identity are allowed to naturally separate themselves in this picture of theexperiences of the individuals. For example, students may be traditionally identified as comingfrom one or more underrepresented groups in engineering and, hence, assumed (wrongly) tohave some “different” attitudes about engineering, without attention to the diversity within suchgroups. Instead, the TDA approach allows for the “normative” or popular attitudinal clusters tobe first identified in the data, and then traditionally underrepresented individuals will appearwithin these attitudinal clusters in a way that is faithful to each individual's response (e.g., atraditionally underrepresented student who reflects dominant attitudes towards engineering willappear in that
the National Science Foundation, award #1704350. Any opinions,findings, and conclusions or recommendations expressed in this material are those of the authorsand do not necessarily reflect the views of the National Science Foundation.References[1] W. C. Lee and H. M. Matusovich “A model of co‐ curricular support for undergraduate engineering students,” Journal of Engineering Education, vol. 105(3), pp. 406-430, July 2016.[2] R.F. DeVellis, Scale development: Theory and applications (Applied Social Research Methods). Los Angeles, CA: Sage Publications, 2011.[3] M.D. Gall, J.P.Gall, and W.R. Borg, Collecting research data with tests and self-report measures Educational Research: An Introduction (8th ed.). Boston, MA: Pearson, 2007
interested who transferred to Virginia Techfrom regional community colleges. To date we have interviewed 28 individuals, including fivefocus group participants. The pool includes 11 women, one (male) underrepresented student,seven first-generation college students, and 14 students who transferred from communitycolleges.AcknowledgementsThis material is based upon work supported by the National Science Foundation under GrantNumber 1734834. Any opinions, findings, and conclusions or recommendations expressed inthis material are those of the author(s) and do not necessarily reflect the views of the NationalScience Foundation. We also wish to thank Ms. Claudia Desimone for help with data collection.References[1] M. Boynton, C. A. Carrico, H. M
liberal arts colleges and large, research-intensiveinstitutions would be productive in moving a particular research area forward.Collaboration also with large research institutions not just ERCs.AcknowledgmentsThis material is based upon work primarily supported by the National Science Foundation (NSF)under NSF Award Number CMMI–1632963 and NSF Award Number ERC-1449501. Anyopinions, findings and conclusion, or recommendations expressed in this material are those ofthe authors, and do not necessarily reflect those of the NSF.References[1] D. Lopatto, “Undergraduate Research Experiences Support Science Career Decisions and Active Learning,” CBE—Life Sciences Education, vol. 6, pp. 297-306, winter 2007[2] S.H. Russell, M.P. Hancock, and
Engineering Education at Virginia Tech. He is also Director of International Engagement in Engineering Education and affiliate faculty with the Higher Education Program at Virginia Tech. His research tends to be at the macro-scale, focused on a systems-level perspective of how engineering edu- cation can become more effective, efficient, and inclusive.Ms. Michelle Soledad, Virginia Tech Michelle Soledad is a PhD candidate in the Department of Engineering Education at Virginia Tech. Her research interests include faculty development and data-informed reflective practice. Ms. Soledad has degrees in Electrical Engineering (BS, ME) from the Ateneo de Davao University (ADDU) in Davao City, Philippines, where she continues to be
. The mentor retreat includes several teambuilding activities and providessocial time for the group to get to know each other. The workshop portion of the retreat is meantto inspire students to be good role models and to reflect on what it means to be a mentor. A fewPMLs conduct activities and give presentations on topics such as making the most of LinkedIn,preparing for internship interviews, leading K-12 outreach activities, and doing what’s rightinstead of what’s easy. Having student leaders present these activities not only builds their ownskill sets, but also inspires newer mentors of the organization to become more involved. SPMalumni who recently graduated have also come back to share their experiences with the programand how it helped
about career plans with faculty,discussing academic performance with faculty, and discussing course material with facultyoutside class. Lower satisfaction with instruction and student-faculty interaction sets the tone forlearning; first-year and senior-level students reported lower levels of engagement in tasksassociated with higher-order learning, reflective and integrative learning, and quantitativereasoning.Instructional Strategy. The instructional material of the program draws on current evidence-based pedagogy andcourse design to teach faculty and staff how to create and/or reinvent STEM courses to belearner-focused and engaging. The aims are to increase student learning, improve studentoutcomes in gateway (high-enrollment, first-year
. Each year, werecruit teams of new instructors from multiple institutions to attend POGIL training workshopsand implement POGIL in their IntroCS courses. These instructors attend the standard three-dayPOGIL training workshop and an extra day of CS-specific sessions. Instructors are connected toexperienced POGIL instructors who serve as mentors throughout their first semester teachingwith POGIL. Instructors complete reflective teaching logs and are invited to a one-day mid-yearmeeting.Objectives III and IV: Assess factors that affect faculty adoption and persistence with POGILand assess the impact of using POGIL on student outcomes. These research objectives involve avariety of data sources, including qualitative, semi-structured interviews at
allow more students to go to community college. Wewill continue to collect and analyze qualitative data from our three case sites.AcknowledgementsThis material is based upon work supported by the National Science Foundation EngineeringEducation and Centers under Grant Number EEC-1647298. Any opinions, findings, andconclusions or recommendations expressed in this material are those of the author(s) and do notnecessarily reflect the views of the National Science Foundation.
