of robot and a camera that provides a top view of entire robot work space. The user can then decide what to do next, restarting the process from Step A. Figure 1. Remote Cozmo Robot System Architecture.Remote Control of Cozmo RobotCozmo robot provides a user-friendly SDK app with examples. Users can modify the examplesto fit new applications. The Cozmo Python program also includes a user friendly graphical userinterface that allow users to easily manipulate the robot with a single key stoke. For example, theW, A, S, and D keys can be used to drive Forward/Left/Back/Right; T is Move Head Up; G isMove Head Down; R is Move Lift Up; and F is Move Lift Down. In Figure 2, the image on theleft is the top view of the
. Results showed that there was an increase inthe utilization of DfAM in design concepts. The work will contribute to the field of DfAMintegration in engineering education curriculum and will improve student self-efficacy in DfAM.AcknowledgementWe acknowledge the first-year faculty members, Dr. ChangHoon Lee, Dr. Charles Roche, Dr. J.Benner, Dr. R. Gettens, Dr. A. Kwaczala, Dr. A. Santamaria, Noah Pare, and Roberto DuranBrea for their help in the execution of the experiments.References[1] ISO/ASTM, “ISO/ASTM 52900: Additive manufacturing - General principles - Terminology,” Int. Stand., vol. 5, 2015.[2] B. Motyl and S. Filippi, “Trends in engineering education for additive manufacturing in the industry 4.0 era: a systematic
and graded for completion only, not for correctness. The day that the homework was due, students were given solutions. The following class period, students completed an in-class quiz similar to the quizzes given for assessment Q.Table 1: Assessment modality, instructors, and number of students for each course offering.Offering 2014 2015 2016 2017 2018 2019 2020 2021Assessment H H H H Q Q QH QH# Students 39 54 41 50 39 41 70 63Instructor(s) A A&B A&B A&C A&C A A AFor all three
concepts or materialalready present in the cybersecurity curriculum. Lastly, our methodology plans to evaluate theeffectiveness of the proposed methodology from both student and instructor perspectives.In this paper, we focus on the first component of our proposed methodology, namely Analysis ofLiterature. We build a semi-automated analysis pipeline that helps us to systematically analyzethe cybersecurity literature for the prevalence and distribution of AI and ML in cybersecurityresearch. Our analysis pipeline aims to achive this through the analysis of over 5000 researchpapers collected from the last five years of the top cybersecurity conferences (i.e., IEEE S&P,ACM CCS, Usenix Security, NDSS, ACSAC, ESORICS). Our analysis of over
National Science Foundation (NSF IUSE #2120156). Anyopinions, findings, conclusions, and recommendations are the authors’ and do not necessarilyreflect the views of the National Science Foundation.References 1. J. Kellar, S. Howard, M. West, D. Medlin, and S. Kellogg “The Samurai Sword Design Project and Opportunities for Metallurgical Programs.” MS&T Proceedings 2009: Status of Metals Engineering Education in the United States. 2. M. West, D. Medlin, J. Kellar, D. Mitchell, S. Kellogg, and J. Rattling Leaf, “Back in Black: Innovative Curricular, Outreach, and Recruiting Activities at the South Dakota School of Mines and Technology.” MS&T Proceedings: Status of Metals Engineering Education in the United States
. However, when possible, questions were kept as theoriginal or only slightly modified. The nanotechnology and STEM attitudes survey was a modified version of theStudent Attitude Toward Science, Technology, Engineering, and Mathematics (S-STEM) instrument developed bythe Friday Institute at North Carolina State [16]. The S-STEM includes scales on attitudes towards mathematics,science, engineering, and technology, 21st century learning skills, and STEM career awareness. For the purposes ofthis project, the mathematics scale was removed and replaced by a nanotechnology focused scale developed duringprevious one-week camps provided for high school students. The nanotechnology scale contains nine questionswhich were modified over its early development
Paper ID #37220Assessing Head- Hand- and Heart-Related Competenciesthrough Augmented-RealityLogan Andrew Perry (Assistant Professor of Engineering Education) Logan Perry is an Assistant Professor of Engineering Education at the University of Nebraska-Lincoln. His research interests lie at the intersection of civil engineering and engineering education and include 1) the transfer of learning, 2) diversity for engineering, and 3) cyberlearning technology.Jeremi S London (Assistant Professor) Associate Professor of Engineering Education at Virginia Tech Chair of ASEE's CDEI during the Year of Impact on Racial
Paper ID #38078Community-focused Senior Design Practicum ProjectsVenkat Allada (Vice Provost for Graduate Studies) Dr. Venkat Allada is a Professor of Engineering Management & Systems Engineering at Missouri University if Science and Technology (Missouri S&T), Rolla, USA. He served as Missouri S&T’s inaugural vice provost of graduate studies from 2007-2017. He served as the 2016-17 chair of the Mid-west Association of Graduate Schools (MAGS). Dr. Allada earned his doctoral degree in Industrial Engineering from University of Cincinnati in 1994. His teaching and research interests are in areas of lean
