successful experiencesand reflections in their creative problem solving processes.Implementation Procedures The students were provided with a list of question prompts after they start their creativeproblem solving in their PBSL project. These question prompts correspond to the process modeland strategies, which are categorized into procedural, elaborative, and reflective prompts.Students were required to write down what question prompts were helpful for them to learnrelevant knowledge and may help develop their innovative solutions. To help students focusattention to some important aspects of the problem solving, participants received questionprompts regularly as reminding through e-mails setups in online software platform Blackboardbesides the
the solution (or parts of the solution) to the problem. FeasibilityAnalysis (FEAS): Assessing and passing judgment on a possible or planned solution to theproblem. Evaluation (EVAL): Comparing and contrasting two (or more) solutions to theproblem on a particular dimension (or set of dimensions) such as strength or cost. Decision(DEC): Selecting one idea or solution to the problem (or parts of the problem) from among thoseconsidered. Communication (COM): The participants’ communicating elements of the designin writing, or with oral reports, to parties such as contractors and the community. Other: None ofthe above codes apply. See table 1. Page
presentations employing a more detailed scoring rubricto produce a composite score with input from the module instructor, the collective plenary andother module instructors, and students. Other activities in the discipline modules includedinvited speakers, student/industry panels, and lab tours to introduce the students to the disciplinemajor. A peer assessment was required for each team, and several of the module instructors usedCATME TeamMaker as the assessment tool at the end of the module rotation.Outcomes and AssessmentIn addition to the College’s general freshman survey, students taking the first-year engineeringprojects course are separately given a pre- and post- surveys. Students taking the pilotintroduction to engineering course were given
this context, this paper provides personal observations common across many organizationsbased on the author’s work in SE, project management, organizational development, and teamdevelopment.STATEMENT OF THE PROBLEMDespite the formulation and development of Systems Engineering capability assessment andcompetency models, certifications, education and training courses, et al, system developmentprojects continue to exhibit technical performance issues concerning the engineering of systems.Contributing to this overall problem are several contributory performance effecters: 1. Misperceptions that writing specifications, developing designs, performing integration
nature of the data and the exploratory nature of our research question,analysis followed a descriptive approach that employs elements of phenomenography in order tocapture the breadth and diversity of responses. Case & Light [16] provide an introduction tophenomenography in their recent paper outlining a selection of qualitative methodologies that are“promising but as yet not well represented in engineering education research.” Recent examplesof phenomenography in use in engineering education can be found in Mann et al. [17], who usedit to study student conceptions of sustainable design; Calvo & Ellis [18], who used it to studystudent conceptions of tutor and automated feedback in professional writing; and Zoltowski et al.[19] , who
project that is selected by the team and thecoach (a STEM teacher at the high school), and that has local significance for the students andtheir community. The project continues from one academic year to the next, with moststudents continuing as well. In the course of their HSE experience, the students solve authenticSTEM problems, perform testing and analyses, build prototypes, manufacture parts, staywithin budgets, write business plans, and manage their own project. HSE teams also haveprogram-facilitated access to expertise and mentoring from faculty and students in highereducation and from professionals in industry. Figure 1 contains a model of the team supportoffered by the HSE program. Most HSE teams operate as afterschool activities, but we
Electrical Engineering Laboratory CoursesAbstract This paper presents our experiences and results in developing and delivering newlaboratory experiments for the sophomore level Electric Circuits Lab, and Introduction to DigitalLogic design courses completely online. The paper will clearly outline how we utilized a newpedagogy to re-write our laboratory experiments so that they can be completed by face-to-faceand/or online students using new portable laboratory instrumentation devices, such as the MobileStudioTM board. We also present detailed descriptions on how we used the Adobe ConnectTMsoftware to allow the students to demonstrate their design and laboratory experiment circuits tothe course instructor from a remote location. We have
, writing the programs, and testing the robotsthat students gained a deeper understanding of the concepts.ModelModels were used to illustrate the robotics concepts and design challenges throughout thecurriculum, especially during the building and testing phases. It was important for instructors todemonstrate what the robots were supposed to do because the challenges typically involved therobot interacting with an environment, such as following a line, avoiding obstacles, or picking upan object. It may also involve pushing other robots around. Since these environments are Page 25.404.9dynamic in nature, it makes the challenge more complicated. So
survey consisted of five sections. These included some general background informationabout the respondent, why the respondent joined the Lawrence Tech Formula HybridTMcompetition team, their experiences while being part of the hybrid team, other comments, andinformation related to if the respondent had left the team. Many of these questions are related tointernal use by the author and advisor of the team for the college of engineering at LawrenceTech, so not every question or its responses are included in this paper. There are, however, someresponses worth noting. At the time of this writing only about 17% of the voluntary responseshad been received (n = 8). But enough responses had been received to be of some use and thedata do shed light on
responded to these challenges with enthusiasm, enjoying their collaborations withthose from the other side of the divide, and demonstrating mastery of much of the technical content provided inthe course. In two other respects, outcomes from the course have far exceeded expectations. First, the range ofphysics demonstrated and the quality of images have been worthy of awards and archival publication 2–5. Second,and certainly more importantly, students report that their perception of the world around them has beenbroadened to include fluid physics, in a way that no other course has done. Students write to the instructor yearslater, enthusing about seeing mixing in a liquid soap dispenser, or vortexes in an unusual cloud. This neverhappens with
we had originally planned to prohibit quarter-and three-quarter length joints between deltas, allowing only full side or half joints, to make calculationseasier, but this was too limiting in the creation of successful designs. We also consideredincreasing the internal area requirement from 100 quarter-deltas to 150. However, a larger areawould require more deltas and thus make it difficult for the entire class of twenty teams to play atonce, resource-wise.Writing New InstructionsThe last change we made to the game was writing a new set of instructions (see Appendix) thatincorporated all of the changes that we made. We divided these instructions into three parts: theDesign Task, instructions for the Project Manager, and instructions for the
new ideas than other members of a system”(p. 22). Based on their innovativeness, individuals can be classified into five adopter categories:innovators (2.5%), who are risk-takers willing to try new things and prepared for associateduncertainty; early adopters (13.5%), who are role models assuming leadership in furthering theadoption of the innovation; early majority (34%), who are individuals deliberately adopting aninnovation before the other half of their peers; late majority (34%), who are suspicious ofinnovations and wait until it is perceived as safe to adopt them; and laggards (16%), who are moresuspicious of innovations than the late majority and adopt innovations last.Rogers’s diffusion of innovation model provides us with both a