of some complexity, and case participants need todiscuss and come to some solution(s) or plan(s) for the case. Shapiro’s book [9] lists the basicprocess as: 1. Case learners prepare for the case by reading and analyzing it 2. Optionally - students can perform a deeper preparation by having a priori small group discussions 3. An in-class discussion is done for the case 4. An end-of-class summary is provided by the facilitatorAs there are many books on the case method, our approach uses ideas from Rosenthal andBrown’s book for examples of pedagogically strong cases [10], and Barnes, Christensen, andHansen’s book [11] on how to teach cases (readers should note that this book is not only good forlearning about the case method, but
was measured using a “catch and time” approach. A beaker was placed inthe lower reservoir to collect solution while a stopwatch was used to determine the time passed.Before each obstruction experiment, fluid volumes were collected over three time intervals: 5minutes, 4 minutes, and 3 minutes. Each volume was divided by its respective time to get anaverage fluid flow rate in mL/s. The lowest flow rate we used in our trials was 0.092 mL/s andthe highest was 0.262 mL/s. The apparatus is capable of sustaining higher flow rates, but theflows were turbulent. Velocity was measured by observing the distance a particle in the flowmoved between two sequential video frames, i.e. ∆t = 1/30 s = 0.033 s. Four trials were averagedto calculate the mean
. In supporting Paradiand Zhu14, Lau 12 discussed that based on DEA’ s simplicity of use and flexibility in datarequirement, it has become a popular tool 12. In his study, Mostafa 15 explained that the DEAtechnique is an adequate tool for benchmarking, since it allows the identification of a group ofefficient DMUs for each non-efficient one 15. Furthermore, Lee and Kim 16 mentioned that thegreatest merit of DEA is that it provides benchmarking guidelines for inefficient DMUs. For each 2 © American Society for Engineering Education, 2015 2015 ASEE Northeast Section Conferenceinefficient DMU
position using two threaded rods to provide stability III. S INGLE C ELL M ODELING , DYNAMICS AND C ONTROLand support. The actuator model used was the L12-I from This section presents the theoretical model of a single cellFrigelli with a 100 mm stroke. The Frigelli L12 actuators were that is operated by four actuators. The kinematic and dynamicchosen due to their low cost and relative high speed (23 mm/s), equations of both the surface and the object are derived. Basedallowing them to respond quickly to control the motion of the on the equations of motion of the object, a simple feedbackobject. Though these actuators have a reduced strength (43 control law is designed for moving the object at a
dt QS m RS W hRSW hZWV m INZ cPM, INZ tREL, INZ tREL, Z m INF DA MA cPM, OA tREL, OA tREL, Z DA MA (26)In contrast, the corresponding equation from EnergyPlus with the missing moisture-related termemphasized is reproduced next: d tREL, Z m DA MA Z c PM,Z
gap, this study aims to gain adeeper understanding of the faculty‟s experience with LTS. Herein, we present the thoroughdevelopment of the LTS Faculty Survey, designed with content and construct validationprocesses in mind and included quantitative and qualitative items, as well as key findings fromsurveyed LTS faculty experts (N=25). The survey enabled us to measure characteristics of LTScurricular and extracurricular efforts, perceived barriers faced by faculty, motivations forimplementing LTS efforts, attitudes about LTS, etc. all from a faculty perspective. Key findingssuggest that major barriers for LTS implementation are (1) faculty time/workload, (2) problemscoordinating with the community, and (3) the lack of policy on the role of LTS
. Raghavan serves as a Professor and Associate Dean of Research and Graduate Studies at Embry Rid- dle Aeronautical University. Her research interests are in the areas of Mechanics of aerospace structures and materials. She joined UCF in Fall 2008 after completing her doctoral studies at Purdue University, Indiana, School of Aeronautics and Astronautics in the area of Structures & Materials. She obtained her M.S., Aeronautical Engineering in Structures at ISAE-SUPAERO, Toulouse, France where she also worked with Messier Bugatti in Velizy, Paris (S-92 wheels and brakes testing). Prior to this, she com- pleted her B.Eng in Mechanical Engineering at Nanyang Technological University, Singapore. She has 7 years of
essential that this work is done intandem, as it would be unethical to recruit women into an environment that is known tosystemically disadvantage them. Though chemical engineering has made great strides in genderparity compared to other engineering disciplines, the results of this study reinforce the idea thatdiversity is not the same as equity.References [1] NSF. Bachelor’s degrees awarded to women, by field, citizenship, and race/ethnicity: Women, minorities, and persons with disabilities in science and engineering, 2008. [2] C. E. Brawner, S. M. Lord, and M. W. Ohland, Undergraduate women in chemical engineering: Exploring why they come. ASEE Conference Proceedings, 2011. [3] J. Trapani and K. Hale, “Higher education in science and
