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
settingup linkages with industry which often leads to employment opportunities for graduates, co-opactivities, and potential development of collaborative research programs. Unfortunately, adjunctsare marginalized by the academic systems in place today; and their contributions to the academicprocess are undervalued. Next, the paper reports on the success story of an adjunct, a practitionerwith good credentials, who “teamed-up” with a “full-time” faculty, in an attempt to bring thepractice to 4thyear students in a geotechnical/ foundation engineering class. The success achievedin meeting course objectives, was attributed, in large measure, to proper planning andcoordination that preceded course delivery. Plus, the willingness, experience and
design and implementation ofcollaborative ill-structured tasks using a research-based framework that outlines the necessaryelements of such tasks: an introduction to the problem that provides context, a description of theproblem itself, the specific task(s) students are expected to achieve as a group, supplementarymaterial that provides information useful for solving the task, and scaffolding tools that studentscan use to develop plans, draw diagrams, and generate solutions [6]. This paper presents amethod to evaluate the design of ill-structured tasks in relation to the interaction processes thatstudents used in their groups. The paper showcases the use of our method by evaluating thedesign of one ill-structured task, and provides suggestions
activity within our modeling-based learning experience.Final design. All three of these bodies of literature inform our final learning design, pullingtogether pedagogical and learning theories while structuring the actual activity into four uniquephases. Figure 1 shows how the alignment of these bodies of literature produced the final design. Figure 1. Alignment of theory and practices to produce our final learning design.The final modeling-based learning experience design consists of four phases. First is Planningthe Model, where students work together to pull from their experiences and observations of thephenomenon within a group to create and explore different modeling pathways. In this stepstudents develop and document a plan for
to participate in ‘teachingsquares’. In these ‘teaching squares’, the faculty members participated infacilitated discussions on class session planning, observed each other andcollected learning assessment data as evidence of attainment of studentlearning outcomes. In this paper, results from these interventions on theattainment of specific workshop outcomes among faculty includingimplementation of some best practices in teaching will be reported. Specificattitudes and misconceptions related to teaching among higher educationpractitioners in India will be discussed.BackgroundAll India Council for Technical Education (AICTE) dashboard [1] shows 3124approved engineering education institutions in India with a total faculty countof 338,193
graduate program in engineering education Jessica Watkins, Vanderbilt University Merredith Portsmore, Tufts University Rebecca Swanson, Tufts University IntroductionAt the end of an 18-month in-service teacher education program for engineering, Margaret, aveteran elementary teacher, talked about a recent engineering lesson she taught to her third-gradeclass. The students had been building rockets for a stomp launcher. They planned, built, testedand revised their rockets over multiple class sessions. In an interview, Margaret recounts herinteractions with one student during testing: This kid, Charlie, he was trying
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
theircapabilities to exercise control over events that affect their lives” [21, p. 1175]. An individual’spersonal agency operates within social systems; agentic actions are therefore produce and areproduct of social systems [22]. Personal agency is achieved through the following capabilitiesintentional actions, forethoughtful perspective, self-reactive a form of self-regulation, andreflectivity [11]. Forethought in personal agency goes beyond future-directed plans because futureplans “cannot be a cause of current behavior,” and, “through cognitive representation, visualizedfutures are brought into the present as current guides and motivators of behavior” [11, p. 164],[16]. For a behavior to count as agentic, the individual must take intentional actions
articulations of engineering knowledge with engineering education. Thatwork appears in tension with students’ differentiation of the highly theoretical world of engineeringschool from their more practical perception of engineering work [7,8]. These perceptions exist aboutthings external to students and provide insight into students’ epistemological boundaries – representinginformation about what the student counts as engineering knowledge [2]. Both individuals and groups ofindividuals hold beliefs about epistemological boundaries, and those boundaries interact.In planning this study, we were especially interested in which disciplinary perspectives studentsmajoring in biomedical engineering drew on in defining engineering. We see understanding
that are testing for lead. In Leon County School District, hometo 34,000 students, tests began in 2016 through a collaboration initiated by researchers at one ofthe local universities. Their lead testing plan and results were shared via that district’s waterquality website. Across the Tampa bay, the Pinellas School District, responsible for 150 schools,started a lead testing program in 2016.Based on personal communication with Florida State University faculty leading testing in LeonCounty, there will be calls for installation of water filters on kitchen faucets and water fountainsin all Florida schools.This local wicked problem resonated with students as many attended the schools in the districtand some had young children who attend or are
