water treatment courses. In this lab, students will have the opportunity to adjust different dosages of reagents and observe their effects on the clarity of water and the clumping of sediment. They can simulate a real water treatment process and observe how small particles gather into larger, heavier clusters that eventually precipitate solid impurities from the water. This experiment helps students understand the chemical reactions and operations involved in water purification and how to optimize water quality. b) Gas Transfer Lab: As shown on the right side of Figure 5, the Gas Transfer Lab is a highly interactive learning environment designed to teach students key knowledge
the following criteria: 1. an ability to perform project management tasks (based on the following deliverables): a. a back-of-the-envelope parametric/analogous estimate of scenic elements at a preliminary design presentation. b. a definitive cost estimate and time estimate for a fully-designed scenic element using prequalified construction techniques. c. a design/build plan based on a critical path analysis presented using a Gantt chart. d. a full set of construction drawings sufficient for a scenic shop to build with minimal additional input from the assistant technical director. e. an installation plan and a tear-down (“strike”) plan based on
, service-learning, and extension outreach to create a new model of community engaged scholarship at the University of Connecticut,” J. High. Educ. Outreach Engagem., vol. 25, no. 2, p. 17, 2021.[10] M. A. Boyer, “Global climate change and local action: understanding the Connecticut policy trajectory,” Int. Stud. Perspect., vol. 14, no. 1, pp. 79–107, Feb. 2013, doi: 10.1111/j.1528-3585.2012.00480.x.[11] B. Hyde and J. Barrett, “Municipal issues and needs for addressing climate adaptation in Connecticut,” University of Connecticut College of Agriculture, Health and Natural Resources, 2017. [Online]. Available: https://clear.uconn.edu/publications/[12] Kellogg Commission, “Returning to Our Roots: The Engaged Institution
negative direction, b (constructive), n and u (interactive).As noted, students’ answers given to questions 3u and 4u that refer to doing hands-on groupactivities during class (use equipment, material, sensors, etc.),” it seems to be a tendency to prefermore practical activities.Figure 7 shows items with significant differences between students’ perception of their actualclass before (blue dots) and after (orange dots) of the implementation of the didactic strategy forall four subdimension of the types of instruction, passive (blue bubble), active (orange bubble),interactive (yellow bubble), and constructive (green bubble). Arrows show positive shift (bluearrow pointing up) and negative shifts (orange arrows pointing down). ACTUAL | Pre
impacts in the capstone ProcessDesign course. It summarizes the technical content of the course based on the grass-root plantdesign for a mid-size commercial production of styrene. It is intended to exemplify the technicalskills covered in the course. It also describes some accompanying skills like teamwork andcommunication skills associated with the technical content. Then it introduces the approach forbroader impacts, mainly (a) a social impact report, where students examine societal impacts fortwo potential sites for the plant (one in the US, one in a foreign country of their choice), (b) aposter as a communication piece to introduce the project to a potential audience of thecommunity around a selected site for the plant, (c) an outreach
activities and projects to use in both formal and informaleducation. We also plan to include a mechanism for users to submit activities that will then bereviewed by experts using a standardized rubric before being added to the database. We havecreated and tested a pilot version of the review process and are currently working on developingthe database. REFERENCES[1] A.V. Feigenbaum, Total Quality Control. New York, NY: McGraw-Hill, 1961.[2] B. Boardman, Introduction to Industrial Engineering. Mavs Open Press, 2020. [E-book][3] P. Senge, The Fifth Discipline: The Art and Practice of the Learning Organization. London,England: Random House Books, 2006.[4] E. Dundon, The Seeds of Innovation. New York, NY: AMACOM