successes of the pilot and are ready to expand the program. We would like todouble the size of our cohort, increase the student financial support for participation and providemore dedicated mentoring for the students. Of the first two cohorts, 80% have remained in SpaceGrant for additional project experience, some moving into project leadership roles. COSGC staffcurrently run the program and mentor the student teams and projects. The plan for AY 23-24 isto expand this mentoring to include near peer mentors in the next cohort. We will also beimplementing a pre and post assessment of student STEM identity.REFERENCESAtkins, K., Dougan, B. M., Dromgold-Sermen, M. S., Potter, H., Sathy, V., & Panter, A. T. (2020). “Looking at Myself in the Future
to and survive in unwelcoming, toxic,and systemically oppressive computing environments, the aforementioned activities (and thoseof the greater Alliance) shift this focus to ensure that staff, educators, and administrators have thetools necessary to address and remove systemic barriers to student success in computing.References[1] S. Zweben and B. Bizot, “2020 Taulbee Survey,” 2020. [Online]. Available: https://cra.org/wp-content/uploads/2021/05/2020-CRA-Taulbee-Survey.pdf[2] M. Broussard, Artificial Unintelligence. The MIT Press, 2018. Accessed: Dec. 21, 2020. [Online]. Available: https://mitpress.mit.edu/books/artificial-unintelligence[3] R. Benjamin, Race After Technology: Abolitionist Tools for the New Jim Code, 1st edition
students' experience with the activities.4.5. Overall Insights of AWPThe benefits respondents listed from participating in the AWP focused on having a betterunderstanding of POGIL and more confidence in their ability to write and implement POGILin their classroom. They also appreciated getting feedback on their work and collaborating withothers in the same discipline. Specific comments included: I feel like I have a MUCH better understanding of what POGIL activities should look like and how to go about writing them. It was also great to have one fully completed POGIL activity and one that`s almost ready to be submitted. Collaborating with colleagues that are interested in the same discipline, and at times in the same
) only report result for the 'sweet-spot' factorsalong one or two dimensions (e.g., student educational history⸺ quizzes, assignment, andexams; demographic features⸺ sex, age, marital status, state) [1-2], (b) are carried out withdiverse and fragmented factors using dissimilar machine learners making their results difficult tocompare [3]. Towards this end, the paper exploits all the attributes (i.e., sixty-seven attributes)over ten dimensions (listed in Table 1) using five machine learning algorithms. The Objective ofthe work-in-progress (WIP) is two-fold: (i)To leverage machine learning to identify the factorsthat are the best predictor of an at-risk student(s) in a programming course and (ii) Compare theperformance of the machine learner(s
accepted responses forseveral weeks.Results and DiscussionImpacts of the AIChE Education Division’s VCP program on the delivery of chemicalengineering courses during the COVID-19 pandemic were wide-ranging. After a web-basedinterest form was circulated to attendees and other members of the AIChE community,respondents answered whether they would like to participate in a VCP, to identify course(s) theywere teaching, and to indicate their willingness and ability to lead/moderate a VCP. Within oneweek, 88 faculty members filled out the form, and the communities began to materialize. Thetotal number of interested participants continued to grow through the semester and into thefollowing semester. From March 2020 to December 2020, 191 participants from
passage throughan atmospheric pressure argon plasma, operated at 1 kW or less power. Specifically, irregularlyshaped particles of gamma-alumina with an average diameter of 11 mu m were converted to smaller(ca. 4 mu m) spherical particles primarily consisting of delta- and alpha- (corundum) phases. Alsonotable was the finding that modifications of the particles, such as changes in surface area, correlateto applied plasma energy. The plasma torch was operated with an argon flow rate of 5 slpm, powerof between 400 and 1000 W, and average particle residence time in the plasma of 0.1 s. IntroductionThere are many methods for producing nanoparticles including, lame reactors, pyrolysis reactors,evaporation and
3 3 -S U MAc ? 0 : / MAc / Ä L - 2 L Õ © PL ? 0 MAc ? / 5PL MAc ? 5PL S Å 3 Ö 2 EI 6 EI 6 EIBy rules 9 and 10 in Section II, the slope sA and the deflection yA at the free end A of the actual cbeam in Fig. 3 are, respectively, given by the “shearing force” VA and the “bending moment” cM A at the fixed end A of the conjugate beam in Fig. 4. We write PL2 3 sA ? VA c ? Acy ? yA ? MAc ? / 5PL 2 EI
