Course", ASEE Annual Conference, Vancouver, BC, 2011.[4]. Bringle, R. G. and Hatcher, J. A., “A service-learning curriculum for faculty,” Michigan Journal of Community Service Learning, (pp. 112-122), 1995.[5]. Peterson, S. J. and Schaffer, M. J., “Service learning: A strategy to develop group collaboration and research skills,” Journal of Nursing Education, vol. 38, no. 5, (pp. 208-214), 1999.[6]. Celio, C. I., Durlak, J., and Dymnicki, A., “A meta-analysis of the impact of service-learning on students,” Journal of Experiential Education, vol. 34, no. 2, (pp. 164-181), 2011.[7]. Gray, M. J., Ondaatje, E. H., Fricker Jr., R. D. and Geschwind, S. A., “Assessing service learning: Results from as
United States according to the annual ASEE 2018 By the Numbersreport. We operationalized “students seeing ethics in a course” by looking at whether an electiveor required course mentioned in a program’s graduation requirements had the word ethics (or avariant) in either the course title or course description. We acknowledge two potential flaws interms of false positives and false negatives - just because a course has ethics somewhere in itsdescription or title does not necessarily send a strong signal about how that was translated intothe classroom (i.e., an instance of a false positive in the data). Likewise, a course description ortitle not having ethics in the title does not necessarily translate to students not learning aboutsome aspect(s
. References[1] K. Chandra and S. Tripathy, “RAMP 2018 Final Report,” Unpublished manuscript [Online]. Available: https://www.uml.edu/docs/RAMP2018-Final- Report_tcm18-309285.pdf[2] C. MacDonald, “Understanding participatory action research: A qualitative research methodology option,” Canadian Journal of Action Research, vol.13, no. 2, pp. 34-50, 2012.[3] A. McIntyre, Participatory Action Research, Qualitative Research Methods Series 52. Los Angeles: Sage Publications, 2008.[4] M.J. Amon, “Looking through the glass ceiling: A qualitative study of STEM women’s career narratives,” Frontiers in Psychology, vol. 8, no. 236, 2017 [Online]. Available: https://www.frontiersin.org/articles/10.3389/fpsyg
during the semester1. Setup: Identify the (1) assumed sample distribution, (2) the exact type of test being run, (3) the number of the ‘tails’ of that test, (4) the formula for your test statistic, (5) the statistical distribution we assume that the test statistic follows, and (6) the null and alternative hypothesis. Calculation: Calculate (1) the test statistic(s), (2) the p value(s), and (3) the effect size(s) or power(s) as appropriate. Interpretation: (1) state the formal result of your test using your hypotheses. (2) explain the result of your test in terms of what it means in the question context – and reference either the effect size or the power as appropriate. Figure 3 Example problem framing for a
Paper ID #28532Implementation of a laboratory experience in reinforced concrete coursesDr. Benjamin Z. Dymond, University of Minnesota Duluth Ben Dymond obtained his B.S. and M.S. degrees in Civil Engineering at Virginia Tech before obtaining his Ph.D. in Civil Engineering at the University of Minnesota Twin Cities. Ben is currently an assistant professor of structural engineering at the University of Minnesota Duluth.Dr. Matthew Swenty P.E., Virginia Military Institute Matthew (Matt) Swenty obtained his Bachelors and Masters degrees in Civil Engineering from Missouri S&T and then worked as a bridge designer at the
Engineering Education 2015 Annual Conference and Exhibition, Seattle, WA, June 14- 17, 2015.[5] R. L. Shapiro, E. O. Wisniewski, E. Kaeli, T. B. Cole, P. A. DiMilla, and R. Reisberg, “Role of gender and use of supplemental instruction in a required freshman chemistry course by engineering students on their course grades and subsequent academic success,” in Proceedings of the American Society for Engineering Education 2016 Annual Conference and Exhibition, New Orleans, LA, June 26-29 2016.[6] B. J. Priem, C. Ghio, H. Boyce, S. A. Morris, E. Kaeli, T. B. Cole, P. A. DiMilla, and R. Reisberg, “A longitudinal study of the effects of pre-college preparation and use of supplemental instruction during the first year on GPA and
vn ≈ vth = = 350 m s−1 (4) mArFor the electron density, we assumed the electrons to be an ideal gas at standard pressure and theaforementioned estimated temperature of 35 eV = 4.1 × 105 K. This corresponds to a numberdensity of 1.8 × 1022 m−3 . This was on a similar order of magnitude to electron densitiesdescribed in Goebel. 5The ionization rate could be determined only through empirical tables. We found one such tablepublished by Chung et al. 8 The closest temperature tabulated was 32 eV, with a correspondingionization rate of 3.112 × 10−14 m3 s−1 .With these values in place, the mean free path came out to λ = 630 nm. Given that this is muchsmaller than the
