follow-ups tracking record through Early Warning System 9 Help session Face-to-face office hours Virtual office through web conferencing, weekly Q&A forums 10 Orientation First day face-to-face lecture “Welcome! Start here” folder on the homepage (including instructor’s greetings and introduction to the course, course walk-through video, introductory activity, syllabus quiz ) Table 1. Path
, T(r | p) T(p | p) for all r p andT(r* | p) T(p | p) when r* = p. [1-4] Many strictly proper scoring rules have been developed.Three of the most popular are given below.Quadratic (Q): Qi (r ) 2 ri r r [1,1] (2)Spherical (S): Si (r) ri / (r r)1/2 [0,1] (3)Logarithmic (L): L i (r ) ln( ri ) ( ,0] (4)The range of possible scores differs considerably. For example, logarithmic scoring holds thepossibility of an infinitely negative score. While this may seem like a defect, we will argue thatthis feature is a benefit of log scoring. Any linear
analytical and experimental studies that incorporate statistical, computer, and other appropriate techniques. (b), (e), (k), (m), (o)4. The ability to communicate effectively for presentation and persuasion using oral, written, and electronic media. (g), (p), (q)5. The ability to organize, lead, coordinate, and participate in industrial engineering and multi-disciplinary teams. (d), (l), (n)6. An appreciation of the humanities, social sciences, and contemporary issues for the general education of the individual and as resources for engineering studies and professional behavior. (h), (j)7. An appreciation of the ethical and professional responsibilities of Industrial Engineers and the benefits of a
-Library of ISU. This indirect and Internet-based approach ofproviding information to the students created a situation where students were encouraged towork together to interpret the various memos, and sort and differentiate the necessaryinformation from other irrelevant and something less than clear information. In addition tothe project package, an optimization (LINGO) tutorial session as well as two Q&A sessionswere provided to help students comprehend and conduct their project better. We note that LINGO is mathematical programming software used to solve the project Page 22.1003.6problem [10]. Specifically, students formulated and solved a
. Harold A. Linstone, Decision Making for Technology Executives: Using Multiple Perspectives to Improve Per- formance, Boston and London: Artech House Publishers, 1999.8. The Massachusetts Institute of Technology (http://esd.mit.edu/); also, refer to SEAri (http://seari.mit.edu/)and LAI (http://seari.mit.edu/): http://search.mit.edu/search?q=case+studies&btnG=go&site=mit&client=mit&proxystylesheet=mit&output=x ml_no_dtd&as_dt=i&as_sitesearch=esd.mit.edu&ie=UTF- 8&ip=127.0.0.1&access=p&sort=date:D:L:d1&entqr=3&entsp=0&oe=UTF-8&ud=1&is_secure=.9. The Massachusetts Institute of Technology (http://sdm.mit.edu/): http://search.mit.edu/search?site=sdm&
starts with the multidimensional definition of quality, Q ? f (Q1 ,..., Q n ) with the nelements that correspond to those factors and features that relate to how the products aredesigned, developed, produced, and used by customers. Functions involving design, production,and service have differing effects among the n dimensions, producing large impact on some andvery little on others. This of course will depend on the particular type of product. The nature ofthe dimensions makes it difficult to establish an overall simple measure of the state of quality,with some dimensions being quantitative while others are very subjective. Warranty feedback, W ? h ] g1 (Q1 ,..., Q n ),..., g m (Q1 ,..., Q n )_ does however, provide an overall weighting of
Training Notes (rough)Q&P Logistics: 1. Classroom a. Review slides up to roles b. Have students review roles, select roles, mind quantities of each role c. GTA provide assigned roles on printed form from data spreadsheets d. Students work on pre-lab to finish off Classroom session, instructional team answers questions, complete pre-lab by beginning of Q&P Lab session, must use Classroom Q&P slides to answer questions 2. Before Lab a. Students finish pre-lab by beginning of Q&P Lab session (continued) b. Setup lab with initial layout (provided below) (see setup qty’s in doc) c. Have each station primed and ready to go with one of each variety
