Paper ID #23384Early-career Plans in Engineering: Insights from the Theory of Planned Be-haviorTrevion S. Henderson, University of Michigan Trevion Henderson is a doctoral student in the Center for Higher and Postsecondary Education (CSHPE) at the University of Michigan. He recently earned his master’s degree in Higher Education and Student Affairs at The Ohio State University while serving as a graduate research associate with the Center for Higher Education Enterprise. Trevion also hold’s a Bachelor’s degree in Computer Science and Engineer- ing from The Ohio State University, where he served as a research assistant in
. c American Society for Engineering Education, 2016 What Do You Want to Do with Your Life? Insights into how Engineering Students Think about their Future Career PlansAbstractThis research paper describes findings from a qualitative analysis of engineering students’ self-reported future career plans on the 2015 Engineering Majors Survey (EMS). The EMS wasdesigned to examine current engineering students’ career goals, especially surroundinginnovative work, and is based in the theoretical framework of Social Cognitive Career Theory(SCCT). With the open-ended responses on the EMS, we can develop a deeper understanding ofstudents’ plans in their own words, providing insights into how they think about their careers andwhy they
the University of Toronto in Canada and a Master’s Degree in Engineering Sciences from Pontificia Universidad Cat´olica de Chile. His research focuses on areas of automated rea- soning in Artificial Intelligence; specifically, automated planning, search and knowledge representation. Currently his research focuses on understanding how machine learning techniques can be applied to the in- telligent decision-making process, on the applicability of reasoning techniques and learning to databases. He is also an assistant researcher at the Millennium Institute for Foundational Research on Data. c American Society for Engineering Education, 2019WIP: Engaging engineering teaching staff with
gathering 2 2 Gather information and resources (observe) organization3 Concept Selection 3 Idea generation4 Conceptual 3 Form an explanatory hypothesis Monitoring combination 4 Idea evaluation5 Idea generation Design and Perform an experiment and 5 Planning 46
out a box, like a rectangle with a laser cutter, and I added this cool design on there as well. Overcome 9% I'm ready for any challenge … I have to keep trying even though if, like sticking say when the computer was shutting down on me, I just didn't give up. point Not give up when I have sticking points, but keep trying. Multi-step 13% My confidence level is pretty high. We've got a project going on, plan actually, we're in the process of just the very basics of creating a vacuform table, so we've started a base. We're attaching the legs very soon… Project 9% I think that's a pretty easy project
weighted survey sample of roughly two thousand early careerengineering graduates. The research is broadly situated in social cognitive career theory anddraws data from the Pathways of Engineering Alumni Research Survey (PEARS), which was apart of the National Science Foundation (NSF) funded Engineering Pathways Study (EPS).Analyses for this study followed a two-step process. First we categorized the engineeringgraduates into seven occupational groups, and then we compared these seven groups along sixother measures of doing engineering work. Four years after graduation, graduates employed inengineering and computer-related occupations tended to identify themselves, their currentposition, and future plans as engineering-related, while graduates
toendure.The proposed measurement framework of SoTE defines nine different criteria. Each criterioncovers one part of the educational system and also the approach. Accordingly, each criterion hasits own set of key performance measures (KPMs). For every KPM, there is one or more keyperformance indicator (KPI) to enable the measurement. Every KPI has its own analytic rubricthat will aid the calculation of different indicators including a one main indicator called theSustainability Indicator (SI) – See Figure 2. The nine criteria are expanded into 34 KPMs.The sustainability criteria upon which we judge SoTE is shown in Table 1. Criterion 1,Leadership and Governance, measures the sustainability of the institutional strategic plans andthe degree of its
workforce.Dr. Joyce B. Main, Purdue University at 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 Apprentice Faculty Award, the 2015 Frontiers in Education Faculty Fellow Award, and the 2019 Betty Vetter Award for Research from WEPAN. In 2017, Dr. Main
Engineering Careers (PEARLS) and for Building Capacity at Collaborative Undergraduate STEM Program in Resilient and Sustainable Infrastructure (RISE-UP). Both projects are funded by NSF.Dr. Sonia M. Bartolomei-Suarez, University of Puerto Rico, Mayaguez Campus Sonia M. Bartolomei-Suarez is a Professor of Industrial Engineering at the University of Puerto Rico Mayag¨uez (UPRM). She graduated with a BS in Industrial Engineering from UPRM (1983), a MSIE (1985) from Purdue University, and a PhD in Industrial Engineering (1996) from The Pennsylvania State University. Her teaching and research interests include: Discrete Event Simulation, Facilities Planning, Material Handling Systems, Women in Academia in STEM fields
