Paper ID #13665Integrating biofuels education into chemical engineering curriculumDr. Q. Peter He, Tuskegee University Dr. Q. Peter He is Associate Professor in the Department of Chemical Engineering at Tuskegee University. He obtained his BS degree in chemical engineering from Tsinghua University, Beijing, China, in 1996 and MS and PhD degrees in chemical engineering in 2002 and 2005 from the University of Texas, Austin. Besides engineering education, he is also interested in process modeling, monitoring, optimization and control; renewable energy; biostatistics and cancer informatics. He has published over 30 journal
Paper ID #8706Building Capacity for Preparing Teacher-Engineers for 21st Century Engi-neeringDr. Elsa Q. Villa, University of Texas, El Paso Elsa Q. Villa, Ph.D., is a research assistant professor at The University of Texas at El Paso (UTEP) in the College of Engineering and is Co-Director of the Center for Research in Engineering and Technology Education (CREaTE). Dr. Villa received her doctoral degree in curriculum and instruction from New Mexico State University; she received a Master of Science degree in Computer Science and a Master of Arts in Education from UTEP. She has led and co-led numerous grants from
topics revolving around game-based training and Virtual Reality (VR) applications. Fields of expertise and study are game development and algorithms, cutMr. Nicholas WallaDr. Chenn Q. Zhou, Purdue University Northwest Dr. Chenn Zhou is the founding Director of the Center for Innovation through Visualization and Simula- tion (CIVS), established in 2009, and the Steel Manufacturing Simulation and Visualization Consortium (SMSVC), established in 2006. She is the Professor of Mechanical Engineering at Purdue University Northwest, and also Professor by Courtesy at Purdue University West Lafayette. Dr. Zhou received her B.S. and M.S. degrees in power engineering from Nanjing University of Aeronautics and Astronautics, China
systems, computer science, and applied mathematics.Mr. John Moreland, Purdue University Northwest John Moreland is Senior Research Scientist at the Center for Innovation through Visualization and Sim- ulation at Purdue University Northwest. He has over 50 technical publications in the areas of simulation and visualization for education and design.Prof. Chenn Q. Zhou, CIVS, Purdue University Northwest Dr. Chenn Zhou is the founding Director of the Steel Manufacturing Simulation (SMSVC) and Visualiza- tion Consortium and the Center for Innovation through Visualization and Simulation (CIVS), Professor of Mechanical Engineering at Purdue University Northwest, and Professor by Courtesy at Purdue University West
Paper ID #17064Evaluating the Usefulness of Virtual 3-D Lab Modules Developed for a Flood-ing System in Student LearningDr. Chandramouli Viswanathan Chandramouli, Purdue University, Calumet (Engineering) Dr. Chandra has more than 20 years of teaching and research experience in Civil Engineering - Hydrology and Water Resources division. His research area includes water resources systems analysis, flood, drought and water quality modeling. He uses artificial intelligence techniques in his research.Dr. Emily HixonDr. Chenn Q. Zhou, Purdue University, Calumet (Engineering)John Moreland, Purdue University Northwest John Moreland
have time to answer them all. I was wondering maybe we should have had a shorter presentation and longer Q & A section. I'm not sure if the students would have enjoyed and learned more with a longer Q & A section. I think if we were given some more time, we could have had the kids do an activity relating to engineering, which could be beneficial. (Note: this comment referred to the amount of time at the school) A similar activity, but with local high schoolers, would be a good opportunity to use more interesting/complex experiments.These and other comments show that the REU students not only enjoyed the experience, butwalked away from the outreach activity seeing benefits to both the K-5
