Conference Session

Measurement and Instrumentation

Collection

2015 ASEE Annual Conference & Exposition

Authors

Anthony Bourne, Wright State University; Nathan W. Klingbeil, Wright State University; Frank W. Ciarallo, Wright State University

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Educational Research and Methods

intervention on studentmathematics self-efficacy: Development and application of revised measurement tool Page 26.1142.2Research into the effectiveness of a mathematics intervention course for first year engineeringstudents revealed anomalous results in relation to student persistence. While previous studies ofperformance of college engineering students showed that ACT Math scores were highly linearlypredictive of student persistence outcomes, the study in question did not show similar results.The study revealed an interaction between ACT Math and high school GPA for students thatcompleted the course. The results showed an inverse relationship between ACT Math

Conference Session

Self-efficacy and Emotion: ERM Roundtable

Collection

2015 ASEE Annual Conference & Exposition

Authors

Laura Hirshfield, University of Michigan; Debbie Chachra, Olin College of Engineering; Cynthia J. Finelli, University of Michigan; Jeremy M. Goodman, Franklin W. Olin College of Engineering

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questions. 1. Did students’ academic confidence or engineering self-efficacy improve after the project course? 2. Were there differences between the academic confidence or self-efficacy of male and female students? 3. Was there a relationship between the tasks students engaged in and their incoming confidence and self-efficacy measures? 4. Did any tasks correlate to observable changes in confidence or self-efficacy measures?Both academic self-confidence and self-efficacy have a strong effect on student motivation anddecision-making. Academic self-confidence in three particular areas (problem-solving,16 mathand science,17–19 and professional and interpersonal skills7) have been found to be importantfactors in student

Conference Session

Motivation, Attitudes, and Beliefs

Collection

2018 ASEE Annual Conference & Exposition

Authors

Andrew Jackson, Purdue Polytechnic Institute; Nathan Mentzer, Purdue Polytechnic Institute; Rebecca Kramer-Bottiglio, Yale University

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Black college oruniversity. Carrico and Tendhar [17] also reported evidence of a significant correlation betweenstudents’ self-efficacy, interest, and goals to pursue engineering. While these two studies usedifferent variables to approximate students’ choice, the predictive utility of self-efficacy andinterest is strengthened when the variables are used together.Using this lens of parallel measures, this paper analyzes the content and year one implementationresults of a 9th-grade design curriculum intended to grow students’ self-efficacy, interest, andcareer choice for engineering. Following our research team’s year-long curriculum developmentprocess, we have now been involved in the implementation process of soft robot design lessonsas they

Conference Session

Degree Pathways and Cocurricular Experiences

Collection

2020 ASEE Virtual Annual Conference Content Access

Authors

Baker A. Martin, Clemson University; Marisa K. Orr, Clemson University; Rachel McCord Ellestad, University of Tennessee at Knoxville

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Tech. Her research interests include the impact of metacognitive and self-regulated learning development on engineering student success, particularly in the first year. c American Society for Engineering Education, 2020 Impact of Self-Efficacy and Outcome Expectations on First-Year Engineering Students’ Major SelectionAbstractDeciding on a major is one of the critical decisions first-year students make in theirundergraduate study. Framed in Social Cognitive Career Theory, this work investigatesdifferences between measures of self-efficacy and outcome expectations by students intending topursue different engineering majors. Our results show that tinkering self-efficacy

Conference Session

Student Perceptions of Self-efficacy, Success, and Identity

Collection

2020 ASEE Virtual Annual Conference Content Access

Authors

Hindolo Michael Kamanda, University of Georgia; Davis George Anderson Wilson, University of Georgia; Joachim Walther, University of Georgia; Nicola W. Sochacka, University of Georgia; Stephen Secules, Florida International University; James L. Huff, Harding University

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students,Bottesi, et al. [25] found that anxiety and intolerance of uncertainty can lead to negative beliefsand outcomes expectations that can affect student performance [see also: 26]. A study ofengineering students [20] found that low stress levels and positive outcome expectationsincreased students’ self-efficacy, a factor that, in turn, significantly predicted academicachievement. Related studies identified stress as a key predictor for low student engagement andpersistence [27] as even students with high ability in science often leave STEM majors due tosignificant accompanying pressure and accompanying physical and psychological distress [28,29].Minority students can be disproportionately impacted by such emotional experiences due to

Conference Session

Experiences of Diverse Students

Collection

2017 ASEE Annual Conference & Exposition

Authors

Mark Schar, Stanford University; Shannon Katherine Gilmartin, Stanford University; Beth Rieken, Stanford University; Samantha Ruth Brunhaver, Arizona State University; Helen L. Chen, Stanford University; Sheri Sheppard, Stanford University

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understand the conditions that mayencourage engineering students to be more entrepreneurial and innovative. Among Epicenter’s severalresearch projects is an ongoing longitudinal survey study of the development of engineering students’career goals around innovation and engineering, referred to as the Engineering Majors Survey (EMS -2016). The EMS study follows a nationally representative sample of engineering students from theirundergraduate experiences through graduation and into the workplace (Gilmartin et al. 2017). Withinthis survey are measures of engineering task self-efficacy and innovation self-efficacy, as well as 39background learning experiences and extra-curricular activities spanning high school throughundergraduate education, which form