inengineering.In this work-in-progress paper, we describe a design-based research project that explores howstudents adopt positive learning behaviors and dispositions through a course, because positivelearning behaviors and dispositions have been shown to increase persistence through challengesand setbacks4.We have designed a course titled Engineering the Mind as an eight-week, second-half semestercourse that is offered for one semester-hour of credit. We plan to pilot this course in Spring 2017to prepare for the Fall 2017 offering.BackgroundDesign-Based ResearchDesign-based research (DBR) is a research paradigm that attempts to bridge laboratory studieswith complex, instructional intervention studies5. DBR is described as “theoretically-framed,empirical
that an individual has in creative and generative processes. It describes an individual's push to search for ways to be innovative and design and test out new ideas for all or a component of a system based on a set of constraints. Project Management The skill set an individual needs to help them bring projects to life, including organization, planning, and decision-making skills. Analysis An individual’s ability to apply math and science and solve the relevant governing equations during design and evaluation. Collaboration Those skills that are necessary for working with other
and college levels: Institution and college normative documents.Our selection of normative documents at the institutional and college-level is adapted fromWilliam (2013), who argues that diversity planning initiatives tend to take on a normative roleand are regarded as a change-making tool. William (2013) suggests that mission and visionstatements, diversity plans, diversity reports, and academic and strategic plans can provide aholistic representation of the normative values, beliefs, and ideologies espoused by an institutionof higher education, in addition to also delineating strategies for achieving them [19]. Withinengineering education, Cross, Lee, Gaskins, and Jones (2018) have taken a similar approach foranalyzing diversity initiatives
activities, iv) Family Caféevents, and v) Summer workshop for STEM teachers.i) NASA-STEM content developmentThe NASA STEM contents were first identified based on the existing lesson plans adopted inparticipating schools in Broward and Palm Beach Counties in Florida. Then, the NASA STEMcontents were embedded into the NGSSS based on the lesson plans and instructional calendar.The methodology adopted for NASA-STEM content development is shown in Figure 1. Thevarious steps were: i) Review and analyze the existing curriculum followed by the schools andwork closely with the STEM teachers to identify available time-slots to introduce NASA-STEMcontent to their existing lesson plans; ii) Download the NASA’s STEM content for Grades 6, 8,11-12 from the NASA
Paper ID #32288Instrumentation for Evaluating Design-learning and Instruction WithinCourses and Across ProgramsSteven Santana, Harvey Mudd College American c Society for Engineering Education, 2021 Instrumentation for evaluating design learning and instruction within courses and across programsIntroductionThis work-in-progress (WIP) paper communicates the initial planning and design ofinstrumentation, deployed through action research, to assess students’ growth in designlearning and their belonging and identity in engineering. The ultimate goal of the datagenerated through this
across all 26-items for all three strategies (i.e., 78 itemscollectively). However, VECTERS can be considered as three sub-instruments addressing thestrategies of formative feedback, real-world applications, and student-to-student discussion.Therefore, Cronbach’s alpha coefficient calculations were applied to each of the three sub-instruments. As recommended by DeVallis 16, Cronbach’s alpha levels of 0.7 or higher weredesired.Construct validity. VECTERS construct validity was evaluated by examining relationshipsbetween respondents’ self-reports of extent to which the three strategies are currently beingimplemented and are planned to be implemented. For each strategy, a 2x3 matrix was produced;these indicated the relationship between
Pontificia Universidad Cat´olica de Chile. Jorge holds a PhD in Computer Science from the University of Toronto in Canada and a Master’s Degree in Engineering Sciences from Pontificia Universidad Cat´olica de Chile. His research focuses on areas of automated rea- soning in Artificial Intelligence; specifically, automated planning, search and knowledge representation. Currently his research focuses on understanding how machine learning techniques can be applied to the intelligent decision-making process, on the applicability of AI techniques for enhancing emotional health in Engineering Education. He is also an assistant researcher at the Millennium Institute for Foundational Research on Data
