-interviewed according to their rich experiences in teaching, research, andindustrial performance were invited to be the interviewees. Seven of them are from industries;eight of them are academic scholars and five are from research institutes. Most ofexperts-interviewed are invited in Taiwan, while 2 of 20 experts-interviewed are invited fromIndia and America, respectively. The profile of interviewees is shown below: 1. 12 experts-interviewed with PHD degree 2. 17 experts-interviewed have working experience over 20 years: 5 in industry, 7 in universities and 5 in Research Institutes Underpinned by employment and certificate guidance, fourteen questions (as tabulated inAppendix 1) were listed to be used for the interviews. These
. Background and MotivationThe purpose of this paper is to introduce mathematical and spatial-reasoning constructs that arekeys to academic success in engineering. The term, “construct”, is defined as a latent,unobservable trait, such as an ability or skill that directs how students select or generate answers totest items.1 Several constructs or latent traits have been identified as important in engineeringeducation. The authors illustrate how test items can be designed given various classroomassessment goals (e.g., course examinations, homework assignments) for two sets of constructsthat can result in reliable and valid scores. Specifically, two mathematical constructs and twospatial-reasoning constructs are the focus of this paper. The mathematical
CCM could be part of the answer.CCMThe main goal of the CCM is to assist in facilitating critical thinking and effective problemsolving among the collaborators. The CCM described briefly in this paper is made up of sixstages: Problem Formulation, Solution Planning, Solution Design, Solution Translation, SolutionTesting, and Solution Delivery. Each stage is further broken down into three phases.For the purposes of this paper we will only focus on the details of the first two stages of theCCM: problem formulation and solution planning. The three phases of the problem formulation Page 15.701.4stage (stage 1) are: Preliminary Problem Description
AC 2010-30: AN INVESTIGATION OF AFRICAN AMERICAN HIGH SCHOOLSTUDENTS' CAREER DECISION SELF-EFFICACYChandra Austin, Utah State University Page 15.167.1© American Society for Engineering Education, 2010An Investigation of African American High School Students’ Career Decision Self-efficacy Underutilization of minorities in science and engineering is a national problem 1. If Americais to maintain its global competiveness, we must educate our populace in high priority areas.African Americans continue to be hesitant to undertake the more rigorous math and sciencecourses that provide a base for preparation in engineering. Research states that this
responses to the EBAE were used to validate the instrumentand analyze the epistemological beliefs – certainty of knowledge, simplicity of knowledge,source of knowing, and justification for knowing – of first-year engineering students. Results ofthis study produced thirteen validated items, which gauged first-year engineering students’epistemological beliefs as slightly sophisticated – mean score of 63.8 ≥ 8.4 out of 100.IntroductionIn 2006, a special report addressing The Research Agenda for the New Discipline of EngineeringEducation identified five research areas to “inform how the content should be taught as well ashow future learning environments should be designed”;[1] one of these areas was EngineeringEpistemologies. Epistemology is a branch
education is to prepare students for engineering in the 21stcentury. Yet critics of engineering education point to the lack of preparation students obtain inschool. This paper examines the career supports and barriers that one cohort of recentengineering graduates experienced in the workplace. Social Cognitive Career Theory (SCCT)describes supports and barriers as environmental factors that individuals perceive as having thepotential to either aid or hinder their pursuit of a particular career goal.1 In this study, supportsand barriers are identified in the engineering departments of four U.S.-based companies. Thedata were gathered from semi-structured interviews with 59 newly hired engineers who hadrecently graduated from college. In two of the
Use of the Critical Incident Technique for Qualitative Research in Engineering Education: An Example from a Grounded Theory StudyAbstract The critical incident technique is a well-established qualitative research method that isuseful in exploring significant experiences in order to better understand resulting behavior. Thecritical incident technique is emerging as a tool for research and for building theories inengineering education.1, 2 This paper describes the initial state of a grounded theory study. Thepurpose of the larger study is to develop a theory that relates how students perceive the role oftheir family in making engineering-related academic decisions. The population
