to get to the shake table faster and getting that out of the way.AcknowledgementsThis material is based upon work supported by the National Science Foundation under Grant No.CMMI-1943917. Any opinions, findings, and conclusions or recommendations expressed in thismaterial are those of the authors and do not necessarily reflect the views of the National ScienceFoundation. The authors would also like the thank Dr. Hong Lin of the Center for FacultyExcellence at the University of Oklahoma for her assistance with the assessment.References [1] K. L. Ryan, S. Soroushian, E. Maragakis, E. Sato, T. Sasaki, and T. Okazaki, “Seismic simulation of an integrated ceiling-partition wall-piping system at E-Defense. I: Three-dimensional
engagement. The tradeoff is that time is needed for problem design,but these problems could be reused and allow automatic grading and customized feedback.In Fall 2019 when Mastering was tried, the author did a survey in the middle of the semester.Despite their willingness to continue using Mastering in that course and potentially in futurecourses, when the students were asked if they would pay for Mastering, no one said yes, asshown in Figure 11. Table 1 has summarized student opinions regarding the Mastering platform.This was the driving motivation for the author to explore alternative approaches to implementmulti-part problems with parameter randomization in LMSs. S T U D E N T P E R C E P T I O N I N FA L L 2 0 1 9 O N M A S T E R I N
Example “I would use a parallel circuit because if one light 1 light(s) 48 goes off, the other will continue working.” “Maybe we could take this, tape it or drill it on a 2 tape 39 tree or something.” “It didn't work the first time, so we tried a second 3 work 36 time and it didn't really work. It just didn't move.” “So we were reading in the kit that the
PrairieLearn’s collaborative assessments to extract the timestamp ofeach student’s submissions to a given collaborative problem. Each submission was labeled asquick (Q), medium (M), or slow (S) based on its duration and whether it was shorter or longerthan the 25th and 75th percentile. We then applied sequence compacting techniques, sequentialpattern mining, and correlation analysis to identify latent patterns that characterize variousproblem-solving strategies across three database query languages (SQL, MongoDB, Neo4j). Theobjective of this study is to investigate the potential of temporal information - the amount of timespent on each submission attempt – in uncovering the recurrent patterns in groups’ submissionsequences. The next step is to perform
expressed in this material are those of the author(s) and donot necessarily reflect the views of the National Science Foundation.REFERENCES[1] E. O. McGee, “Interrogating Structural Racism in STEM Higher Education,” EducationalResearcher, vol. 49, no. 9, pp. 633–644, Dec. 2020, doi: 10.3102/0013189X20972718.[2] Y. A. Rankin, J. O. Thomas, and S. Erete, “Real Talk: Saturated Sites of Violence in CSEducation,” in Proceedings of the 52nd ACM Technical Symposium on Computer ScienceEducation, Virtual Event USA: ACM, Mar. 2021, pp. 802–808. doi: 10.1145/3408877.3432432.[3] E. W. Huff et al., “Going Through a Process of Whitening: Student Experiences WithinComputer Science Education,” in Proceedings of the 52nd ACM Technical Symposium onComputer
Paul, Oregon State University ©American Society for Engineering Education, 2023 Lab Safety Awareness in Incident and Near-miss Reporting by Students Participating in Engineering Societies: A Case StudyAcademic laboratory safety has gained considerable attention from researchers and researchinstitution administrators since several high-profile incidents in the late 2000’s. Another part ofstudent learning in engineering, though informal, occurs in co-curricular activity such asengineering societies and team competitions where students conduct hands-on activities toachieve certain objectives, usually with minimal (if any) authoritative figures in presence. Thesafety aspect of these co-curricular
either Discord or a Google account.AcknowledgmentsThis material is based upon work supported by the National Science Foundation under the NSFEAGER Grant DUE-1745922. Any opinions, findings, and conclusions, or recommendationsexpressed in this paper are those of the authors only and do not necessarily reflect the views ofthe National Science Foundation. The authors extend their gratitude to all interview participantswho allowed us to add their narratives to this study. The authors also extend their appreciation tothe anonymous reviewers for their thoughtful comments and feedback.References[1] C. Hodges, S. Moore, B. Lockee, T. Trust, and A. Bond, “The Difference Between Emergency Remote Teaching and Online Learning,” Educase Review, no. 27