Conservation Lab Condition Assessment, which are essentially reports that explain the types of damage that could be seen in ranges of books (these sometimes also point out certain call numbers). However, the majority of time it will just be a range of books and you will have to pull what you think looks damaged within that range. 2. Types of damage you will see in the reports and what you are looking for i. Binding/Spine Damage 1. 2. 3.ii.Headcap Damage 1. 2.iii. Red Rot - https://en.wikipedia.org/wiki/Red_rot 1. 2.iv. Brittle Pages, Loose Pages, or Pages Falling Out 1. 2. b
Vanderbilt University.Dr. Kenneth W. Van Treuren, Baylor University KEN VAN TREUREN is a Professor in the Department of Mechanical Engineering at Baylor Univer- sity and serves as the Associate Dean in the School of Engineering and Computer Science. He received his B. S. in Aeronautical Engineering from the USAF Academy in 1977 and his M. S. in Engineering from Princeton University in 1978. He completed his DPhil in Engineering Sciences at the University of Oxford, United Kingdom in 1994. He then taught at the USAF Academy until his military retirement. At Baylor University since 1998, he teaches courses in fluid mechanics, energy systems, propulsion sys- tems, heat transfer, and aeronautics. Research interests include
Elements: A Systematic Literature Review,” 2022 International Congress on Human-Computer Interaction, Optimization and Robotic Applications (HORA), Ankara, Turkey, 2022, pp. 1-8, doi: 10.1109/HORA55278.2022.9799876.[5] Li, Tingting, and Zehui Zhan. 2022. ”A Systematic Review on Design Thinking Integrated Learning in K-12 Education” Applied Sciences 12, no. 16: 8077. https://doi.org/10.3390/app12168077[6] Sulastri, Ai, Badruzsaufari, B., Dharmono, D., Aufa, M. N., & Saputra, M. A. (2022). Development of Science Handouts Based on Critical Thinking Skills on the Topic of the Human Digestive System. Retrieved from https://dx.doi.org/10.29303/jppipa.v8i2.1156.
Paper ID #38612Board 249: Developing and Creating Affective Knowledge Spaces forTeachers as Advocates for Social JusticeMrs. Sabrina Lynette Strong-Nasabal, University of Illinois, Urbana-Champaign Sabrina Lynette Strong-Nasabal is a Ph.D. student in the Department of Education, Policy, Organization, and Leadership (EPOL). Her concentrations are Higher Education, also Social Science, and Education Policy. She has an M.S. in Academic Advising and a B.S in Interdisciplinary Studies with a concentration in Social Science. She is researching Black middle-class first and second-generation college students’ transitions and
processes and advanced materials (cokes, carbon fibers) from oil residues, and became a business leader for specialty products (lube oils, asphalts, waxes, cokes) at Petroleos de Venezuela, PDVSA (1983-1998). He is a founding member of Universidad Monteavila (Caracas, Venezuela) (1998—2018) and became the Chancellor of this university (2005-2015), and the President of the Center for Higher Studies (2015-2018), including teaching in the Humanities. After rejoining the University of Pittsburgh, he has been teaching Pillar courses on Reactive Process Engineering, Process Control, Process Control Lab, and Process Design. In addition to technical courses, his service extends over curriculum development, outreach programs
Sustainable Development (EESD15) Vancouver, B.C. Published in the UBC digitial repository cIRcle, 2015. [Online]. Available: https://circle.ubc.ca/ [Accessed 25 February 2023].[12] B. Lonergan, Topics in Education (Vol 10, Collected Works of Lonergan). R.M. Doran and F.E. Crowe, Eds., Toronto, ON: University of Toronto Press, 1993.[13] K. Galotti, Making Decisions That Matter: How People Face Important Life Choices. Mahweh, N.J.: Lawrence Erlbaum Associates, Publishers, 2002.[14] R. Keeney, Give Yourself a Nudge: Helping Smart People Make Smarter Personal and Business Decisions. Cambridge, UK: Cambridge University Press, 2020.[15] P. Freire, Pedagogy of the Oppressed. New York: Herder and Herder, 1970.[16] S. Turkle (Ed.), Falling
