Purdue University’s School of Engineering Education. His re- search interests includes diversity, equity, and inclusion and empathy within the engineering pedagogy.Dr. Joyce B. Main, Purdue University, West Lafayette Joyce B. Main is Associate Professor of Engineering Education at Purdue University. She received an Ed.M. in Administration, Planning, and Social Policy from the Harvard Graduate School of Education, and a Ph.D. degree in Learning, Teaching, and Social Policy from Cornell University. Dr. Main examines student academic pathways and transitions to the workforce in science and engineering. She was a recipi- ent of the 2014 American Society for Engineering Education Educational Research and Methods Division
Engineering Education, vol. 86, no. 2, pp. 69-70, 1997.[4] L. J. Shuman, M. Besterfield-Sacre and J. McGourty, J. “The ABET “Professional Skills” – Can they be taught? Can they be assessed?” Journal of Engineering Education, vol. 94, no. 1, 41-55, January 2005.[5] R. Stevens, A. Johri and K. O’Connor. “Professional engineering work,” in Cambridge Handbook of Engineering Education Research, A. Johri, B. M. Olds, Eds. Cambridge: Cambridge University Press, pp. 119-138, 2014.[6] R. F. Korte, S. Sheppard and W. C. Jordan. “A study of the early work experiences of recent graduates in engineering,” in Proceedings of the American Society for Engineering Education Conference, Pittsburgh, Pennsylvania, 2008.[7] R. Korte
. Fabrikant, “Thinking about the weather: How display salience and knowledge affect performance in a graphic inference task.,” J. Exp. Psychol. Learn. Mem. Cogn., vol. 36, no. 1, pp. 37–53, 2010, doi: 10.1037/a0017683.[12] N. Johnson‐Glauch, D. S. Choi, and G. Herman, “How engineering students use domain knowledge when problem-solving using different visual representations,” J. Eng. Educ., vol. 109, no. 3, pp. 443–469, 2020, doi: https://doi.org/10.1002/jee.20348.[13] J. Heiser and B. Tversky, “Arrows in Comprehending and Producing Mechanical Diagrams,” Cogn. Sci., vol. 30, no. 3, pp. 581–592, 2006, doi: 10.1207/s15516709cog0000_70.[14] S. F. Mazumder, C. Latulipe, and M. A. Pérez-Quiñones, “Are Variable, Array and Object
course. The grading scheme is summarized bypresenting how each of these three categories of practices were implemented.Rethinking the 0-100% ScaleGrading in this course is based around tokens; 26 tokens are required for an A, 23 for a B, 20 for aC, and so on. Students earn tokens by answering exam questions, completing labs, and/orcompleting mini-projects. The token progression was built around Webb’s Depth of Knowledge, alearning taxonomy that breaks learning into 4 levels, shown in Figure 1 [12]. To earn a C,students must meet all of the level 2 objectives. Level 3 and 4 objectives could be completed toearn additional tokens.Depth of Knowledge 1 (DK1) is recalland reproduce. In the case of Circuit Analysis1, a DK1 skill might be using Ohm’s
. Orsmond, S. Merry, and A. Callaghan, “Communities of practice and ways to learning: charting the progress of biology undergraduates,” Stud. High. Educ., vol. 38, no. 6, pp. 890–906, 2013.[17] E. Wenger and B. Wenger, “Communities of practice: A brief introduction,” 2015.[18] K. L. Priest, D. A. Saucier, and G. Eiselein, “Exploring Students’ Experiences in First-Year Learning Communities From a Situated Learning Perspective,” p. 11, 2016.[19] President’s Information Technology Advisory Committee, Computational Science: Ensuring America’s Competitiveness. National Coordination Office for Information Technology Research & Development, 2005.[20] National Research Council, Report of a workshop on the pedagogical aspects of
Paper ID #34949Identifying Signature Pedagogies in a Multidisciplinary EngineeringProgramDr. Kimia Moozeh, University of Toronto Kimia Moozeh has a PhD in Engineering Education from University of Toronto. She received her Hon. B.Sc. in 2013, and her Master’s degree in Chemistry in 2014. Her dissertation explored improving the learning outcomes of undergraduate engineering laboratories by bridging the learning from a larger context to the underlying fundamentals, using digital learning objects.Lisa Romkey, University of Toronto Lisa Romkey serves as Associate Professor, Teaching Stream and Associate Chair, Curriculum