highlyexpressive and widely used in formal verification tools such as the model checkers SPIN [8] andNuSMV [2] . LTL is also used in the runtime verification of Java programs [18]. Formulas in LTL are constructed from elementary propositions and the usual Boolean operatorsfor not, and, or, imply (¬, ∧, ∨, →, respectively). In addition, LTL provides the temporal operatorsnext (X), eventually ( ), always (✷), until, (U), weak until (W), and release (R). These formulasassume discrete time, i.e., states s = 0, 1, 2, . . . The meanings of the temporal operators arestraightforward1 • The formula Xp holds at state s if p holds at the next state s + 1, • p U q is true at state s, if there is a state s ≥ s at which q is true and, if s is such a state, then
. Fromabsorbance data, students can evaluate the effectiveness of removal of the contaminant underpredetermined conditions (i.e. contaminant concentration, water superficial velocity).The procedure for running the experiment is: (a) open a browser to the server’s IP address; (b)download the “Labview” runtime (automatically prompted for download and installed if it is notalready installed on the user’s computer); (c) rinse the contaminant from the media with a diluteacid solution (~10% HCl) for about 30 s by pushing the “acid rinse” pump toggle switch toinitiate the acid rinse, and pushing it again to stop; (d) flush the acid from the media by flowingclean rinse water (purified water) through the column for 2 min by using the “rinse water” pumptoggle
engineering students at the J.B. Speed Schoolof Engineering (SSoE) at the University of Louisville must take.The interest barrier, defined in this paper as “student beliefs related to the significance and/orusefulness of engineering”, inherently includes student perception(s) related to the level ofpleasure experienced in conducting engineering-related tasks or activities. Research has identifiedinterest as the most significant retention impediment for SSoE students; specifically, an increasein interest predicted which students remained in engineering. Yet the significance of the interestquestion extends well beyond SSoE to engineering programs all over the country.First-year engineering makerspace courses can have a positive impact on first-year
follow-on group. It would providevaluable experience to the students if more clients could be recruited from the community.AcknowledgementsThe authors would like to thank the following ME students who participated in this project: Arlint,A., Durbin, T., Hayes, T.S., Jefferson, S., Jewett, S., Maltbie, J., Mihalec, B., Milne, S., Richards,T., Ward, M., and Willard, J..References[1] R. H. Todd, S. P. Magleby, C. D. Sorensen, B. R. Swan, and D.K. Anthony. “A survey ofcapstone engineering courses in North American,” Journal of Engineering Education, vol. 84,pp.165-174, April 1995.[2] A. J. Dutson, R. H. Todd, S. P. Magleby, and C. D. Sorensen. “A review of literature onteaching engineering design through project-oriented capstone courses,” Journal
systems, conducting research inengineering education domains focused on interaction-dominant phenomena, and meeting critical datacollection and analysis needs, complex systems research can provide important insights for theengineering education community. ReferencesAnylogic (2016) Retrieved from: http://www.anylogic.com/Benson, L., Kirn, A., & Faber, C. (2013, June). CAREER: Student motivation and learning in engineering. In ASEE Annual Conference Proceedings.Berggren, K. F., Brodeur, D., Crawley, E. F., Ingemarsson, I., Litant, W. T., Malmqvist, J., & Östlund, S. (2003). CDIO: An international initiative for reforming engineering education. World Transactions on Engineering and
being measured. The EGCI aims to measureunderstanding in engineering graphics concepts; thus, unrelated constructs that should not beassociated with an EGCI construct should not have a significant correlation with performance onthe instrument. For examples, high performance on the EGCI should correlate with performancein solid modeling courses or other courses requiring an understanding of engineering graphicsconcepts such as machine design or production design, that require the creation or reading oftechnical drawings, but perhaps not with performance in history or philosophy classes for thesame participants. Works Cited[1] Sadowski, M., & Sorby, S. (2014). (2014). Defining concepts for an
. These figures show the comparison of the various parameterchanges with respect to the blade span at 5ms-1 Effect of Angle of Incidence variation on Effect of Angle of Incidence variation Tangential Force Coefficient CD on Drag force from baseline at 5m/s Normal Force Coefficient CN Lift force from baseline at 5m/s
