tobetter understand how engineering students experience shame, we used interpretative phenomenologicalanalysis (IPA) to critically examine the individual experience of shame in the case of a high-performing,White woman who was a junior mechanical engineering major at a faith-based university (n=1). Inparticular, we attended to the complex relationship between personal expectations that formed the contextfor her shame experiences: achieving excellence in performing tasks while maintaining strong socialrelationships with others. We discuss the implications of this single case study on broader narratives ofinclusion in the context of engineering education.Introduction I feel like, because I make good grades already, people know that, whether
-makingcompetency.Theoretical FrameworkThe Self-Regulation Model of Decision-Making (SRMDM), posits that that self-regulateddecision-makers spend time in three phases: generation of options, evaluation of options, andlearning from the results. Additionally, adaptive decision-makers are aware of moderatingfactors (such as stress or lack of information) and work to overcome them [1]. The model isillustrated in Figure 1 and described in more detail below. Generation Evaluation Learning Phase Phase Phase Moderating factorsFigure 1. Byrnes’ Self-Regulation Model
atthree study sites to develop predictive models for student success.Motivation for this studyEngineering and computing education remains critical for U.S. workforce development andtechnological innovation now and into the future [1]–[3]. Many students recognize theimportance and opportunity associated with studying STEM majors, and engineering andcomputing programs today have a talented applicant pool [4]. As a consequence, manyinstitutions see relatively uniform and strong applicant credentials in terms of high school GPA,standardized test scores, and leadership experiences [5].Each admitted student has the clear potential for academic success in the undergraduatecurriculum. However, while some thrive at the university, many languish near the
engineering. c American Society for Engineering Education, 2018 WIP - A Multi-Modal Method for Assessing Student Emotions During Programming Tasks1. IntroductionComputer programming is considered a necessary skill for engineering students [1]. As aconsequence, programming courses are introduced to undergraduates early in their engineeringeducation. However, learning programming is difficult [2]: it requires patience and persistence[3]. It is also challenging because novice students may not have accurate mental models ofcomputer programs [2]. Hence, students in a programming course may experience a wide arrayof emotions that may positively or negatively impact their performance and
phase of this work will be alarger-scale study of engineering intuition across multiple disciplines and institutions that willpropel us towards developing classroom interventions for “teaching” intuition.IntroductionAs technology-aided problem solving has become standard practice, an engineers’ ability to“intuit” the results obtained through technology grows increasingly urgent. Studies on classroomlearning gains from technology use report both shallow learning [1] and deeper learning [2-5].The technology that aids today’s engineers in problem solution is not without limitations, asthese tools are based on underlying assumptions that may or may not hold true. Thus,engineering students must learn to use technology intelligently and critically
-specifichands-on research by utilizing small internal grants designed for undergraduate research. Thisstudy mostly focuses on the strategies of engaging undergraduate students in teaching focuseduniversity settings. The teaching focused primarily undergraduate institutes (PUI) have limitedresources and funding for research compared to that of major research universities (R1).Therefore, some of the strategies may work better at the PUI setting compared to R1 setting.Literature ReviewThere have been many research studies on the various aspects of undergraduate research (UR)including benefits of UR, faculty perceptions of UR, students’ perceptions of UR, strategiestaken by individual faculty, or discipline or even universities. Craney et al. [1
in students’ affective domain valuing of the roles of creativity, analysis, andinvestigation in engineering design. The adoption of Engineering Design Days is expandingacross the Faculty of Engineering as a result. We discuss lessons-learned and strategies forensuring the sustainability of Engineering Design Days.1 Introduction1.1 HackathonsHackathons have been gaining in popularity for many years. For example, the University ofWaterloo’s annual “Hack the North” hackathon has been running since 2014 [1] and smallerstudent society-sponsored internal hackathons have been running for several years. Hackathonsare broadly appealing, widely recognized to improve non-technical skills, and are typicallycharacterized by focused intensity
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
