inappropriately, but examining every word in context is too time- consuming for a large-scale study. For the results reported here, we compiled a list of 37 words that are often vague, absolute, unnecessary or inaccurate, based on previous analysis of student papers and faculty input. Occurrences of the words were examined in context. For example, you is accurate when referring to the reader (e.g. closing a technical memorandum to a client with It was a pleasure serving you) but inaccurate when it does not refer to the reader (e.g. Using the graph, you can calculate...). In the future, we plan to expand the list. (Other language features with other analyses are used in the project but are not included in this paper.) 3. Holistic
15 questions were directly related to conceptual functionknowledge, with the rest of the questions related to concepts such as derivatives, integrals,power series, and programming preferences. Results regarding the questions that are notcovered in this paper are planned to be published elsewhere.Research Problem The question evaluated in this study is designed to observe participants’ ability todetermine the intervals of increase-decrease, convexity, critical points, horizontalasymptotes and vertical asymptotes of a quotient function to be able to graph it by using allthese properties. This problem aims to observe participants’ ability to calculate analyticalcalculus problems and their ability to reflect the obtained information on a
engineers are, and how they can work together to make things happen. Our experience has shown that creating opportunities for reflection are useful for both engineering and non- engineers. Future plan for the project As engineering educators, we know that the value of quantitative data is of great importance to most engineering faculty. Consequently, The most important challenge for understanding the data remains to be the answer to the questions: “How to create a quantitative measure of what we are seeing?” or “Is it possible to create meaningful quantitative data for this type of work?” Our goal will be to do a systematic analysis that would help us understand ways to have meaningful quantitative assessment of
knowledgeregarding its use.4 However, it is a general test and does not assess discipline-specific issues.16 There have been several attempts to develop engineering-specific tests to assess moraljudgment. At conferences in 2003 and 2004, initial results of a study to develop a test werereported.11,15 The reports seemed promising, but Barry and Ohland reported that the principalinvestigators were no longer working on the project and had no immediate plans to resume thestudy (p. 384).4 Davis and Feinerman developed a method of comparing ratios of pre- and post-tests Page 26.240.5developed by the instructor. This method allows instructors to customize
nutritional needs15. We expandedupon the previously published project description by separating into two phases. Phase I consistsof the following: (1) reading primary research on the intersection of obesity, energy, and foodcost16; (2) researching nutrition in various foods via exploring the grocery store to gathernutritional content; (3) integrating their understanding of energy balances by planning a menu fora day with constraints of varying budgets, $5, $10, and unlimited budget, and (4) meeting anutritional caloric intake for an individual in that budget constraint. Given the course schedule,the BIOE students start the project 1 week earlier than the CHBE students. As a result, we expectthe BIOE team to lead the first phase and act as data
Page 26.257.19 Figure 16. Rubric used for direct assessment of student designs in semesters with and without PBL techniques. Page 26.257.20References 1. Carpenter, D., Hayes, K., Ward, C., Gerhart, A. (2011) “Assessment and Evaluation of a Comprehensive Course Modification Plan.” The Journal of Engineering Entrepreneurship. Vol. 2, No. 2. 2. Gerhart, A. and Carpenter, D. (2013) “Campus-wide Course Modification Program to Implement Active & Collaborative Learning and Problem-based Learning to
, and ultimately,help determine whether the core information literacy outcomes have been achieved, in bothtraditional and credentialed instructional settings.Description of CoursesCompetency Based ProgramOverview of ProgramThe Purdue Polytechnic Institute (PPI) houses a recently formulated competency based degreeprogram offered in the College of Technology. One guiding principle of the program is thedevelopment of the whole person as a complete learner, not just teaching skills in a particulartechnical field. This includes intentional integration of traditional technical and humanitiessubjects. The PPI degree plan has information literacy embedded in the outcomes andcompetencies the students are expected to achieve on multiple levels throughout
