could be investigated empirically, grounding research into theory, and seekinggeneralization among studies. The workshop sought to promote the principles of rigorousresearch in engineering education and facilitate developing an understanding of these principlesamong the participants. The workshop was designed based on ideas that align with the theory oftransformative learning10, 11, providing participants with the opportunity to reflect and engage ina discourse with the peers and workshop facilitators.Forty-three engineering and engineering technology faculty members from across the countryand abroad with at least some prior
Page 24.911.1 using pre- and post- concept inventories to assess improvement, an online reflection tool to assess pro- cess, and a grading rubric to assess the solution (general model and specific solution). We are identifying numerous problem solving processes used by the student teams, as well as the range of problems that c American Society for Engineering Education, 2014 Paper ID #10443 can be addressed, to determine how effective the various processes are relative to improved conceptual understanding. Collaborators Mary Besterfield-Sacre, University of Pittsburgh, Larry Shuman, University