. Two research questions guided the study: (1) What are the gaps, if any,between the instructor’s and students’ interpretation (explicit and implicit task features) of aproblem-solving task?; and (2) How do students’ task interpretation (explicit and implicit)change after engaging in self-evaluation of their problem-solving processes? One hundredtwelve (112) second year engineering undergraduates voluntarily participated in the study. Thepreliminary analysis revealed that students faced challenges interpreting tasks related to theassigned thermodynamics problems, even after engaging in self- evaluation of their problemsolutions. It was also found that students experienced greater difficulty identifying the implicittask information than the
Engineering and ME in Environmental Engineering from Utah State University. c American Society for Engineering Education, 2018 Establishing Quality in Qualitative Research with Linguistically and Culturally Diverse Research ParticipantsQualitative research is becoming increasingly prominent in the field of engineering education aspractitioners and researchers seek diverse methods for understanding the human dimensions ofengineering.[1],[2] All research, whether qualitative or quantitative, must meet standards of rigorand quality in order to lead to reliable insights that advance research and practice.[3] However,due to the diverse methods and theoretical stances embraced by qualitative
investmentin the infrastructure of PROGRAM. “[The purpose of PROGRAM is to] Promote and sustain a culture of engineering education scholarship and innovation that reaches across all programs in the College of Engineering and promotes educational excellence and institutional diversity.”The emphasis on culture, as a key element of the proposed initiative, was notably restated withinan accompanying figure from the proposal (Figure 1). This figure conceptualizes a developingEngineering Education (ENED) culture as providing connections between educational researchand pedagogical innovation and practice. Figure 1: Conceptual Diagram of PROGRAM EcosystemIn addition, the following key principles were developed by PROGRAM
coursemodel traverses from one location in time and space to another.Background: Replication vs. Mutation of the Wright State Model for EngineeringMathematics EducationThe Wright State Model (WSM) is a semester-long math course that teaches fundamentalconcepts of Calculus 1, 2, 3, and Differential Equations in an engineering context through hands-on laboratory experiences and application-rich problems. The WSM is designed to disrupt thetraditional rigid sequencing of undergraduate engineering curricula by decoupling mathematicsprerequisites from engineering coursework—introducing undergraduates to sufficientmathematical tools in the one-semester course to enable them to get started and make progress intechnical engineering coursework, regardless of
as Head of the Department of Computer Science at Virginia Tech, and retired on September 1, 2016. Dr. Ryder served on the faculty of Rutgers from 1982-2008. She also worked in the 1970s at AT&T Bell Laboratories in Murray Hill, NJ. Dr. Ryder’s research interests on static/dynamic program analyses for object-oriented and dynamic programming languages and systems, focus on usage in practical software tools for ensuring the quality and security of industrial-strength applications. Dr. Ryder became a Fellow of the ACM in 1998, and received the ACM SIGSOFT Influential Educa- tor Award (2015), the Virginia AAUW Woman of Achievement Award (2014), and the ACM President’s Award (2008). She received a Rutgers School of
rubric13 forinstructional design as a way to describe the details of the case. The College ExperienceFramework captures influences and outcomes associated with the “system” and contextsurrounding the design and implementation of course innovations, and the culture, attitudes, andbeliefs of the faculty member, see Figure 1.Figure 1. Systems framework of influences on faculty and student beliefs and outcomes12,14The Quality Matters program focuses on designing a process for course quality assurance. Thisscalable process is presented in a rubric, which offers course design standards and a replicableprocess for peer review13. Below are three of the main Quality Matters foci: • Train and empower faculty to evaluate courses against these standards
a recent process of curriculum reformin an undergraduate engineering program. Curriculum continues to hold a prominent spacein discussions around engineering education, yet there are limited exemplars of full scalecurriculum reform around the globe. At the University of Cape Town (UCT) in South Africa,the design of the new chemical engineering curriculum drew on contemporary shifts inthinking about the engineering profession [1, 2], as well as a focus on widening access to thedegree and coupling this with success. Furthermore, engaging with current deliberations onthe problem-based curriculum, this design took on a problem-centered focus [3]. Thiscurriculum design demanded a far more integrated mode of course delivery than is typical ina
-engineer students) performed a second pilot using an improvedprotocol. Finally, a panel of experts was asked to review the process for a final protocol. For theactivity designed, participants were asked to review 118 profiles of people with diverse academicand social backgrounds. The goal was to choose 3 profiles for each of four categories, aiming toidentify those participants who were the best representatives of each of the categories: 1.Engineers with a low level of Lifelong Learning (ELL), 2. Non-Engineer with a low level ofLifelong Learning (nELL); 3. Engineers with a high level of Lifelong Learning (EHL), and 4.Non-Engineer with a high level of Lifelong Learning (nEHL). The time for the assignment waslimited to 90 minutes, and a think-aloud