can be better understood by examining the studentexperience holistically.Theoretical Framework Veenstra et al. proposed a few minor changes to Tinto’s model to reflect the departuredecision of undergraduate engineers (See Figure 1).23 In their retention model, pre-collegecharacteristics affect how students experience college both academically and socially. Thestudent experience in turn impacts two broad commitments and academic success that influencea student’s decision to persist in the discipline. Thus the student experience is a critical variableand is defined by the student’s academic and social integration. Accordingly students’ academicand social integration is a key predictor of persistence in the Model of Engineering
; ≠ a participatory method to elicit, identify, and document student success needs; ≠ a mapping process to develop precise need statements that holistically capture a comprehensive set of engineering student needs of students; and a ≠ questionnaire to evaluate the S2ONA frameworkII. Student Success Theoretical Perspectives The S2ONA framework (within the S2OSD methodology) is motivated by a collection ofstudent success theoretical perspectives. A cursory review of the most comprehensive andinfluential theoretical perspectives is presented in Table 1 to provide an understanding of those Page 15.1122.2factors associated
-solving,and build collaborative skills emphasized in reform literature. Modeling as a key strategy toengineering education carries risk that exclusively didactic and sequential approaches do not, butit appears that much of this risk can be mitigated.IntroductionThe word curriculum has two related lineages from the original Latin term currere. One refers tothe rut in the ground that wheelbarrows would follow in ancient agrarian cultures. The rutguides, but is inflexible and uni‐directional. Another involves a more literal meaning of currere,to run. This implies a sense of dynamism and motion [1]. Curriculum development traditionallyhas largely involved following a pedagogical, instructional and representational scheme as it canbe used to render a
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understand the differences in grading an artifact and rating itaccording to the rubric.1. OverviewSection 2 of this paper gives a brief background on critical thinking in general, a short review ofcritical thinking primarily with respect to engineering education, and explains why the Paul-Elder framework was selected by the University of Louisville as a specific model to guide the Page 15.1022.2implementation and emphasis of critical thinking throughout the university and engineeringcurriculum. Section 3 discusses the relationship between critical thinking and the ABEToutcomes, emphasizing why critical thinking and its assessment, both as an
of terms and definitions, raising an important methodological question. Shouldwe exclude discussions of educational practices and activities that did not meet our definition?How we answered the question of what to count as “interdisciplinary” would have a substantiveimpact on our analysis. If we prioritized the extant theoretical definitions in the literature (whichguided the study) over the definitions-in-use of our study participants, we would eliminate fromconsideration of interdisciplinary teaching activities that 1) were not clearly focused on theintegration of disciplinary knowledge, and 2) designed solely for engineers.This question of what to “count” as interdisciplinary is philosophical, as well as methodological.Qualitative
implemented.CNC Machine Replacement. This is a two part MEA. Specifically, the chief engineer isinterested in replacing an aging but quite functional CNC machine with a newer model. He viewsthis as a significant opportunity, especially since the purchase would not come out of hisoperating budget. Consequently, the chief engineer requests a group of consultants (i.e., thestudent team) to demonstrate that the new machine will outperform the current one as measuredby unit production time, cost, and quality; thus building a strong case for purchase (Part 1). In Page 15.499.5Part 2, the team is asked to re-do their analyses to show that the replacement is
competenciesnecessary for the next generation of engineers, suggests that future engineers will need to“possess a working framework upon which high ethical standards and a strong sense ofprofessionalism can be developed,”1 and the Accreditation Board of Engineering andTechnology (ABET) has stressed the importance of colleges and universities providing studentswith effective ethics engineering education2.Despite these calls, ethics education efforts have differing levels of success. In another report,NAE expressed concern that students are not being well-educated to understand the “social andethical implications” of their technical skills3, and empirical evidence suggests that some of thepractices used in engineering ethics education, including case studies and
