byexplaining that, “if I get something wrong when I’m taking the quiz, I think there’s somethingwrong with the quiz or the rubric.” This participant is not reflecting on the results of the trainingin a way that will improve consistency. They perceive training as being quizzed to prove abilityrather than the calibration process it is intended to be.Implications and Recommendations Each of the themes identified in the previous section indicate potential root causes forinconsistencies in grader interpretations, decisions, and behaviors. While some of these issueshave been identified previously in the literature, these findings present a few new ideas andprovide additional nuance to refine or extend upon old ideas. Notably, these findings
movement and stopping of two LEGO robot cars (local and express).The colored paper pieces help identify the locations where the robots stop temporarily.Throughout the two lessons, the following general assumptions are made: (i) the robots are well-designed and the programs are accurate; (ii) the students possess basic skills to operate the LEGOrobots, e.g., commanding the robots by pressing buttons; (iii) the students are able to use theactivity sheets and the selected activities truly reflect the lesson topics; (iv) the students areinterested to perform hands-on activities in teams; (v) the lesson topics and the activities align withthe CCSSM and the NGSS; etc.Statistics of the teachers and students who participated in the robotics-focused
Associate Vice Provost for Graduate Education.Dr. Helen L. Chen, Stanford University Helen L. Chen is a research scientist in the Designing Education Lab in the Department of Mechanical Engineering and the Director of ePortfolio Initiatives in the Office of the Registrar at Stanford Univer- sity. Chen earned her undergraduate degree from UCLA and her Ph.D. in Communication with a minor in Psychology from Stanford University. Her current research interests include: 1) engineering and en- trepreneurship education; 2) the pedagogy of ePortfolios and reflective practice in higher education; and 3) redesigning the traditional academic transcript. c American Society for Engineering Education, 2017
through, for example, iterative revision, peer response and reflection, to be continually ready to learn to learn how and to teach each otherRather quickly it became clear that to be able to realize these needs, we needed to create a newMAE communications curriculum and design a research program for assessment. This newcurriculum and the adjoining research program is known as the MAE/ECP EngineeringCommunications Initiative.There are three key components to the initiative: 1. Creating a pilot partner course, ENGRC 2250, Communication for Mechanical Engineering Design at the sophomore level to be taught in conjunction with MAE 2250, Mechanical Synthesis. 2. Coordinating and supporting through teaching partnerships communication
, the VIP Program is intended forstudents of sophomore rank and above. Freshmen who participate are exceptions to the rule, who oftenhave related experience and high motivation. The higher means reflect these traits. If the programactively recruited freshmen, the mean would likely approach that of or be lower than the sophomoremean.Analysis of variance on giving help also showed statistical significance for the number of semestersstudents were in VIP, with groupings of one, two, and three or more semesters. However, VIP experienceis related to academic rank, as both increase over time. The correlation is not one-to-one, because studentscan begin VIP at any academic rank, but they are related. This can be seen by visually mapping upperoutliers
necessarily reflect the views of theNational Science Foundation or the US Department of Education.REFERENCES1. NSF, Division of Science Resources Statistics. 2017. Women, Minorities, and Persons with Disabilities in Science and Engineering. Available at https://www.nsf.gov/statistics/2017/nsf17310/.2. National Center for Education Statistics, Digest for Education Statistics, Available at https://nces.ed.gov/programs/digest/d16/tables/dt16_219.70.asp.3. Joint Venture Silicon Valley (2012). The 2012 Index of Silicon Valley p. 36, Available at http://www.jointventure.org/images/stories/pdf/2012index-r2.pdf.4. NSF, Division of Science Resources Statistics. 2017. Women, Minorities, and Persons with Disabilities in Science and Engineering
thedata collection and analysis process, with coding in cycles and frequent reflection as described inthe following sections. Cycle 1: Initial read-through with attribute coding. Silverman (1993) assertedsuperior qualitative research must draw interpretations and remain consistent with the dataIMPACT MENTORING PROGRAM 12collected. Therefore, an initial read-through of the transcripts was independently conducted usingthe basic deductive concepts of thematic content analysis to develop attribute codes. This processallowed for detection and identification of factors that potentially influenced any issuesgenerated by the participants that aligned to the conceptual
technological literacy. 12.Tobias, Sheila Comment on John Heywood’s paper: Technological literacy and for whom?13.Trevelyan, James and Bill Williams. Literacies of entrepreneurship and value creation. 14 –16.Cheville, Alan. Technological literacy without proficiency is not possible. 17 – 18.Krupczak, John. Unfinished business for the ASEE TelPhe Division and other engineeringeducators 19.Siller, Tom. The purpose of technological and engineering literacy. 20 – 21.Mina, Mani. Why and for whom as historical reflection. 22 – 23.Drew, David. E. Moving the needle from literacy to knowledge. 24 – 25.Sychov, Sergev. V. Technological literacy and global society. 26.[2] K. Richmond Culture and General Education. A Survey. London. Methuen, 1963[3] B. Hirsch