product of ongoing team meetings between the VirginiaTech, Purdue, and NSBE teams. Through these meetings, the Virginia Tech, Purdue, and NSBEteam members have become better aware of the components necessary to both hold SEEK campsand assess the impact of these camps.AcknowledgementsThis material is based upon work supported by the National Science Foundation EngineeringEducation and Centers under Grant Number DRL-1614710. Any opinions, findings, andconclusions or recommendations expressed in this material are those of the author(s) and do notnecessarily reflect the views of the National Science Foundation.ReferencesNtiri, D. W. (2001). Access to higher education for nontraditional students and minorities in a technology-focused society
differences intheir approach towards solving a problem. Engineering is described with a formal process, withcaution taken by using theory to reach a solution. Making is described as more informal wherethey solution is found through trial-and-error.ConclusionsThe responses for engineering and making were similar with making described as more informalthan engineering across most of the responses. Responses such as trial-and-error for “What isMaking?” reflect learning and understanding of concepts through practice while responses for“What is Engineering?” suggest an understanding through theory and calculations. The ability tolearn through practice and self-guidance show how makers exhibit traits such as lifelong learningfrom The Engineer of 20201
and Drop Problem Solving Interface Part IIAs we continue to work on our prototype, we are writing new items to reflect the concepts thatour research has highlighted as problematic. This involves an item analysis of concepts coveredon mid-terms and final exams that students tend to score the lowest on. One of the primary goalsof this project is to use the innovation in order to systematically study how technology-richenvironments can enhance the learning, teaching, and assessment of complex knowledge.Consequently, our exercises will be designed to enhance and accelerate conceptual learning(rather than use of rote algorithms) by minimizing the extraneous cognitive load of tediouscalculations that can limit student ability to holistically
reflective stagesof learning, preparing them for success in future research and professional design engagement.As a bridge between academic and professional worlds, it can provide the initiating sense oflegitimately belonging to a profession, a crucial step toward long-term productivity within theprofession [11].The application of the impacts of SBL and of the exploration of developing trans-disciplinarystudy firmly rooted in a process acknowledging inherent conflicts between methods and modelsembedded within each participating discipline should provide useful data, insights, andreplicable models for programs seeking to improve minority persistence and success in STEMresearch and professional practice.In addition to the program’s potential to more
modelingrelated questions at the end of the semester. In addition, they provided longer responses andmore specific words related to modeling types at the end of the semester. Further analysis isneeded to understand the extent of their knowledge gain during the semester.AcknowledgementsThis work was made possible by a grant from the National Science Foundation (IUSE 1827406).Any opinions, findings, and conclusions or recommendations expressed in this material are thoseof the author and do not necessarily reflect the views of the National Science Foundation.Table 6 – Word cloud representation of student responses. Course Pre Post Publi c Scho ol Priva te Scho ol Cour se 1 Priva
xProject Management x x xBusiness Impact x x x x xAcknowledgementsThis work was made possible by a grant from The National Science Foundation (1935683). Anyopinions, findings, and conclusions or recommendations expressed in this material are those ofthe author and do not necessarily reflect the views of The National Science Foundation.References[1] S. S. Balram, “Perceptions of Model-based Systems Engineering as the Foundation for Cost Estimation and Its Implications to Earned Value Management,” M.S. thesis, College of Syst. and Ind. Eng., University
students the opportunity to work withindustrial scale equipment. This experience will potentially help students to develop skill setsneeded for the automation field. Future directions include evaluating instructional effectiveness,identifying which aspects of the experience help students learn, and determining optimal timeframes for completing assignments.AcknowledgementsThis material was supported by the National Science Foundation’s Advanced TechnologyProgram (Award no. 1304843). 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.Bibliography[1] U.S. Census Bureau. U.S. Trade in Advanced Technology Products
(PVSC), pp. 2389-2391. IEEE.This material is based upon work supported by the National Science Foundation (NSF) underNSF EEC-1560031, as well as by the NSF and the Department of Energy (DOE) under NSF CANo. EEC-1041895. Any opinions, findings and conclusions or recommendations expressed inthis material are those of the author(s) and do not necessarily reflect those of NSF or DOE.
