, augmenting humans, or unsuitable forthe task). BASIS OF THEIR PROPOSAL RELATIONSHIP AUTHORS TO HUMANS Exhibit intuition, insight and learning. Machines that think, that REPLACE NEWELL, SHAW, learn, that create … the range of problems which they can SIMON[16] handle will be coexistive with the range to which the human mind has been applied. Programming a robot with an integrated suite comprising REPLACE Nilsson, N. J.[17] planning systems, models of the world and sensory processing systems enables it to successfully accomplish tasks in the real world settings. Role of AI cased
questions and provide feedback.The NEES REU leadership team explored multiple options for the second major activity for theVPTs. The intended purpose of the second activity was to engage the teams in a challenge taskthat required knowledge building together, managing ideas, and making decisions. Ideally VPTswould have completed a design project or research project where the team worked to exploreoptions, critically evaluate alternatives, make a decision, and prepare a development plan. At thesame time, the leadership team was concerned with the overall workload of the students, whichlimited the scope of the projects VPTs could complete. Therefore, the second major activity ofthe VPTs was to generate a short report recommending potential conferences
the interpreter project that was part of the course. After the completionof this activity, in each course, students were asked to complete a survey about their experiences inusing the tool. In Section 4, we present an analysis of the survey results which suggest a very posi-tive effect of the approach on students’ learning, and highlights the importance of various featuresof our approach. We conclude in Section 5 with a brief summary and plans for future work.2 BackgroundOur approach builds on two key notions that have been used successfully in various branches oflearning sciences over the past few decades: Cognitive Conflict Driven Learning and Computer-Supported Collaborative Learning.2.1 Cognitive Conflict Driven LearningPiaget’s
students in ourcourse. Through these case studies, we would also like to provide a compelling example of howtightly bound the ethical choices are to the design and implementation decisions of a mobileapplication that is developed for social good.5.1 Combating obesity in young adolescentsObesity has become a major public health issue in most countries around the world. In addition,adolescent obesity is increasing at an alarming rate all over the world. Many attempts have beenmade to address this issue that ranges from doing exercise to following a diet plan to playinggames. While the existence of the above works indicates the past and ongoing efforts to combatadolescent obesity, they are clearly not enough since it is still rising. Researchers
such as NAEP or PISA that would allow those programs to offer assessments ofcomputational thinking.In future research we plan to: a) Extract new, visualization-informed measures derived from thetime series used in these visualizations. E.g., first and second order derivatives, means andvariances to infer CT constructs can be used. b) Use the newly extracted measures to providereal-time feedback to students and/or teachers. c) Explore the use of the newly extractedmeasures as new features for inputs to machine learning models and algorithms.References[1] H. M. Madill, R. G. Campbell, D. M. Cullen, A. A. Einsiedel, A.-L. Ciccocioppo, and M.- A. Armour, “Developing Career Commitment in STEM-related Fields: Myths versus Reality,” in Women
in the first weeks of the quarter and letting usfocus on the logic of programming and on problem solving. The online web-based simulator alsowas a pleasure to use during lectures, supporting code stepping, displaying variable updates, anddepicting flowchart views of code. The students indicated they enjoyed using the simulator aswell, and we had no reports of students having trouble accessing or using the simulator.However, we believe we got a few things wrong in the initial design of the Coral-to-C++approach. Based on the experience, we plan to make several changes in our next offering inSpring 2020 (ongoing at the time of this paper's writing): ● We taught Coral for 5 weeks, covering input/output, assignments, branches, loops
tominimize these behaviors and design an equal learning environment for students in a computer-supported, especially HMD VR-supported, class. This proposed study is expected to fill the gap. Being motivated from the activitydescribed in [3], I will conduct a research to explore whether the dominating behaviors can beeased when more HMD headsets are available for a team in a collaborative learning activity andwhat are the design principles of an equal learning environment for collaborative learning underHMD VR environment. The research question that leads the study is: How to design an equal engineering class environment for students’ collaborativelearning with HMDs? To answer the research questions, I plan to conduct an experiment