to connect with researchers who have previously exploredsimilar issues or may experience them in their current work. Student Pathways in Engineeringand Computing for Transfer Students (SPECTRA) is an NSF S-STEM program that providesfinancial assistance to students transferring from the South Carolina Technical College Systeminto Engineering or Computing majors at Clemson University [1]. SPECTRA also assistsstudents by connecting them with peers at the technical colleges who move together through thetransfer process to Clemson and are supported by the SPECTRA program until graduation. Inaddition to exploring the experiences of current SPECTRA participants, we investigate how theproject can be scaled to include more students and sustained
investigatesubpopulation differences in MH distress and MH related help-seeking perceptions.Help-seeking behavior in college studentsIn the broader college student population, it has been hypothesized that the most effective way toincrease MH help seeking behaviors in college students is to change their self-perceptions andattitude toward professional MH services [8]-[10]. Research has also examined help seekingbehaviors of students in self-identified high-stress academic programs (e.g., law [11], medicine[12], [13], nursing [14], dentistry [15], [16]). In these studies, the most significant factors for notseeking help for MH concerns pertained to perceived stigma(s), fear of disclosure, and perceiveddetriment to academic and/or career success; students in these
virtuallyand the instructor session conducted in person. Ideally, the sessions with students would includemultiple members from their project team. In future applications of the method, it may also beinteresting to conduct sessions with students and instructor (and/or TA) in the same session. 3) Decide on focal factor(s): To start the mapping process, participants were asked to identify the focal factor(s), which should be a variable within the system that is central to the problem, per the original protocol. To assist participants in focal factor identification, we used the following prompts: What were the key inputs in your project? What were the key outputs? What were the key elements of the project that you controlled? What
/10.1061/9780784415221[4] A. Johri and B. Olds, “Situated engineering learning: Bridging engineering educationresearch and the learning sciences,” Journal of Engineering Education, 100(1), 151–185, 2011.http://dx.doi.org/10.1002/j.2168-9830.2011.tb00007.x[5] S. R. Brunhaver, R. F. Korte, S. R. Barley, and S. D. Sheppard, “Bridging the gaps betweenengineering education and practice,” In R. Freeman & H. Salzman (Eds.), Engineering in aglobal economy. University of Chicago Press, 2018.[6] A. R. Bielefeldt, K. Paterson, and C. Swan, “Measuring the value added from servicelearning in project-based engineering education,” International Journal of EngineeringEducation, 26(3), 535-546, 2010.[7] K. Litchfield, A. Javernick-Will, and A. Maul, “Technical
investigation which includes investment in infrastructure such as internetaccess, capacity, and equipment, as well as in teacher training. Constant communication andversatility in using remote delivery tools can help as well. Innovative methods relying on newtechnology such as AI and VR are desperately needed to revolutionize education on the long run,but for now, access seems to be a pressing issue in both the technical and social sides.References[1] S. Nagarajan and T. Overton, "Promoting Systems Thinking Using Project- and Problem-BasedLearning", Journal of Chemical Education, vol. 96, no. 12, pp. 2901-2909, 2019. Available:10.1021/acs.jchemed.9b00358.[2] J. Krajcik and N. Shin, "Project-Based Learning", in The Cambridge Handbook of TheLearning
Protector with other learning contexts and audiences.References[1] J. M. Hoekstra, T. M. Boucher, T. H. Ricketts, and C. Roberts, “Confronting a biome crisis: global disparities of habitat loss and protection,” Ecology letters, vol. 8, no. 1, pp. 23–29, 2005.[2] T. J. Lark, S. A. Spawn, M. Bougie, and H. K. Gibbs, “Cropland expansion in the United States produces marginal yields at high costs to wildlife,” Nature communications, vol. 11, no. 1, pp. 1–11, 2020.[3] D. M. Engle, B. R. Coppedge, and S. D. Fuhlendorf, “From the dust bowl to the green glacier: human activity and environmental change in Great Plains grasslands,” in Western North American Juniperus Communities, Springer, 2008, pp. 253–271.[4] V. J. Horncastle, E. C
creating supports that aid in identity development. Creating spaces for exploring identity development over the course of the engineering and computer degrees, particularly working with student-led Latinx organizations. Redesigning engineering and computer science spaces to be more culturally relevant and inclusive, rather than exclusionary and white.Acknowledgments: This work was supported by NSF grant numbers 1647181 and 1647104 atThe University of Texas at Arlington with Principal Investigator Panos S. Shiakolas and TexasA&M University - Commerce with Principal Investigator Sarah L. Rodriguez. Any opinions,findings, and conclusions or recommendations expressed in this work are those of the authorsand do not necessarily