. The reflection questions toassess SRL strategy use throughout the semester was altered from a previous study assessing theSRL strategies in an Industrial Engineering course3. The interview protocol to examine students’FTP was modified from a previous protocol used to analyze the connection between FTP andproblem-solving, as well as other task-specific, current actions5. This protocol was first tested forvalidity, including a pilot study with four undergraduate engineering students4. A secondinterview protocol was developed to explore the connection between FTP and SRL, as a follow-up to the first interview. Underlying theory and the advice of experts were used to develop thequestions, and the protocol was piloted with an engineering
-based learning wrapped up in Making-Based Learning. We have sharedlearning attributes of making; it could be a useful intellectual exercise to consider how suchvalues are amplified or lessened within an engineering learning culture. The concept of additiveinnovation is mentioned above. Can that be supported in K-12 and undergraduate learningexperiences? Is the current implementation more convergent and less exploratory in nature?The study of Makers, Making and Making-Based Learning is a ripe opportunity for theengineering education community to reflect on our approach to teaching and learning. Making-Based Learning may already fit into some aspects of the engineering curriculum, such as first-year Introduction to Engineering courses and project
based onMessick’s Unified Theory of Validity. Licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 3.0 Unported License.[12] Spencer, D. (2009). Card sorting: Designing usable categories. Rosenfeld Media.AcknowledgementsThis work is supported by the U.S. National Science Foundation award EEC-1564629. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the authors and do no necessarily reflect the views of the National Science Foundation.
1734834. Any opinions, findings, and conclusions or recommendations expressed inthis material are those of the author(s) and do not necessarily reflect the views of the NationalScience Foundation. We also wish to thank Mr. William Michael Anderson and Ms. ClaudiaDesimone for help with data collection.References[1] S. Byun, J. L. Meece, M. J. Irvin, and B. C. Hutchins, “The role of social capital in educational aspirations of rural youth,” Rural Sociology, vol. 77, no. 3, pp. 355–379, 2012.[2] C. Carrico, H. M. Matusovich, and M. C. Paretti, "A qualitative analysis of career choice pathways of college-oriented rural central Appalachian high school students," Journal of Career Development, 2017.[3] Carrico, C.A., “Voices in the
introductory and advanced technical writing courses.Data-driven learningAs the educational marketplace expands, institutions of higher learning are experimenting withhow active learning increases student success. Freeman et al.’s meta-analysis of STEM educationstudies found that active learning significantly increased course grades over didactic methodsand was particularly effective in classes of 50 or less students. In contrast, students were 1.5times more likely to fail a course that lacked active learning strategies [1].The spectrum of active learning ranges from simple activities, such as writing minute papers orpausing for reflection, to more complex activities, such as hands-on technology and inquirylearning. Active learning is being promoted as
understanding the long-term impacts of the work being done in this area. Amongthe tools under consideration for development are the housing of certain evaluation instrumentsdirectly on the site with data to be collected from the instruments available for analysis as well asa recollective survey for past participants in activities to reflect on the impacts those activitieshad on their current education and career choices.AcknowledgementsThis material is based upon work supported by the U.S. National Science Foundation underGrant Nos. 165005, 1625335, 1757402, and 1745199.References [Need to blind][1] Code.org. Available online: https://code.org/ (Accessed 4 February 2019).[2] Girls Who Code. Available online: https://girlswhocode.com/ (Accessed 4
an institution will not be representative, but can be considered a sort of upper bound on the needed mathematics at a more typical institution. • Interviews with faculty may not be completely reliable, they may overstate the mathematics they need. However, this limitation is mitigated by the analysis of course artifacts. • Opinions of faculty are only opinions, they may not reflect the true needs of their students. • The analysis of course artifacts only examined two engineering courses, and is far from comprehensive. • The response rate in the student opinion survey was poor (about10%). This decreases confidence in those results. • Engineering mathematics exists in a complicated