laboratories community through Twitter connections," Twitter for research handbook, 2015, [Online]. Available: http://www.academia.edu/download/41349806/Massimo.Menichinelli_MakerLaboratoriesCommunit y_on_Twitter_PREPRINT_HIRES.pdf.[15] V. Wilczynski, "A Classification System for Higher Education Makerspaces," 2017.[16] M. B. Jensen, C. C. S. Semb, S. Vindal, and M. Steinert, "State of the Art of Makerspaces - Success Criteria When Designing Makerspaces for Norwegian Industrial Companies," Procedia CIRP, vol. 54, pp. 65–70, Jan. 2016.[17] E. Mañas Pont, "Analysis and comparison of representative locations in the general makerspace panorama," Universitat Politècnica de Catalunya, 2014.[18] Craig Forest, Ms. Helena Hashemi
andPractice, vol. 14, (1), pp. 309-322, 2014.[17] *S. B. Wortel, "No title," STEM Identity Formation through Undergraduate MentoringExperiences and Middle School Learning in an Urban Informal Afterschool Program, 2019.[18] *M. R. Gates, Middle School Mathematics and Self-Efficacy at a SoutheasternMassachusetts Middle School. 2015.[19] *R. Reynolds, Reconstructing “digital Literacy” in a Constructionist Computer Club: TheRole of Motivation, Interest, and Inquiry in Children's Purposive Technology Use. 2008. [20]*D. C. Smith, The Effects of Title I-Funded Mathematics and Language Arts Tutoring onRENAISSANCE Standardized Test Scores. 2006.[21] *B. Gallegos, "The Role of Virtual Avatars in Supporting Middle School Students fromCulturally and
his Ph.D. in Sociology from the University of Notre Dame and his interests include social movements, political sociology, Latin American Studies, sociology of disasters, digital media communication, and research methods. Most of his work is cross-national, comparative, and with a regional focus on Latin America, Mexico and the US-Mexico Border. His work has been published in Mobilization, Sociological Inquiry, Sociological Perspectives, and Qualitative Sociology, among others.Lorissa B. B. Humble, New Mexico State University Lorissa Humble is a recent graduate from New Mexico State University with a Bachelor’s in sociology and a minor in math. She is set to begin her Master’s program in applied statistics in Fall
they believe each engineering undergraduate degreeprogram should be able to cultivate in their students, including: (a) an ability to apply knowledgeof mathematics, science and engineering, (b) an ability to design and conduct experiments, aswell as to analyze and interpret data, (c) an ability to design a system, component, or process tomeet desired needs within realistic constraints such as economic, environmental, social, political,ethical, health and safety, manufacturability, and sustainability, (e) an ability to identify,formulate, and solve engineering problems, and (g) an ability to communicate effectively (ABETCriterion 3. Student Outcomes (a-k)). We argue that all of these skills are essential componentsof the argumentation process
behavior as they fill incells in the matrices. One of the strengths of their paper is the correspondence between examwrappers and professional software engineering practice, but that was not evident in the surveyinstrument itself. There was no software engineering specific content except for the errorclassification.The two entries for our study refer to (1) the midcourse exam wrapper given twice during theterm (appears in Appendix A), and (2) an end-of-term exam wrapper given in Appendix B. Table 2. Characterization and Counts of Exam Wrapper Questions: Total (with Open-ended in Parentheses) paper total preparation performance planning other [7] 4(2
-9830.2011.tb00003.x.[2] J. E. Froyd and J. R. Lohmann, “Chronological and Ontological Development of Engineering Education as a Field of Scientific Inquiry,” in Cambridge Handbook of Engineering Education Research, A. Johri and B. M. Olds, Eds.: Cambridge University Press, 2014.[3] B. K. Jesiek, L. K. Newswander, and M. Borrego, “Engineering Education Research: Discipline, Community, or Field?,” J. Eng. Educ., vol. 98, no. 1, pp. 39–52, 2009, doi: 10.1002/j.2168-9830.2009.tb01004.x.[4] J. Seniuk Cicek and M. Friesen, “Epistemological Tensions in Engineering Education Research: How do we Negotiate Them?,” in 2018 IEEE Frontiers in Education Conference (FIE), San Jose, CA, USA, 2018, pp. 1–5.[5] B. Jesiek, M. Borrego, K. Beddoes
