).AcknowledgementsThis research was funded by the National Science Foundation under Grant DUE-0831811to the University of Texas at Austin. The opinions expressed herein are those of theauthors and not necessarily those of the NSF. For additional information aboutUTeachEngineering curricula and research see http://www.uteachengineering.org/.References1. Berland, L. K., & Hammer, D. (2012). Framing for scientific argumentation. Journal of Research in Science Teaching, 49(1), 68–94. Page 25.884.92. Berland, L. K. Martin, T. H., Ko, P., Peacock, S., and Rudolf, J. (under review). Student Learning in Challenge-‐Based
I like the following session(s). 17 25 21 25 29 20 20 I think the following session(s) needs 2 1 6 3 5 8 7 9 improvement. I was able to understand the theory in 3 N/A 22 25 17 20 15 14 lectures better by doing the experiments. Especially the following experiment(s) 4 N/A 17 20 21 18 14 13 was helpful to understand the theory. Especially the
classroom engagement and its effect on student performance.The emergence of Web 2.0 and SNT as a dominant force for communication and interactionamong various groups of people has led to discussion among the academic community regardingwhether or not these technologies are actually effective within the classroom setting. Whileeffectiveness in regards to classroom performance has not been successfully determined and stillexists as a gap in the academic community’s knowledge of Web 2.0’s effect on higher education,there are parallels that exist between using online courses and Web 2.0. Several studies7, 8, 10have been conducted to determine if there are any significant differences between students whohave chosen an online course of study versus a
Sketchup strike a balance between the ease-of-use necessary for classroomlearning and the flexibility to solve various design challenges. Digital fabrication, leveragingdesktop computer-aided manufacturing (CAM) promises to transform society in wayscomparable to the desktop computer revolution of the 80’s and 90’s25. Students who enter theworkforce with familiarity with such technologies will be well positioned to lead the way.Digital desktop fabricators are dropping in price and increasing in user-friendliness (e.g.,RepRap http://www.reprap.org; UP! 3D printer http://www.pp3dp.com; Fab@Homehttp://www.fabathome.org) with communities of 3D designers coalescing to share designs (e.g.,http://www.thingiverse.com). WISEngineering will smoothly
D ata: Assoc of Universi ty Technol ogy Manag er s (AUTM ) S urvey 2004 NIH supports institutions & people (Extramural Research) > 4,000 institutions > 300,000 scientists & research personnel ~ 85% of the NIH budget NIH Grant StatisticsFiscal Year 2010• 88,000 applications received (all mechanisms)• 240 Review Officers organized 1,600 meetings with 18,000 reviewers• Over 62,000 research grants reviewed … improving health by leading the development and accelerating the application of biomedical
% Hispanic or Latino 6% Ethnicity Not Hispanic or Latino 94% American Indian or Alaskan Native 0% Asian 25% Race Black or African American 6% Native Hawaiian of Other Pacific Islander 0% White 69% U. S. Citizen 72% Residence
working for the Innovation and Techno- logical Development Centre of UNED (CiNDETEC). He is an expert in learning management systems (LMS) and web development applications. Currently, he is collaborating in a research project of open services integration for distributed, reusable, and secure remote and virtual laboratories (s-Labs). Page 25.326.1 c American Society for Engineering Education, 2012Dr. Tovar Edmundo, Universidad Politcnica de Madrid Edmundo Tovar, computer engineering educator, has a Ph.D. (1994) and a bachelor’s degree (1986) in computer engineering from the Universidad
in appropriate subsequent analyses. From the Y2 data, we observed no significantdifferences at the 95% confidence level (α = 0.05) between any student sections’cumulative pre-test score, and thus, we include this data in the appropriate analyses in Section 4. When looking atindividual parts of the pre-test, however, we did find a significant difference between section 1 andsection 4 on the Lab 5 portion of the pre-test (p-value = 0.04), with section 4 having a significantlylower average on this portion of the material. Because of this, student section 4’s data was omittedin the Lab 5 analyses for Y2. 4 Results 4.1 Educational Benefit from Course The first question we sought to answer was whether or not the students learned and
