firstattempt, while additional attempts are recognizing the fact that they are still in the learning phaseand may require some “guidance”. No partial credit is given for problems with incorrect answer.The overall strategy is to simulate learning progression from educational environment toindustry/work setting. Although these modifications were initially greeted by students withapprehension, at the end of the course students recognized the benefits of this structured andrigorous approach and expressed very positive attitude towards the examination strategy.ResultsThe study was performed on the results collected during eight semesters (S’13 – F’16). Thecourse modification was made in the Fall ’14 and implemented in the Spring ’15. The reportedresults
technical writing skills in STEMdisciplines is well documented. Solutions have been proposed, implemented, and inconsistently sustained.One approach to improving disciplinary technical writing is through Writing Assignment Tutor Trainingin STEM (WATTS). WATTS is an interdisciplinary, collaborative approach in which STEM faculty workwith writing centers and generalist peer tutors to provide just-in-time assignment-specific feedback tostudents. WATTS research was funded by an NSF IUSE collaborative grant (award #s 2013467,2013496, & 2013541). In WATTS, the STEM instructor collaborates with the writing center supervisorand prepares materials for the tutor-training including assignment examples, a glossary of terms, areas ofconcern, and the
Education, 2016 123rd ASEE Annual Conference and Exposition New Orleans, LA, USA, June 26-29, 2016 Zhang, Z., Zhang, M., Chang, Y., Esche, S. K. & Chassapis, C. A Virtual Laboratory System with Biometric Authentication and Remote Proctoring Based on Facial Recognition Zhang, Z., Zhang, M., Chang, Y., Esche, S. K. & Chassapis, C.AbstractVirtual laboratories are used in online education, corporate training and professional skilldevelopment. There are several aspects that determine the value and effectiveness of virtuallaboratories, namely (i) the cost of development which includes the cost of
workplaces, which can positively affect productivity,commitment, and performance [20].Theoretical FrameworkWithin engineering education, the role of values remains relatively underexplored (perhapsbecause engineering culture often positions itself as free of values or biases), but outside ofengineering education, examining these issues is not new. Researchers in social andorganizational psychology have examined values through numerous approaches and frameworks,e.g., [46]-[49]. For this study, we turn to Schwartz et al.’s values framework [50] [51], which weleverage due to its seminal and popular nature and proven utility in understanding how valuesinfluence behaviors and priorities in a range of domains (e.g., workplaces [51] [52]). WhileSchwartz et
about 40%. 1028 1026 959 962 926 1117 1160 1179 1227 1196 989 1114 1164 100 90 s Enroll Calculus I t 80 P u Pass Calculus I e d C 70 r e a Enroll Calculus II c n l 60 e t c Pass Calculus II n s u t 50 l a s Enroll Multi‐ u g t 40
papersthat were reviewed: 5 in pre-college, 25 in college, and 6 in post-college. A code sheet was developed using the categories necessary to answer the two researchquestions. The categories for the code sheet were ethnicity, race, gender, language(s), generationin the U.S., generation in college, and institution (college-only). When reviewing each article,the authors noted how each category was used for the purpose of data analysis. Additionally, inthe review of each article, the authors also noted the main conclusions of each study as theserelated to the status of Latinxs in engineering. After reviewing the majority of the assignedarticles, the authors met to review the preliminary findings and patterns they saw in theirrespective notes
STEM Scholars Bridge Program for Increased Student Retention, Internship and Career Exploration at University of Southern Maine NSF Awardees Poster Session 2015 ASEE Conference Page 26.1397.2 AbstractIn the summer of 2012, the National Science Foundation (NSF) awarded the University ofSouthern Maine (USM) with a scholarship grant for “STEM Opportunities for AcademicallyCapable and Financially Needy Students: University of Southern Maine STEM ScholarsProgram” (S-STEM
project.References[1] W. Schilling, “Issues effecting doctoral students returning to engineering educationfollowing extensive industrial experience,” in Proceedings of the American Society forEngineering Education, June 2008, Pittsburgh, PA.[2] M. L. Strutz, J. E. Cawthorne, D. M. Ferguson, M. T. Carnes, and M. Ohland, “Returningstudents in engineering education: Making a case for ‘experience capital’,” in Proceedings of theAmerican Society for Engineering Education, June 2011, Vancouver, BC.[3] D. L. Peters and S. R. Daly, “The challenge of returning: Transitioning from anengineering career to graduate school,” in Proceedings of the American Society for EngineeringEducation, June 2011, Vancouver, BC.[4] D. L. Peters and S. R. Daly, “Why do
