Likert Taxonomy Criteria Scale Level(a) 4 Examine correct equation for d(min) 3 Interpret d(max) 0 = No work 3 Execute the equation 1 Report units 1 = Method and/or understanding(b) 4 Examine correct zero air void line significantly below standard equation 1 Remember to use specific gravity in 2 = Touches on right method but equation significant errors in concept 3 Interpret optimum water content 2 Identify S = 1.0 for the zero air void 3
, tutorials and documentationdeveloped by MRE faculty can significantly help with widespread use and adoption of open-sourceplatforms in higher education institutions. 12References[1] Laurent, A. M. S. (2004). Understanding open source and free software licensing: guideto navigating licensing issues in existing & new software. "O'Reilly Media, Inc.".[2] Open Source Hardware Association (OSHWA). Brief History of Open Source Hardware:Organizations and Definitions. https://www.oshwa.org/research/brief-history-of-open-source-hardware-organizations-and-definitions/ [accessed December 2019][3] OpenSource.com. What are Open Hardware. https://opensource.com/resources/what-open-hardware [accessed
especially true at public institutions driven toexpand access while improving retention rates, based on performance metrics set by the state.Retention studies have been conducted for nearly every sub-population including women andmany racial and ethnic groups. Some of the work has shifted to intersectional analyses—forexample, Archer’s exploration of black male students’ resistance to “geeky” identities [10], orJohnson et al.’s study which highlights some Native American and Latina women’s preference towork as scientists within their ethnic communities as a method of balancing ethnic andengineering identities [11]. However, less work has been done on the interactions that occuracross different student cohorts. Indeed, scholars have argued that due
Scherer, L. 2018. Graduate STEM Education for the 21st Century. Washington,DC: The National Academies Press. https://doi.org/10.17226/25038.Meredith, J. R., Shafer, S. S., Sutton, M. M., Mantel, S. J. Jr. (2010) Project management inpractice (4th ed.). Wiley.National Institutes of Health. (2012). Biomedical Research Workforce Working Group Report.https://acd.od.nih.gov/documents/reports/Biomedical_research_wgreport.pdfNational Science Board. (2015). Revisiting the Workforce: A Companion to Science andEngineering Indicators 2014. https://nsf.gov/pubs/2015/nsb201510/nsb201510.pdfWendler, C., Bridgeman, B., Cline, F., Millett, C., Rock, J., Bell, N., McAllister, P. (2010). ThePath Forward: The Future of Graduate Education in the United States
Computing Sciences (ICCS), (pp. 151-160). doi:10.1109/ICCS.2018.00033Beavis, P., Sardar, M., Sircin, L., Janack, G., Pack, D., Griffith, A., & Barrett, S. (2005). Using Robots to Teach Complex Real Time Embedded System Concepts. Proc. 2005 ASEE Annual Conference. Portland, Oregon. Retrieved from https://peer.asee.org/14719Berry, C. (2010). Mobile Robotics: A Tool for Application Based Integration of Multidisciplinary Undergraduate Concepts and Research. Proc. 2010 ASEE Annual Conference & Exposition. Louisville, Kentucky. Retrieved from https://peer.asee.org/15642Berry, C. A. (2017). Robotics education online flipping a traditional mobile robotics classroom. Proc. 2017 IEEE Frontiers in Education
throughout the country. Finally, 348 questionnaires were collected, of which 284 were valid. The Cronbach ’s α coefficient of all items is 0.955. 4.2 Descriptive statistics of samples The industries of respondents cover multiple industries such as “Machinery and Transportation Engineering”, “Information and Electronic Engineering” and so on. Theindustries distribution of respondents is shown in Figure 3. The organization ofrespondents is shown in Table 2. 58.8% units have more than 1,000 people and 14.79%have 501-1000 people, indicating that TRIZ is mainly applied in large and medium-sized units. As for the nature of the units surveyed, state-owned enterprises, privateenterprises, and research institutes account for 33.47%, 34.275,29.84
those who elected not to take it (blue). It is not surprisingthat students who scored in the 90’s were not interested in the mastery exercise or the second-chance exam. The majority of students who chose to take the second-chance exam consists ofthose who scored at and below 80% (C, D, and F grades) and, especially, those in the long tail onthis first-chance assessment. While the mean grade on the first-chance exam 2 for all 404students was 70.9%, the mean grade (standard deviation = 23.9) of those who later elected totake second-chance exam 2 (N=208) was only 62.2% (standard deviation = 18.9) which is nearlya full letter grade lower than the class average. Even more significantly, this mean grade of thosewho elected later to take second-chance