activitiesAdaptations were made for class activities such as in-class exercises and group discussions. Fourparticipants stated that they initially had Q&A time for in-class exercises, but these activitieswere discontinued because of the lack of feedback or inconvenience of communicating to bothvirtual and in-person students. For similar reasons, two participants canceled group discussionsessions for their courses.Two participants tried using the Zoom breakout room function for group discussion. Two otherparticipants mentioned using polls to help engage students. Also, two other participantsmentioned using more help from teaching assistants to moderate virtual discussions.3.2.6. Adaptations made for examsExams were held online for the hybrid classes and
providevaluable guidelines for ISE departments that allow better understanding of Generation Zstudents' needs for eLearning acceptance.References:[1] M. Zalaznick, “What Do Students Think of Online Learning?” University BusinessMagazine, June 18, 2020. [Online]. Available:https://universitybusiness.com/onlineLearning-survey-classes-degrees-generation-z-in-person-wily-regenerations/. [Accessed October 6, 2021].[2] World Health Organization (WHO), “Coronavirus,” World Health Organization, 2020.[Online]. Available: https://www.who.int/emergencies/diseases/novel-coronavirus-2019,https://www.who.int/news-room/q-a-detail/q-a-coronaviruses. [Accessed January 23, 2021].[3] Centers for Disease Control and Prevention (CDC), “Coronavirus Disease2019 (COVID-19
, IdealFirstly, descriptive statistics was performed to have an interpretation if there was a gapbetween expectations and perceptions. To determine the significance in differences wasused Mann Whitney test was used (Normality Test was used, but every Q had a non-normaldistribution). In Tangibles dimension, Q2 (Sequence on topics) and Q5 (Topics and RealExamples – Study Cases) as a significant difference between perception and expectation Page 26.1312.7(P100points willTedious be Course selected. TheseComfortprojects are in the “Projects with more weight” column, and
ofthe case study, students delved into the “central limit theorem”, which is a key concept in thecourse. The students are expected to visualize the central limit theorem for the given data. Thisalso motivates them to explore graphical tools in Python in order to produce various plots fromthe data, such as Q-Q plots. In addition, students got to practice with cumulative distributionfunctions and understand the concept more in depth. The case study was designed such thatstudents were required to revisit the majority of the probabilistic concepts (e.g. conditionalprobability, integration technique) and apply them at the same time in a different, realisticcontext. This case study also went one step further, and the students were introduced with
gc 2 gc 2Establish SP1 on the upstream surface of the water and SP2 on the downstream surface. There isno heat added between the SPs, therefore Q 12 0 . The temperature of the water does notchange appreciably, so the internal energy (u) does not change, nor does the specific volume ofthe water (v). The pressure on both free surfaces is atmospheric pressure. Therefore the changein u (u) and flow work (pv) each cancel. Establish the reference elevation at the downstreamsurface (SP2). Therefore z2 = 0. There is a downstream velocity. Convert the 10 mph to 14.67ft/sec. Eliminating terms that either cancel or are negligible results in the following: gz V2 2
, pp. 34–50, 2019, doi: 10.1080/19378629.2019.1567521.[5] T. Brown and B. Kats, Change by design: how design thinking transforms organizations and inspires innovation. Harper Collins Pusblishers, 2009.[6] ISO, “ISO 6385:2016(en) Ergonomics principles in the design of work systems,” 2016. [Online]. Available: https://www.iso.org/obp/ui/#iso:std:iso:6385:ed-3:v1:en.[7] O. Crosby, “Usability engineer,” Occup. Outlook Q., vol. 44.4, no. 202, pp. 48–49, 2000.[8] ABET, “Criteria for Accrediting Engineering Programs 2020-2021.” https://www.abet.org/accreditation/accreditation-criteria/criteria-for-accrediting- engineering-programs-2020-2021/.[9] J. Rubin and D. Chisnell, Handbook of usability testing [electronic
.” www.iienet.org/public/articles/index.cfm?Cat=1492, 2005. Page 11.267.109. Kiattikomol, Kraiwood. “South-East Asia Centre for Engineering and Technology Education (SEACETE).” Global J. of Engineering Education. 8(1), 2004.10. Leinonen, Tatu, Esa Jutila, and Ismo Tenhunen. “On the Requirements of Industry in Mechanical Engineering Education.” Global J. of Engineering Education. 1(1), 1997.11. Nguyen, Duyen Q., and Zenon J. Pudlowski. “Should standardization or diversity be embraced in the development of future engineering education curricula?” World Transactions on Engineering and Technology Education 2(1), 2003.12. Noor