results of this research, first-year and second-yearstudents found online learning as the worst outcome of the pandemic compared to social distancingand unemployment. Hence, integrating self-discipline training or courses into curriculumespecially for new college students will be a game changer during these unprecedented times.Imbedding more active learning elements, group projects and assignments, optional in-person labsand meetings, and breakout rooms activities to online courses besides sending weekly updates canstimulate students and mitigate the effect of social isolation.References[1] J. Crawford, K. Butler-Henderson, J. Rudolph, B. Malkawi, M. Glowatz, R. Burton, P. A. Magni, S. Lam, “COVID-19: 20 countries’ higher education intra
Conference and Exposition, 2013.[12] H. B. Carlone and A. Johnson, “Understanding the science experiences of successful women of color: Science identity as an analytic lens,” J. Res. Sci. Teach., vol. 44, no. 8, pp. 1187–1218, Oct. 2007.[13] H. G. Murzi and L. D. McNair, “Comparative dmensions of disciplinary culture,” in ASEE Annual Conference and Exposition, 2015.[14] M. Eliot and J. Turns, “Constructing professional portfolios: Sense-making and professional identity development for engineering undergraduates,” J. Eng. Educ., vol. 100, no. 4, pp. 630–654, 2011.[15] D. M. Riley, “Aiding and ABETing: The bankruptcy of outcomes-based education as a change strategy,” in ASEE Annual Conference and Exposition
: Rethinking the racial wealth gap,” Social Currents, vol. 4, no. 3, pp. 199–207, Jun. 2017, doi: 10.1177/2329496516686620.[8] A. B. Abad, “Paying the Price: College Costs, Financial Aid, and the Betrayal of the American Dream by Sara Goldrick-Rab,” The Review of Higher Education, vol. 42, no. 1, p. E-7-E-10, 2018, doi: 10.1353/rhe.2018.0041.[9] A. M. Shahiri, W. Husain, and N. A. Rashid, “A Review on Predicting Student’s Performance Using Data Mining Techniques,” in Procedia Computer Science, Jan. 2015, vol. 72, pp. 414–422, doi: 10.1016/j.procs.2015.12.157.[10] N. Kronberger and I. Horwath, “The Ironic Costs of Performing Well: Grades Differentially Predict Male and Female
Covid-19 on Higher Education around the World. 2020.[2] J. J. B. Joaquin, H. T. Biana, and M. A. Dacela, “The Philippine Higher Education Sector in the Time of COVID-19,” Front. Educ., vol. 5, no. October, pp. 1–6, 2020, doi: 10.3389/feduc.2020.576371.[3] T. Khraishi, “Teaching in the COVID-19 Era: Personal Reflections, Student Surveys and Pre-COVID Comparative Data,” Open J. Soc. Sci., vol. 09, no. 02, pp. 39–53, 2021, doi: 10.4236/jss.2021.92003.[4] D. Chadha et al., “Are the kids alright? Exploring students’ experiences of support mechanisms to enhance wellbeing on an engineering programme in the UK,” Eur. J. Eng. Educ., vol. 0, no. 0, pp. 1–16, 2020, doi: 10.1080/03043797.2020.1835828.[5] M. Schar, A
. Liu, D. Byrne, and L. Devendorf, “Design for collaborative survival: An inquiry into human-fungi relationships,” Conf. Hum. Factors Comput. Syst. - Proc., vol. 2018-April, pp. 1–13, 2018.[16] W. Odom, R. Wakkary, Y. K. Lim, A. Desjardins, B. Hengeveld, and R. Banks, “From research prototype to research product,” Conf. Hum. Factors Comput. Syst. - Proc., pp. 2549–2561, 2016.[17] S. Hauser, D. Oogjes, R. Wakkary, and P. P. Verbeek, “An annotated portfolio on doing postphenomenology through research products,” DIS 2018 - Proc. 2018 Des. Interact. Syst. Conf., pp. 459–472, 2018.[18] S. Hyysalo, C. Kohtala, P. Helminen, S. Mäkinen, V. Miettinen, and L. Muurinen, “Collaborative futuring with and by
Paper ID #34308Work in Progress: Measuring Stigma of Mental Health Conditions and ItsImpact in Help-seeking Behaviors Among Engineering StudentsMatilde Luz Sanchez-Pena, University at Buffalo Matilde Sanchez-Pena is an Assistant Professor in engineering education at University at Buffalo - SUNY. Her current research areas include (a) advancing institutional diversity, (b) cultures of health in engineer- ing education, and (c) data analysis skills of engineers. She aims to promote a more equitable engineering field in which students of all backgrounds can acquire the knowledge and skills to achieve their goals. She