that 74% of students in L01 and 81%of students in L02/L03 participated in writing the makeup quizzes. Table 1: Quiz and Make Up Quiz Results for L01 (Mechanical Engineering Students) Quiz 1 Quiz 2 Quiz 3* Quiz 4 Quiz 5 Quiz 6 Kinematics Relative Kinetics Kinematic Kinetics Impulse and Subject Tested of Particles- motion of of s of rigid of rigid momentum Curvilinear particles particles bodies bodies Overall Class Average, First
require to be proficient intechnological literacy? That is a central issue of this discussion.As a matter of policy in the 1980’s governments seem to have taken the view that it is amatter of the economic good that students should study technology in schools [15], and by1992 a World Council of Associations for Technology Education had been founded. Theconference proceedings associated with the founding of this organization, had the title“Technological Literacy, Competence and Innovation in Human Resource Development”[16].Yet, in this extensive report there are only two papers that mention technological literacy[17; 18]. Both authors are American; one, Michael Dyrenfurth is a member of ASEE. Hisdefinition was,“Technological literacy is a concept
dark arts (of Cyberspace) universities are offering graduate degrees in cybersecurity,” IEEE Spectr., vol. 51, no. 6, pp. 26–26, Jun. 2014.[2] M. Lloyd, “Negative Unemployment: That Giant Sucking Sound In Security,” Forbes, 21- Mar-2017.[3] B. NeSmith, “The Cybersecurity Talent Gap Is An Industry Crisis,” Forbes, 09-Aug-2018.[4] A. Bicak, X. (Michelle) Liu, and D. Murphy, “Cybersecurity Curriculum Development: Introducing Specialties in a Graduate Program,” Inf. Syst. Educ. J., vol. 13, no. 3, p. 2015.[5] S. A. Kumar and S. Alampalayam, “Designing a graduate program in information security and analytics,” in Proceedings of the 15th Annual Conference on Information technology education - SIGITE ’14
team re-designed each of these three major coursedeliverables, with the goal of fostering an Entrepreneurial Mindset in students and leveragingsynergies between the Entrepreneurial Mindset and the existing goals of the course (engineeringdesign and technical communication). In particular, the faculty team created a new linkagebetween the research sequence and the humanities assignment. The new research sequence isbuilt around the U.N.’s Sustainable Development Goals; each student chooses one of the goals toexplore through their individual rhetorical analysis, annotated bibliography, and literaturereview. The humanities assignment is a team project in which students explore solutions tosustainability problems on the campus of Rowan University
problem solvers from poor ones by their awareness of which strategies theyhave used and their knowledge of where they are in their thinking relative to the final solution[18].Such criticisms have led some to back away from the “teaching problem solving” approachemerging from the 1970’s [19–21]. In fact, Schön went as far to argue that there is no such thingas problem solving in the engineering profession as “no engineer has ever been given a problemto solve.” Schön’s contention is the value of engineers’ work is not found in their problemsolving abilities. Rather, the essential facet of engineers’ work is found in their “problemsetting.” Engineers make sense of a given messy world from which many factors need to beconsidered, organized, and
herself, "This is really mentally affecting me." Erin noticed thetoll that graduate school had on her mental health and attributed this to the lack of preparationon the part of advisors and mentors. She stated, I had realized the mental and emotional toll that grad school was heaping on [me], honestly, unrealistic level[s] of expectations, the multiple projects, and the teaching, and still dealing with personal life, and all while being thrown in the deep end. No one actually ever teaches you how to do research. You just kind of sink or swim.Giselle’s increased mental distress led to her decision to take a leave of absence. She shared, I had to take a leave of absence, because I couldn't deal with it. I had to take a
] Criterion Description Amount of Mixing There should be nontrivial, meaningful mixing in a mixed methods publication, else the study would be better classified as multi-method. This criterion spotlights methodologists’ attention to integration in mixed methods research [see 1]. Interpretive Interpretive comprehensiveness refers to how the researcher(s) Comprehensiveness engage different perspectives in their study. This can be accomplished throughout the design by picking extreme or negative cases, testing competing hypotheses, and
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
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