toanalyze the end solution or product as a design analysis act. TABLE 1: Comparison ofComputer Automation vs. Human Value Judgment (see Appendix) has been provided predictingwhat aspects of design are likely to be automated and what are not.The most recent article advocates the increasing role of contextual fit as part of this new designanalysis component and a change in assessment to reflect that shift.15 The new contributionmade in this paper is not proving that this is occurring or arguing the nuts and bolt of whichCAD programs do what. It puts forward an explanation of what the designer is experiencing, asdescribed by a set of characteristics, when we automate parts, the design experience and integrateother technological functions that affect
attributes, business practices, and human resource management practices.The second stage was to identify unique characteristics relevant to undergraduate studententrepreneurs in universities based on Anik’s comments, reflections, and perspectives. Theobjective of this methodology was to develop a set of suggestions for programs and activities foruniversities to foster desired characteristics and behaviors of undergraduate entrepreneurs.The findings for the singular case of Anik Singal’s experiences were then compared to findingsof critical success factors from the 90 undergraduate students of the Hinman CEOs Program.Using a qualitative approach through an online survey and one-to-one 30 minute interviews: • 91.7% stated their “knowledge base
manufacture this product (f) Worldwide demand or sales for this chemical; and (g) Unit pricing ($/kg, $/gal, etc.) (Note: this should reflect bulk pricing, not pricing of small units from Fisher Scientific, etc.)2. From the textbook index, select a technical topic that begins with the same letter as your lastname or the nearest possible letter (for example Brent -> Bubble point). Find three papers (notweb sites) in the recent literature that deal with this topic. Copy and paste their citationinformation and abstracts. Find these three papers, photocopy or print out their first pages, andattach them to the homework. Page
, it is not unusualfor a student in engineering to repeat a course. However, at UT Martin, the GPA that is reportedon the transcript is based on the most recent grade earned in a course. Thus, the GPAs for thesecond and sixth row students in Table 6 would reflect actual courses taken since these studentsdid not repeat any course. The GPAs for all the other students in Table 6 will be artificiallyhigher than a true GPA reflecting all the attempts made. Since this GPA computation isunalterable due to computer constraints in the program that archives the grades, this presents aunique problem in terms of predicting success in passing the FE exam for the program
Course in the MajorSenior Year • Bring Integration and Closure • Career Services to College Experience • Alumni Development • Provide Opportunities to Programs Reflect on the Meaning of the • Capstone Courses Undergraduate Experience • Internships • Prepare for the Personal and Professional Issues Related to Post-College Life Figure 5. Developmental Needs and Suitable Programs for Students. Page 11.365.18 Cognitive Domain
transfers have left the School of Engineering by the spring of 2005, and the rest was eithergraduated by that time, or still in the School of Engineering. Narrowing further to the studentswho are ready to take calculus I or higher at entry, retention improves considerably. Of thefreshmen 48 percent had left the School of Engineering, of the transfers 50 percent. For transfersthe difference in retention between those who can start in calculus I and those who cannot issmall, because the majority of transfers could start in calculus I or higher to begin with. Thefindings for 'calculus-ready' students reflect the national average 4, and they are in the middle ofthe range of retention rates for engineering students reported earlier 9.Academic
theirunderstanding through reflective writing. In this paper, we will share with you the pilot studyoutcomes regarding student learning, retention, and satisfaction based on the implementation ofthe Collaborative Learner-constructed Engineering-concept Articulation and Representation Page 11.918.2(CLEAR) instructional model. The study compared students from two sections (blended vs.traditional instruction) taking a sophomore level chemical engineering course.Theoretical FrameworkSocial constructivists view learning as being a product developed from individuals interactingwith each other and the environment10-12. One form of this social constructivists
different rules.Enron, for example, touted a 64-page code of ethics, which the company required all employees–including management–to read and then sign an oath attesting to their commitment to highethical standards. Enron took its ethics code very seriously, at least on paper, as noted in a 2000memo penned by CEO Ken Lay: “I ask that you read them [“commonsense rules of conduct”]carefully and completely and that, as you do, you reflect on your past actions to make certain thatyou have complied with the policies. It is absolutely essential that you fully comply with thesepolicies in the future.”1 Similarly, Tyco’s board of directors established as a goal “highstandards of honesty, integrity, and ethics throughout the organization.”2 Yet corporate