some even leavefor opportunities outside of school all together. As the field of engineering education researchgrows, more opportunities arise to examine what happens between the declaration of a major andthe planned graduation date that prompts so many students to exit the field. Much researchdiscusses how and why students initially choose a major (e.g., [1],[6]), but further discussion ofwhat happens between major declaration and planned graduation date is lacking in the existingliterature.Major selection is the focus of a large body of research involving higher education (e.g. [1], [2],[7], [8]). Research looking into major selection has been pursued from a variety of perspectives.Some research has focused on a broad range of college majors
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
, including the mentors’ offices. Our initialattempt failed to consider the nuances of lab collaborative work resulting in the observer missingmany of the interactions.This epic failure helped the research team to take the nature of lab experiments into account fordesigning our future research plan. For example, a timeline is needed in advance of the REUprogram. The frequency of observation needs to be more frequent (e.g., once per day) rather thanonce per week to detect changes. All types of interactions, including face-to-face/verbalinteractions and distance/non-verbal interactions should be observed.Additional InfluencersThe settings for these observations are important to note when situating the research. This isimportant even when the program is
accompanymany of the courses in engineering programs, as well as the long prerequisite chains that tend toexist in these curricula.To gain a better understanding of the aforementioned factors, consider the electrical engineeringdegree plan shown in Figure 1, offered by a university in the southwest of the United States that hasa high curricular complexity score. The analysis provided in this figure was created by utilizingthe Curricular Analytics Toolbox, an open source framework created for the purpose of analyzinguniversity curricula.6 The complexity associated with a given course c is a function of the numberof courses that are “blocked” by c (i.e., the number of courses that cannot be attempted until cis successfully completed), and the longest
Indian scenario) by paying for their services. Therefore, by doing just one ‘major project’ work, the students do not get enough experience in the institute to handle the real projects when they reach the industry. b) In such a scenario, often the main objectives of the project work of developing skills such as, planning, leading teams, communication, working in teams, decision making, and such others do not get developed by just one ‘major project’ offering in the last program. This is much to the disadvantage of the student, as most of the times the ‘major project’ is a group activity. Therefore, the requisite project handling skill- sets hardly gets developed as it is offered only once in
, significantly and positively predicted likelihood of being retained in an engineeringmajor. Studying with other students and participating in an internship program also positivelypredicted retention in engineering. Women and students who in their first year felt more likely tochange major were less likely to be retained, while students with a parent employed as anengineer and who at college entry were planning engineering as a career were more likely to beretained. The results not only indicate engineering identity can be important for retention inengineering, but several characteristics and experiences that relate to engineering identity arealso associated with retention in engineering.IntroductionNational reports have indicated colleges and
Problem Solving Proficiency in First Year Engineering (PROCESS).The full rating plan required four raters to use the PROCESS to assess the problem-solvingability of ~70 engineering students randomly selected from two undergraduate cohorts at twoMidwest universities. The many-facet Rasch measurement model has the psychometricproperties to determine if there are any characteristics other than problem-solving that influencethe scores assigned to students, such as rater bias or differential item functioning. Prior toimplementing the full rating plan, the analysis examined how raters interacted with the six itemson the modified PROCESS when scoring a random selection of 20 students’ solutions to onetextbook homework problem. Follow up inter-rater
improvement. The project is groundedconceptually using the Academic Plan Model (APM) [11], which provides a holistic view of theeducational environment and provides context for how the educational environment is shaped.Viewing the FEC educational environment as an academic plan provided a way to criticallyexamine the educational environment, the elements that comprise it, and the factors thatinfluence it.The Academic Plan Model identified accommodating the “characteristics, goals and abilities” ofstudents (learners) ([11], p. 15) as a key element in decision-making for the educationalenvironment. In considering the FEC learning environment through APM, we acknowledge thatstudents’ past educational experiences influence why and how they engage in the
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
taskdeveloped.Self-Regulation in Action (SRA) also known as Strategic Action, is at the heart of models ofself-regulated learning (SRL). SRA is comprised of iterative and recursive cycles of interpretingrequirements, planning (e.g., resources, time, strategies), implementing cognitive processes,monitoring progress, evaluating progress against internal and external standards, and continuallyrefining approaches so as to better achieve goals (see Figure 1) [26], [27]. Numerous studieshave found that enhancement of SR abilities strengthens learning skills [28]-[36] and improvesacademic success [37]-[41].From a metacognitive perspective, research describes SR as relying on both students’ knowledgeand beliefs about themselves and tasks (i.e., metacognitive