, played into the meritocratic game to prove that she could solve difficult equationseasily and thus was a “good engineer.” Yet, her approach was common, as Seron et al. [19] hasdocumented that the culture of engineering reproduces a particular way of being, in that itsocializes women into believing that raising concerns about marginalization is “tangential … towhat counts as the “real” practical and objective work of engineers” [p. 4]. At the end of the fourthinterview, Kitatoi’s reflection of what constituted a “good engineer” was filled with resentment,while she received a B in her statics class, the image of who belonged in engineering left anunpleasant feeling, stating, I think it’s really messed up. I think a lot of the times tambien
artsand communication university students towards science literacy activities and applications. Sahen-dra linked mathematical self-efficacy with representation during mathematics problem-solving andfound that high self-efficacy students were more likely to use strategies requiring multiple repre-sentations, and reference those representation when verifying their solutions [17]. In engineering,Lent et al. [14] measured self-efficacy of succeeding in engineering courses as (a) completing basicscience and math requirements with good grades, (b) excelling in upcoming semesters and years,and (c) completing required upper-level courses for the degree. Carberry et al. [18] developedan instrument for measuring engineering design self-efficacy. It asked
Bandura is used as the theoretical foundation for this study. It incorporatesthe elements of behavioral and the cognitive aspects of learning such as attention, motivation,and memory functions [13-14]. According to this theory, the learning outcomes depend on threefactors:(a) personal factors: internal cognitive factors based on knowledge and attitude(b) behavioral factors: outcome expectations influenced by observable behavior in others(c) environmental factors: social norms, community access, social support, and barriers The social cognitive theory was applied to this study to explain the relationship between anindividual student, the peers or instructor/TA, and the learning environment. A visual illustrationmodeling this relationship is
ofthree NGSS disciplinary core ideas (ETS1.A, ETS1,B, and ETS1.C) that relate to the three-stepNGSS engineering design process. More information about these topics can be found on theirstandards summary page [34].The working draft of the assessment instrument contained at total of 17 items, some of whichwere supplementary assessment measures and alternate, short form, versions of the ADE items.These consisted of ten selected-response items focused on concepts represented in NGSSstandards MS-ETS1 and MS-ETS1-2. We also designed four simple problem-solving itemsaimed at capturing indications of students’ ability to make use of the engineering design process,touching to elements in both NGSS standards MS-ETS1-3 and MS-ETS1-4, and cross
one’s skills and experiences beyond the classroom. Astudy was conducted at NYU Tandon School of Engineering and found students lack support inidentifying and developing their career pathways. This study indicates that a combinede-portfolio and micro-credentialing platform could benefit students by a) providing students witha tool to reflect on and showcase their experiences, b) matching students with upper-class andalumni mentors in career pathways they are interested in, and c) providing them with curatedlists of on-campus and experiential opportunities and micro-credentials that would support theircareer pathways.IntroductionEvery student’s experience through engineering school culminates in different results -- students’future pathways range
the activities of various stages.Deliverables are achieved at the end of each activity. The gate keepers review thedeliverables with the help of the criteria and take decisions (GO/KILL/HOLD/RECYCLE)during the gate reviews.For example, the first stage is to establish context and need. The main activities of this stageare namely . a. Survey stakeholders b. Collate the inputs from various stakeholdersThe working team consists of the faculty members responsible for quality improvement inprograms, curriculum redesign and some more faculty members to carry out the activities partof this stage. The gate keepers are the senior administrators of the academic institution, thehead of the department of the program concerned and curriculum design