, research suggests that preserviceteachers do not feel academically prepared and confident enough to teach engineering-relatedtopics.This interdisciplinary project provided engineering students with an opportunity to developinterprofessional skills as well as to reinforce their technical knowledge, while preserviceteachers had the opportunity to be exposed to engineering content, more specifically coding, anddevelop competence for their future teaching careers. Undergraduate engineering studentsenrolled in a computational methods course and preservice teachers enrolled in an educationaltechnology course partnered to plan and deliver robotics lessons to fifth and sixth graders. Thispaper reports on the effects of this collaboration on twenty
participation (e.g., as subjects in research studies) with an uncertain value proposition.Research method innovations are needed to reduce barriers to access, minimize risks and costs toparticipants, and more quickly generate actionable insights for partner firms.Given the preceding discussion of trends and challenges, we plan to carry out and investigate theefficacy of multi-institutional, multi-sites field research using novel methods such as agileethnography, trace ethnography, and network ethnography. These methods are new andevolving, and thus have scarcely been used to study engineering practice. Yet they appear verypromising given their potential to generate research findings much more rapidly and with a
thinking involves considering holistic approaches toproblem-solving that understand and analyze the complexity of various elements and theirinterrelationships in the overall ecosystem (McKenna, Froyd, & Litzinger, 2014). Strategicthinking is the ability to create a plan of action to achieve the desired vision and act upon theother ways of thinking (Warren et al., 2014).Guided by this framework, the research question addressed by the study is: What is the factor structure that captures futures, values, systems, and strategic thinking associated with interdisciplinary engineering education research?Research MethodsInstrument DevelopmentThe survey instrument (see Appendix) was developed through iterative construction andvalidation
decide on the subject matter to cover inthe PLTL workshops. The two selected subjects were Resume Building and Creation of E-portfolios. They had already received a training on resume building and the creation of e-portfolios, and the goal was to help other LIATS to complete theirs. Two planning sessions wereheld previous to each session to decide on logistics, contents, and practice. Then all the studentsparticipating in the PEARLS Program were equally distributed among the ten peer leaders.Training the leaders was done using a cognitive apprenticeship framework, as it works well withPLTL [13, 14]. PLTL is rooted in Vygotsky’s zone of proximal development [2]. Here the PLTLcoordinator models behaviors for the PLTL leader to follow, providing
rubric marking was conducted by raters whose training addressed the specificcontext and content of course assignments. Raters were undergraduate students and graduatestudents, with faculty called on for subject area expertise when necessary. The raters wereengaged longitudinally through the study and where possible markers used across disciplines toprovide consistency of ratings. This stresses the importance of having a well-planned, well-supported process to rate artefacts using the VALUE rubrics and an environment whichfacilitates rater discussion and interaction.Participants and ResultsParticipants consented to participate in standardized tests and to have samples of their coursework scored by trained graders using VALUE rubrics. The
as a resource for inquiry anddesign, rather than as a challenge 20, 21. The three authors of this paper were the co-facilitators ofthe CBE Institute.The institute included the following phases: • Learn - Week 1 (Three 2.5-hour sessions): During the learn “Learn” phase participating volunteers were engaged in learning through exploration of the engineering design process. They designed and tested prototype solutions to two engineering design problems posed by the institute instructors. • Plan - Week 2 (Three 1- hour sessions): During the “Plan” phase the participants worked in pairs to plan an engineering module for elementary students. The problems had been previously
Contemplation Contemplation I have considered using the instructional practice but have not taken any steps to implement it Preparation Preparation I am currently developing plans/curriculum to implement the instructional practice in my course Action Action I will implement the instructional practice for the first time in my course this upcoming term Maintenance Maintenance I have been regularly using and modifying the instructional practice in my course Termination Standardized