thatparticular paper or because the author(s) felt it was an obvious part of any such program. Table 3: Bridge Program Non-Academic Content References Advising Social Professional Skills College Knowledge [35, 16] X X X [22] X X [27] X X X [3, 25, 21, 24] X X [29, 8, 46] X X [10, 11] X X [34, 23, 36, 19, 20] X [12, 13] X X [37] X X
. In contrast to the concept map view, the topics provides a rich environment toqualitatively examine related data.Data CollectionGaming research papers in engineering education were infrequent in the early 2000’s 10 9 , andprior to 2006, there were few abstracts published in the ASEE annual conference proceedings.Therefore, the data search included all ASEE annual conference papers from 2006-2020 using theASEE Conference Proceedings Search.The search terms included game, gaming, gamer, gamify,and gamification in the title of the paper. Relevant paper abstracts and metadata were included inthe sample. We reviewed each abstract and excluded papers on topics not related to games andlearning, such as game theory or sports, and papers without
ethnicity of the childparticipants included 36.7% African American, 13.3% Asian, 36.7% Caucasian, and 13.3% self-identified as “other” or two or more ethnicities. Caregiver’s educational backgrounds rangedfrom a high school degree to a doctoral degree and approximately 30% of the caregivers having acareer in a STEM field and/or some experience related to STEM. Pseudonyms are used toidentify participants.ResultsResults are organized by research aim and include finding highlights from on-going analyses.The data sources that informed these insights are from multiple data sources – interviews withchild(ren) and caregiver(s), video recordings of in-person sessions using stand-alone cameras,and video recordings of at-home interactions with the
. [Accessed: 06- Mar-2021].[4] R. Miller and B. Linder, “Is Design Thinking the New Liberal Arts of Education?,” 2015.[5] A. F. McKenna, “Adaptive Expertise and Knowledge Fluency in Design and Innovation,” in Cambridge Handbook of Engineering Education Research, A. Johri and B. M. Olds, Eds. Cambridge: Cambridge University Press, 2014, pp. 227–242.[6] M. J. Safoutin, “A methodology for empirical measurement of iteration in engineering design processes,” Citeseer, 2003.[7] A. F. McKenna, J. E. Colgate, G. B. Olson, and S. H. Carr, “Exploring Adaptive Expertise as a Target for Engineering Design Education,” in Volume 4c: 3rd Symposium on International Design and Design Education, 2006, vol. 2006, pp
during thefaculty connection hour events helped our instructions in the fall semester; (b) Q8-Q14 gauge facultyinterest and preference for future development opportunities.Again, your honest feedback is greatly appreciated.Q1 How many times did you attend the faculty connection hour(s)?Q2 What did you benefit the most from the faculty connection hour(s)?Q3 I believe that I was better prepared for my lab course(s) because of attending the faculty connectionhours. A. TRUE (1) B. FALSE (2)Q4 The faculty connection hour(s) helped me mentally while preparing for the fall semester. A. TRUE (1) B. FALSE (2)Q5 The faculty connection hour(s) helped me better engage my students in the fall semester. A. TRUE (1) B. FALSE (2)Q6 Many strategies
Science Foundation under Grant No.2000599. Any opinions, findings, and conclusions or recommendations expressed in this materialare those of the authors and do not necessarily reflect the views of the National ScienceFoundation. The preliminary stages of this work are supported by funds from the Office of theExecutive Vice President and Provost at The Pennsylvania State University as part theuniversity’s strategic plan related to transforming education.References[1] D. R. Brodeur, P. W. Young, and K. B. Blair, “Problem-based learning in aerospace engineering education,” ASEE Annu. Conf. Proc.,2002, doi: 10.18260/1-2-10974.[2] J. T. Bell and H. S. Fogler, “Implementing virtual reality laboratory accidents using the half-life game
Case-Based Learning: A Creative Experience in Comparison to Traditional Teaching Methods Waddah Akili Geotechnical EngineeringA b s t r a c tThis paper describes the steps taken in planning, developing, and executing a case study/ casehistory course in geotechnical/ foundation engineering at an international university. The paper ed : a ab e a ec e a a ed a ; e a a ecourse; and the results of evaluating the effectiveness of this approach versus traditionallecturing. Problems and challenges that could arise when offering the course for the first time arealso addressed. Embedded in this