topics.Mr. David W Reazin, Purdue University Dave Reazin is currently a third year student at Purdue University working towards a B.S. in Electrical Engineering with a focus on Automatic Controls and Integrated Software Methods. Scheduled to grad- uate in 2016, Dave plans to enter industry before returning to school to complete his Masters. Through- out his time at Purdue, Dave has also worked as a Resident Assistant and Staff Resident for University Residences, a Teaching Assistant and Grading Systems Team Lead for the Purdue University First Year Honors Engineering Program, and an Electrical Engineering Intern for United Launch Alliance in Cape Canaveral, FL
class time in whichthe instructor has set aside time and planned the lesson to provide instruction specifically on theCAD/E tool. We refer to informal instruction as those occasions at the start, middle or end ofclass where an instructor spends a couple of minutes providing simple direction or guidance toassist students in learning or using the CAD/E tool. This may occur as a result of a surveyresponse, in response to a question a student had during additional instruction/office hours, or asa result of a question before or during class. An example of informal instruction that could resultfrom the survey would be to show the Active-HDL help index at the beginning of the next classperiod. We learned in our Master Teacher Program that addressing
that our learning is maximally effective for cause-and-effect relationships when delay is minimized, but that our psychological tolerance for delay ismuch higher. This conflict between competence perception and objective reality impactsuniversity information technology infrastructure and pedagogical software design. This isespecially the case for the emerging field of long-distance web education. These studies exposeflaws in perception-based assessment of these areas. Continued studies are planned to assesscategory-specific differences such as age, gender, and major.IntroductionThe use of web-based learning tools is continuing to increase today as well as the promotion oflong-distance learning and assessment1. Many standardized tests, such as
pedagogical concepts to support teaching of mathematics for mathematicians, engineers and natural scientists - at the TU Berlin in 2001, as a research assistant at SFB609 in Dresden from 2002-2004, and is now part of the Team of the MuLF (Center for Multimedia in Education and Research) at the TU Berlin). In the past three years, Olivier Pfeiffer focused on the organization and coordination of the involved teams and contributed to several other eLTR related projects. He is also involved in the planning and application of future eLTR projects at the Berlin University of Technology and the local coordinator at the TU Berlin of the EMECW3 project. His research interest focuses on the
, are discussed in a later section.In addition to regular courses, the NDPL was made available to students, faculty, and staff of theuniversity to fulfill their senior project requirements, conduct independent research, and preparefor industrial and national certification (in areas such as Networking, Telecommunications, and Page 13.363.5Operating Systems Administration) respectively. Many of the senior projects will be anexpansion of work started by the students in the key targeted courses.Engineering Plan & LayoutThe lab uses a total of approximately 22’ x 36’ lab area. The infrastructure networkingequipment was complemented by the
, whichprovides exposure to engineering topics to interested and motivated high school sophomores fromaround the state. Only about 100 applicants are accepted each year for this program, now in its22nd year. The students live on the University campus for three weeks and learn about humanities,sciences, and engineering. A sequence of classes/demos is given by the ECE department, whichcovers a broad range of topics in digital systems. We plan to augment several of those lessons byusing the C6713 DSKs with winDSK6 software. In particular, audio special effects and a verybasic introduction to sampling are appropriate for this audience.We also conduct the Engineering Summer Program (ESP) for high school juniors. This program ismuch newer than HSI, is focused
Page 14.358.8Requesting Information through Facebook GroupsTo determine the effectiveness of using Facebook Groups for requesting information from ourgraduates, two exercises were conducted in the fall of 2008. One of the questions that is oftenasked by prospective students or their parents is with regard to what sort of job one can get witha degree in a particular field. To assist in answering this question, the first exercise involvedrequesting members of our Alumni Facebook Group to mail in one of their business cards. Thegroup members were all sent a message that first stated the often-asked question, then requestedthat they contribute to a planned display of business cards that would creatively serve as a visualaid for addressing this
