program, 40% of the population is comprised of women, a stark contrast to thesmall percentage of women represented in more traditional engineering programs. We felt thatinterviewing a proportionally larger number of women in a context different than traditionalengineering programs might provide insight into their construction, understanding, and valuingof knowledge(s). We acknowledge that this might risk having the male student having tokenrepresentation, and a follow-up study and analysis plans to address this gender imbalance.Data Collection: Participants were recruited from the AME capstone course and were chosenbecause the course is only taken by students approaching graduation; we felt that these studentshad ample experience with the program
andhence they were familiar with each other, and have a history of prior collaboration for workingon different problems.Data Sources• Discourse moves. Student teams completed a performance task towards the end of the semester. The task included an information and data package and asked student teams to decide on the best system to reduce the energy consumption and cost of a town library (adding solar panels, installing a green roof, or making no changes to existing design) and make a recommendation to the client. The task also promoted students to document their problem scoping, their plan for managing time and team, explain the formulae for total system cost, construct a graphical representation for 10-year cost for current
educationprofessionals to improve delivery and assessment is ongoing, and processes to promotetransferability of research findings are under development.References: 1. American Society for Mechanical Engineering web site, accessed May 6, 2014: “Washington Policy Report May 2013.” 2. FEDERAL SCIENCE, TECHNOLOGY, ENGINEERING, AND MATHEMATICS (STEM) EDUCATION 5-YEAR STR ATEGIC PLAN, A Report from the Committee on STEM Education National Science and Technology Council, May 2013 3. National Academy of Engineering (2014), Making a World of Difference, National Academies Press. 4. National Academy of Engineering, Grand Challenges for Engineering, www.engineeringchallenges.org, updated 9/2013. 5. Johnson, Steven (2012). Future Perfect
should be subjected to further structural analysisto provide insight on each of these other forms of validity.Using data collected from design thinking students, future analysis is planned to compare thegroup design decision results to constructs known to negatively impact decision making, such aswithin group conflict, to illuminate discriminant validity. Outcomes of effective decisionmaking, such as high quality decisions and satisfaction with the decision, will also be used toshow criterion validity and see if the instrument is useful for predicting future attitudes.Positive student perceptions of effective decision making are necessary antecedents for actuallyusing a good decision making process. However, another concern for validity is the
sequential “Levelsof Use” describing how the users’ efficacy and efficiency with the innovation increase as theyadopt it. Past work in CBAM has shown that instructors’ Levels of Use rise (and therefore thepositive impacts of the innovation increase) as they develop and address concerns6. In CBAM aconcern is “any thought or feeling that affects evaluation or planning of curricula materials6.”Similarly to Levels of Use, concerns typically progress through the corresponding Stages ofConcern as instructors’ use of the innovation develops. In short, research based in the CBAMframework has shown that strategically targeting interventions to address new adopters’ concernsis effective in increasing their Level of Use and Stage of Concern, and thereby
better understand what students learn in ENGR 1620. to sense a person’s posture, store that information, and display it. Make a flowchart of the design process you would use for such a system. What steps would you plan to go through? DO spend the full 10 minutes on your response Your job is to create a design process for a specific project. Print Your Name Here Print Your Instructor’s Name Here Page
engineer who retired from IBM after serving for 30 years. He is a development engineering and manufacturing content expert. He develops and teaches all related engineering courses. His responsibility as a director of Center on Access Technology Innovation Laboratory include the plan- ning, implementation and dissemination of research projects that are related to the need of accessibility. He received his BS from RIT and his MS from Lehigh University. His last assignment with IBM was an Advanced Process Control project manager. He managed team members in delivering the next generation Advanced Process Control solution which replaced the legacy APC system in the 300 mm semiconductor fabricator. Behm has fifteen patents