internships. These results aredemonstrated in Figure 1. The vertical axis indicates the total number of learning behaviors (orfine codes) demonstrated in an internship and each bar indicates the number of learningbehaviors under each style. In this study, three learning styles dictated students’ internshipexperiences as demonstrated by subordinating learning behaviors. 9 8 7 6 5 4 3 2 1 0 ex ias y s t ax hn yn ley ecca na il y Ki m Al b elb ar
: Bluebeam, Revit, Archicad, Tekla,Assemble, Procore, Navisworks, BIM 360, Sketchup, P6, and Synchro.The course is currently divided into five teaching modules, including: (1) drawing managementand processing, (2) modeling, (3) model-based cost estimating, (4) project management, and (5)scheduling and 4D (schedule dimension) simulation. Each module utilizes one or more softwaresystems. Table 1 highlights the software systems utilized for each teaching module.Table 1 – Cal Poly SLO’s Teaching Modules Software SystemsTeaching Module Software System(s) Utilized(1) Drawing Management Bluebeam(2) Modeling Revit, Archicad(3) Model-Based Cost Estimating
addition, each assignment has Grading Criteria with valuable clues on various simulation aspects such as footnotes, hyperlinks, and an Appendix featuring multiple examples that are relevant to the given simulation. 3. Students’ final grade is determined by performance on simulation assignments and three exams. Assignments have two components: structured (with step-by-step instructions) and unstructured (IBL). We use interviews with students throughout the semester and after the course(s), as well as instructors’ observations to tweak individual assignments and the overall simulation assignment line-up for the upcoming semester. 4. Our online environment is the Blackboard® learning management system (LMS
Undergraduate Engineering Students Enhance Novel Instrumentation to Detect the Mach Effect Peter Mark Jansson PE PhD and Peter S. Kaladius Bucknell UniversityAbstract – Undergraduate electrical engineers performing summer research have enhanced thereal-time data collection system of one of their professor’s novel detectors to uncover someremarkable results. Over the past two summers at Bucknell University students in engineeringhave been working on an innovative detector that has repeatedly produced results indicative of areal Machian like reaction force to inertia. Each summer (2018 and 2019) multiple studentscontinued to make electrical enhancements and
of GIS Virtual Learning Environments for Interactive Visualization Using Desktop Virtual Reality (VR) & iSpace”, in ASEE Annual Conference and Exhibition, New Orleans, LA, USA, June 25-29, 2016.[4] F. Castronovo, S. Yilmaz, A. Rao, W. Condori Jr, K. Monga, H. Gooranorimi, “Board 63: Development of a Virtual Reality Educational Game for Waste Management: Attack of the Recyclops’, in ASEE Annual Conference and Exhibition, Salt Lake City, UT, USA, June 23-27, 2018.[5] F. Castronovo, D. Nikolic, S. Mastrolembo, V. Hroff, A. Nguyen, H.P. Nguyen, S. Yilmaz, R. Akhavian, C. Gaedicke, “Design and Development of a Virtual Reality Educational Game for Architectural and Construction Reviews”, in ASEE Annual Conference and
, A.E. Geller, and N. Lerner, The Meaningful Writing Project. Logan, UT: UtahState Univ. Press, 2017. 8[10] J. Kellar, W. Hovey, M. Langerman, S. Howard, L. Simonson, L. Kjerengtroen, L. Sttler, H.Heilhecker, L. Ameson-Meyer, and S. Kellogg, “A problem-based learning approach forfreshman engineering,” in 30th Annual Frontiers in Education Conference (FIE), Feb. 2000.[11] H. Lei, F. Ganjeizadeh, D. Nordmeyer, and J. Phung, “Student learning trends in afreshman-level introductory engineering course,” in 2017 IEEE Global Engineering EducationConference (EDUCON), April 2017, pp. 152–156.[12] L. A. Meadows, R. Fowler, and E. S. Hildinger, “Empowering students with choice in thefirst year,” in 2012
] J.J. Kosovich, J.K. Flake, and C.S. Hulleman, “Short-term motivation trajectories: A parallel process model of expectancy-value,” Contemporary Educational Psychology, vol. 49, pp. 130-139, 2017. [2] E. Seymour and N.M. Hewitt, Talking about leaving: Why undergraduates leave the sciences. Boulder, CO: Westview Press, 1997. [3] S. Beecham, N. Baddoo, T. Hall, H. Robinson, and H. Sharp, “Motivation in Software Engineering: A systematic literature review,” Information and Software Technology, vol. 50, nos. 9-10, pp. 860-878, 2008. [4] E.S. Elliott and C.S. Dweck, “Goals: An approach to motivation and achievement,” Journal of Personality and Social Psychology, vol. 54, no. 1, pp. 5-12, 1988. [5] R.J. Vallerand, L.G. Pelletier