(Exam (Final exam, intervention) improvement 1, improvement1, control) control) intervention) Data Set 1A: X = 75.4 X = 77.8 X = 6.0 X = 6.6 Control vs. All intervention, participants s = 12.9 s = 12.8 s = 10.9 s = 10.1 Prof. X N = 30 N = 27 N = 30 N = 27 (Fall 2015) X = 67.5 X = 69.8 X = 8.8 X = 8.6 Q1
1.210 Using VR helped provide a better overview of the content. 134 3.51 1.237 Using VR helped to identify the critical concepts from topics in the lesson(s). 134 3.52 1.225An important aspect of the VR lesson design was usability including opportunities for interactionwith the lesson. All the 10-items of this dimension registered mean responses in the direction ofagreement with the items (Table IV). The responses indicated the user interface was userfriendly. The average of the responses was highest for the ability to review the lesson andunderstand the mistakes.Table IV: VR Lessons Usability (N = number of respondents, SD = standard deviation) Overall, I am satisfied with how easy it was to understand
transfer students at four-year institutions, with the goal of strengthening engineering identity and supporting national STEM advancement. Prior to joining FIU, Daniel served as a STEM Specialist with the Ministry of Education in Dubai. He is also an author and founder committed to advancing inclusive and impactful STEM education.Dr. Bruk T Berhane, Florida International University Dr. Bruk T. Berhane received his bachelorˆa C™s degree in electrical engineering from the University of Maryland in 2003. He then completed a masterˆa C™s degree in engineering management at George Washington University in 2007. In 2016, he earned a PhDr. Jingjing Liu, Florida International University Dr. Jingjing Liu is a Postdoctoral
of origami task (O-folding instructions 19 . LI-2).Modules were provided online via the course management system. Participants had one week tocomplete each module and submit the appropriate task deliverable(s) via the online system. Thedeliverable for each origami-based module was a photograph of the object(s) they created (Figure2). The deliverable for each CAD-based module was a SketchUp file of their final drawing(s)(Figure 4). Figure 4: Deliverable of CAD task (C-LI-1).Figure 3: Example of CAD task (C-LI-1) mul-tiview orthographic drawings
ethics and social responsibility and how these views are influenced byorganizational/institutional cultures. We anticipate that our findings will also benefit engineeringstakeholders in both academia and industry, namely by generating new insights about what typesof learning environments and experiences have the biggest impacts on how engineering studentsand professionals perceive and practice ethics, social responsibility, and related concerns.AcknowledgmentsThese materials are based in part upon work supported by the National Science Foundation underGrant Nos. 1449479, 2024301, and 2130924. Any opinions, findings, and conclusions orrecommendations expressed in these materials are those of the author(s) and do not necessarilyreflect the views
Scholars Program” Award # 1153281AbstractThe National Science Foundation awarded the University of Southern Maine with a grant forSTEM Opportunities for Academically Capable and Financially Needy Students entitled the“University of Southern Maine STEM Scholars Program,” Award # 1153281. At the completionof our fifth year, this poster presentation provides an opportunity to present data on the successof our S-STEM program, as well as share some of the best practices learned and applied. TheUSM STEM Scholars Bridge Program has been a model for blending the elements ofrecruitment, retention, and placement into an integrated, comprehensive but non-intrusiveprogram that promotes student success in transitioning from high schools and communitycolleges
):902–18.4. Diekman AB, Brown ER, Johnston AM, Clark EK. Seeking congruity between goals and roles: a new look at why women opt out of science, technology, engineering, and mathematics careers. Psychol Sci. United States; 2010;21(8):1051–7.5. Cheryan S, Master A, Meltzoff AN. Cultural stereotypes as gatekeepers: increasing girls’ interest in computer science and engineering by diversifying stereotypes. Front Psychol. 2015;6:49.6. Ridgeway CL, Correll SJ. Unpacking the Gender System: A Theoretical Perspective on Gender Beliefs and Social Relations. Gend Soc. 2004;18(4):510–31.7. Charles M, Bradley K. Indulging Our Gendered Selves? Sex Segregation by Field of Study in 44 Countries. Am J Sociol. 2009;114(4