, increasing the datasets tomore than one semester may increase the accuracy of the models.References[1] J. Gardner and A. Koch, “The First-Year Experience Thirty Years Later: It is Time for an Evidence-Based, Intentional Plan,” Purdue SoLar Flare Practitioners' Conference, West Lafayette, IN, 2012.[2] ACT, National Collegiate Retention and Persistence to Degree Rates, 2012. Available at http://www.act.org/research/policymakers/pdf/retain_2012.pdf[3] K. Green, “Campus computing, 2009,” The 19th national survey of computing and information technology in US higher education, 2009.[4] S. Huang and N. Fang, “Predicting student academic performance in an engineering dynamics course: A comparison of four types of
effort goingforward. By generating many versions of questions, we are trying to reach the point where, evenif students have all of our problems and their solutions, it would be less effort for them to learnthe course material than to memorize all of the solutions. Once we’ve reached that point, then wecan re-use exam questions from semester to semester. More precisely, we plan to take our currentpool of questions, periodically add new questions to the pool, and each semester use a subset ofthe questions.Building up a pool of short answer questions for PrairieLearn, was relatively straight-forward forus for Fall 2014. We had already been using a web-based homework system for a number ofsemesters that included problem generators that randomized
. During this process, faculty are challenged to beginforming their CoPs before funding for faculty-led efforts is granted. Faculty must identify theshortcomings of the course and propose potential innovations that they will pursue. Theleadership and evaluation teams help the CoPs identify potential RBIS that may addressidentified shortcomings, but let faculty decide which RBIS (if any) to pursue. The evaluationteam concurrently helps faculty develop evaluation instruments to measure progress towardstated goals.At a minimum, CoPs are expected to meet on a regular basis (i.e., weekly) and commit to anevaluation plan. The goal of these commitments is for the faculty to create jointly-owned coursesthat will be delivered by various members of the CoP
group of data scientists who hopeto make Utah a leading area of data mining, predictive analytics and machine learning. This area is aprime location for the research proposed in this paper because it hosts many call centers fromcompanies as diverse as Visa, NuSkin, Adobe, EMC, Bluehost, Domo and several contract call centers.Between the University of Utah, Brigham Young University and Utah Valley University, there is acritical mass of all levels of university students studying machine learning and data mining. Not only isthere a data mining focus at Utah Valley University, the University of Utah also has a program andinfrastructure specializing in Data Management.18The plan being proposed here is to approach these companies to determine who is
steps crucial to the success of this program. First, we installed all the requiredsoftware. Since the S2 can be programmed using its own graphical user interface, weinstalled this software onto the computers we planned to use. The link to this softwarewas obtained from the vendor’s website. We chose the GUI because research [10] hasshown that it is easier to use than its text-based counterpart.Our most important step was to conceive design ideas for our art catalogue. An initialbrainstorming session was used to formulate possible projects and determine theworkflow for the activities. After each activity was conceived, we figured out the stepsrequired to accomplish its goal. We also studied the tutorials in order to understand howto manipulate
above.b) work as a team, especially to develop standard procedures including safety rules, share resources, and exchange technical ideas.c) obtain new experience and knowledge, which will not only be used for millimeter-class mechanisms but also for other engineering applications.d) experience interdisciplinary work.Two case studies describing developments of electrostatic force driven grippers and suctiondevices for micro-assembly applications are presented in the next two sections. A summary ofother ongoing projects and future plans of our group will be given in the conclusion section.Case Study 1: Electrostatic force–driven grippersGripper designFor one of the projects, a group of a few students decided to develop a miniature 1-DOF
affective components of student engagement (Dixson, 2015) Online Course Management Systems One of the negative effects which was detected in online learning environments is thatoften new generation of learners can behave as “butterflies fluttering across the information on thescreen, touching or not touching pieces of information (i.e., hyperlinks), quickly fluttering to anext piece of information, unconscious to its value and without a plan” (Kirschner & vanMerriënboer, 2013). Some researchers do not agree that today's learners are digital natives andefficient multitaskers, who learn best if the specific learning styles are catered or they learn as self-educators (Kirschner & van Merriënboer, 2013). Some even suggested