) plans by setting goals for playing and timing; (2)strategizes by deciding which strategy to use for a task or when to change a strategy; (3)regulates time use, effort, pace, or performance; and (4) regulates motivation, emotion orenvironment (i.e., volition control). The resulting sub-categories for the earthquake engineeringcontent knowledge category were: (1) interconnectivity, (2) importance of water, (3) redundancy,(4) resilience, (5) human element, (6) safety, and (7) real-life applications.When a player showed evidence on the video record for an item on the GBL checklist, we usedMicrosoft Word to code the corresponding segment of the video transcription according tochecklist categories. A Design phase focus group member and the game
dimensions ofengineering-student success—the non-cognitive and affective factors that potentially influencetheir performance. This understanding could begin to answer the call for ways, beyond GPA andSAT/ACT test scores, to predict performance and suggest interventions to promote success.During the 2017-2018 school year, we are conducting the full SUCCESS survey. We surveyedstudents from the partnering institutions, two of which were included in this pilot data. At theseschools, we plan to link survey response data with registrar data as well as Dean of Studentsrecords to have a more complete picture of our student populations for future modeling work.Additionally, we plan to launch an international survey across many universities in the U.S. aswell
thepopulation for inclusion in the survey. Approximately 260 programs were selected into the firstsample. Due to low response from programs in the first sample, this procedure was repeated toselect two additional sets of programs. The sample plan ensures the sample is representative ofthe population in terms of location, size, and program. We expect to collect at least 2500 studentresponses by early 2018.Contact information for each program on the sample program list was gathered for the programchair, graduate coordinator, and other pertinent staff from program and/or university websites.Each program was emailed an initial invitation to participate. The invitation included generalinformation about the research project and a request for the recipient to
, electrical, and mechanical engineering [7]. Srivastva [8]identified ‘map scale’, ‘datums’, and ‘data models’ as threshold concepts within the spatialsciences (i.e., geographic information systems, surveying, and remote sensing), where the subjectarea is similar to geomatics engineering.The rest of the paper proposes methods to be used in exposing threshold concepts in a fewgeomatics engineering courses. Some preliminary results are then shown. As this is a work-in-progress, recommendations are suggested for future development of the project at the end of thepaper.Proposed methodsIn terms of methodology for identifying threshold concepts in geomatics engineering, the authorsplanned/are planning a number of activities: In-class observations (where a
Paper ID #21569WIP: How Do Visual Representations Affect How Engineering Students Learnand Solve Problems Within and Across Disciplines?Ms. Nicole Johnson-Glauch, Nicole received her B.S. in Engineering Physics at the Colorado School of Mines (CSM) in May 2013. She is currently working towards a PhD in Materials Science and Engineering at the University of Illinois at Urbana-Champaign (UIUC) under Professor Angus Rockett and Geoffrey Herman. Her research is a mixture between understanding defect behavior in solar cells and student learning in Materials Science. Outside of research she helps plan the Girls Learning About
definitions and appropriateness ofassociated examples. We plan to share insights gained throughout this process and engage incontinued discussions about potential findings and directions from further analysis within thebroader study in presenting this paper. In addition, how authors engaged an intersectionalapproach to data collection and analysis will be included in future work.This research aims to contribute to other scholarship that employs asset-based approaches toexamine persistence by investigating interventions with successful outcomes, including tohighlight avenues through which students can successfully navigate institutional and societalchallenges faced on their journey to be an engineer [6], [8], [14]–[16]. It is also expected thatresults
: the app produced for the course required users to enter their own recipes into a database. A full-featured version would include an aggregator feature which searches the web for open recipes. iOS Mobile Swift An app that enables users to enter their class schedules and post times and locations that they plan to study for courses. The app assists users in finding study groups and locations on campus. Note about scope: the app for the course utilized a pre-built database of
Byrnes is a student at Harvey Mudd College, currently pursuing a BS in Mathematics. Ellie has an interest in doing work in STEM education and expects to graduate from in May of 2021.Dr. Laura Palucki Blake, Harvey Mudd College Laura Palucki Blake is the AVP for Institutional Research and Effectiveness at Harvey Mudd College, where her primary role is to coordinate data collection, interpretation and dissemination to support teach- ing and learning, planning and decision-making across the college.Matthew Spencer, Harvey Mudd College Matthew Spencer is an assistant professor at Harvey Mudd College. His research interests include experi- ential and hands-on learning, and integrating mechanical, chemical and quantum devices