resources.References[1] P. D. Crompton, J. Moebius, S. Portugal, M. Waisberg, G. Hart, L. S. Garver, L. H. Miller, C. Barillas-Mury,and S. K. Pierce, "Malaria immunity in man and mosquito: insights into unsolved mysteries of a deadly infectiousdisease," Annual review of immunology, vol. 32, pp. 157-187, 2014.[2] A. S. Fauci, and D. M. Morens, "Zika virus in the Americas—yet another arbovirus threat," New Englandjournal of medicine, vol. 374, no. 7, pp. 601-604, 2016.[3] V. Vijayakumar, D. Malathi, V. Subramaniyaswamy, P. Saravanan, and R. Logesh, "Fog computing-basedintelligent healthcare system for the detection and prevention of mosquito-borne diseases," Computers in HumanBehavior, vol. 100, pp. 275-285, 2019.[4] S. Sareen, S. K. Sood, and S. K. Gupta
topics related to the structure of the course; assignments; enthusiasm, or lack of it; andpersonal concerns and tragedies that students share [6]. Indeed, research shows that teachersapply empathy in their interactions and relationships with students [6].Researchers have conceptualized empathy in multiple ways. Empathy is a complex concept thathas been generally defined as an individual’s ability to understand and respond to anotherperson’s perspective and feelings [7]. Cuff et al.'s [8] review of empathy research identifiedforty-three distinct definitions of the concept. In another review, Batson describes eight distinctyet related concepts of empathy [9]. In the context of nursing education, Kunyk and Olson [3]categorized types of empathy into
Paper ID #36785An Analysis of STEM Students’ Integral and Area Under theCurve KnowledgeEmre Tokgoz (Associate Professor)Samantha Scarpinella Pennsylvania State University Industrial Engineering PhD Student © American Society for Engineering Education, 2022 Powered by www.slayte.comAn Analysis of STEM Students’ Integral and Area Under the CurveKnowledge1 Emre Tokgöz, 3Samantha Scarpinella, 3Michael Giannone, 1Elif. N. Tekalp, 1Berrak S. Tekalp, 2Hasan A.Tekalp1 Emre.Tokgoz@qu.edu, 1Elif.Tekalp@qu.edu, 1Berrak.Tekalp@qu.edu, 2Hasan.Tekalp@qu.edu3 ses6506@psu.edu, 1Michael.Giannone
problem would be remained.”Impact of the S-L project on student performanceA comparison of exam 3 grades for Cohort 1 was performed. Exam 3, unlike the previous exams,was administered within a week after the service-learning project was completed. The final examwas not considered since exemptions were granted for high achieving students, which includedmany students that participated in the service-learning project. The exam 3 results, presented inFig. 4, were split into three groups: S-L project, case study, and no project. The S-L projectgroup were Cohort 1 students (12 total), the case study group (10 total) were given a columndesign project assignment, and the no project group (32 total) chose to do neither S-L nor casestudy project
in 2016 [16][17] [18]. “YOLO” network allows multiple object recognition at high accuracy [19]. Multipleversions of YOLO networks are implemented, including version 4 (YOLOv4) on the darknetplatform, and version 5 (YOLOv5), which is integrated into ROS [20]. 2022 ASEE Annual Conference & Exposition Minneapolis, Minnesota, USA, June 26-29, 2022 Wang, Y., Zhang, Z., Chang, Y.YOLOv5 contains four types of architectures which are named with suffix s for small, m formedium, l for large, and x for extra-large, according to the number of residual units in CSP1_X,CBL in CSP2_X, and convolutional kernel number.Simultaneously localization and mapping
. High water cooling rates can be achieved with ~50 °C water, eliminating the need to usehotter fluid, which would introduce safety concerns. The water flow rate can be varied betweenapproximately 10-30 mL/s by adjusting the quarter-turn valve on the pump assembly, and the airvelocity can be changed by adjusting the power supplied to the fan, either by using batteries withdifferent voltages or by changing the resistance from the battery to the fan. The evaporativecooler set-up shown in Figure 2 operates in non-steady state recycle mode, as the water isrecycled continuously out of and back into the reservoir, resulting in temperature changes overtime. However, if separate, large water supply and collection basins are used instead of a singleone
and beliefs thatbest predict help-seeking intention in undergraduate engineering students. Findings will help toidentify empirically driven targets for interventions aimed at improving help-seeking inundergraduate engineering students.AcknowledgmentsA grant from the National Science Foundation (#2024394) supported this study. This grant wasfunded through the Research Initiation in Engineering Formation program.References[1] S. K. Lipson, S. Zhou, B. Wagner, K. Beck and D. Eisenberg, "Major differences: Variationsin undergraduate and graduate student mental health and treatment utilization across academicdisciplines." Journal of College Student Psychotherapy, vol. 30, no. 1, pp. 23-41, 2016.[2] D. Eisenberg et al., "The Healthy Minds Study