windows are available to a given user at a single time,allowing an individual to analyze multiple features of submitted data simultaneously.As previously noted in the Related Work section of this paper, if a resource were to behaveunresponsively, the system scheduler would purge the task on the resource, providing an errormessage for user guidance (alongside additional messages if a GRC file were to fail atcompile-time, runtime, etc.) and enabling re-submission to an alternate resource. (a) Three-channel time sink I/Q data - GRC (b) Three-channel time sink I/Q data - Our system
questions.Qualitative Data & ResultsPhase 1: Open-ended QuestionnairesPhase 1 of the qualitative data collection consisted of open-ended questionnaires that weredistributed at seven regional EWB-USA conferences in the fall of 2011. Participants were askedto answer the following questions in a corresponding colored box on a piece of paper shown inFigure 2: Q.1. How do you describe yourself? Q.2. How do you describe an engineer? Q.3. How do you describe an EWB-USA member? Q.4. What do you think an engineer needs to know? Q.5. What, if any, are the gaps in your engineering education? Q.6. What are your biggest gains from your experience with EWB-USA?Of the 505 respondents who answered these questions and
,teachers reported that their students returned the equipment in good condition. Second, theexpanded resource library addressing common challenges will provide additional support forstudents who take part in the sensor immersion unit in their classrooms. These resources mayenable them to more successfully and independently tackle difficulties that arise during theirinvestigations. Lastly, developing shared norms around small group communication remainsrelevant no matter the context. Regardless of whether instruction takes place remotely or inperson, student discourse is a critical element of the sensor immersion unit and teachers nowhave a wider variety of tools and skills to promote student-student conversations.References1. Biddy, Q., Gendreau
. Wigfield, “MOTIVATIONAL BELIEFS,VALUES, AND GOALS,” 2002.[12] J. S. Eccles, A. Wigfield, and U. Schiefele, “Motivation to succeed,” in Handbook of child psychology: Social, emotional, and personality development., Vol. 3, 5th ed., N. Eisenberg, Ed. Hoboken, NJ: John Wiley & Sons Inc, 1998, pp. 1017–1095.[13] Jacquelynne S. Eccles, “GENDER ROLES AND WOMEN’S ACH IEVEMENT- RELATED DECISIONS,” Psychol. ofWmn Q., vol. 11, pp. 135–172, 1987.[14] G. Hofstede, Cultures and organizations: Software of the mind. 1991.[15] R. L. Kajfez, M. J. Mohammadi-Aragh, A. Clark, S. Sassi, and J. Petrie, “Board 29: Initial Qualitative Exploration into First-Year Engineering Community and Identity,” in 2019 ASEE Annual
Engineering and Computing Diversity (CoNECD),[3] J. Miller, Engineering Manhood: Race and the Antebellum Virginia Military Institute. Lever Press, 2020.[4] D. A. Chen, J. A. Mejia, and S. Breslin, “Navigating equity work in engineering: contradicting messages encountered by minority faculty,” Digital Creativity, vol. 30, no. 4, pp. 329–344, Oct. 2019.[5] D. R. Simmons and S. M. Lord, “Removing invisible barriers and changing mindsets to improve and diversify pathways in engineering,” Adv. Eng. Educ., 2019, Available: http://files.eric.ed.gov/fulltext/EJ1220293.pdf. [Accessed: Jul. 01, 2021][6] P. Freire, Pedagogy of the oppressed. Routledge, 1973.[7] R. Q. Shin et al., “The development and validation of the Contemporary
learning goal/outcome. There were two versions of interviewquestions, faculty version and student version, trying to explore the same topics. The interviewquestions only varied slightly, asking both the faculty and the student to reflect on the expectedstudent experience. Each interview lasted approximately fifty minutes. And an emergingthematic analysis will inform other prongs of the research. Example interview questions arelisted below in Tables 1 and 2.Table 1: Example interview questions in Area 1: Classroom Experience Q: Can you tell me your perceptions about students’ expected learning experiences through the curriculum? Walk me through the classes students take? (faculty) (probe) What knowledge and skills are they