, in the following sectionan example of the assessment of an outcome and the planned program response to it is given, andin the final section conclusions are drawn.For each program outcome, several performance criteria3 were developed using verbs based onBloom’s taxonomy4, 5. Bloom’s taxonomy comprises six levels (knowledge, comprehension,application, analysis, synthesis, and evaluation), in which each level assumes attainment of thelower levels. By basing the performance criteria on verbs tied to Bloom’s taxonomy, it ispossible to gain precision regarding the level of ability expected from students for eachperformance criterion. Lists of active verbs describing actions students are able to do at each ofBloom’s levels have been developed, for
for Model 2 includes subscales of items with significantly larger weightvalues from the previous study. The resulting subscales selected based on the weighting valuesare: planning (from meta-cognition scale), motivation (from career), dysfunctional belief(from career), leadership (from leadership), deep learning (from learning type) and surfacelearning (from learning type). Ultimately, Model 2 contains fifty nine items from six of theaforementioned subscales. The input for a third model, Model 3, includes individual input items with higher weightvalues without considering their scale or subscale classification. Based on the weightinformation obtained from previous all-item combination model, forty nine items wereselected to include in this
(SPOCK) [16], an established measure of student study strategies. MethodsParticipants 171 engineering students from multiple sections of an introductory engineering classat a large southwestern university were recruited to participate in the study; 91 completed theonline survey for a 53% response rate. Over 70% of the participants were male and in theirfirst year at the university. The majority (90%, n =80) are or plan to become engineeringmajors.Procedure Data for the current study were collected via an online survey constructed usingpopular web-based data collection software. Scales were randomized within this software.Because the target sample of the study consisted of undergraduate
. Psychonomic Bulletin & Review, 6 (4), 58-597.Loewenstein, J., Thompson, L., & Gentner, D. (2003). Analogical learning in negotiation teams: Comparing cases promotes learning and transfer. Academy of Management Learning and Education, 2 (2), 119-127.Reusser, K. (1993). Tutoring systems and pedagogical theory: representational tools for understanding, planning, and reflection in problem solving. In: Lajoie, S. P., and Derry, S. J. (eds.), Computers as Cognitive Tools, Lawrence Erlbaum, Hillsdale, NJ, pp. 143–178.Schoenfeld, A.H., & Herrmann, D.J. (1982). Problem perception and knowledge structure in expert and novice mathematical problem solvers. Journal of Experimental Psychology: Learning, memory
: exploration of anddecisions about components and subsystems, and their configuration. SLD starts with thesolution approach decided in the conceptual design, and encompasses elements fromembodiment design,2 system architecture,3,4 preliminary design,5 product planning,6 andmodularity.7 These decisions are extremely important to the overall success of a design project.Interestingly, system level design has not been heavily studied. Some information is availablefrom specific experiences of a designer or educator. These authors often state the importance ofsystem level design, but do not supply a method or tool to fill that gap. For example, one designtext states that this intermediate phase requires “a flexible approach with many iterations andchanges
significanceof the class in real-world engineering (eventually including commentary from professionalengineers), as well as the class’s relevance with respect to other areas within the mechanical Page 12.515.10engineering curriculum.This page can list prerequisites, estimated work load, places to get help, related books and/orinternet sites, and complementary classes the student might find of interest in the event thathe or she enjoyed this class.Interests PageAs the name indicates, the aim of this page is to permit the student to plan their way thoughmechanical engineering in a way that emphasizes their own particular interests. The pageprovides information
-section disparity was a common concern raised by the studentsthroughout the semester, since several faculty members are required to handle the highenrollment. A course coordinator was tasked to organize and oversee the multiple sections, butinconsistencies in pace and depth of the material presentation were inevitable and common.Some instructors chose to introduce some form of active learning problems during lecture wherethe students worked on their own or in informal groups on an example problem, while otherslectured the entire period and worked example problems directly. Increased exposure to exampleproblems was another common student request considered in the course revision. Course RevisionThe plan to improve the course involved arranging