groups of students were allowed to take the course, but were warned that they wouldbe responsible for pre-requisite knowledge. Students were also given access to content from thepre-requisite course. For building teams, the CATME tool was used to design a survey that would obtain responsesto the following questions from each student: 1. Sub-discipline within civil and environmental engineering that they specialize in (undergrad- uate students at the University of Illinois are required to specialize in a primary area of study as well as a secondary area, while graduate students are required to specialize in one area) 2. Whether they had taken the pre-requisite course(s) 3. Months of work experience 4. Availability to meet
Paper ID #21841Impact of Undergraduate Research Experiences on Diverse National and In-ternational Undergraduate ResearchersDr. Jacques C. Richard, Texas A&M University Dr. Richard got his Ph. D. at Rensselaer Polytechnic Institute, 1989 & a B. S. at Boston University, 1984. He was at NASA Glenn, 1989-1995, taught at Northwestern for Fall 1995, worked at Argonne National Lab, 1996-1997, Chicago State, 1997-2002. Dr. Richard is a Sr. Lecturer & Research Associate in Aerospace Engineering @ Texas A&M since 1/03. His research is focused on computational plasma modeling using spectral and lattice Boltzmann
promoting diversity in graduate engineering education, Proc. 2006 ASEE AnnualConference, Chicago, IL, June 2006.4. Eugene M. DeLoatch, Sherra Kerns, Lueny Morell, Carla Purdy, Paige Smith, Samuel L. Truesdale, and BarbaraWaugh, Articulating a multifaceted approach for promoting diversity in graduate engineering education, Proc. 2007ASEE Annual Conference, Honolulu, HI, June 2007.5. Phillip C. Wankat, Analysis of the first ten years of the, Journal of Engineering Education 88 (1), 1999, pp. 37-42.6. R.G. Batson, T.W. Merritt, and C.F. Williams, Barriers to increased engineering graduate enrollments:counterforces and their implementation, Journal of Engineering Education 82 (3), 1993, pp. 157-162.7. S. Baker, P. Tancred, and S. Whitesides, Gender and
unchanged pre to post.Table 1: All Students Pre to Post Comparison Pre Post Pre Post S Effect S Effect#1 Mean2 Mean2 Size3 Opinion4 Change5 #1 Mean2 Mean2 Size3 Opinion4 Change5 Interest in learning Relationship to Math and Science1 2.5 2.43 0.06 Disagree Extreme *6 6 3.93 3.98 0.05 Agree Extreme12 3.09 3.16 0.07 Agree Extreme 11 4.17 4.05
, 2006.[2] X. Tang, Y. Yin, Q. Lin, R. Hadad, and X. Zhai, “Assessing computational thinking: A systematic review of empirical studies,” Comput. Educ., vol. 148, no. January, p. 103798, 2020.[3] H. Shoaib and S. P. Brophy, “A systematic literature-based perspective towards learning and pedagogy of computational thinking,” ASEE Annu. Conf. Expo. Conf. Proc., vol. 2020-June, 2020.[4] P. J. Denning, “Computational Thinking in Science,” Best Writ. Math. 2018, pp. 67–77, 2019.[5] D. Weintrop et al., “Defining computational thinking for mathematics and science classrooms,” J. Sci. Educ. Technol., vol. 25, no. 1, pp. 127–147, 2016.[6] K. Brennan and M. Resnick, “New frameworks for studying and
a standardizedevent and take place in more real-world settings. !ReferencesAnsari, D., Smedt, B. D., & Grabner, R. H. (2012). Neuroeducation – A Critical Overview of An Emerging Field. Neuroethics, 5(2), 105–117. https://doi.org/10.1007/s12152-011-9119-3Bembich, S., Clarici, A., Vecchiet, C., Baldassi, G., Cont, G., & Demarini, S. (2014). Differences in time course activation of dorsolateral prefrontal cortex associated with low or high risk choices in a gambling task. Frontiers in Human Neuroscience, 8. https://doi.org/10.3389/fnhum.2014.00464Bunce, S. C., Izzetoglu, K., Ayaz, H., Shewokis, P., Izzetoglu, M., Pourrezaei, K., & Onaral, B. (2011). Implementation of fNIRS for Monitoring Levels of
D me pe s-o dE pt D me pe s-o dE ce joy ros nd are ce joy ros nd are on E n e P Ha Sh on E n e P Ha Sh C tur C tur Fu
, U.K., Ashgate, 2008, pp. 57-80.[5] S. E. Dreyfus and H. L. Dreyfus, "A Five-Stage Model of the Mental Activities Involved in Directed Skill Acquisition," California University Berkley Operations Research Center, No. ORC-80-2, 1980.[6] R. R. Hoffmann and G. Lintern, "Eliciting and representing the knowledge of experts," in Cambridge Handbook of Expertise and Expert Performance, New York, Cambridge University Press, 2006, pp. 203-222.[7] R. R. Hoffman and J. Smith, Toward a general theory of expertise: Prospects and limits, New York: Cambridge University Press, 1991.[8] S. E. Dreyfus, "The Five-Stage Model of Adult Skill Acquisition," Bulletin of Science, Technology, & Society, vol. 24, no. 3, pp. 177-181, 2004.[9] D
creatively and effectively. Leaders alsoneed to constantly develop skills and intellectual tools to understand soft skills or people skillsand build relationships internally [48]. Results of Gitsham et al.’s [28] survey of CEOs and other executives focus on how softskills and hard skills are beneficial for leaders at all levels of the organization. Specifically,acquisition of interpersonal skills may provide added benefits of knowing and understanding ofhow to interact with people with different cultures and apply the skills to improve organizationalperformance. Soft skills are a set of interpersonal and social skills, whereas hard skills includethe technical or administrative procedures in which the results are quantifiable and measurable[43