Bay Area, received a National Science Foundation Scholarshipsin Science, Technology, Engineering, and Mathematics (S-STEM) grant to develop a scholarshipprogram for financially needy community college students intending to transfer to a four-yearinstitution to pursue a bachelor’s degree in a STEM field. In collaboration with the College’sMathematics, Engineering, and Science Achievement (MESA) program – an academic, personal,and professional support structure has been designed and implemented to maximize thelikelihood of success of these students. This support structure aims to create a learningcommunity among the scholars through a combination of academic counseling and mentoring,personal enrichment and professional development opportunities
partnered with The Henry Ford, both of which are located in the Detroitmetro area. As a result, Lawrence Tech‟s camp was focused on exploring creativity, innovation,and ingenuity as it relates to the American experience and manufacturing. In subsequentsummers, Boston University and St. Louis University will host summer enrichment opportunities Page 25.364.3in their respective metro areas. (Themes, details, and objectives for the Boston and St. Louiscamps had not been finalized by the time of publication of this paper.)2. Lawrence Tech Summer Enrichment ProgramThe Detroit metro area is well known as being the world‟s automotive industry capital and
2 Q A process occurs toState Change S S irrev change the system’s state. 1 1 Q2 , out 1W2 , out 1 T
/latino_children_in_the_2010_census 2 Huband, F.L. (2006). “An International Flavor,” Editorial, PRISM magazine, ASEE, December. 3 Gibbons, M. T. (2011) “The Year in Numbers.” ASEE Profiles of Engineering and Engineering TechnologyColleges, 2011 Edition. 4 Frehill, L.M., DiFabio, N.M., & Hill, S.T. (2008). Confronting the "new" American dilemma --Underrepresented Minorities in Engineering: A data-based look at diversity. White Plains, NY: National ActionCouncil for Minorities in Engineering (NACME). 5 Tinto, V. (1994). Leaving college: Rethinking the causes and cures of student attrition (2nd ed.). Chicago:University of Chicago Press. 6 Noel, R. C., & Smith, S. E. (1996). Self-disclosure of college students to faculty: The influence of
advancedstudents with better working memory capacity 4. An illustrative example is discussed asthe following. A normalized standard deviation is used customarily to represent the GPSsignal S4 index. 2 ∑ (x − x ) x S4 = N ⋅ x2where x denotes the mean, x is the current CNR (Carrier/Noise) value, and N is the totalnumber of samples or the sample window. To simplify the implementation, it would be Page 25.197.5 s-diff[] + = avg*avg - 2*CNRtemp*avg + CNRtemp*CNRtemp; cumsum[] += CNRtemp;where ‘x += y’ means ‘x = x+y’. The cumsum[] is a cumulative sum of the CNR values,divide it
this paper, we describe a scaffolding scheme that helps student managetheir learning during academic semester. In this scheme, students were given a deadline for eachcompetency, instead of having only one end-of-semester deadline for all 8 of their competencies,which is usually the last day of classes. The results show that the proposed time allocation planbetter helped students complete their competencies at the end of the academic semester.1. IntroductionProject-Based Learning (PBL) as well as problem-based learning was first established in themid- 1950’s and has been effectively used in Medical schools 1. It has since been adopted in avariety of educational fields such as Engineering, Science, Business, Education, Law, etc. 2,3,4. Itis
. Page 25.1023.1 c American Society for Engineering Education, 2012Panel Session –Case Study Teaching in Computing CurriculaMassood Towhidnejad, Salamah Salamah, Thomas HilburnEmbry-Riddle Aeronautical University600 S. Clyde Morris Blvd.Daytona Beach, Fl, 32114towhid@erau.edu, salamahs@erau.edu. hilburn@erau.eduAbstractThe use of case studies is an effective method for introducing real-world professional practices into theclassroom. Case studies have become a proven and pervasive method of teaching about professionalpractice in such fields as business, law, and medicine. Case studies can provide a means to simulatepractice, raise the level of critical thinking skills, enhance listening/cooperative learning skills