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
faculty and • Four participants requested more time for graduate student facilitators for facilitator-led times to work through examples as a Q&A on complex topics cohort during the exit interview. • “Unexpected personal development learning by interaction with individuals and groups in this type of setting are what I look forward to in this type of “Peer-to-Peer Support” professional development environment.” (Week 3) Participants will benefit from • “Have one day a week where the class eats lunch additional time for socializing together provided by the program
, North Dakota State UniversityDr. Peng Zeng, Auburn University Department of Mathematics and Statistics, Auburn UniversityDr. Bo LiuDr. Peter He, Auburn University Dr. Q. Peter He is Associate Professor in the Department of Chemical Engineering at Auburn University. He obtained his BS degree in chemical engineering from Tsinghua University, Beijing, China, in 1996 and MS and PhD degrees in chemical engineering in 2002 and 2005 from the University of Texas, Austin. Besides engineering education, his current research interests are in the area of systems engineering en- hanced data analytics with applications in manufacturing, renewable energy, food-energy-water nexus, and broad area of disease detection/diagnosis and
presented at 2015 ASEE Annual Conference & Exposition, Seattle, Washington. 10.18260/p.2421614. Ciston, S., & Carnasciali, M., & Zelenak, V., & Hollis, M. J. (2012, June), Adult Undergraduate Engineering Student Experience Paper presented at 2012 ASEE Annual Conference & Exposition, San Antonio, Texas. https://peer.asee.org/2089615. Mikel, T. K., & Hoang, F., & Kim, P. S. H., & Carnasciali, M., & Ciston, S. (2016, June), What Does It Mean to Be an Engineer? A Comparison of Adult Students at Three Institutions Paper presented at 2016 ASEE Annual Conference & Exposition, New Orleans, Louisiana. 10.18260/p.2719216. Hoang, Frank Q., Tressa Kay Mikel, Emi Okada, Pedro Sung Hoe Kim, Audrianna
. Journal of Science Education and Technology, 18, 163-172.[45] Concannon, J. P., & Barrow, L. H. (2012). A reanalysis of engineering majors' self-efficacy beliefs. Journal of Science Education and Technology, 21, 742-753.[46] McWhirter, E. H., Hackett, G., & Bandalos, D. L. (1998). A causal model of the educational plans and career expectations of Mexican American high school girls. Journal of Counseling Psychology, 45(2), 166- 181.[47] Dika, S. L., Pando, M. A., Tempest, B. Q. (2014). Pre-college interactions, early expectations, and perceived barriers: Are there differences for underrepresented engineering students? Proceedings of the 2014 American Society of Engineering Education conference
hydrogels for oral drug delivery. For this experiment, studentsprepare pH-responsive hydrogels based on p(MMA-EG) and characterize the network structureof the swollen hydrogel through mesh size modeling in different pH environments. Students canoptimize the hydrogel for oral drug delivery by varying its structure. They identify importantdesign variables, practice translating quantitative laboratory measurements into data used indesign evaluation, and learn aspects of polymer characterization, which can be applied to otherareas of material science and engineering.Mesh size is determined from correlations using existing tensile and experimental density data tocharacterize how the gels respond to pH variations.The swelling ratio, Q is found from
Proceedings of the 18th international conference on computers in education. 2010.2. Kulman, R., T. Slobuski, and R. Seitsinger. Teaching 21st century, executive-functioning, and creativity skills with popular video games and apps. in Learning, Education and Games. 2014. ETC Press.3. Wang, Q. and M. Abbas. Using Game Engines for Designing Traffic Control Educational Games. in Intelligent Transportation Systems (ITSC), 2015 IEEE 18th International Conference on. 2015. IEEE.4. Qichao Wang, M.A., Lisa McNair. A Knowledge-Delivery Gravity Model to Improve Game-Aided Pedagogy. in ASEE Conference. 2015.5. Wang, Q. and M. Abbas. Using a Novel Gravity Model for Ranking and Assessment of Educational Games. in 2016