courses is alsoECNS 225 Networks 4 upgraded through industry sponsorship and equipment donation. A net simulation and design software program available for student also improves significantly.ECNS 315 Network Greater lab emphasis on WAN network implementations.Theory and TestECNS 325 Wireless The Control Networks course topics are significantly modified toNetworks reflect graduate needs for greater wireless network knowledge. GPS and Cellular theory are also introduced. As industry shifts to primarily TCP/IP and other non-proprietary protocols, the material is omitted. CAN topics moved to digital courses. Course also
reporting thenumber of positions currently staffed at their own institutions, 33% of respondents indicated zeroor one staff member. Their comments also reflected a perceived lack of available positions: It will be desirable to have someone help us with some of the above mentioned type of positions listed in question 3. But we do not have the luxury of hiring anyone for these positions due to the lack of funds. Unfortunately, we don't have the resources to staff any of the positions you list. My answers were, in effect, "what if" answers. As Associate Dean, I do most of the other tasks mentioned in Q3. We are seldom explicitly seeking individuals to fill such positions. We just do not have these types of
student creators can engage other students tobecome interested in these interdisciplinary topics and research in general. Section 2 provides a brief overview of the training that was provided to the student teamand process they undertook interviewing experts to gather information on PLM. Section 3discusses the origin of PLM and presents the main goals and objectives of this process. InSection 4 the application of PLM in the aviation industry is discussed. Section 5 presentslifecycle assessment in relation to environmental monitoring. Finally, Section 6 concludes thepaper with students' reflections on the co-creation project and future research.2.0 Training Methods, Focus Groups and Communicating with Experts The professional
students’ labor market outcomes. Whether macro or microscale, however, these examples reflect educational practice firmly anchored to the experiences ofstudents journeying through the real problem spaces of our time.In this paper, we take the school-to-work pathways view one step further and place ourinvestigation in a specific real world context: the pathways of environmental engineeringundergraduate students within a time of environmental decline and climate crisis. We see thistime as a revealing societal moment in which beliefs, decisions, and leadership about ourenvironment move us towards sustainable solutions or away from them. We considerenvironmental engineering students as designers and agents of these sustainable solutions, aswell as
researchers seek to understand whether and to what extent thedevelopment of engineering “habits of mind and action” in middle school STEM (science,technology, engineering, and math) courses leads to improvements in problem solving abilities,integration of STEM content, and increased interest in engineering. The Next Generation ScienceStandards (NGSS; NGSS Lead States, 2013) call for “raising engineering design to the samelevel as scientific inquiry in science classroom instruction at all levels” (p. 1). Reflecting thisemphasis on engineering as a core idea, recent reforms include proficiency in engineering designas a key component of college and career readiness (Auyang, 2004; Carr, Bennett, & Strobel,2012; Duderstadt, 2008; Kelly, 2014
(3) including both Google Docs and interactive videos in the third. End-of-Course Surveys consistently show that the students enjoyed the weekly hands-on labs. After thethird class offering, an additional survey of student experience with the new technologies wasconducted. The results reflected a positive student experience with the course delivery.EE110 Course Description and ObjectivesIntroduction to Engineering, EE110 provides the beginning engineer with fundamentalknowledge and skills associated with the electrical or computer engineering professions. It willintroduce common electronic components, basic circuit configurations, and laboratoryinstruments. Bench practices and lab reports will be introduced along with computer aidedanalysis
,analyses of award winning products, and a case study of a long-term design project, DesignHeuristics capture the cognitive “rules of thumb” used by designers to intentionally vary their setof candidate designs[23]. These strategies appear to be ones that expert designers employautomatically, without consciously deciding to do so[24]. The heuristics were individuallyextracted across multiple concepts from multiple designers to reflect a useful level of abstractionin describing how to alter design characteristics to create new ones[25]. The resulting set of DesignHeuristics capture 77 different strategies, each of which can be applied independently or in tocreate new designs[26].The set of Design Heuristics is packaged as an instructional tool for