appreciate the valueof different aspects), teamwork and consensus-building, such as that employed in the rubricstudy, could be a valuable strategy for sustainable design. Our poster will explore additionalconnections across our studies which provide insights into how engineering students maydevelop cognitive flexibility and how we can better measure it.AcknowledgementThis material is based upon work supported by the National Science Foundation under Grant No.1811170 Developing and Assessing Engineering Students' Cognitive Flexibility in the Domainof Sustainable Design. Any opinions, findings, and conclusions or recommendations expressedin this material are those of the authors and do not necessarily reflect the views of the NationalScience
material are those of the authors and do not necessarily reflect the views of the NationalScience Foundation.References1. Koretsky, M., Falconer, J., Brooks, B., Gilbuena, D., Silverstein, D., Smith, C., and Miletic, M. 2014. The AIChE Concept Warehouse: A Tool to Promote Conceptual Learning", Adv. in Eng. Ed.2. Meyer, J.H.F. and R. Land. 2003. Enhancing Teaching-Learning Environments in Undergraduate Courses Occasional Report, Centre for Teaching, Learning and Assessment, The University of Edinburgh.3. Male, S.A. and C.A. Baillie. 2011. Threshold capabilities: an emerging methodology to locate curricula thresholds, Research in engineering education symposium. Madrid.4. Champagne, A., L. Klopfer, and R. Gunstone. 1982
relations in the processes and the dynamics connecting climate andecosystems. The overarching goal of this study is to address the needed paradigm shift inundergraduate education of engineering hydrology and water resources to reflect paralleladvances in hydrologic research and technology, mainly in the areas of new observationalsettings,1,2 data and modeling resources,3,4,5 professional practice, and web-based technologies6,7.This paper presents efforts to develop a set of learning modules that are case-based, data andsimulation driven, and delivered via a web user interface. The modules are based on real-worldcase studies from three regional hydrologic ecosystems: Coastal Louisiana, Florida Everglades,and Utah Rocky Mountains. Each ecosystem
otherneighboring cities of Montebello, Downey, La Puente, Norwalk, City of Industry, and easternLos Angeles. It is a federally designated Hispanic Serving Institution (HSI).The total enrollment (unduplicated annual headcount) is approximately 27,000. As its district ismore than two-thirds Hispanic, the students reflect the demographic; 67.7% of the studentsidentify as Hispanic. Among first-time students, 76% state that an academic degree or transfer toa four-year institution is their educational goal; however, 98% of them assess into a basic skillsmathematics course.2 The college is ranked 24th nationally for the number of Associate degreesawarded to Hispanic students.3STARSS ObjectivesThe purpose of STARSS is to support academically talented, financially
exploring scanning probe microscopy using shoeboxes and marshmallows. Throughfunding from the NUE grant, a video camera was purchased to capture nanotechnology-relatededucational activities and to share the outreach activities with the community through othervenues, such as Facebook and YouTube.A group web page for this NUE program was created on nanoHUB. The web page name isNanoSEEd at MSU (Nanotechnology in Science and Engineering Education at Mississippi StateUniversity). The web page name was chosen to reflect that this is a collaborative effort betweenthe College of Arts and Sciences and the Bagley College of Engineering at MSU. The page iscurrently under construction, but materials developed under this grant will be added as theproject
1245482. Any opinions, findings, and conclusions or recommendations expressed inthis material are those of the authors and do not necessarily reflect the views of the NationalScience Foundation.References1. Koretsky, M., Falconer, J., Brooks, B., Gilbuena, D., Silverstein, D., Smith, C., and Miletic, M., "The AIChE Concept Warehouse: A Tool to Promote Conceptual Learning", Adv. in Eng. Ed. (2014).2. Meyer, J.H.F. and R. Land. 2003. Enhancing Teaching-Learning Environments in Undergraduate Courses Occasional Report, Centre for Teaching, Learning and Assessment, The University of Edinburgh.3. Male, S.A. and C.A. Baillie. 2011. Threshold capabilities: an emerging methodology to locate curricula thresholds, Research in