describesthe geometry of the deformed lamina. Only the essential results of the analysis are presentedhere. The solution yields expressions for the height h and the span s in terms of two parameters,related to the slope α at the ends:𝑘 ≡ sin ≡ sin 𝜃 which is dimensionless, and a second related to the applied force (2) P and the bending stiffness, EI.E = modulus of elasticity or Young’s modulusI = moment of inertiac ≡ (EI ∕ P)1/2 which has the dimensions of length. (3)The solution gives:s = 2c⋅[2F1(k) – F2(k)] (4a)h = 2ck
video. Then, respondents answered a series of questions abouttheir interest and knowledge of several STEM topics, both before and after watching thevideo(s). This retrospective pre/post questionnaire technique helps to alleviate response-shift biaspresent in self-assessed changes in learning attitudes. Our findings show that collaborativepresentation videos increased self-reported audience interest in engineering, and perceptions ofdisciplinary relatedness more than the non-collaborative, individual presentations made by thesame researchers. These results suggest a beneficial role for collaborative communicationstrategies to foster interest in engineering among public audiences, even among people without abackground in STEM. Further
perceive their learning experiences in laboratory environments (remote and in-person)? The study was conducted at a Research-1 institution in the Northeastern region of the UnitedStates in a capstone senior engineering laboratory course. Qualitative and quantitative data wascollected via post-questionnaires and interviews. Data was analyzed in terms of laboratoryenvironment, i.e., in-person or virtual/remote and student background/experiences as described ininterviews. This work will help researchers and educators understand what aspects of courseevaluation instruments are useful in comparing laboratory environments and how theseinstruments relate or inform the instructor about perceived usefulness of course content andmechanism(s) of
accommodation does not appear to work witha course structure, the disability office can often help to adapt the accommodation to the course.3) Do not ask students to disclose their disabilities.When a student has obtained accommodations through the university, they have gone throughthe process of providing their official diagnosis(s) and the appropriate paperwork for experts todetermine their accommodations. The information an instructor receives will simply state thatthe student has a disability, and will outline the associated accommodations, but will not revealthe disability diagnosis. While it might seem like a harmless question, an instructor asking astudent to disclose their disability can be a frightening thing.1,28 Students are not obligated
the formal introduction of SLRs to the field of engineering education in 2014by Borrego and colleagues, increasing trends in SLR use and impact were observed. While thegoal of SLRs is to answer a clearly formulated (set of) research question(s), the goal of SMRs isto define and describe the broader landscape of existing scholarly research on a topic. In this way,SMRs may be particularly useful for defining the scope of follow-on SLRs in engineeringeducation research.Keywords: literature reviews, systematic maps, systematic mapping reviews, systematic literaturereviews, engineering education Introduction The field of engineering education research (EER) has experienced rapid growth since
. Ofthe undergraduate students, 82% are white, 5.9% are Hispanic, 4.2% are African Americans, and0.3% are American Indian or Alaska Native. At the graduate level, these numbers are 80.6%,3.2%, 3.5%, and 0.4%, respectively. In comparison, the statewide demographics are: 79.2%white, 5.3% Hispanic, and 14.1% African American. Efforts to focus on inclusion and equity atthe university level have a long history. In the 1970’s, the university established the MulticulturalCenter that supported a wide range of cultural activities as well as academic and supportprogramming to the Minority Education Cohorts: Minority Science Education Cohort, MinorityTeacher Education Cohort, and Minority Business Education Cohort. This was the primaryapproach at the
disambiguation framework consists of fouriterative stages to create a “best-guess” of a completely resolved network data set and provides ageneral structure for future algorithmic methods. Results of this work will better enableresearchers to study larger, more holistic educational networks. BackgroundStudents benefit from social interactions in a variety of ways. For example, Kalaian et al.’s [5]meta-analysis identified that across 18 studies, formal small group settings enhance student’sabilities to succeed academically—especially among first-year engineering students (d = 0.84).Studying students’ online social media interactions, Su and Huang [6] found that students whofrequently use social media for academic
demographic information.Table 1. Participant information Child Caregiver(s) Child Child Caregiver Ethnicity Pseudonym Pseudonym Age/Grade Gender Information Jennifer worked in an Billy Jennifer 9/4th Male White elementary school as an art teacher. Edward 12/7th Male John worked in a John African