initiative is the first, and currently the only one of its kind,which makes college credit available at scale, worldwide. It also provides a pathway toadmission to the university for students who may not otherwise qualify. The MOOC explores theNational Academy of Engineering (NAE)’s Grand Challenges for Engineering and related globalchallenges. This course, based on an on-ground counterpart offered at ASU, is designed to alsohelp students develop the necessary interdisciplinary systems perspective and entrepreneurialmindset to solve the complex global challenges presented. This course fuses engineering with thesocial sciences, asking students to explore the interactions between society and technology,including the influences of human behavior
surveyed on their perception of the effectiveness of the CW. Cohort 1was polled as the course was ending while Cohorts 2 and 3 were emailed a survey link at thebeginning of the following semester. Cohort 1 had a 100% response rate with all 14 studentswhile Cohorts 2 and 3 were emailed a survey link that yielded 116 responses, 34% of theenrollment. Cohort 1 responded to a prompt that included all teaching exercises utilized by theinstructor while Cohorts 2 and 3 responded to the following prompt which asks about the CWspecifically. Tables 2 and 3 chart the breakdown of the responses. Table 2 is a reflection ofCohort 1’s response to the CW, specifically with a rating of 4.1/5.0. Cohorts 2 and 3 were notpolled separately and are shown combined in
Communication Program at the University ofWashington, including: Tina Loucks-Jaret, Lisa Owen, Kate Mobrand, Mary-Colleen Jenkins,Chris Wrenn, Tamara Neely, and Kevin Shi.References 1. Ambrose, S. A. (2013). Undergraduate engineering curriculum: The ultimate design challenge. The Bridge: Linking Engineering and Society, 43(2). 2. Ambrose, S. A., Bridges, M. W., DiPietro, M., Lovett, M. C., & Norman, M. K. (2010). How Learning Works. San Francisco, CA: Jossey-Bass. 3. Kaplan, M., Silver, N., LaVaque-Manty, D., & Meizlish, D. (Eds.). (2013). Using Metacognition and Reflection to Improve Student Learning. Sterling, VA: Stylus Publishing. 4. National Research Council (NRC). (2000). How People Learn: Brain, Mind
transition to independent research, Studies in Higher Education, 30:2, 137-154.[4] Gardner, S. K. (2010). Contrasting the socialization experiences of doctoral students in high- and low-completing departments: A qualitative analysis of disciplinary contexts at one institution. The Journal of Higher Education, 81(1), 61-81.[5] Gardner, S. K. (2008). “What's too much and what's too little?”: The process of becoming an independent researcher in doctoral education. The Journal of Higher Education, 79(3), 326-350.[6] Lovitts, B. E. (2008). The transition to independent research: Who makes it, who doesn't, and why. The journal of higher education, 79(3), 296-325.[7] A document preparation system. (n.d.). Retrieved
examine these changes on student performance as well, and a morein-depth analysis with an automated tool needs to be conducted on how student code quality isimpacted. Also, future studies could look at developing methods to better enforce code qualityand good style practices in short exercises. In addition, future studies should confirm the Bloom’sTaxonomy level of CS exercises before their use, and perhaps they should even aim to work withother instructors to create a bank of CS exercises and come to a consensus on how to map CStopics to BT.References [1] S. Zweben and B. Bizot. The taulbee survey. Computing Research Association, 2018. URL https://cra.org/resources/taulbee-survey/. [2] Vincenzo Del Fatto, Gabriella Dodero, Rosella Gennari
: Colleges Are Changing to Reach the Next Generation" The New York Times, https://www.nytimes.com/2018/08/02/education/learning/generationz-igen-students-colleges.html, Aug 2, 2018.[11] Freeman, S. and Eddy, S. and McDonough, M. and Smith, M. and Okoroafor, N. and Jordt, H. and Wenderoth, M. P. “Active learning boosts performance in STEM courses”, Proceedings of the National Academy of Sciences 111 (23) 8410-8415; DOI: 10.1073/pnas.131903011, June 2014.[12] Narasareddy, M. R. G. Walia, G. S. and Radermacher, A. D. “Gamification in Computer Science Education: a Systematic Literature Review”, https://www.asee.org/public/conferences/106/papers/22808/view 2018 ASEE Annual Conference & Exposition, June 24-27, 2018.[13] “Why