. Instructional Design, on the other hand, is the systematic and reflective process oftranslating principles of learning and instruction into plans for, instructional materials, activities,information resources, and evaluation [1]. Teaching refers to the learning experiences that arefacilitated by a human being. Smith and Ragan [1] identifies three steps in instructional design inthe following way: a. Identifying the Goals through Analysis – This involves consideration of the learning outcomes to be achieved, background of students and the nature of the teaching activity such as lecture, workshop, and lab work. b. Development of an Instructional Strategy – This is the planning of how the instruction will take place
. Produces practical solutions based on meeting requirements of analyzed problem components. g1. Reports describe goals, methods and solutions at the level appropriate for the reader. Relevant technical literature is identified and used appropriately. g2. Presentations clearly describe goals, methods and solutions. g3. Responds to questions, comments and criticism in a clear and appropriate manner in oral interactions. h1a. Exhibits curiosity & initiative. h1b. Exhibits reflection. h2. Participates in discipline-relevant professional societies and organizations. i1. Demonstrates an understanding of the Code of Professional Engineers. i2. Recognizes importance of respect for diversity. j1. Identifies both potential benefits and adverse
Psychology from Stanford University. Her current research interests include: 1) engineering and en- trepreneurship education; 2) the pedagogy of ePortfolios and reflective practice in higher education; and 3) redesigning the traditional academic transcript.Dr. Sheri Sheppard, Stanford University Sheri D. Sheppard, Ph.D., P.E., is professor of Mechanical Engineering at Stanford University. Besides teaching both undergraduate and graduate design and education related classes at Stanford University, she conducts research on engineering education and work-practices, and applied finite element analysis. From 1999-2008 she served as a Senior Scholar at the Carnegie Foundation for the Advancement of Teaching, leading the
Science and Biomedical Engineering Courses. 2016. 2. Betebenner D. Norm-‐and criterion-‐referenced student growth. Educ Meas Issues Pract. 2009;28(4):42–51. 3. Tam M. University impact on student growth: a quality measure? J High Educ Policy Manag. 2002;24(2):211–218. 4. Carberry A, Krause S, Ankeny C, Waters C. “Unmuddying” course content using muddiest point reflections. IEEE; 2013. p. 937–942. 5. Cohen GS, Blumberg P, Ryan NC, Sullivan PL. Do final grades reflect written qualitative evaluations of student performance? Teach Learn Med Int J. 1993;5(1):10–15. 6. Allen JD. Grades as
bedetermined through qualitative analysis of course names and descriptions.This study has currently finished phase 1 (online data collection). Phase 2 will be completedduring the first semester of 2017, and phase 3 during the summer of 2017. The results in thispaper reflect findings for phase 1 and are aimed at helping CM educators evaluate the presentlevel of collaboration between AEC undergraduate programs in the United States.Partial ResultsSample DemographicsThere are 129 ASC affiliated schools in regions 1 through 7 in the association’s website.Region eight was excluded from the analysis as it encompasses only schools from outside ofthe United States. Other exclusions were made and are presented below. Finally, this researchwas conducted using
. In DFM, a more functionally constrained project could accomplish the same thing.• Building the Connection between Function and GD&T This follows from the previous point and reflects the challenge noted earlier that students experience the greatest difficulty when they are required to come up with the correct controls, and more so specific values of tolerance that will result in a desired function. In industry, this experiential knowledge has been acquired over time and is captured in standards and procedures for dimensioning and tolerancing the specific products that are designed and manufactured. Though it is difficult to reproduce this in an academic setting, tooling design again represents a good application
. Trevor Scott Harding, California Polytechnic State University, San Luis Obispo Dr. Trevor S. Harding is Professor of Materials Engineering at California Polytechnic State University where he teaches courses in materials design, sustainable materials, and polymeric materials. Dr. Harding is PI on several engineering education research projects including understanding the psychology of engi- neering ethical decision making and promoting the use of reflection in engineering education. He serves as Associate Editor of the journals Advances in Engineering Education and International Journal of Ser- vice Learning in Engineering. Dr. Harding has served in numerous leadership roles in ASEE including division chair of the
survey were also modified or removed.Following revisions, the survey contained 15 items to measure the four hypothesized dimensionsof the STV construct. The dimensions and their items are shown in Table 1. Notably,respondents were instructed prior to seeing these items that “first position” could includeemployment and/or graduate/professional school to accommodate the broad range of career pathsthat engineering students take after graduation. This language was reflected in many of the itemstems used to measure the various STV dimensions as well. Table 1 – Items Developed to Measure STV Related to Finding a First Position Construct: Item Dimension No. Item Stem