problems), and (b) engineering as knowledge (comprising thespecialized knowledge that helps and motivates the process of problem-solving). Moreover,Streveler et al. [3] posit that gaining conceptual knowledge in engineering science is a vitalfactor in the development of competence and expertise as professional engineers.As recommended by the Accreditation Board for Engineering and Technology (ABET),technical skills are one of the attributes that an engineering student must obtain by the time ofgraduation [12]. The term technical skills encompass the knowledge and abilities required toperform a specialized task. These skills are practical and have real-world applications. Forstudents to develop these critical skills, engineering faculty must teach
citationpractices belie a more complex system of relationships. Historically, they have established powerrelationships among authors, ideas, and larger sociotechnical systems within the university[26].Our citations reflect our reading practices while establishing field boundaries and contours andultimately funneling into the larger economy of the university. They undergird this universityeconomy in a number of ways: (a) we form communities of practice/discourse communities inhow we cite, excluding and including particular ways of knowing; (b) we give particular ideaspower and visibility in how we cite; (c) we decide whose work matters, who should be tenuredand promoted, who belongs; and (d) we teach ethics and intellectual property through citations.These
the basic concepts taught in thecore STEM courses is a strong contributing factor to student attrition. Strategies to improvelearning experiences in STEM courses by all students at colleges and universities are thereforeneeded so that they persist in the STEM career pipeline. A group of STEM faculty members at aHistorically Black University is committed to this important need through the far-reaching use ofVirtual Reality (VR) in its STEM courses and investigating its impact on learning outcomes,engagement and persistence in STEM.The two big questions that continue to be examined by STEM education experts are: (a) Why dostudents change their majors from a STEM to a non-STEM major? and, (b) Why do studentsstruggle with STEM concepts leading
used for the purpose ofmapping and geo-spatial analysis. This software enables students to use the GPS application forasset management showing natural as well as in-built assets on the ground. The students werealso exposed to learning opportunities though mobile museums organized in the schools bySouth Florida Science Center and Aquarium (Figures 4b and 4c). a) b) c)Figure 4. Student Learning Activities: a) Asset Mapping of School Playground usingArcGIS Collector App, b) Mobile Museum in Middle School, c) Mobile Museum Set-up inHigh School Gymnasiumiv) Family Café events for the Middle and High SchoolsParental involvement in a student’s education has a
bring to their early learningexperiences.References[1] L. Kaczmarczyk, E. Petrick, J. P. East, and G. L. Herman, “Identifying studentmisconceptions of programming,” in Proceedings of the Forty-First ACM Technical Symposiumon Computer Science Education, 2010, Conference Proceedings, pp. 107–111.[2] R. Lister, B. Simon, E. Thompson, J. L. Whalley, and C. Prasad, “Not seeing the forestfor the trees: Novice programmers and the solo taxonomy,” in Proceedings of the 11th AnnualSIGCSE Conference on Innovation and Technology in Computer Science Education, ser.ITICSE ’06. New York, NY, USA: Association for Computing Machinery, 2006, p. 118–122.[Online]. Available: https://doi.org/10.1145/1140124.1140157[3] J. D.Bransford, A. L.Brown, and
Classification Scheme for ‘Introduction to Engineering’ Courses: Defining First-Year Courses Based on Descriptions, Outcomes and Assessment,” in Proceedings of the American Society for Engineering Education Annual Conference & Exposition, 2014.[14] B. Schneider, “The People Make the Place,” Pers. Psychol., vol. 40, no. 3, pp. 437–453, 1987.[15] E. Godfrey, “Cultures within Cultures: Welcoming or Unwelcoming for Women?,” in Proceedings of the American Society for Engineering Education Annual Conference, 2007.[16] E. Godfrey, “Understanding Disciplinary Cultures: The First Step to Cultural Change,” in Cambridge Handbook of Engineering Education Research, A. Johri and B. M. Olds, Eds. New York, NY