Society for Engineering Education, 2020 Educating Civil Engineering TechnologistsIntroduction Civil engineering work has evolved to encompass the distinctive roles and competencies of professional engineers, technologists and technicians. A civil engineering technologist is a specialist trained to work in one or more technical areas within the civil engineering field. Engineering technologists often work under professional engineers, yet they are expected to demonstrate competency for completion of independent activities within their particular area(s) of specialty. In many cases, civil engineering technologists acquire unique skills and knowledge that complement those of a professional engineer. In contrast, civil
easy to follow solution process, Meets including required diagrams and figures Minimum Competency Incorrect answer due to one or two minor II 80% errors but supported by a correct solution process as described in Level I Does Not Meet Minimum III 0% Incorrect answer due to conceptual error(s) CompetencyBecause no points are awarded for answers that are “conceptually wrong”, students do notreceive credit for memorizing and writing out the solution to a similar problem they have solved.Points are only given for correct answers with correct support
disciplinesincluding everyday life, not just mechanical engineering. Several temperature measurementsensors are introduced including, resistance temperature detectors (RTDs), thermistors, infraredtemperature sensors, thermocouples, and silicon bandgap sensors. Their application ranges,costs, accuracies and durability are discussed. This affords the students the opportunity todevelop a trade space analysis to select the appropriate sensor(s) for the experiments presented.Understanding trade space analyses generalize to other sensors and more globally for the studentto product design in real-world situations. The students select a minimum of two experimentspresented, each with a different sensor for the measurement of temperature.The learning objectives of this
, which constantly collect data s thestudent plays the game. At several points within the game, the system adjusts the content to fit thestudent’s areas of difficulty. The game also offers support or prompts to encourage progresswithin the game. While the overarching problem is the same for every student, the path they taketo reach the solution will vary drastically.The proposed PING system combines techniques of statistical inference, cognitive psychology,education research, sensor informatics, and machine learning techniques to provide students apersonalized education process. The contextual problem-solving situation engages students,giving them incentives to succeed in their learning process while allowing them to both beentertained and move
MATH 204 (Elementary Linear Algebra) EE111 (Circuit Analysis I) Textbook “Electric Circuits”, Nilsson J.W., Riedel S., Prentice Hall # of Credits 4 Schedules 10 weeks with 3 hours of lecture and 2 hours of lab per weekTable 3: Course Information of EE210 Circuit Analysis II Desire Learning Outcomes of EE210 Circuit Analysis II 1. Analyze RL, RC, and RLC switching circuits with DC sources 2. Understand and competent in analyzing simple AC circuits using complex numbers, reactance, impedance, and phasors. 3. Understand the concepts involved with power in AC circuits. 4. Be able to design and analyze AC RLC circuits. 5. Understand the concepts of frequency response
Paper ID #29558Analyzing the Effectiveness of Competition and Interdisciplinary Teamsin Student LearningCol. Aaron T. Hill Jr., United States Military Academy Colonel Aaron Hill is an Assistant Professor and Design Group Director in the Department of Civil & Mechanical Engineering at the United States Military Academy, West Point, New York. He holds a Bachelor of Science degree from West Point, a Master of Science degree in Engineering Management from Missouri S&T, a Master of Science degree in Civil Engineering from Virginia Tech, and a PhD in Civil Engineering from The University of Texas at Austin. Aaron has
=growth+mindset&ccag=growth+mindset&cckw=%2Bgrowth%20%2Bmindset&cccv=content+ad&gclid=Cj0KEQiAnvfDBRCXrabLl6-6t-0BEiQAW4SRUM7nekFnoTxc675qBMSJycFgwERohguZWVmNDcSUg5gaAk3I8P8HAQ [Access January 15, 2020].[3] USG Facts. https://www.usg.edu/news/usgfacts [Accessed January 15, 2020].[4] What is a Momentum Year? https://completega.org/sites/default/files/resources/Momentum_Year_Overview_2019.pdf [Accessed January 26, 2020].[5] B. L. Yoder, “Engineering by the Numbers” https://www.asee.org/papers-and-publications/publications/college-profiles/15EngineeringbytheNumbersPart1.pdf. [AccessedJanuary 15, 2020].[6] P. Meiksins, P. Layne, K. Beddoes, B. Acton, M. Lewis, M, A. S. Masters, and M.Roediger, “Women in Engineering: A Review of the