‘Technique’. Ball equated engineering design with Bloom’s synthesis. The workingparty also found that the sub-abilities did not necessarily apply to the category they had beendesignated when attempts were made to utilize Bloom. To be fair, the authors of the Taxonomyunderstood that their categories would not fit every subject. Moreover, when considered from theperspective of the process of engineering they were not hierarchically ordered.Eventually the working party took the view that for each major component or domain objectiveof the examination a particular type of assessment would be necessary. Because the examinationincorporated a number of different objectives it was originally called a multiple objectiveexamination. This also reflected the
Puerto Rico and the U.S. VirginIslands reflect an increase in sea level of about 0.08 inches (2.0 mm) per year for the period 1962–2017 for Puerto Rico and for 1975–2017 for the U.S. Virgin Islands. The bottom panels show acloser look at more recent trends from 2000 to 2017 that measure a rise in sea level of about 0.24inches (6.0 mm) per year. Projections of sea level rise are shown under three different scenarios ofIntermediate-Low (1–2 feet), Intermediate (3–4 feet), and Extreme (9–11 feet) sea level rise. Thescenarios depict the range of future sea level rise based on factors such as global greenhouse gasemissions and the loss of glaciers and ice sheets. Sources: NOAA NCEI and CICS-NC.There are significant multi hazard challenges to the
conclusions or recommendations expressed in thismaterial are those of the author(s) and do not necessarily reflect the views of the NationalScience Foundation. We would like to acknowledge the family who participated in the study. References[1] Farenga, P. (1999). John Holt and the Origins of Contemporary Homeschooling. Paths of Learning: Options for Families & Communities, 1, 8–13.[2] U. S. Department of Education. (2014, October 5). Statistics About Non-Public Education in the United States [Information Analyses]. http://www2.ed.gov/about/offices/list/oii/nonpublic/statistics.html - homeschl[3] Wing J. M., “Computational Thinking,” Commun. Assoc. Comput. Mach., 2006.[4] Cuny, J
discussed how the semester was progressing, any areas of struggle, andgoal setting. A number of students described that having a peer mentor was helpful. As onestudent commented, “it was comforting to know someone was looking out for us,” and anothercommented, “[as a STEM transfer student] the mentor knows exactly what we are going throughand can give suggestions from [the mentor’s] perspective.” Several students also described thebenefit of goal setting and having the opportunity to reflect on these goals. Other students foundthe peer mentoring less useful during year two, because they already felt successful in theircoursework, and had already identified their goals. Because these meetings could occur throughe-mail, most students did not find
response of “5” meant “stronglyagree.” Due to the topics changing from year to year, only selected statements are used in thispaper. It should also be noted that wording was changed from 2017 to 2018, with input from theSTEM Librarian, to better reflect what was trying to be assessed. For comparison purposes,Table 3 uses a coded statement, and shows the exact wording that was used for both years. Tosee the entirety of the surveys for both 2017 and 2018, see Appendix C.1 and C.2.Table 3. The coded statements used for comparisons, and the corresponding statements used inthe 2017 and 2018 surveys. Coded Statement 2017 Statement 2018 Statement Soft Skills - Soft skills are an important aspect Soft
, theinability to speak a foreign language doesn’t prevent someone from being accepted into orrising through the ranks of the U.S. Foreign Service or the military” [14]. If L2 proficiency isnot required for promotion where it is critically needed –the U.S. Foreign Service and themilitary– it is understandable that the perception of lack of importance is widespread in theU.S. what in turn explains the shortage in such qualification among the general population. Interestingly, there is some ideological pressure to comply with the idea that theknowledge of an L2 is somewhat valuable or, more plausible, that denying the value of L2 competence reflects negatively on the respondent. That explains why 50% of Eddy’s [10] sample disagreed or strongly
) 0, (𝑏)The compatibility score for one team is calculated as a weighted sum of each of the attributescores and the schedule score. As previously described, each attribute score ranges between 0and 1, and the schedule score ranges roughly between 0 and 1. These values are multiplied by theinstructor’s chosen weighting factors in order to reflect their relative importance. Onto thiscompatibility score is added any prevented teammates penalty, required teammates penalty,and/or gender isolation penalty. This final sum is then normalized in order to give a score thatlies generally within the range 0 to 100. A team score can go outside this range only bybecoming negative because one or more of the penalties applies, or by going over 100
skills related to mathematical modelcomplexity, modifiability, and reusability dimensions. This research will build upon this idea byfurther analyzing impact of the revised modeling language in more courses and covering moretypes of modeling, including physical and business models.AcknowledgementsThis work was made possible by a collaborative research grant from the National ScienceFoundation (DUE 1827392; DUE 1827600; DUE 1827406). Any opinions, findings, andconclusions or recommendations expressed in this material are those of the author and do notnecessarily reflect the views of the National Science Foundation.References[1] A. R. Carberry and A. F. McKenna, "Exploring student conceptions of modeling and modeling uses in engineering