. No time for Q&A Student dresses 1 Dress was Dress was Dress was casual. Dress was Not appropriately. appropriate for acceptable for very casual. done. technical technical presentation. presentation. Confidence was weak. Exuded Confidence was
, 2006.10. R.R. Thomas, Beyond Race and Gender: Unleashing the Power of Your Total Work Force by Managing Diversity, American Management Association, 1991.11. Stanford Graduate School of Business, Diversity and work group performance, 1999. Accessed January 1, 2018, http://www.gsb.stanford.edu/news/research/diversity-work-group- performance.12. J. Surowiecki, The Wisdom of Crowds, Anchor, 2005.13. R Core Team, R: A language and environment for statistical computing, R Foundation for Statistical Computing, Vienna, Austria, 2018.14. Q. McNemar, “Note on the sampling error of the difference between correlated proportions or percentages,” Psychometrika, 12(2), 153-157, 1947.15. H.B. Mann and D.R. Whitney, “On a Test of Whether one of Two
correctly and lacked questions.questions & confidently. confidence.comments. No time for Q&AThe student 1 The dress was The dress was The dress was casual. Dress was Notdresses appropriate for acceptable for very casual. done.appropriately. technical technical
results from the in-videoquizzes. This study will provide evidence on the impact that short-length videos have on learningoutcomes based on whether students engage with the videos on-schedule or if they wait untilreviewing for the final exam. Table 1 shows the video lengths for all videos in the study. Theinstructors worked to make sure the sum of the short-length videos in a given section was similarto the video lengths of the medium-length videos from the semester before. A few timediscrepancies exist due to variance in re-recording the lectures. Videos containing a quiz have a Qin the label (e.g. 7.2Q).Table 1: Number of videos, video length, and defined label for each video chapter (Q next to the videos’ label show
for both the firm and society. Managerial economics, on its own, helps toclarify the vital roles firms play in society, and to identify methods of improving their operationsfor society’s benefits. Page 12.909.5The firm’s production function specifies the maximum output forthcoming from specified inputcombinations. In a simplified model, we utilized a version of the production function found ineconomics texts, where the firm employed only two inputs: labor and capital. This is referred toas the Cobb-Douglas production function. The function is given by the expression:Q = A Kα Lβwhere Q = Rate of Output K = Quantity of Capital L
’ 4’s and separated by a space or hyphen. Letters should be grouped together rather than interspersed. Bold printing & high contrast should be used B, D, I, O, Q, and Z and numbers 0, 1, and 8 should be avoided Label Research Label Research Research Recommendation: Arial or Verdana Font Sans Serif (Arial or Verdana) Student survey Student survey suggests Arial Bold 51 students surveyed
) conducted an Australian national study to examine the genericattributes of graduates of Australian undergraduate degree programs with majors in InformationSystems. Wright, Cushman, and Nicholson (2002) investigated the desired attributes of graduatesfrom apparel design programs using Q-methodology. They also examined the disparity ofthoughts between the faculty and industry professionals.Several variations of the Delphi technique are found in the literature. It is reported that it is verydifficult for the respondents to rank the questionnaire items when the number of them is quitelarge10. For this study, the respondents were asked to rate rather than rank the questionnaireitems. A few researchers developed the Delphi technique by sending the second
this ‘cycle’ in other ASEE publications. Page 25.221.9APPENDIX B : Sample Spreadsheet for Collecting Data STUDENT # X T Q M RUBRIC: FLUID MECHANICS RUBRIC BASED ON THE PRINCIPLES OF CRITICAL THINKING RUBRIC COURTESY OF W. S. U. WASHINGTON STATE UNIVERSITY PULLMAN, WA. 99164. LIKERT SCALE WEIGHT DISTRIBUTION : 5 4 3 2 1 1 Break down all barriers. √ 2 Create consistency of purpose with a plan. √ 3 Adopt the new philosophy of quality. √ 4 Establish high Standards. √ 5 Establish Targets / Goals
: Buros Institute of Mental Measurements, University of Nebraska.12. Kauffmann, Paul, Tarek Abdel-Salam, and John Garner. “Predictors of Success in the First Two Years- A Tool for Retention.” Proceedings of the American Society of Engineering Education Annual Conference, Honolulu, June 2007.13. Goldberg, L. R. “The Structure of Phenotypic Personality Traits.” American Psychologist, 48, 1993, pp., 26- 34.14. Srivastava, S. (2006). “Measuring the Big Five Personality Factors.” Retrieved December 15, 2007 from http://www.uoregon.edu/~sanjay/bigfive.html.15. McCrae, R. R., Costa, P. T., & Busch, C. M. (1986). Evaluating comprehensiveness in personality systems: the California Q-set and the five-factor mode