results. Based on the emergence of multi-disciplinary storiesrelated to access, pathways, and persistence, it seems likely that this work will need to bepublished in multiple papers.Conference PresentationsTo reach key stakeholders who teach subdisciplines of engineering, we have had our proposals topresent panels sessions at ASEE 15 accepted for Chemical Engineering, MechanicalEngineering, and Industrial Engineering. Page 26.11.7Publications Related to this GrantJournal Publications1. Ohland, M. W., S. M. Lord, and R. A. Layton, “Student Demographics and Outcomes in Civil Engineering in the U.S.,” Journal of Professional Issues in Engineering
length of the data presented. Thisindicates that models optimized with cognitive features are particularly adept at distinguishingbetween binary outcomes. The most accurate predictions were made by ChatGPT 4.0 (as shownin Figure 3(b)), achieving an accuracy of 67% with 2-week data, and improving to 69% accuracyfor both 4-week and 8-week datasets. Nonetheless, when tasked with a more nuanced four-classclassification using only cognitive features, the accuracy across all three datasets falls below50%.The incorporation of background features (C + B) notably enhances binary classificationaccuracy. For example, ChatGPT 4.0’s accuracy for 2-week data improved to 73%, and furtherincreased to 75% and 77% with 4-week and 8-week data, respectively. Gemini
(FYEE) Conference Facilitating Pathways to Engineering: First Year Summer ExperienceProposal AbstractThe [SCHOOL OF ENGINEERING] is a limited enrollment program at the [UNIVERSITY].Unfortunately, not all students who are interested in studying engineering are directly admittedinto the [SCHOOL OF ENGINEERING], but instead are admitted into [UNIVERSITY]’sDivision of Letters and Sciences (L&S). There are many students of minoritized identities (suchas women and racial/ethnic minoritized students) who are not directly admitted into the[SCHOOL OF ENGINEERING], but instead are admitted to the L&S division. Students notdirectly admitted will later have the opportunity to re-apply to the
Program Chair for the ASEE Faculty Development Division, and the Vice Chair for the Research in Engineering Education Network (REEN). He holds degrees in Industrial Engineering (BS, MS) from the National Experimental University of T´achira, Master of Business Administration (MBA) from Temple University, and Engineering Education (PhD) from Virginia Tech.Dr. Jennifer Lyn Benning, Virginia Polytechnic Institute and State University Dr. Jennifer Benning is an Instructor in the Engineering Education Department at Virginia Tech.Donna Westfall-Rudd ©American Society for Engineering Education, 2023 P R E S E NT A T I ON B Y Q U A L L A J O K E T CH U MWALKING BETWEENTWO WORLDSCreating a Framework for
, New Orleans, June 20165. K. Connor, Y Astatke, C. Kim, M. Chouikha, D. Newman, K. Gullie, A. Eldek, S. Devgan, A. Osareh, J. Attia, S. Zein-Sabatto, D. Geddis, “Experimental Centric Pedagogy in Circuits and Electronics Courses in 13 Universities,” ASEE Annual Conference, New Orleans, June 20166. K. Connor, D. Newman, K. Gullie, Y. Astatke, M. Chouikha, C. Kim, O. Nare, P. Andrei, L. Hobson, “Experimental Centric Pedagogy in First-Year Engineering Courses,” ASEE Annual Conference, New Orleans, June 20167. Y. Astatke, K. Connor, J. Attia, O. Nare, “Growing Experimental Centric Learning: The Role of Setting and Instructional Use in Building Student Outcomes,” ASEE Annual Conference, New Orleans, June 20168. Y. Astatke, J
time of flight, t = P + Q*sqrt(-1) for example, could have a physical interpretation.For an object being thrown upward inside a well of depth -120m under a gravity downwardpulling of 9.8 m/s/s, the equation 0 = v0*t + 0.5*9.8*t*t -120 would support a physical situation 2018 ASEE Mid-Atlantic Spring Conference, April 6-7, 2018 – University of the District of Columbiawith a modified depth of (-120 + 0.5*9.8*Q*Q) which carries P as the time of flight since thesqrt(-1) terms must cancel out. Kinematics learning requires a minimum memory capacity whencompared to other physics topics. The long term memory of putting the initial numerical valuesin their appropriate terms could be learned by analyzing each math term in a given equation. Theshort
control blocks (i.e., blocks contain statements ortuple G(V, E, s, t, e), where G’(V, E) is a simple digraph. The vertex set V = Vs *control statements) in M, respectively. The edge set E represents the flow of controls betweenstatement and control blocks in M, i.e., E ⊆ {Vs →Vc ∪ Vc →Vs} where d is a predicate de-t is a termination vertex represents the exit point of M. e contains one edge e1=s →V and acision with either True or false value. s is a start vertex represents the entry point of M andset of edges e2 ⊆ {v →t}. It indicates that a program only has one incoming edge and mayhave a set of e2 if it has multiple return statements.2.3 Construct