al., 2015). Yet, about 500,000computing positions remain vacant in the US ("The state of K-12 computer science", 2016), andmany nations need more computer scientists. Therefore, the underrepresentation of women incomputer science is an important topic that has begun to garner university program’s attention.This shortage of computer scientists has prompted the computing community and educationresearchers to be more reflective about current practices in order to try to attract and retain morestudents, especially women, to keep pace with industry demands. As such, researchers haveexplored various engagement strategies in the field of computer science. One of the strategies withincreased attention in the last two decades is the idea of
, this individual goes on to say that they could not be as lenient for programs that “havethose absolute course requirements,” such as engineering.As a result, much effort is directed toward ensuring student veterans are aware of transferpolicies and receive course credit, if possible, for work completed elsewhere. Some universitystaff spend a great deal of time negotiating and advocating for student veterans to receivetransfer credit. However, several interviewees indicated that the transfer evaluation process hasmany shortcomings. The IAs expressed that the process is “tricky” “frustrating” and “somethingthat could be improved across the board.” This was particularly the case for engineering.In reflecting on challenges that student veterans
Workshop. Parallel tracks continuedthroughout the day. Members of the Program Committee who served as the Track Chairs alsodesignated two breakout sessions from each track so that elements of the White Paper receivedsufficient time to be emphasized. The day ended with a tour of new active learning spaceinfrastructures and facilities that could support various aspects of DMTL. Tuesday’s sessionsbegan with a keynote address followed by a track debrief by each track chair to the entireworkshop. The workshop breakout sessions commenced after a Reflection Debrief havingemphasis on trends and progress made and areas to focus the remaining time to maximize theparticipants work together. After parallel tracks concluded, there was the formation of
andgraduate work. High level skills in scientific and academic argument and analysis requirestudents to make inferences from their data, relate their data to previously published results, anduse their data in order to justify their conclusions.5 Since lab reports typically require tasks suchas statistical data analysis, graphical presentation of results, and uncertainty analysis, theybecome an excellent medium to assess the development of these high level skills.A variety of methods have been employed to teach writing skills and related data analysis skills.The Science Writing Heuristic6 is a method of guided inquiry that leads students to reflect onwhat they are learning and ask a series of standard questions about their data and observations.This
, but technicalcourses should also present a discussion of how that technical content aligns with and integrates into theengineering design process. Additionally, the students should be given opportunities to practiceintegrating the design considerations of each area into a design context. This might be done through ahands-on project or through reflective design portfolios. 14Conclusions/Future WorkThroughout the conceptual design process, many constructs of coordination of knowledge about adesign are apparent. First, the tasks set forth by textbooks of aerospace design align with a high-leveltask and subtask structure. It’s also noted that each task has a goal or expected outcome. For
the micro- and nanoscales; and must know how to conceive, design, and operate engineering systems of great complexity. They must also work within a framework of sustainable development, be creative and innovative, understand business and organizations, and be prepared to live and work as global citizens. That is a tall order…”Engineering education has progressed with the introduction of different active learningpedagogies over the years, including project-based learning, problem-based learning, service-learning, and peer-led team learning. However, students are still mostly trained to solve welldefined problems which do not reflect the complexities of real-world problems.10 We proposethat translational research can
, adjustments were made to the questionnaires and later to the learningoutcomes to reflect the content of each camp theme..The structure and basic nature of the questions used in our questionnaires were initially based onour learning outcomes, feedback offered by our experts, and the research literature. Prior to the2013 camp, initial (pre-) and concluding (post-) questionnaires were piloted among a focus groupof five youths representing the age range of camp participants. The two goals of this focus groupwere to ensure that questions were not too easy or too challenging for the intended age group andto determine whether the students understood what was being asked of them. The focus grouprevealed valuable information regarding survey instructions
regular progress/status reports; schedules Plan/Manual 29 user manual or training manual; business plan; manufacturing plan General 17 varies; client determined deliverables; many deliverables; the usual Student peer evaluations; ethics assignments; individual reflections; classAccountability 16 attendance and participation Final report Interim reports Final recommendation Patent disclosure Conference or journal paper 0 50 100 150 200 250
data. Ideas or phenomena were first identified and flagged to generate alisting of internally consistent, discrete categories (open coding), followed by fractured andreassembled (axial coding) of categories by making connections between categories andsubcategories to reflect emerging themes and patterns. Categories were integrated to formgrounded theory (selective coding), to clarify concepts and to allow for interview interpretations,conclusions and taxonomy development. Frequency distribution of the coded and categorizeddata were obtained using a computerized qualitative analytical tool, Hyperrresearch® version3.5.2. The intent of this intensive qualitative analysis was to identify patterns, make comparisons,and contrast one transcript of