student and faculty perceptions of productive conflict. Themain conflicts that were reported in our study included conflicts of commitment, differentideas about the project direction as well as different working styles.Results from this research will enable us to rethink common models of team conflict anddevelop direct and indirect intervention strategies that can help students to better integrateemotion and intellect in engineering design and innovation.IntroductionAlthough design projects and course structures may vary, there has been a consistentattempt to integrate team experiences into the engineering design curriculum 1-5. Whilethere has been significant work that describes instructional approaches for integrating andassessing teamwork
fromgroups traditionally underrepresented in science and technology fields. Seventy percentof the participants qualified for Title I remediation and the school ranked in the top 12%of the bottom tier in the district-wide standardized test. The current 7th and 8th gradeclasses have had a NSF GK-12 fellow in the science class for 13 months. The 5th and 6thgrade classes have only had 3 months of dedicated science class with the GK-12 fellowand this is their first long term project in science. To date the 6th, 7th and 8th grade classes Page 15.1325.3have completed their graphic novel. The completion percentages per class are tabulatedin table 1. As
responsible for its lack of effectiveness in technical areas, such as engineering.IntroductionThe importance of creativity was aptly described by Dr. Joseph Bordogna, Deputy Director andChief Operating Officer of the National Science Foundation as “what societal progress… is allabout,” in a 2002 speech at the Rochester Institute of Technology.1 Numerous others haveextolled the importance of creativity, including the Editor in Chief of “Power ElectronicsTechnology” who points out that Engineering Innovation requires creativity.2 Given recentscience and technology challenges for new enabling technologies in the fields of energy, healthand the environment, it is generally agreed that creativity is of critical importance to produce thisrequired technical
traditionalmale traits and is male dominated, women often attempt to assimilate by disqualifying theirfemininity and by matching the male styles of behavior12.Survey Version 1In the first survey, we asked respondents to rate the relative importance of various attributes(including hands-on ability) for new engineering hires. Our list of nine attributes looks similar tothose compiled by various engineering organizations, including the NAE. The surveys wereadministered to exhibitors at an engineering conference in October 2008 and to recruiters at an Page 15.149.3on-campus career fair in February 2009. Respondents rated the nine traits on a scale of 1
the Fusion Model toCATS. Each phase had a specific objective that was tied to a primary research question. Thispaper focuses on phase 1 – the generation of a Q-matrix that relates a set of cognitive attributesto specific CATS questions. The process used in this phase of the study consisted of analyzingthe items in CATS and determining the cognitive attributes required for students to choose thecorrect answer. These attributes were identified based on Minstrell’s framework – facets ofunderstanding. Results from this study led to the development of a Q-matrix in which 13attributes were identified among the 27 items. Six of those attributes were identified andexpected to be more problematic. Identification of these attributes provide an
. Page 15.1085.2© American Society for Engineering Education, 2010 Model-Eliciting Activities: A Construct For Better Understanding Student Knowledge and SkillsIntroductionThe ABET criteria for engineering programs include that students should have “an ability toapply mathematics, science and engineering”, “an ability to design a system, component, orprocess to meet desired needs”, “an ability to identify, formulate and solve engineeringproblems”, and “an ability to communicate effectively”, and “a knowledge of contemporaryissues”1. One manner of integrating teamwork and engineering contexts in undergraduateengineering is through the educational construct of Model-Eliciting Activities (MEAs). MEAsare a class of
; defining specific learning objectives for the course;and assigning a rating of student performance from 1 to 4 for each of the program outcomes andlearning objectives. A rubric has been developed to assist with the assignment of scores for theprogram outcomes. Other aspects of the Department’s assessment plan include senior exitinterviews, review of course assessments by members of our Industrial Advisory Board (IAB),and senior design presentation reviews by IAB members. One of the weaknesses of theassessment process has been a lack of consistency among faculty members in terms of therubrics used for evaluation of student work. The development of the rubrics discussed in thispaper is an effort to create consistent instruments which can be used for
among the various toolswithin the machine learning community. During the past decades it has been widely usedin technical applications involving prediction and classification, especially in areas ofengineering, business and medicine22,23. The neural network model is especially attractivefor modeling complex systems because of its favorable properties: universal functionapproximation capability, accommodation of multiple non-linear variables with unknowninteractions, and good generalization ability24. More modeling details on applying NN topredict student retention in engineering can be found in Imbrie et al.4.C. Retention ModelsFive different forms of retention models (A, B, C, D and E as shown in Table 1) wereused in this study to evaluate the