can be tested in future research among Native American engineeringstudents, and that can be employed when considering educational interventions for currentstudents.References[1] B. L. Yoder "Engineering by the Numbers," in Engineering College Profile & Statistics Book, Washington DC: American Society for Engineering Education, 2016, pp.11-47.[2] R. W. Lent, S. D. Brown, and G. Hackett, “Toward a unifying social cognitive theory of career and academic interest, choice, and performance,” Journal of Vocational Behavior, vol 45, pp. 79-122, Aug. 1994.[3] R. W. Lent, S. D. Brown, and G. Hackett, “Contextual supports and barriers to career choice: a social cognitive analysis,” Journal of College Student
Paper ID #41826Work in Progress: Transformation Course-Based Undergraduate ResearchExperience (T-CURE)Dr. Heather Dillon, University of Washington Dr. Heather Dillon is Professor and Chair of Mechanical Engineering at the University of Washington Tacoma. Her research team is working on energy efficiency, renewable energy, fundamental heat transfer, and engineering education.EC Cline, University of Washington Tacoma Associate Professor in Sciences and Mathematics, and Director of ACCESS in STEM, an NSF S-STEM supported program that supports students in natural science, mathematics, and engineering at UW Tacoma.Dr. Emese
AchievementAbstractThe National Science Foundation (NSF) Scholarships in Science, Technology, Engineering, andMathematics (S-STEM) program supports low-income, high-achieving STEM students throughscholarships and tailored support services. This paper compares the implementation and impactof three different S-STEM projects across three diverse institutions—Rowan University, AlbanyState University, and Tennessee University, highlighting their distinct approaches and outcomesfor diverse student populations.At Rowan University (RU), a public R2 university in the northeastern United States, the 5-yearS-STEM project — Engineering Persistence: Support System for Low-Income Students toCatalyze Diversity and Success — targets undergraduate engineering students
Science and Engineering Fairs (Evaluation)Science and Engineering (S&E) fairs are a valuable educational activity that are believed toincrease students’ engagement and learning in science and engineering by using inquiry-focusedlearning, engaging students in authentic scientific practices and engineering design processes [1-3], and emphasizing creativity [4, 5]. Proponents also argue that S&E fairs enhance students’interest in science and science careers [6, 7] as well as engineering [2]. From the fair, studentsreport that they have learned more about the scientific process and engineering design, althoughthey may not all feel their attitudes towards STEM fields has improved [2, 8]. In this paper, wefocus on science attitudes, but because
with engineeringoutreach activities to enhance the learning experience of the students enrolled in an engineeringcourse (EGR 299 S course). The objective was to improve the retention of underrepresentedengineering students (majority at CPP) by providing them with opportunities to use theirtechnical engineering skills and by providing them with opportunities to work in diverse andmultidisciplinary teams (building confidence in their knowledge) in order to build relationshipswith K-12 students and to motivate the K-12 students to pursue STEM fields.Introduction to CPP engineering programsCal Poly Pomona is a four-year institution well-known by the diversity of its student population(0.2, 23.6, 3.3, 38.9, 0.1, 19.7, 3.9, 4.4 and 5.7 % of American
. Students establish methodologies for recognizing minerals based on what theyhave learned. From this knowledge, they develop recovery processes motivated by points foreach mineral correctly collected, identified, and accounted for. This can be used as one form ofinsight into the curriculum’s influence on the team’s decision processes and also an indicator ofwhether student learning of science occurred through the use of the structured EDP [30], [32],[33]. The comparison and analysis of the three final days (11,12 and 13) of the curriculumagainst team dialogue is performed.Day 11 Target Group 1 and 2 After preprocessing the conversation for Target Group 1, the result was a 2,824 x20matrix. Target Group 2’s preprocessed conversation produced
that ourapproach can be replicated in other fields and other student populations.AcknowledgementsThis material is based upon work supported by the National Science Foundation under Grants1842166 and 1329283. Any opinions, findings, conclusions, or recommendations expressed in thismaterial are those of the authors and do not necessarily reflect the views of the National ScienceFoundation. We thank the SPHERE research group for their helpful feedback.References[1] S. Kovalchuk, M. Ghali, M. Klassen, D. Reeve, and R. Sacks, “Transitioning from university to employment in engineering: The role of curricular and co-curricular activities,” in 2017 ASEE Annual Conference & Exposition, 2017.[2] R. Korte, S. Brunhaver, and S. Zehr