continue to be refined as needed.AcknowledgementThis work presented in this manuscript is based upon work supported by the National ScienceFoundation under Grant DUE #1348547 and DUE #1348530. Any opinions, findings, andconclusions or recommendations expressed in this paper, however, are those of the authors anddo not necessarily reflect the views of the NSF.ReferencesBaker, R. S. J. D., Corbett, A. T., & Wagner, A. Z. (2006). Human Classification of Low-Fidelity Replays of Student Actions. Paper presented at the The Educational Data Mining Workshop at the 8th International Conference on Intelligent Tutoring Systems.Goldstein, M. H., Purzer, S., Adams, R. S., Xie, C. (2015). “High School Students’ Ability to Balance
can be seen that the input from the instructorshelped reshape the format of the workshop between the years but the same underlying principlesexisted: collaboration, interest in student understanding, and material development. With thesecore principles remaining the same across the workshops, we can then compare how theinstructors’ attitudes and beliefs changed throughout this timeframe.Theoretical FramingFor this research, the Concerns Based Adoption Model (CBAM) has been utilized to compareand contrast how the instructors’ beliefs and attitudes towards the innovation changed over time2.CBAM is a well-researched educational model created in the 1970’s ad 1980’s that helps depictthe change process in an educational setting. There are three
authors and do not necessarily reflect the views of the National ScienceFoundation.References1. Committee on Equal Opportunities in Science and Engineering, “Broadening participation in America’s STEM workforce: 2011–2012 biennial report to Congress,” National Science Foundation, Arlington, VA, 2014. Retrieved from https://www.nsf.gov/od/oia/activities/ceose/reports/Full_2011- 2012_CEOSE_Report_to_Congress_Final_03-04-2014.pdf2. S. Hurtado, K. Eagan, and M. Chang, “Degrees of success: Bachelor’s degree completion rates among initial STEM majors,” Higher Education Research Institute at UCLA, 2010.3. M. Ong, C. Wright, L. Espinosa, and G. Orfield, “Inside the double bind: A synthesis of empirical research on undergraduate and graduate
regular use of taxonomic language throughout thefull duration of the statics course will help with long-term retention of conceptual understandingto support procedural approaches to problems.The objective of the current work-in-progress is to present the early stages of development of theTOPS to a community of educators and researchers that can provide valuable feedback prior tothe tool being applied in the first phase of the aforementioned research design.References[1] R. Streveler, T. Litzinger, R. L. Miller, and P. S. Steif, “Learning conceptual knowledge in the engineering sciences: Overview and future research directions,” J. Eng. Educ., vol. 97, no. 3, pp. 279–294, 2008.[2] M. T. H. Chi, “Three types of conceptual change
relate to forces and creating free-body diagrams [6]. Moments (of a force)have also been identified as a particular area of confusion for students both because ofconflicting terminologies [3] and their role as “intermediate quantifier[s] of the rotational effectof interactions [between bodies]” [7]. That is, while the net force is the quantity proportional to amass’s translational acceleration, the moment is proportional to the mass’s angular acceleration.That moments build on the already difficult concept of force likely only complicates learning.This work in progress paper describes an early pilot of a study to investigate the process ofconceptual change related to moments in an engineering statics course. Preliminary results fromthe pilot
means and standard deviations of student work term performanceindicators. The results are communicated through Mean Standard DeviationMatrixes (MSDM’s) or Delta Mean Standard Deviation Matrixes (ÄMSDM’s).The problem of matching curricular content with industrial needs has been, bothnationally and internationally, approached on a variety of levels. Accountabilityconcerns have created a focus on practical learning outcomes deemed importantby industry. The Accreditation Board for Engineering and Technology (ABET)2000 Criteria, developed in the late 1990’s, strongly emphasize an understandingof market needs. Measurement, feedback and continuous improvement formcorner stones of the ABET 2000 philosophy. The thinking behind the criteria islargely
and that of the U. S. born population. These statistics point towards asignificant improvement made for the Hispanics during the past three decades. These gains havenot produced a notable convergence with the level of education in the native-born U. S.population due in part to marked improvements of education in U. S. that outpaced the progressof the immigrant’s. The number of high school educated Hispanic immigrants has doubled, andthe number with less than high school has decrease by one-half.1 These changes produced animproved educational profile of the entire adult Hispanic immigrant population.Statistics regarding Hispanics that attend schools in the U.S. have also improved. More than 80percent complete high school or college; that