-division coursework. That said, the author envisions a future research plan where the MSE instrument gets usedas an “awareness tool” for considering how we might choose to structure teaching in a manner ofthis sort. Being that the author is focused on the development of cognitive learning instruments(psychometrics) in the field of engineering education, the latter is deemed “detail work” thatsubsequent teaching researchers will hopefully find useful.Bibliography[1] Bandura A. (1981). Self-Efficacy: The Exercise of Control. New York, NY: W.H. Freeman and Co.[2] Bandura A. (1986). The explanatory and predictive scope of self-efficacy theory. Journal of Clinical and Social Psychology, 4: 359-373
information, how do we package that within the school is a tricky issue.A second faculty member from MIT shared this sentiment, arguing that students should beexposed to fields outside the limits of engineering.An ASU professor described a multidisciplinary team functioning like a corporation taking aproblem from production through implementation: And I would love to even see a situation where people from the business school are incorporated. So really get a multidisciplinary team so it’s kind of like a small corporation, where you’re going from a business plan to the implementation, the marketing, all of that stuff. And that’s really something that I think could be very unique and could really teach our engineering students how to
targeted at graduate students from the engineering, medical,law and business school programs. Medical Innovation is based on experiential learningand team-based processes. Student teams consist of about 8-9 members and twoinstructors. Teams go through the phases of ideation, prototyping, legal protection,market sizing and business plan development. In contrast to EDC and IDP where a client Page 15.309.3has pre-defined project, the MI students have to find their own project throughobservation and shadowing. Typical enrollment is about 65 students.The student surveys were sent to 147 EDC students, 65 MI students, and 25 IDP students,totaling 237 students in
data showed increases in yearly retention numbers and highsatisfaction with the course from the students. Following years of success, the course was fullyincluded in the curriculum for engineering majors and continued success was apparent asretention rates among engineering majors continued to increase. As a result of these trends alongitudinal study was planned to provide greater understanding of the effects of the course.A longitudinal analysis of the effects of the EGR 101 intervention demonstrates the increase instudent performance as a result of the course.1 As summarized in figure 1, graduation rates forstudents taking EGR 101 increased significantly across ACT math scores from 18 to 30. Theseresults are for engineering students that
; 3) coaching through deliberate and planned feedback to guide students performance as they move from novice to expert level, and 4) fading of support, by removing the existing scaffolds as students become more competent;This redesign activity focused on both classroom activities and the development of supportingmaterials that students could use outside the classroom. The process started with identifyingclassroom activities that match various stages of the cognitive apprenticeship and, when neededredesign them to better address the goals of each stage. Page 22.891.3For some of these activities, we developed supporting materials
: Multi-year program plan. Retrieved from: http://apps1.eere.energy.gov/buildings/publications/pdfs/ssl/ssl_mypp2011_web.pdf12. Kelley, T., & Littman, J. (2001). The art of innovation: Lessons in creativity from IDEO, America’s leading design firm. New York: Doubleday.13. Smith, S. M., Ward, T. B., & Schumacher, J. S. (1993). Constraining effects of examples in a creative idea generation task. Memory & Cognition, 21(6), 837–845.14. Amabile, T. (1982). Social psychology of creativity: A consensual assessment technique. Journal of Personality and Social Psychology, 43(5), 997–1013.15. Christiaans, H. H. C. M. (2005). Creativity as a design criterion. Creativity Research Journal, 14(1), 41–54
Journal of Educational Research, 1997. 90(5): p. 269-277.15. Creswell, J.W., Educational Research: Planning, Conducting, and Evaluating Quantitative and Qualitative Research. 3rd ed. 2008, Upper Saddle River, New Jersey: Pearson Education, Inc.16. National Center for Education Statistics. CCD - Build a Table. 2010; Available from: http://nces.ed.gov/ccd/bat/.17. Bowen, W., M. Chingos, and M. McPherson, Crossing the finish line: Completing college at America's public universities. 2009: Princeton Univ Pr.18. United States Dept. of Education, Table No. 265: Bachelor's, master's, and doctor's degrees conferred by degree granting institutions, by sex of student and field of study: 2005-06. 2007, National Center for