PG Research Experimental Computer based- Nature of institution Research University Teaching institution Subject Areas Science and Arts and Commerce Technology Specialization Generalist Specialist Prosperity of Rich Poor Stakeholders Access to information Information haves Information have nots - Page 17.7.18EVOLUTION OF UNIVERSITY RESEARCH ANDINDUSTRIAL CONSULTANCY IN INDIA During the Early Years (70’s) ―Publish or Perish‖ Later Years (80’s) ―Publish and Consult; or Perish
or engineering design. The language of industry may not be typical oflanguage used in the classroom or in the text book(s). While issues of jargon and terminologymake clarity of communication via a survey challenging, it can lead to dialogue needed toachieve commonality in meaning. This dialogue was sought with the open-ended questions. In apaper, or survey; however, dialogue is still somewhat illusive. Nonetheless, by the time thispaper is published, it is expected that some face-to-face dialogue on this area of capstone willhave occurred at the bi-annual Capstone Conference (http://www.capstoneconf.org/).Table 1: Problem statement characteristics (coding) used in the Likert scale question General statement, definition or description, an
example, if the mainerror being made is related to switching the x and y components of a force due to sine and cosineconsideration. A non-graded worksheet could be prepared that focuses on that specific non-conceptual error. Some thought has been given to developing a booklet of problems thatspecifically identify the common errant paths; however, there is still a lot of data to analyze priorto the execution of that thought.Bibliography 1. Newcomer, J. L. and Steif, P. S. (2008) “What Students ‘Know’ About Statics: Specific Difficulties Common Among Students Entering Statics”, Proceedings – 38th Annual Frontiers in Education Conference, ASEE/IEEE. 2. Newcomer, J. L. (2010) “Inconsistencies in Students’ Approaches to Solving
Career Development model is based on a life-long process where individualsreflect on their changing self concepts as they pass through stages of growth, exploration,establishment, maintenance, and disengagement with each career decision and transition. 6, 7Super used the “growth” and “exploration” stages to develop a children’s model that he believed“contribute[s] to career awareness and decision making”. 8 This model includes stages of Page 25.907.3curiosity, exploration, using occupational information, identifying helpful people, naming likesand dislikes, recognizing locus of control, and understanding one’s self-concept. 8Identifying helpful
enrollments at theseinstitutions are: over 10,000 at PUC, over 8,000 at Ivy Tech, and more than 28,000 at COD. The NSF-ATE project goals are: 1) augment and reorganize existing electrical andmechanical engineering technology courses into thirty-two enhanced modules at three differenttiers, 2) incorporate experiential learning in each module level so that the modules aremeaningful and practical, and 3) incorporate innovative delivery of lecture and laboratorymaterials. The innovative aspects of this project are: a) meet student learning needs based on theirdiverse educational background, b) provide multiple delivery options, c) complete modules(rather than courses) to receive college credit(s) or certificate(s), and d) provide
Language 8 Page 25.33.4 Ruby Unit Testing Relational Databases Web Application Frameworks 9 Introduction to Ruby on Rails Ruby on Rails 10 Testing in Rails Final Exam Week 11 (Practicum in C or Ruby) Table 1. – SE350 Course OutlineClass ActivitiesActivities were developed for each class and are worked on by student pairs. Classes have s
everyday experiences.into sub-factors. Second, to come up with multidimensional scales of Engineering-related Beliefsitems, a content validity test was conducted.Systematic Literature ReviewWe selected three representative journals of engineering education: such as Journal ofEngineering Education (JEE), European Journal of Engineering Education (EJEE), andInternational Journal of Engineering Education (IJEE). The search for JEE and IJEE wereperformed in Web of Science (up to January 2012) with the following search terms: "beliefs" or"perception" or "understanding" – AND – "survey" or "test(s)" or "questionnaire" or "scale"–AND – journal name (i.e. “Journal of Engineering Education”, “International Journal ofEngineering Education”). The search for