SCMcurriculum [10], and is proven to be very effective and popular across all levels of programsincluding undergraduate, graduate, and executive education [11]. Developed by MIT′s SloanSchool of Management in the 80s, the Beer Game was originally created to teach students systemsconcepts and systems thinking [12]. However, as the content area of SCM continues to expand, sodo the Beer Game learning extensions which now span demonstrating the bullwhip effect, risk-pooling, and technology integration, to name a few [13]. In response, student participants get thechance to actively learn about the benefit of supply chain awareness and communication, theimportance of supply chain collaborative strategic decision making, and the benefit of working asa team to
comprehensive studies exploring student roles played, ABET relatedoutcomes, and impacts on class and career readiness.In the spring of 2017 (from May 2 to May 14, 2017), a confidential online survey wasadministered to students involved in an activity at the BIC. In total, 52 students providedresponses to the survey. The majority of these students were involved with a competitionteam/club (73%, N=38). About a quarter of students either used the BIC for their capstoneprojects (15%, N=8) or were involved in other activities (12%, N=6). The results from thissurvey are reported with appropriate IRB approvals.Students were asked to indicate how much their BIC experience(s) contributed to their ability toengage in various behaviors. The response options
student runs a solar annualanalysis for panel 259, finding it produces 344 kWh over the year. Next, the student looks at theGraph tab Basics which contains information like the physical dimensions and locations ofpanels (a non-solar move that is ignored because it is within the noise threshold). Panel 259 isremoved and they add another panel near 259’s previous location. Finally, they edit panel 318,which is over 10 feet away from panel 259’s location in two dimensions (roughly height andlength) and run a solar annual analysis finding 318 produces 269 kWh per year.Some variations on this micro-iteration include: analyzing daily solar production of panelsinstead of annual production and varying location and solar cell efficiency for locations. As
,Ericson, Wu, & Martinez, 2012; Romine, Sadler, Presley, & Klosterman, 2012), there have beenfew that systematically gather the information across all STEM subject areas (Erkut&Marx,2005; Tyler-Wood, Knezek, & Christensen, 2010). There have been two surveys that haveutilized the SCCT framework in their development: the Student Attitudes toward STEM (S-STEM; Unfried, Faber, Stanhope, & Wiebe, 2015) and the STEM Career Interest Survey(STEM-CIS; Kier, Blanchard, Osborne, & Albert, 2013). The S-STEM (Unfried et al., 2015)measures student attitudes in STEM and interests in STEM careers. However, it does notseparate the various socio-cognitive mechanisms of self-efficacy, outcome expectations, andpersonal goals. The STEM-CIS
the project, the instructor began searching for prospective students. It was envisionedthat the project would offer a learning platform to students allowing them to generate novelmethods of applying energy conversion, while providing a practical result to the client.The laboratory background of this project was a 1/3 scale 1960’s style Ford Model T built byMcCullough Co, changed to Toro Co, then to Sharp Mini Cars. The charge given by the clientwas to convert the vehicle’s prime mover from gasoline to electrical using the design criteriaoutlined below:Hard Project Requirements • Retain original controls for Front, Neutral, and Reverse [F-N-R] using a lever on the left- hand side [LH] and the throttle which was a lever on right side of
engineering entrepreneurship education.AcknowledgementsThis project is funded by the U.S National Science Foundation through grant number 1531533.The opinions are those of the authors and do not necessarily represent the National ScienceFoundation.References[1] D. T. Rover, “New economy, new engineer,” J. Eng. Educ., vol. 94, no. 4, pp. 427–428, 2005.[2] T. Byers, T. Seelig, S. Sheppard, and P. Weilerstein, “Entrepreneurship: It’s Role in Engineering Education,” Bridg., vol. 43, no. 2, pp. 35–40, 2013.[3] S. K. Gilmartin, H. L. Chen, and C. Estrada, “Investigating Entrepreneurship Program Models in Undergraduate Engineering Education,” vol. 32, no. 5, pp. 2048–2065, 2016.[4] J. A. Katz, “The chronology and intellectual
University S =Symbolic Student Faculty Admin.Less Emphasis on More Emphasis on O = Org.Viewing course as Thinking about