field and prior engineering identity studies. In particular, we seek tounderstand which factors may influence Hispanic students’ engineering identity development.We begin by answering the following research questions: 1. How do the engineering identity, extracurricular experiences, post-graduation career plans, and familial influence of Hispanic students attending a Hispanic Serving Institution (HSI) differ from those of Hispanic students attending a Predominantly White Institution (PWI)? 2. How do the same measures differ for Hispanic students attending a PWI from those of non-Hispanic white students at that PWI? 3. How do the same measures differ for Hispanic students attending an HSI from those of non-Hispanic
enrollment [19]. Therefore, the need for and potential of the S-STEMProgram at Kennesaw State University are enormous.Program expectations for students include progression items (target GPA, course enrollment andstatus), connective activities (faculty mentors, advisors, industry partners, outreach), and optionalactivities (living learning community, career services events, undergraduate research, studentorganizations, tutoring). Achievement of these expectations is driven through the mentor/menteerelationship where both provide and accept feedback, and advice and resources are activelysolicited and provided to encourage students’ responsibility for their learning. The first year ofthe project primarily focused on planning, marketing, and recruitment
Computing in Engineering is a course required for all 200 engineering students ata research university in Massachusetts. In the last few years, the course underwent a transitionfrom a large, lecture-based course taught by one professor to several smaller sections taught bydifferent professors, each using their own instructional technique. In the spring of 2019, fourprofessors taught the Introduction to Computing Course using three different instructionalmethods. All courses had the same syllabus goals, outlined in Table 1 below. Table 1. Course Goals (as defined in the 2019 syllabi) Overall Goal Key ComponentsFluency in a Master basic Know common Use good code Plan
or radio to express my concerns about global environmental, social, or political problems. GCE2.5: Before I graduate, I will sign an email or written petition seeking to help individuals or communities abroad. GCE2.7: Before I graduate, I will contact or visit someone in government to seek public action on global issues and concerns.Removed for significant cross-loadings: GCE2.11: Before I graduate, I will participate in a campus forum, live music, or theater performance or other event where people express their views about global problems. GCE1.11: During my undergraduate career, I have been or plan to get involved in a program that addresses the global environmental crisis. GCE1.12: After I graduate, I plan to get involved
interests include the use of machine learning in general and deep learning in particular in support of the data-driven and self-driven management of large-scale deployments of IoT and smart city infrastruc- ture and services, Wireless Vehicular Networks (VANETs), cooperation and spectrum access etiquette in cognitive radio networks, and management and planning of software defined networks (SDN). He is an ABET Program Evaluator (PEV) with the Computing Accreditation Commission (CAC). He served on many academic program design, review and planning efforts. He serves on editorial boards of multiple journals including IEEE Communications Letter and IEEE Network Magazine. He also served as chair, co-chair, and technical
Mexico State University. He completed his bachelor’s degree in 2018 and is set to graduate this summer after completing a thesis project on microaggressions amongst undergraduates in STEM using a focus group methodology. He has worked as a research assistant for the past two years on a grant sponsored by the NSF that explores URM success. He plans to apply to a PhD program for the Fall of 2021.Miquela K Gorham, Miquela Gorham is a graduate student at New Mexico State University in the Sociology Department. She also completed her Bachelor’s of Arts in Sociology at New Mexico State University. Her research interest focuses on sociology of education, social inequality, and race and ethnicity.Miss Lorissa Humble, New
ASEE Literature on the Maker Movement,” presented at the ASEE Annual Conference and Exposition, Conference Proceedings, 2018, vol. 2018.[9] V. Wilczynski, A. Wigner, M. Lande, and S. Jordan, “The Value of Higher Education Academic Makerspaces for Accreditation and Beyond,” Plan. High. Educ., vol. 46, no. 1, pp. 32–40, 2017.[10] L. Martin, “The promise of the maker movement for education,” J. Pre-Coll. Eng. Educ. Res. J-PEER, vol. 5, no. 1, p. 4, 2015.[11] J. Oplinger, M. Lande, S. Jordan, and L. Camarena, “Making Leaders: Leadership Characteristics of Makers and Engineers in the Maker Community.,” Am. J. Eng. Educ., vol. 7, no. 2, pp. 65–82, 2016.[12] S. Vossoughi, M. Escudé, F. Kong, and P. Hooper, “Tinkering, learning