internal funding of a faculty member. Under this model, one or more individualsparticipate in a faculty member‟s research and are funded either directly by the research orthrough supplemental funding obtained through a funding agency such as the National ScienceFoundation (NSF). Another model, the focus of the current research, is the establishment of aresearch experience site targeting a certain segment of the population. There are also researchprograms for prospective students in K-14 levels, including a week-long hands-on high schoolresearch experience camp7 with desired program outputs and a two-week community collegeresearch experience program with retention and recruitment goals8.A research experience site can be sponsored by an external or
The AIMS 2 Program S. K. Ramesh Dean College of Engineering and Computer Science04/17/12 EDI 2012_Ramesh 1 •Jacaranda Hall- Courtesy Prof. Steven Stepanek Outline • Overview of CSUN • What is the AIMS2 program? • Goals and Objectives • Project Activities • Work in progress04/17/12 EDI 2012_Ramesh 2• CAMPUS SIZE: 356 acres• FACILITIES: Over 100 buildings totaling nearly 4 million square feet• ENROLLMENT
AC 2012-3204: EXPANDING YOUR HORIZONS: THE IMPACT OF A ONE-DAY STEM CONFERENCE ON MIDDLE SCHOOL GIRLS’ AND PAR-ENTS’ ATTITUDE TOWARD STEM CAREERSDr. Lisa Massi, University of Central Florida Lisa Massi is the Director of Operations Analysis in the UCF College of Engineering & Computer Sci- ence. Her primary responsibilities include accreditation, assessment, and data administration. She is a Co-PI of a NSF-funded S-STEM program at UCF entitled the ”Young Entrepreneur & Scholar (YES) Scholarship Program.” Her research interests include factors that impact student persistence to graduation and STEM career intentions.Dr. Charles H. Reilly, University of Central Florida Charles H. Reilly is the Associate Dean
of trans-disciplinary engagement thatcould be transferred to similar contexts or efforts. We conclude the paper with an outlook on theplans for an empirical investigation of student development through this initiative.2 Theoretical framework: Conceptions and functions of empathy in the field of social workThe historical evolution of the concept of empathy has its roots in the German aesthetic idea ofEinfühlung (“feeling into” objects) introduced by the philosopher Robert Vischer in the late1800s, reflecting the “projection of human feeling on to the natural [or physical] world” (ascited in 12). Building on Vischer‟s work, in 1903, Theodor Lipps, another German Philosopherexpanded the notion of Einfühlung away from its application to
RP Simulator to learnFDM operations and other applications. At the end of each activity corresponding to each group,a written test comprised of 10 multiple choice questions was taken to evaluate students’knowledge of the FDM 3000 operations and applications. The test scores from three groups weretabulated and illustrated below (see Table 3): Table 3: Comparison of student performance based on Group A, Group B and Group C Group A Group B Group C (Live Instruction) (Video) (The RP Simulator) S. No For 10 S. No For 10 S. No For 10 1 4
for relevant statistical constructs, are then presented and discussed. An analysis ofvariations in approach to teaching on the basis of a range of key variables are presented anddiscussed. Finally we provide conclusions and areas for future exploration.BackgroundThe approaches to teaching inventory (ATI) has been developed and refined over the lastdecade. It has its origins in phenomenographic studies of teachers’ attitudes to teachingand learning in the mid 1990’s. A description of the developmental history and statisticalanalysis of the instrument can be found elsewhere2, 3 .Prosser and Trigwell advance the view that there is a fundamental qualitative differencebetween a student-centric and teacher-centric view of the learning process3
# open u3 library06 d = u3.U3() # open and report the device07 print d.configU3()['DeviceName']0809 # bitmap representing channels, with FIO0 being the lsb10 d.configIO(FIOAnalog = 0x03)1112 # For single ended channels, match each with NChannel 3113 d.streamConfig( NumChannels = 2, PChannels = [ 0,1],\14 NChannels = [ 31,31], Resolution = 3,\15 SampleFrequency = 2500 )16 missed = 0; dataCount = 017 d.streamStart()18 myfile = open(FILE_NAME,"w")1920 for r in d.streamData():21 if r is not None:22 if dataCount >= MAX_REQUESTS: # The stop condition23 break24 if r['errors'] != 0:25 print "--- Error: %s ; " % r['errors']26