, Eds., Rotterdam: Sense Publishers, 2008, pp. 99–117; 288–291.[12] C. M. Cunningham, Engineering in elementary STEM education: Curriculum design, instruction, learning, and assessment. Teachers College Press, 2018.[13] L. Katehi, G. Pearson, and M. A. Feder, Eds., Engineering in K-12 education: Understanding the status and improving the prospects. Washington, DC: National Academies Press, 2009.[14] G. J. Kelly and P. Licona, “Epistemic practices and science education,” in History, Philosophy and Science Teaching, Springer, 2018, pp. 139–165.[15] B. Boyle, D. While, and T. Boyle, “A longitudinal study of teacher change: What makes professional development effective?,” Curric. J., vol. 15, no. 1, pp. 45–68, 2004.[16] L. B
Conference, 2012.[2] H. Carlone and A. Johnson, “Understanding the science experiences of successful women ofcolor: Science identity as an analytic lens,” Journal of Research in Science Teaching, vol. 44, no.8, pp. 1187– 1218, 2007.[3] M. M. Chemers, E. L. Zurbriggen, M. Syed, B. K. Goza, S. Bearman, “The role of efficacyand identity in science career commitment among underrepresented minority students,” Journalof Social Issues, vol. 67, no. 3, pp. 469-491, 2011.[4] K. Rainey, M. Dancy, R. Mickelson, E. Stearns, and S. Moller, “Race and gender differencesin how sense of belonging influences decisions to major in STEM,” International Journal ofSTEM Education, vol. 5, no. 10, 2018.[5] D. L. DeNeui, “An investigation of first-year college students
responded to the modified Rydell-Rosen Ambiguity Tolerance survey(RRAT) (Appendix A, [21]). Of the 154 respondents, 116 were freshman while 38 weregraduating seniors. The survey has 20 true/false items. The Godwin [22] Engineering Identity(EI) (Appendix B) survey was also administered to the students. The EI survey which measuresthe responses on a 5-point Likert scale (Strongly Agree (SA) =5; Agree (A) = 4; Neutral (N) = 3;Disagree (D) = 2, and Strongly Disagree (SD) = 1) has 11 items that measure three dimensionsnamely, Acceptance (3 items), Interest (3 items), and Competence (5 items). A total of 292freshmen and 35 graduating seniors responded to the EI survey. The data was collected usingGoogle forms. The surveys were administered to freshmen at
the letter grade to a numeric value. Table 6: Grade from letter to numeric value Letter Grade Integer value A 95 A- 90 B+ 87 B 83 B- 80 C+ 77 C 73 C- 70 D+ 67 D 63 D- 60 F 50 2. Numbers of hours that the student spent on each course subject. In figure 2, input 7 through 12 represents the number of hours of each of the six courses. 3. General Education Course survey results will be collected by using table 1. In figure 2
, and a published author. He is a former McNair Scholar, National Academies of Sciences, Engineering, & Medicine-Ford Foundation Fellow, Herman B. Wells Graduate Fellow, Inter- national Counseling Psychologist, former Assistant Professor at the University of Kentucky, and current Post-Doctoral Research Scholar at the University of Pittsburgh. Dr. Z.’s research program focuses on examining the impact of intersectional oppression on historically excluded groups & creating culturally relevant interventions to enhance their well-being. Within this framework, he studies academic persis- tence and mental wellness to promote holistic healing among BIPOC. He earned Bachelor’s degrees in Psychology &
university studies or International profile in unemployment income degree degree education experience social media Group margin TG margin TG margin TG margin TG margin TG margin TG margin TGMale#Finnish 0.504 A 5041 4.218 AB 4.773 AB 3.279 A 3.679 A 2.057 AMale#Other 0.731 AB 4368 A 4.765 C 4.525 A 3.965 BC 4.500 B 2.979 BFemale#Finnish 0.800 AB 4585 A 4.113 A 5.046 B 3.613 AB 3.663 A 2.109 AFemale#Other 1.027 B 3912 4.659 BC 4.799 AB 4.299 C 4.483 B 3.031 BMargins denote the marginal linear predictions based on the respective variance analysis; margins sharing a letter in theTukey group (TG) label are not significantly