Confident Confident ConfidentSample Operations Survey Questions ∧ ∧ ∧Q-1 I can generate forecasts and use them in Yes …… 1 2 3 4 5 6 7 8 9 10 production planning. NoQ-6 I understand the relationship between MRP and Yes …… 1 2 3 4 5 6 7 8 9 10 ERP systems. No I can provide examples of how production Yes …… 1 2 3 4 5 6 7 8 9 10Q-10 planning and control decisions are linked to No accounting/finance.Sample Technology Survey QuestionsQ-1 I can navigate around
Women and Minorities in College Science and Engineering Education. Educ. Stat. Q. 2, 59–60 (2000).8. Kokkelenberg, E. C. & Sinha, E. Who succeeds in STEM studies? An analysis of Binghamton University undergraduate students. Econ. Educ. Rev. 29, 935–946 (2010).9. Geisinger, B. N. & Raman, D. R. Why They Leave: Understanding Student Attrition from Engineering Majors. This Artic. is from Int. J. Eng. Educ. 29, 1–12 (2013).10. Jensen, L. & Konradsen, F. A review of the use of virtual reality head-mounted displays in education and training. Educ. Inf. Technol. (2018). doi:10.1007/s10639-017-9676-011. Freina, L. & Ott, M. A literature review on immersive virtual reality in education: state of the art
Libraries’ Efforts in Inclusion and Outreach Activities Using Social Media,” LIBRI, vol. 65, no. 1, pp. 34–47, 2015.[11] B. M. Moskal, C. Skokan, L. Kosbar, A. Dean, C. Westland, H. Barker, Q. N. Nguyen, and J. Tafoya, “K-12 Outreach: Identifying the Broader Impacts of Four Outreach Projects,” Journal of Engineering Education, vol. 96, no. 3, pp. 173–189, 2007.[12] M. Borrego, “Development of engineering education as a rigorous discipline: A study of the publication patterns of four coalitions,” Journal of Engineering Education, vol. 96, no. 1, pp. 5–18, 2007.[13] E. Specking and R. Almaian, “An Analytic Hierarchy Process Approach to Engineering Outreach Decisions,” in IIE Annual Conference. Proceedings, 2013, p. 1078.[14] S. H
internet," Production and Operations Management, vol. 9, pp. 31-39, 2000.[42] A. Oroojlooyjadid, M. Nazari, L. Snyder, and M. Takáč, "A Deep Q-Network for the Beer Game: A Reinforcement Learning Algorithm to Solve Inventory Optimization Problems," arXiv preprint arXiv:1708.05924, 2017.[43] S. K. Chaharsooghi, J. Heydari, and S. H. Zegordi, "A reinforcement learning model for supply chain ordering management: An application to the beer game," Decision Support Systems, vol. 45, pp. 949-959, 2008.[44] O. Analytics, "5 Reasons We Created the Opex Analytics Beer Game," in Opex-Analytics, ed: @opexanalytics, 2019.[45] L. Bosman and S. Fernhaber, "Applying Authentic Learning through Cultivation of the
metacognition in natural settings. Proc. - Front. Educ. Conf. FIE 730–732 (2013). doi:10.1109/FIE.2013.668492231. Walther, J., Sochacka, N. W. & Kellam, N. N. Quality in interpretive engineering education research: Reflections on an example study. J. Eng. Educ. 102, 626–659 (2013).32. Bloom, B. S. et al. Taxonomy of educational objectives: The classification of educational goals: Handbook I, cognitive domain. New York 16, 207 (David McKay Company, 1956).33. Owens, R. J. Q. & Pauk, W. How to Study in College. (Cengage Learning, 2013).34. Bean, C. H. The Curve of Forgetting. (Press of the New era printing Company, 1912).35. Finkenbinder, E. O. The Curve of Forgetting. Am. J. Psychol. 24, 8–32 (1913).36. Latham, G. P
answer categories below, which arevisualized in Figure 10: 1. More forms of active feedback or direct contact between client and project teams, 2. More definition and data prioritization at the beginning of the project, 3. Client involvement in project team formation, and 4. No change needed.Over half of the responses made it clear that more consistent communication and more optionsfor communication between the project team and the client were desired. One student suggested,“Offer maybe a Q&A conference call once a month or every other week to begin the project andoffer that human interaction to help reduce any confusion with people. I felt like some of theanswers given in the email didn't always get answered right away.”Figure
]. Leone, C. M., and Richards, M. H., (1989), “Classwork and homework in early adolescence - the ecology of achievement,” Journal of Youth and Adolescence, 18 (6), 531-548.[18]. Lin, R., Biswas, P., Bachnak, R. A., Chappa, E-L., Goonatilake, R., and Ni, Q., “Creating Virtual Teaching Assistants to Improve Mathematics, Engineering, and Physics Curriculums