viewers. Her primary research interest is science identity, STEM education, and participation in online communities.Mary Wyer c American Society for Engineering Education, 2018 Fitting In Across STEM: Comparing Science/Math and Engineering/Technology Students’ Perceptions of Their Fields and Futures IntroductionIncreasing the recruitment and retention of students into STEM has been a goal of the field forsome time now [1]–[3]. Not only are more STEM majors still needed to meet projectedemployment goals, but there remain ongoing issues with representation and diversity [4]–[6].Confronting these issues and recruiting more equally from marginalized
engineeringpedagogy is sub-optimal to fostering student engagement and meaningful learning [1]. Somereports have also indicated that students’ motivation for learning engineering concepts are on thedecline – the result of which is observed in a progressing pattern of low student-retention inengineering programs [2, 3]. However, dwindling student retention in STEM and engineeringprograms could undermine our strategic national objective of training and graduating a sufficientpool of science and engineering personnel to minimize a STEM professional deficit. Researchershave proposed and studied several approaches to fostering student engagement within andbeyond the classroom. In some cases, entire curricular changes are proposed to promote‘pedagogies of student
appear intraditionally taught courses, with women reporting lower autonomous motivations and highercontrolled motivations compared to men. The motivations of men and women are both moresimilar, and more positive overall, in STEM courses that employ non-traditional and mixedpedagogies.Introduction and Research BackgroundLearner motivation, the psychological intention and energetic drive to do something [1], is acritically important aspect of the learning process. While learner motivations are complex andmultifaceted, a simplified model positions motivational processes between personal andcontextual factors as antecedents, and learning engagement, behaviors, and outcomes asconsequences (Figure 1). Research shows that positive forms of motivation
alternativestrategies for course redesign) as a support tool as they develop and revise courses.MethodsSetting and ParticipantsThe setting of this study was a second-year embedded systems course meant for electrical,computer, and software engineering students at a large university in the midwestern UnitedStates. A team of nine educators (Table 1) formed an x-team (a cross-functional, collaborativeteam with diverse expertise) to make revisions to the course over each of the next four semesters.The team formed and met 2-3 times per week during the summer before the first course iteration.The team then continued to meet about once per week during the Fall 2017 semester, from whichdata for this study was collected.Data CollectionPrevious studies have found
instrument (StRIP instrument; DeMonbrun et al., 2017). Survey 1 wasadministered between the fifth and seventh weeks of Winter 2017. This timing allowed studentsto gain an understanding of the types of instruction most frequently used in the course.Additionally, prior experience items asked them to draw upon experiences in an engineeringcourse in the previous academic semester. Survey 2 was administered between the thirteenth andfifteenth weeks in the course, immediately prior to final examinations. This allowed students toaccurately depict their responses to each type of instruction frequently experienced in the currentcourse as well as their general evaluation of the course (evaluation construct items). In Survey 1, students were asked to
. As a result, in 200-level programming classes, faculty membersspent lots of time reviewing fundamental programming concepts that had already been taught inthe introductory course. Another observation is that students often procrastinated taking theirhigher-level programming courses because of unfavorable experiences in the introductory course.Based on the above observations, the goals of this project were to: (1) improve students’performance, (2) help students retain their programming knowledge/skills, (3) motivate studentsin learning programming, (4) improve classroom engagement, and (5) give students a betterprogramming experience in the introductory course so that they will not defer enrolling in 200-level programming classes.Research
gives four options, one from each quadrant (i.e., AC,AE, CE, RO). Students then mark the options one through four according to their personalpreference. These scores and then added together to determine where the student’s fall on eachspectrum.The responses were then totaled according to a proprietary algorithm provided by the Hay Group.The data was programmatically checked for integrity, and the results were input into aspreadsheet.The LSI does not use the individual scores to plot the student’s learning style on the AC−CE andAE−RO axes so additional columns were added to compute these values. These values are bestexplained by example. Student 6 in the study scored CE=24, RO=33, AC=23, and AE=40 so thecomputed values are AE−RO=7 and AC−CE=-1