use a portion of the survey and interview Page 15.227.4data—those which questioned individuals who describe themselves as not currently holdingpositions as practicing engineers or engineering managers. We originally surveyed 2500 alumni of a large, public university’s college ofengineering. We received 93 responses from individuals who selected their current professionalpositions as being, “Engineering background, but not in an engineering field.” We asked thefollowing open-ended questions of these individuals: 1) Even though you are working in a different field, do you still consider yourself anengineer? Why or why not
incorporating her work on metaphors into better understanding current models of women’s underrepresentation in the context of Purdue, and creating new models via institutional ethnography. Her past research has focused on using the metaphor of a boundary as a tool to better understand how faculty determine what counts as engineering, and to identify how engineering might be understood as a gendered discipline. Address: School of Engineering Education, 701 W. Stadium Ave., West Lafayette, IN 47907, 1-765-496-1209 (v), apawley@purdue.edu. Page 15.882.1© American Society for Engineering Education
. Page 15.1086.3MEAs use open-ended case studies to simulate authentic, real-world problems that are addressedby student teams. First developed as a mechanism for observing the development of studentproblem-solving competencies and the growth of mathematical cognition, it became increasinglyclear that well-designed MEAs provide both instructors and researchers with tools to engagelearners in productive mathematical thinking and model construction. Specifically, a ModelEliciting Activity (MEA) presents student teams with a thought-revealing, model-eliciting [1],open-ended, real-world, client-driven problem. Originally developed by mathematics educators,MEAs were first introduced to engineering students, primarily at the freshman level, at
students may have. This framework is based on the works ofReiner, Slotta, Chi and Resnick 1 and Chi 2. The second framework from the works of Steif 3describes the common errors that students make in their solutions of Statics problems and theStatics concepts that they represent. Findings of this study show that students who got the answerincorrect made four common errors. In conjunction, when explaining the reasoning behind theseerrors, students talked about the force(s) as represented in the problem and solution as asubstance or a material object. Introduction The scientific principle taught in Statics is the principle of equilibrium. The primaryscience prerequisite to understanding the principle of
difficulty level of an engineering problem, until they realize the weakperformance that students exhibit in solving such a problem on an exam. Therefore, the lack ofproblem-solving skills among engineering students has to be further addressed throughinvestigating and researching the underlying reasons for this deficiency.Over the past two decades, extensive research on conceptual knowledge has focused on assessingand enhancing the student’s understanding of the engineering concepts1-4. Research onconceptual knowledge is central to all research addressing engineering instruction and learningmechanisms. Concept inventories (CIs) 1 were developed to assess the student understanding of aspecific engineering course or domain. These inventories have
data analyst and co-op coordinator for the college. Tony is on track to defend his doctoral dissertation in Spring 2014.Prof. Nathan W. Klingbeil, Wright State University Nathan Klingbeil is a Professor of Mechanical Engineering and Dean of the College of Engineering and Computer Science at Wright State University. He is the lead PI for Wright State’s National Model for Engineering Mathematics Education, which has been supported by both NSF STEP Type 1 and CCLI Phase 3 awards. He has received numerous awards for his work in engineering education, and was named the 2005 Ohio Professor of the Year by the Carnegie Foundation for the Advancement of Teaching and Council for Advancement and Support of Education (CASE).Dr
, like mother like daughter],” there areestablished connections between family background and students' educational aims andoutcomes.3,4 Families are critical to providing support for student attainment through emotionalas well as financial dimensions, from purchasing textbooks to paying for college.3,5 Parents shapechildren's attitudes, motivations, values, and aspirations through a socialized family culture andare a locus of control in the education of their children.6,7 Social scientists have noted thisinfluence and the patterns by which students “inherit” the occupational status of their parents.This finding, especially true for sons, and is referred to as occupational inheritance whichoperates by two primary mechanisms: 1) socialization of