efficacy and success of the program are addressed. Each item represents a uniquedimension, or learning objective, where positive gains indicate improvements prior to and afterparticipation in the program. Results indicated positive, statistical change in four out of sixintended dimensions: students’ confidence, self-awareness, and ability to recognize theirstrengths and weaknesses were all significant, as was the students’ perception of the success ofthe program. Analysis of the remaining two dimensions, students’ preparedness to work in teamsand student’s ability to perceive the value in cooperation for group success, also indicatedimprovement in the intended direction. These results reflect an all-around improvement instudents’ perceptions of
results of Aluminum andSteel specimens for different cases of loadingꞌ, promoted critical thinking and communication.Therefore the essential motivation was to re-confirm to the well-established perception thatꞌhands-on experiences will always outperform traditional or passive learning methodsꞌ. Howeverhands-on activities should be done in a way to provide sufficient opportunities for reflection,metacognition and a deeper understanding of the principle or physical phenomena underlying theexperimental activity. Poorly designed experiments would negate the benefits of hands-onlearning. In order to explore the effectiveness of a modeling tool as a substitution for hands-onactivity the project for spring 2016 was conceived. The ambit of tasks was much
63.6 know very little about them Yes, I have searched for them 4 18.2 and perused a few Yes, I have used open educational resources in one 2 9.1 or more classes No response 1 4.5In response to a question about having ever considered using an OER in a course, 48% ofrespondents indicated that they have never used or considered OERs. Other respondentsindicated that they had used OERs, had examined them in the current semester, or had looked atthem 5-10 years previously.At the end of the survey, four open-ended questions asked faculty to reflect on
consideration (required) as well as commentary onwhether the obtained results resemble the expected results (to establish whether the studentsunderstand what they are looking for). Further commentary would explain what factorsinfluenced the results to be non-ideal (which would indicate understanding of both the systemunder study and the data collection system at issue in the lab). Grading reflects mastery of theexperimental system—the more the student explains, the better the mark.As the students master the details of project set-up, we shift to more formal reporting, with shortreports that ask for project motivation, goals and methods as well as results, and we support thisby providing examples and by providing lectures on the structure of and
of active learning practices in the classroom. As part of the analysis, welooked at beliefs about student-centered learning strategies and at classroom practices at twoseparate times (one at the beginning of the semester, or start of the professional developmentseries, and one at the end of the semester when the professional development series was ending).The study was framed by the following research question: To what extent are faculty beliefs about student-centered strategies reflected in instruction practices in the undergraduate engineering classroom?Review of Related ResearchStudent-Centered Teaching in Engineering EducationStudent-centered teaching strategies address key course concepts and skills in an engaging
conductstructured observations of in-class engagement.Our preliminary analysis suggests that building on the interests, experiences, and knowledge thatpotential CS majors bring with them to class, and connecting curricula to emerging issues cansupport the learning experiences of students traditionally underrepresented in CS. For example,in the extension of the week 2 module in which students programed agents to draw their names,students were asked to create a design to reflect something about themselves. Students drewspirals, sine waves and other geometric shapes; some students wrote their names in cursive (onewith step-by-step agent instructions, another creating curves from mathematical functions); manydrew intricate emblems or logos illustrating aspects
, educational psychology, and social work in the context of fundamental educational research. Dr. Walther’s research program spans interpretive research methodologies in engineering edu- cation, the professional formation of engineers, the role of empathy and reflection in engineering learning, and student development in interdisciplinary and interprofessional spaces. c American Society for Engineering Education, 2017 Deepening student understandings of engineering dynamics principles through industry-inspired, problem-based learning activitiesAbstractThis paper describes the development, implementation, and evaluation of project-based learning(PBL