the current state (e.g., output 0 for state A) and the next state based on the current state andvalue of the input (e.g., the top row of the next state is 01 for state A).The tabular representation is then translated into a set of Boolean expressions (see diagram 3 inFigure 2) that determines how the state transitions and outputs are implemented. Assuming thatD-type flip-flops are used in the circuit, the next-state encoding and the D input of the flip-flopsare equivalent, so D is often used in place of Q+ in these equations. Boolean expressions can besimplified to minimize the number of operators in the expression using a variety of techniques.Finally, the Boolean expressions are used to construct a schematic for the sequential circuit
Dame, A. Holmes forusing it in ECE 2630 at the University of Virginia, and T. Frank and B. Matar for using it in EEE202 at Glendale and Chandler-Gilbert Community Colleges. We thank Daniel Sayre of JohnWiley & Sons, Inc. for his support of the project.References1 K. VanLehn, “The relative effectiveness of human tutoring, intelligent tutoring systems, and other tutoringsystems,” Educat. Psychologist 46, 197 (2011).2 B. J. Skromme, C. D. Whitlatch, Q. Wang, P. M. Rayes, A. Barrus, J. M. Quick, R. K. Atkinson, and T. Frank,“Teaching linear circuit analysis techniques with computers,” in Proceedings of the 2013 American Society forEngineering Education Annual Conference & Exposition (Amer. Soc. Engrg. Educat., Washington, D.C., 2013), p
, Association for Computational Linguistics, Nov. 2020.[14] J. Wei, X. Wang, D. Schuurmans, M. Bosma, B. Ichter, F. Xia, E. Chi, Q. Le, and D. Zhou, “Chain-of-Thought Prompting Elicits Reasoning in Large Language Models,” Jan. 2023. arXiv:2201.11903 [cs].[15] K. Bhatia, A. Narayan, C. De Sa, and C. R´e, “TART: A plug-and-play Transformer module for task-agnostic reasoning,” June 2023. arXiv:2306.07536 [cs].[16] S. Huang, L. Dong, W. Wang, Y. Hao, S. Singhal, S. Ma, T. Lv, L. Cui, O. K. Mohammed, B. Patra, Q. Liu, K. Aggarwal, Z. Chi, J. Bjorck, V. Chaudhary, S. Som, X. Song, and F. Wei, “Language Is Not All You Need: Aligning Perception with Language Models,” Mar. 2023. arXiv:2302.14045 [cs].[17] J. Wei, M. Bosma, V. Y. Zhao, K. Guu, A
under grants EEC#1929484 and #1929478. Any opinions, findings, and conclusions or recommendationsexpressed in this material are those of the author and do not necessarily reflect the views of theNational Science Foundation.References[1] R. L. Spitzer, K. Kroenke, J. B. Williams, and P. H. Q. P. C. S. Group, “Validation and utility of a self-report version of PRIME-MD: the PHQ primary care study,” Jama, vol. 282, no. 18, pp. 1737–1744, 1999.[2] R. P. Cameron and D. Gusman, “The primary care PTSD screen (PC-PTSD): development and operating characteristics,” Primary Care Psychiatry, vol. 9, no. 1, pp. 9–14, 2003.[3] D. Van Dam, T. Ehring, E. Vedel, and P. M. G. Emmelkamp, “Validation of the Primary Care Posttraumatic Stress Disorder
pre-program to prepare the participants for the summer program. In thefirst year, the RET participants learned more about faculty mentors in the pre-program throughtheir bios, project descriptions, short video introductions, and more. We also hosted a virtualmeet-the-mentors session, where RET participants met with the mentors virtually, learned moreabout their research, and discussed potential project ideas. In the second year, based on the first-year evaluation feedback, we changed the pre-program to information Q&A sessions where theteachers learn about the program requirements, ask questions and share concerns, while theprogram team also learns more about the teachers, their subject areas, and their goals for theprogram.Summer Program