from other instructors are highly valuated.1.1 Power Engineering Education Issues and ChallengesThe size and complexity of power system or electrical machine problems have questioned theuse of dedicated software packages in education. Extensive use of software programs in powerindustry started few decades ago are playing an indispensable role in power system planning,operation, analysis, modeling, and training. A further growth is anticipated in the development ofsuch software tools in near future with the development of smart grids. Nevertheless powerengineering educators waited relatively a long time to respond favorably and to use computingtools as teaching aids. Moreover, several reports suggested that university educational programsin
) theaddition of special topics lectures and demonstrations in robotics in a group setting, whichfacilitated discussion; 2) virtual office hours with screen sharing for mentoring; and 3) a postersession exhibit with 3D models for team projects. None of these were possible with earlierofferings of this online course. The current author plans to use this tool in additional onlineofferings and evaluate with a larger sample size. It is also intended to explore the benefits ofcustomized environments, analytics, and the Python scripting tool for more interactiveexperiences in the 3D environment. Based on the student feedback, the author also intends toprovide additional orientation and training for the students, as well as to investigate some of
in projects rather thanautomate team formation. These aspects will be examined in future work.Future WorkAs part of planned future work, the authors wish to investigate how useful the interest star ratingfeature is in comparison to a interest priority ranking. This would be similar to the bid priorityranking but would instead rank projects in the order of interest so as to disambiguate between theinterest level of students towards multiple projects. This feature would allow the students tospecify a unique ranks, instead of three stars, to projects of their preference, allowing to prioritizeprojects and more easily break ties not just for team formation, but also during the process ofproject assignment to teams.Another avenue of exploration
from engineering and other disciplines may be useful ininforming design decisions and providing insight into issues of performance and scale. Duringthe EarSketch project, model development occurs concurrently with the design and roll out of theeducation innovation. This is unique from previous efforts to model school systems and theinterventions within them, where models were created in a ‘post mortem’ analysis of the projectimplementation to add additional understanding to the factors at play14, 17. In this work, insightsfrom the modeling efforts not only inform sustainability planning, but also guide thedevelopment of the innovation.In the remainder of the paper, the EarSketch intervention is briefly described and someobservation-based
students’ interest in this course, which also improved their performance.1. IntroductionRobotics is becoming one of the most attractive majors in the Colleges of Technology because ofthe advantages in respect of applications, jobs, and prospects. Therefore, more and more Collegesof Technology have or are planning to create robotics program. Usually, as an interdisciplinaryfield, the robotics programs are provided by either Computer Engineering Technology or MET.However, students of Engineering Technology, especially MET, are facing two dilemmas whenproviding robotics courses:(1) Technology programs mainly focus on hands-on skills and there are fewer fundamentalrobotics-related courses in the MET curriculum than in electrical engineering
economic decisions, cost is a factor in college selection. In fact, the cost of a particularcollege has been shown to be a rising concern for first-year students.27 As a result, morefirst-year students are attending colleges near their homes and almost one-fifth of incomingfirst-year students plan to live with relatives during the first year of college. The impact of coston college decision is especially important for first-generation college students. Despite the factthat these students are accepted to their first choice institutions at similar rates as their peers, firstgeneration students are less likely to attend a first choice institution.27 In addition to financialpressures, first generation college students have been found to have more
teasers are suitable to transfer theinformation of the experiments as their main aim is to support the idea of student centeredprojects rather than helping the students to understand such topics in detail. For such deepunderstanding of other groups’ projects there is basically no need in the OPLChem as eachstudent group has to conduct their own newly defined project but it turned out that there is astrong need for qualitative best practice examples and ideas at the beginning of the semester tohelp the students quickly define their own project topics [11], [14].In the OPLChem the students conduct their own projects and plan their own experiments in theframework of RBL. The topics are often related to contemporary research topics in ecology