variables, we used items from Sustainability and Gender in Engineering(SaGE) (Godwin, Potvin, Hazari, et al., 2013) and Hazari et al.(Hazari et al., 2010).SaGE contained the phrasing of items as seen in Table 1. To generate the three domainareas for our survey we replaced the word “subject” with “math”, “physics”, or“engineering” to form three sets of questions that addressed performance/competence,interest, and recognition for each domain area. Our dependent variable is a newly createdtwo-item engineering identity scale consisting of one visual and one verbal item relatingto the extent to which respondents believe their personal identity overlaps with theidentity of an engineer (Borrego, Patrick, Martins, & Kendall, 2018). This factor was on
from a desire to: enhance learning through increasedengagement of the students (see Astin, 1999); increase retention rates; pay greater attention topersonal development of graduate attributes as well as intellectual or epistemological development(as defined by Perry, 1999; Schommer-Aikins, 2002); develop students’ self-directed learning andgroup collaboration abilities; and also help students conceptualize technical and non-technicalcontent in more effective ways.Peer learning groups or Faculty Learning Communities (FLC) can help motivate individuals todevelop new competencies and empower them to enact change. In studying how small groupsaccomplished widespread change, Edintaite (2012) identified three desirable elements: (1)individual
properties of materials and the processes used tocreate and control those properties [1]. The discipline has its roots in metallurgy, but today itincludes the study of nanomaterials in a wide variety of applications, including energy technology,biotechnology, and many others. In short, materials science does not only deal with metalsanymore.As such, materials science and engineering encounters and investigates phenomena that can becomplicated and complex. Here, complicated refers to phenomena that require a non-trivial seriesof causal links to explain. Complex, however, refers to phenomena that require a systemsframework to explain. Specifically, complex systems share the following aspects: (1) they involvemultiple related processes; (2) their
face significant challenges that prevent broadernational success [1-3]. Educators have increasingly realized that relying solely on traditionallectures is ineffective for engaging a new generation increasingly connected to the digital world,and have therefore initiated numerous efforts to integrate technology into the teaching-learningprocess [4, 5]. In addition to this, there is an increasing recognition that learning complexengineering concepts can benefit from more in-depth clarity pre-requisites than previouslyunderstood [6]. Teaching-learning models that blend technology with traditional lectures to ensurequality of instruction have been reported promising for engaged and effective learning of higherlevel skills [7, 8]. Exploiting more
in an Engineering ClassroomIntroductionThis research paper describes a study that examines a testing effect intervention deployed in anengineering classroom setting. The testing effect is based on the premise that learning isimproved when students engage with newly acquired information by challenging themselves toanswer questions about the content instead of using other means of interacting with the content,such as rereading a text. The testing effect has been established in laboratory research studies[1]. To translate this finding into educational practice, classroom research studies [2]-[6] aim todefine the conditions for which the testing effect remains robust in authentic classroom settings.In the classroom domain, a testing effect
(US) have outpaced men inhigher education enrollment and degree obtainment 1. However, their representation in STEM(Science, Technology, Engineering, and Mathematics) fields, and especially in the engineeringfield, has significant scope for improvement 2 3. Figure 1 provides the percentage engineeringbachelor's degrees awarded to female students of all engineering bachelor's degrees in the USfrom 2006 to 2014. While the earlier downward trend is reversed, the significantunderrepresentation of women in engineering remains. Percentage engineering bachelor's degrees awarded to female students from the US engineering institutions 20.5 20 19.5 19 18.5
program because in this framework students are led to view the coursecontents as unconnected pieces. Thus, students lack the understanding of how theseunconnected course materials build on each other to form the core knowledge expected of acompetent electrical engineer. This lack of understanding manifests itself in low studentmotivation, interest, and knowledge regarding the discipline. Furthermore, it results in studentsperceiving a lack of value and career opportunities relative to the amount of effort required togo through the program [1]-[4]. As a result, attrition rates in engineering departments havebeen higher than expected. For example, the number of American students earning bachelor’sdegrees increased by 16% over the past 10 years