. Since then, there have beennumerous adapted definitions proposed and used by various researchers and educators [1]. Thedefinition used in this paper was proposed by Bringle, et al. in 2006: Service learning is a credit-bearing educational experience in which students (a) participate in an organized service activity that meets identified community needs and (b) reflect on the service activity in such a way as to gain further understanding of course content, a broader appreciation of the discipline, and an enhanced sense of personal values and civic responsibilityThis definition of service learning works well for engineering classes because it explicitlydescribes the goal of students both identifying and working
discussed above, a selection of B, C, and D motors were tested as possiblecandidates. After testing in the field, the Estes C5 motor was determined to be the best fit for thecourse. This was mainly due to its unique thrust curve (Figure 4).The thrust curve in Figure 4 displays a graph of thrust vs time. To overcome the limitations of aheavy rocket takeoff, we looked for engines with a high thrust in the beginning that would ensurea safe takeoff (if the rocket comes off the rail slowly, it is unstable). What also needs to beconsidered is the delay charge (time between thrust and parachute deployment). Afterconsidering the range of payload mass for the rocket, the optimal delay charge for all rockets wasthe best at around 3 seconds, therefore we use
%, Pell enrollment ~50% of the total enrollment. Based on a total enrollment of about 1500 students per class. * African American average GPA gap is significantly higher than URM, typically 0.3-0.85, and enrollment is about 5% of the total. A 0.4 gap in GPA separates ‘B+’ and ‘A-’ grades, for example. Data provided by the California State University Student Success Dashboard [30]To overcome the GPA gap and the DFW disparities, we plan to redesign six critical-path, largeenrollment courses ENGR1 Introduction to Engineering, ENGR17 Introductory Circuit Analysis,EEE117 Network Analysis, EEE108 Electronics I, EEE161 Applied Electromagnetics, andEEE180 Signals & Systems, based on active
link. This Qualtricslink included the details of the study and requested their voluntary consent to a) use their coursework (quiz responses, feedback responses, and assignments/ discussions for analysis and b)complete a 20–25-minute student engagement and satisfaction survey, including demographicdetails. Finally, c) this link asked the students if they would participate in a 20–30-minute focusgroup session. Only those who agreed to participate were included in the data. Of the 363students registered in the Fall 2022 cohort, 99 students started the online survey, and 39 studentscompleted the survey.Students (n=34) who showed interest were invited via email to participate in a 15–20-minute in-person or virtual focus group with 2-5 peers. The
analyzed using the Student Responses for their top 3 ranked projects. For thisevaluation, effort was measure through a combination of: a) The RAL of all Student Responses for the respective year. b) The EKC between each Student Response and the Engineering Keywords from each respective slide from the project pitch activity. c) Whether they mentioned or not any qualification for joining the ranked project.Each effort element was analyzed independently, then aggregated for an overall analysis.RQ2: What type of project features have the most impact on students when ranking projects?For this question, Student Responses are analyzed to determine the frequency with whichstudents mention features that attracted them to the projects. The
programimplementation and a lack appropriate facilities to support the “problem-based” curriculum(Reid & Feldhaus, 2007; Shields, 2007). This study goes beyond the qualitative findings anduses a quantitative approach to determine key predictors of adoption with the goal of identifyingresources to better support implementation efforts. Theoretical FrameworkDiffusion of Innovation (DOI) Theory purports that novel ideas are spread through socialnetworks through a process that involves (a) awareness of the need for a novel approach toaddress an issue, problem, or situation, (b) a decision by individuals to adopt the novel idea, (c)the testing of the idea in relation to one’s own particular circumstance, and (d) the continued