six groups of4 (approximately) members each. The instructor meets with each team individually and discusses theirquestions and explains to them how specific questions can be clarified and improved. Although, theentire activity from start to finish is carefully monitored by the instructor with continuous feedbackand grading of team-performance, independent team work and individual responsibility are alsoemphasized. This activity can be replicated in other CGT courses as well other disciplines. The resultssuggest that it can be an effective means to strengthen CG course pedagogy. This approach willfacilitate assessment of tactile learning methods in CGT course curriculum and help with a continuous‘Course Improvement Plan’. Ultimately this
postdoctoral fellow in the area of bioacoustics. He teaches dynamics, machine design, numerical methods and finite element methods. He has work for the automotive industry in drafting, manufacturing, testing (internal combustion engines—power, torque and exhaust emissions, vibration fatigue, thermo-shock, tensile tests, etc.), simulations (finite element method), and as a project manager (planning and installation of new testing facilities). c American Society for Engineering Education, 2016 Analytical Solution, Finite Element Analysis and Experimental Validation of a Cantilever BeamIntroductionThe purpose of this work is to show how a series of labs can be used to provide
and someone proposed this mission, would you approve it? Why or why not? 2. If you were planning this trajectory, would you be worried about the lifetime of the spacecraft? Why or why not? 3. Would you fly this mission? Why or why not?In the chemical engineering course, the AspenTech programs HYSYS and Aspen Propertieswere used for simulations. Aspen Properties is a chemical property database that allows users tolook up thermodynamic information for chemicals and chemical systems. HYSYS is thesimulation software that allows users to simulate a chemical plant or process. HYSYS is widelyused in industry, and in chemical engineering senior design courses throughout academia.Because of technical difficulties throughout the term
virtual objects and omnidirectional treadmills enable unrestrictednavigation through a virtual environment by natural walking movements. Other tools as 3-dimensional joysticks or sensor-enhanced clothes may come into play. To evaluateperspectives and potential for the use of mixed reality settings within engineering educationan empirical study was carried out, focusing on the impact of spatial presence and flow oncognitive processes. Therefore an experimental research design was chosen. A mixed realitysimulator (Virtual Theater) was used which combines two natural user interfaces: a headmounted display (HMD) and an omnidirectional treadmill. To assess the effects of naturaluser interfaces on cognitive processes, a two-group-plan (treatment and
, have similar results. This allows us to increase our data set and tounderstand if these methods are more generally applicable to a range of courses and under whatconditions. Our second direction, which we have learned might be the most important part of thiswork, is how should the criterion map be created? Even though our results seem to show positiveresults, we suspect that the criterion map is fundamental in this process. For example, if the termsin a field are highly connected (larger degree) then does this make it easier or harder for a student.Also, how does the timing of when the terms are presented in the course impact the longitudinalstudy. Our plan is to use this new metric in these studies and to try and answer these questions forthe
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
al., SIIP was designed to focus on creating collaborativeteaching environments that enabled faculty to iteratively and sustainably innovate instruction.This environment was created by organizing faculty into Communities of Practice (CoPs) thatwould choose what innovations to pursue and evaluate their efforts to create those innovations. ACoP is an organizational structure that effectively spreads knowledge, decreases the learningcurve for novices, minimizes reenactments of failures, and promotes creativity11,12.The MatSE CoP is composed of one tenured and five tenure-track faculty who meet on a weeklybasis to discuss course administration, data collection, and future plans. The goal of thesemeetings is to develop a common set of resources
-based retrieval, supervised learning for regression-based time series prediction, andBayesian models for causal inference on the decision support end.Both informal assessment of the system and intensive user testing on a pre-release version haveyielded positive feedback. This feedback is instrumental in feature revision, both to improvesystem functionality and to plan the adaptation of the design of these two data explorationcomponents to other STEM disciplines, such as computer science and mathematics. Lessonslearned from visualization design and user experience feedback are reported in the context ofusability criteria such as desired functionality of the pattern inference system.The paper concludes with a discussion of the system as an