from an academic failure or if they left part of the survey failure.” blank. Initial analysis shows that these five categories do not appear to influence each other greatly.In later work, we plan on comparing each category with the three identity categories, as well asstudy existent relationships in the literature between these five categories and motivation. More prominently, we did find a connection between identity in terms of race/ethnicity andgrit/determination. This connection also correlated with which section of the course studentswere in. In the earlier section of the class, the majority of students identified as White orCaucasian, while the second section included a higher
women in engineering. Her technical work and research focuses on sustainable chemical process design, computer aided design, mixed integer nonlinear programing, and multicriteria decision making. c American Society for Engineering Education, 2019 Epistemic Beliefs of Chemical Engineering Faculty (Work in Progress)This paper is a work-in-progress for proposed research. The purpose of this paper is to introducethe engineering education community to the field of epistemic beliefs research and to seekfeedback concerning a planned research study.BackgroundEngineering education researchers frequently call for improving students’ critical thinking as aprimary skill to
single session [8], rather than spacing out their learning. Hora and Oleson [9]found in a qualitative study that almost half of STEM students reported “cramming” for theirexams, meaning they began studying for an exam sometime from a few days before the exam tothe night before it.In terms of STEM-specific studying requirements, STEM as a discipline is distinct in many waysfrom other college majors. It involves scientific inquiry, problem-solving (often collaboratively),creativity, and a broad understanding of interdisciplinary concepts and how they relate to eachother [10]. In particular, math is known to be more cognitively challenging than many othertraditional academic subjects [11] and requires effective planning for success, not just
, or a couple of students can have the ”instructor role” to ensure the ratio is met. This isa resource-intensive activity so it is easier to implement in small-sized classes and programs. AtIRE and YCP class sizes are between 8-12 and 15-18 students, respectively. However, it is notused as a regular classroom activity and only occurs one to two times a semester due to theamount of planning and setup required.Finally, the instructor decides if this is to be an individual or group activity. For an individualactivity, there should be a variety of questions both in the content area and depth so students whoare stuck on one question can move onto another and use their time wisely. More details on thissetup can be found in iteration one and two in
maker cultureinto our STEM courses to increase the enrollment as well as the retention rate ofunderrepresented students, including females and minorities. This improvement of teachinginfrastructure and pedagogy at a minority serving institution will significantly enhance theteaching quality and eventually will have a positive impact on the US's economy and well-being.The main question that will guide the investigations of this study is: “What are the effects of thecontextualized and student-centered instruction in computer science courses on students’learning outcomes and experiences?” This paper reports our planned activities that will beimplemented in Fall 2019 semester.2. BackgroundHow People Learn (HPL) framework [11] and the student
. In these open-ended spaces, students experience uncertainty about projectgoals, roles and designs, and how learning paths take shape moment to moment is unclear, oftendiffering student to student.In project-based curricula, much is unknown, unspecified, and ambiguous, conceptually andrelationally. Learners must tolerate much of this ambiguity and select what and when they callattention to uncertainty – places where they see fault or limitation in their own or the group’sdesigns, knowledge, or plan. In this analysis we saw that when facing much uncertainty - oftenacross many aspects of a project - how students select what to bring attention to, and how theyrespond when uncertainty is raised by others, cannot be well predicted by the material
Paper ID #27399Engineering Graduate Students’ Salient Identities as Predictors of PerceivedTask DifficultyMr. Derrick James Satterfield, University of Nevada, Reno Derrick Satterfield is a Ph.D. student in Engineering Education and Chemical Engineering at the Uni- versity of Nevada, Reno. He graduated from the University of Nevada, Reno in May 2017, and plans to pursue a career in academia in the future. His research interests are in graduate student attrition rates within academia, engineering identity development and the factors that influence decision making on persistence.Ms. Marissa A. Tsugawa, University of Nevada
forcestudents to develop nonobvious solutions, which in this case was a boat. Furthermore, weare interested in testing different engineering disciplines and comparing their self-assessedand judged scores. This research effort continues, and we plan to elaborate by presentingfirst-year and senior-year students with more open-ended problems multiple timesthroughout a semester. Additionally, our panel of experts are still judging the students’solutions for creativity and validity. In the future, we may expand our judging panel toinclude engineers from industry as their perception of creativity may or may not bedifferent. The small sample size of judges may lead to variance in scoring, but we hope thatfuture studies include more judges to decrease possible