-that-wont-be-automated (accessed Jan 1, 2022).[15] J. Meister. "How companies are using VR to develop employees’ soft skills." Harvard Business Review. https://hbr.org/2021/01/how-companies-are-usingvr-to-develop- employees-soft-skills (accessed Jan 1, 2022).[16] J. Dixon, C. Belnap, C. Albrecht, and K. Lee, "The importance of soft skills," Corporate finance review, vol. 14, no. 6, p. 35, 2010.[17] M. L. Matteson, L. Anderson, and C. Boyden, "Soft skills": A phrase in search of meaning," portal: Libraries and the Academy, vol. 16, no. 1, pp. 71-88, 2016.[18] B. Schulz, "The importance of soft skills: Education beyond academic knowledge," 2008.[19] M. Wats and R. K. Wats, "Developing soft skills in
measured by Spearman’s coefficients (Knapp 2018). When engineeringidentity was cast through a multi-dimensional lens, it revealed more nuanced connections withteamwork experience. For example, “contributing to the team’s work” (behavior metric 1, B.1)tended to boost virtually all dimensions of engineering identity, but it exerted the strongestconnection with the performance/competence dimension of engineering identity (P.1 through P.3in Table A.1). A similar theme also emerged from qualitative analysis of interview transcripts:several students professed that when they were able to apply themselves in teamwork they feltthat their EI grew as a result and that when they were unable to contribute their EI took a hit andfor two female students it
,” The Student Public Interest Research Groups (Student PIRGs), 2016. [Online]. Available: https://pirg.org/resources/covering-the-cost/[3] N. B. Colvard, C. E. Watson, and H. Park, “The Impact of Open Educational Resources on Various Student Success Metrics,” Int. J. Teach. Learn. High. Educ., vol. 30, no. 2, pp. 262–276, 2018.[4] J. J. Jenkins, L. A. Sánchez, M. A. K. Schraedley, J. Hannans, N. Navick, and J. Young, “Textbook Broke: Textbook Affordability as a Social Justice Issue,” J. Interact. Media Educ., vol. 2020, no. 1, p. 3, May 2020, doi: 10.5334/jime.549.[5] J. Hilton III, “Open educational resources and college textbook choices: a review of research on efficacy and perceptions,” Educ. Technol. Res. Dev., vol. 64, no
andassessments.References[1] J. L. Segil, J. F. Sullivan, B. A. Myers, D. T. Reamon, and M. H. Forbes, “Analysis of multi-modal spatial visualization workshop intervention across gender, nationality, and other engineering student demographics,” in 2016 IEEE Frontiers in Education Conference (FIE), Erie, PA, USA: IEEE, Oct. 2016, pp. 1–5. doi: 10.1109/FIE.2016.7757525.[2] S. A. Sorby, “Developing 3D spatial skills for engineering students,” Australas. J. Eng. Educ., vol. 13, no. 1, pp. 1–11, Jan. 2007, doi: 10.1080/22054952.2007.11463998.[3] R. Gorska, S. A. Sorby, and C. Leopold, “Gender differences in visualization skills - An international perspective,” Eng. Des. Graph. J., vol. 62, no. 3, 1998.[4] R. Wodak and M. Meyer
Paper ID #37512Board 133: The Design, Implementation, and Lessons Learned of anAtmospheric Water Generator DeviceDr. Karim Altaii, James Madison University Dr. Altaii holds a Ph.D. in mechanical engineering, and received his doctorate from The City Univer- sity of New York. He is a professor in the College of Integrated Science and Engineering (CISE) at James Madison University. He is a registered Professional Engineer and holds five patents in solar energy applications and irrigation system. He is the director of CISE Energy and Environmental Projects- an international summer program in Costa Rica. He is the Director of
Entrepreneurial Mindset Acquired through Curricular and Extra-curricular Components,” in Proceedings of 126th ASEE Annual Conference & Exposition, Tampa, lorida, June 2019. Available: https://peer.asee.org/319056. S. Purzer, N. Fila, and L. Nataraja, “Evaluation of Current Assessment Methods in Engineering Entrepreneurship Education,” Adv. Eng. Educ. vol. 6, no. 1, pp. 1-27, 2016. Available: http://advances.asee.org/wp-content/uploads/vol05/issue01/Papers/AEE-17-E- ship-Purzer.pdf7. J.B. Du Prel, B. Röhrig and M. Blettner, “Choosing Statistical Tests: Part 12 of a Series on Evaluation of Scientific Publications,” Dtsch Arztebl Int. vol. 107(19), pp. 343-348, May 2010, ePub. May 2014, doi: 10.3238/arztebl.2010.0343.8. G.M