;0.01Discussion and ConclusionThe implementation of the model was very successful overall. One important lesson however isthat we need to increase the flexibility in the syllabus so that students can repeat laboratoryexperiments when needed. This, of course, is not unlike what happens in authentic researchlaboratories. We also did not fully take into account the increase in laboratory prep time andstaffing needed in the original budget model. We plan to increase the number of researchstreams in Biology and Chemistry in future years.One important consideration in interpreting the results is that students apply, i.e., self-select, intothe research sections. A bias is formed when students self-select a group. This bias can be seenwhen the pre factors were
problem at hand. The smoothness and benefits of thisintegration process may be attributed in part to the institution’s small program (roughly 10-20students in each academic year cohort) and unique, sustained team building opportunities.Further research is needed to see if different cohorts will behave differently at the authors’institution and in larger programs. Regardless, students also suggested integrating teams withbroader experiences and perspectives (e.g. electrical engineering) for a more comprehensivescope of the final design. Students agreed that their greatest learning point was to plan better (e.g. spend more timeunderstanding the problem and how to approach the problem) by learning from others first.They identified that a good
design thinking.5.1. Finding 1 - Eight different types of information requested, Playground design most popular,no other noticeable trend.The high variety of information gathered and low frequency that each type of information wasgathered suggests that among the five participants in this study, there is no common thinkingprocess by which they requested and used the information. Additionally, the diversity in thetypes of information gathered and the utilization of the information might suggest that thesestudents do not have an established information gathering process, meaning their informationrequests and utilization is not planned; the participants did not appear to have a systemic way ofgathering information. Information request seemed to
selected engineering at 5-10 times the rate oftypical students8. Though this report concluded women were not well-represented, they expectedthe implementation of Biomedical Engineering PLTW courses would attract females at highernumbers, thereby increasing the participation of women in engineering university programs.This study also found that 80% of PLTW students planned to go to college, compared to 63% oftheir peers. Further, 90% indicated they knew what they wanted to major in because of theirPLTW experience and 80% indicated their PLTW experience would significantly assist theirsuccess in their postsecondary education8. This comprehensive report suggests further evidencePLTW increases the quantity, quality and diversity of engineering
’ Perceptions of a First-Year Engineering Design Course and their Engineering Identification, Motivational Beliefs, Course Effort, and Academic Outcomes. International Journal of Engineering Education, 2014. 30(6(A)): p. 1340-1356.14. Paretti, M.C., et al., Work in Progress: A Mixed-Methods Study of the Effects of First-Year Project Pedagogies on the Motivation, Retention, and Career Plans of Women in Engineering, in 40th ASEE/IEEE Frontiers in Education Conference. 2010: Washington, DC.15. Mccord, R., Thinking About Thinking in Study Groups: Studying Engineering Students' Use of Metacognition in Naturalistic Setting, PhD Dissertation in Dept. of Engineering Education. 2014, Virginia Tech: Blacksburg, VA.16. Brown, P
institutions, they were designed and implemented to provide some supplementary skills and experiences that will address some of the voids in their education. Additionally, the international network of peers has fostered the ability for continued peer networking to occur between LSWE and the undergraduates from the UMSWE. It is planned that the Leadership Camp will be carried out by the University of Michigan graduate students for multiple years until members of LSWE begin to graduate and are able to facilitate the camp’s programing thereafter. Additionally, the partnership will look to expand its capacity as it supports LSWE members past their undergraduate education, as they look for engineering employment and to apply to graduate school
Week Due 2st Semester 9 Updated Drawing Package from First Semester 2 10 New Gantt Chart w/WBS and Milestones 2 11 Functional Prototype 8 12 Mid-Term Peer Evaluation 8 13 Prototype Test Plan 9 14 Prototype Test Results oral report 12 15 Prototype Test Results & Evaluation Report 14 16
human interfacing) in real-life problem solving. The experience enhances students’ hand-oncapability and prepares them for entering real world career in robotics and system automation[10]. Future plans include combining multiple robots to form a large robotic network systemwhich can collaborate in the large area surveillance and patrolling in multi-room scenario,exchange sensed data among them and stitch each piece of fragmental information into a bigpicture which reflects an overall view of the entire environment. This kind of data processing canbe sent to Cloud for further analysis for any response to be taken if necessary. Besides thedomestic service applications, the same idea can be applied to industrial environment as well,especially for