. ✆✮✯ ✰✱✲✳ ✴✵✶✷✸✹ ✰✱✲✳ ❀✆❁❁ ✺ ✰✱✲❄ ✴✵✶✷✸✹ ✺ ✺✻✼✽✳✾✿✱ ✻✼✽❂✾❃✱ ✻✼✽✳✾✿✱ ❅❆✴ ❇ ❈✆❉❊❊✵✺❋✆✵●❍❉■❏❍ ❇ ❇ ❇ ❅❉❑✆✸❏❍❉ ❅❆✴ ❇ ▲✷✹ ▲✶❊✹✶✆▼▼✷✸✹ ❇ ◆✆❖✆ ▲✶✷❑✆❏ ❇ ❆❍✮ ❅✵✵ ●❍✯❊■✶❏❍ ❇ Figure 4: The evaluated labs during 2014-2015. 1. How much time in total did you spend in completing the lab exercise? 2. Your level of interest in this lab exercise. (high, average, low) 3. How challenging is this lab exercise? (high, average, low) 4. How valuable is this lab as a part of the course? (high, average, low) 5. Are the supporting materials and lectures helpful for you to finish the project? (very helpful, somewhat helpful, not helpful) 6. How confident do you feel on applying the skills learned in the lab to solve other problems? (high, average, low) ❯❘ ❯◗ ❵❭❬ ✐❥❦❧ ♠♥♦♣q♣r♦ st
://www.nsf.gov/pubs/2020/nsf20101/nsf20101.jsp (accessed Feb. 13, 2022).[2] C. Wang, J. Shen, and J. Chao, “Integrating Computational Thinking in STEM Education: A Literature Review,” International Journal of Science & Mathematics Education, vol. 20, no. 8, pp. 1949–1972, Dec. 2022, doi: 10.1007/s10763-021-10227-5.[3] X. Tang, Y. Yin, Q. Lin, R. Hadad, and X. Zhai, “Assessing computational thinking: A systematic review of empirical studies,” Computers & Education, vol. 148, p. 103798, Apr. 2020, doi: 10.1016/j.compedu.2019.103798.[4] Y. Yin, R. Hadad, X. Tang, and Q. Lin, “Improving and Assessing Computational Thinking in Maker Activities: the Integration with Physics and Engineering Learning,” J Sci Educ Technol, vol. 29
points from 1 as “None at all” to 9 as “A great deal”.Our RET site survey also adopted nine points Likert scale to allow for finer data comparison ofpre-program and post-program results. 4. Evaluation Result and Discussion 4.1 Survey Result and Discussion The developed RET site survey was used to measure the self-efficacy of teachers in summer2022. Because each cohort only has 12 teachers which are not sufficient for drawing statisticallysignificant results, we only use descriptive statistics to compare the pre-program and post-programresults, as shown in Table 2. Figure 1 illustrates the difference in percentage. Table 2. Descriptive statistics to compare the pre- and post-program results Q# Pre
they were resolved. I think 2) is really hard in a 3-day workshop. The R operations aren’t intuitive and it’s probably really hard for a newbie to make much sense of them. So, I think I'd probably spend more time thinking about storyboarding how someone might use MF to approach a question. That was touched on during Thurs, but something like: To answer X, you need to know Y. You could get Y by combining Z and Q. Z is in MIDFIELD, but Q would need to come from outside. I think that might have been more helpful on Thurs am than the R exercise. But I think there are good nuggets in the R exercises. They're worthwhile, but to really understand the scripts takes time. • I think the data visualization
. Each created a 10-20 minute video which was posted on the IEC website a few daysbefore the meeting. The session began with a short presentation on the video highlights, followedby an open Q&A. The stories shared were very powerful, demonstrating many opportunities lostby the panelist’s home institution. Mentoring was identified as a critical issue and a variety ofexamples were presented that showed the impact of both good and bad mentoring. Thepresentation and the Q&A both helped to motivate the Anti-Racism workshops being offered byIEC spring 2021.The next two sessions were organized and presented by Prof. Russ Korte of George WashingtonUniversity and IEC leadership.Session 6: Team Science Part 1 (October 2020) Teamwork and task work
environment. Some of thoserecommendations included (1) a website video to introduce the project to the schools and engagefamilies and students; (2) an enhanced web presence to engage with students and families online,and (3) monthly industry spotlight videos to students to build program momentum. The researchteam also presented regular research Q&A talks to student cohorts within the first day of theircourse beginning with the goal of boosting research participation.Equitable Access to High Quality Teachers. Teachers are an essential partner in the collaborativemodel. Securing high-quality teachers in rural districts is a persistent challenge in the literature(Goodpaster, Adedokun, & Weaver, 2012). Data shows rural districts are more likely