performance.Limitations The primary limitation of this study is the lack of diversity among the participants. Wewere able to get good analyses of how motivational and early life experiences impact spatial skillsbut were not able to investigate how this effect might vary across different demographics. Wewere also not able to make good comparisons of different demographic groups. Future studieswill incorporate data from a more diverse set of participants.Future Research The authors’ future research plan is to use the results of this study to implement and testthe instructional interventions. The first intervention will focus on the instruction regarding thenature of knowledge and how this impacts self-efficacy beliefs and further impacts spatial
experience Active Experimentation Reflective Observation planning/trying what has been learned reviewing/reflecting on the exprience Abstract Conceptualization concluding/learning from the experience Fig. 1. Kolb’s cycle of experiential learning [7]. However, practically there are many obstacles in applying Experiential Learning methods. Thefirst problem comes from the limitation of students’ knowledge and experience, as wells as the © American
, J., & Magana, A.J. (2015). Exploring Design Characteristics of Worked Examples to Support Programming and Algorithm Design. Journal of Computational Science Education, 6(1).22 Shiflet, A. B., & Shiflet, G. W. (2014). Introduction to computational science: modeling and simulation for the sciences. Princeton, New Jersey: Princeton University Press. Appendix A Due to space limitations, a reduced rubric describing only the lowest and the highest score is presented here. Criterion Description Poor (0-2) … Excellent (9-10) Evaluates the student’s plan for - No strategy is
learningexperiences. We will then pilot these elements with educators who are designing learningexperiences and then reverse engineer our tool to help these designers assess whether they areeffectively designing a learning experience aligned with Perkins’ model.Discussion and Future Work In this paper, we presented the first stage of a larger project whose aim is to develop atool that will help educators develop courses and learning experiences as well as assess theeffectiveness of their design and their pedagogical objectives, offering both planning andfeedback functions. More specifically, this paper situates this study in the context of broaderengineering education priorities, provides an overview of the Making Learning Whole3framework and
Research Fellowship. His research interests range from sophomore-level engineering curricula to spatial ability and creativity to student entrepreneurship.Mr. Steven David Wood, Utah State University Steven Wood is a junior in the Civil Engineering program. After finishing his BS he plans on completing a MS in Civil Engineering. In addition to studies, he is a teacher’s assistant and he teaches a recitation class for the Statics course. His Interests in the field of engineering are public transportation, specifically in rapid and heavy rail systems. His research interests include spatial ability, learning styles, and gender differences in meta-cognition. c American Society for Engineering
and many have elective courses focused on I&E. • Only a few had I&E as part of the core curriculum. • There was almost universal interest in increasing the presence of extracurricular and elective course offerings and a majority view that I&E should be part of the core curriculum. • On most campuses, the number of faculty engaged in supporting I&E education was said to be limited. • Most saw their university leadership as supportive of I&E, and engaged in early or more advanced stages of strategic planning. • Common challenges included finding space in the engineering curriculum, overcoming faculty and, to a lesser degree, administrative resistance
Peer Evaluations 16 Week Due 2st Semester 9 Updated Drawing Package from First Semester 2 10 New Gantt Chart w/WBS and Milestones 2 11 Functional Prototype 8 12 Mid-Term Peer Evaluation 8 13 Prototype Test Plan 9 14 Prototype Test
appropriate, with Expanded participation including many of the attendees from the first workshop, and including Both pairwise and three-way interactions among themes to explore connections. An important outcome of the second workshop will be to identify small leadership teams for each theme. The workshop steering committee would begin that process in the planning stage.”The foregoing demonstrates that this objective was met. Substantial progress was made in each of thethree groups resulting in specific recommendations and action items. One overarching recommendationwas again that there should be a third such workshop to address some of these specifics, and todisseminate progress that has been made in