Conference Session

Educational Research and Methods Division Poster Session

Collection

2017 ASEE Annual Conference & Exposition

Authors

S. Zahra Atiq, Purdue University, West Lafayette

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Educational Research and Methods

students have been conducted in the context of team discourse and studentachievement5, engineering design projects6, and developing validated self-efficacy instruments forengineers7. Moreover, there is evidence in literature on measuring self-efficacy of engineeringstudents in the context of programming8-9. Askar et al., examines factors related to self-efficacyfor Java programming in first year engineering students. These factors include gender, computerexperience, general computing skills, frequency of computer use, and family computer usage.Findings from this study confirm the link between students’ self-efficacy beliefs and their choiceof subject. It was also found that computer engineering students had higher self-efficacy beliefscompared to

Conference Session

Measurement and Instrumentation

Collection

2015 ASEE Annual Conference & Exposition

Authors

Adam Kirn, University of Nevada, Reno; Lisa Benson, Clemson University

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Diversity

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Educational Research and Methods

a specific task such as problem solving or design.1 Results have indicated thatstudents with higher self-efficacy (a task-specific motivation2) have been shown to have improvedlearning and understanding in introductory engineering courses.3 Work focused on long-termgoals, such as graduating with an engineering degree, has shown that students who have higherexpectancies for their performance in engineering have significantly higher grade point averages(GPAs).4,5 Connections between these two scales of motivation have been proposed, yet little workhas been done to examine how these levels are connected and influence one another.6 Theoverarching purpose of our research is to understand the connection between multiple levels of

Conference Session

Problem Solving, Adaptive Expertise, and Social Engagement

Collection

2018 ASEE Annual Conference & Exposition

Authors

Janna H. Ferguson, Northeastern University; Jennifer Lehmann, Northeastern University; Yevgeniya V. Zastavker, Franklin W. Olin College of Engineering; Susan Chang, Northeastern University; Reid P. Higginson, Harvard University; Cigdem P. Talgar, Northeastern University

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], as well as self-efficacy and resilience. Therevised scale included modified items from Fisher and Peterson’s 2001 survey [20], additionalitems of our own construction, and several items based on work by van der Heijden [33],Charbonnier-Voiirin et al., [36], Bohle Carbonell et al., [35], and the General Self-Efficacy Scale(GSES-12) [37], [38].We were guided to include domain skills by the near-consensus in the adaptive expertiseliterature that adaptive expertise is built on top of subject-specific routine expertise. Ourproposed domain skill items address student perception of growth in their field, as well as theirability to pursue expertise and integrate new developments in the field [33], [35]. Innovativeskills by contrast focus on student

Conference Session

Assessment and Outcomes: ERM Roundtable

Collection

2015 ASEE Annual Conference & Exposition

Authors

Samantha Ruth Brunhaver, Arizona State University; Shannon Katherine Gilmartin, Stanford University; Helen L. Chen, Stanford University; Holly M Matusovich, Virginia Tech; Sheri Sheppard, Stanford University

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Diversity

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Educational Research and Methods

theirbachelor’s degrees in engineering. We focus on these individuals due to the scarcity of researchon their experiences and the relevance of their perspectives to engineering education.29-31Implications of this work will focus on recommendations for educational research and practice.Framework and LiteratureThe overall EPS project is broadly situated in social cognitive career theory (SCCT) which positsthat a variety of factors influence career choice including self-efficacy beliefs, outcomeexpectations, and learning experiences.32 SCCT has been used extensively in the study ofengineering students’ career choices.33-37 A main goal of our study has been to identify theschool and workplace factors related to the career choices made by engineering

Conference Session

Student Approaches to Problem Solving

Collection

2020 ASEE Virtual Annual Conference Content Access

Authors

Vanessa Svihla, University of New Mexico; Amber Gallup, University of New Mexico; Sung "Pil" Kang, University of New Mexico

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Diversity

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Educational Research and Methods

the content against bothprior analysis and relevant literature. Content validity through expert review We drafted materials for expert review, including a 1-page definition of framing agency and its sub-constructs, a version of the survey, and a scoring sheet. Given the relatively novel nature of the construct (e.g., as compared to developing a scale for self-efficacy in a new domain), we were concerned about the possibility of inclusion bias (i.e., in not having true expertise due to the newness of the construct, would experts tend to rate every question as relevant?). We developed 17 distractors to evaluate experts’ tendency to include constructs that may be interesting but not included as

Conference Session

Approaches to Assessment and Student Reflection

Collection

2020 ASEE Virtual Annual Conference Content Access

Authors

Sabrine Griffith, Harvey Mudd College; Spencer Rosen, Harvey Mudd College; Eleanor Byrnes, Harvey Mudd College; Laura Palucki Blake, Harvey Mudd College; Matthew Spencer, Harvey Mudd College

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moving fromconcrete experiences into reflective observation is essential for learning.This learning was assessed by direct assessment of students’ performance on an in-lab exam thatassessed both theoretical and experimental skills, surveys of self-efficacy administered beforeand after the treatment, coding student answers to reflection questions in the lab manuals, andcounting the number of answers to interactive questions to determine compliance.Significant results from the experiment indicated that students in the treatment group took longerto complete the lab, felt greater time pressure, performed more poorly on the in-class evaluation,and had fewer metacognitive gains than the control group. The treatment appears to haveincreased the

Conference Session

Beyond the Classroom

Collection

2015 ASEE Annual Conference & Exposition

Authors

Denise Rutledge Simmons PE, Virginia Tech; Chosang Tendhar, Virginia Tech; Rongrong Yu, Virginia Tech; Eric A. Vance, Virginia Tech; Catherine T. Amelink, Virginia Tech

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. Amelink is the Director of Graduate Programs and Assessment in the College of Engineering Virginia Page 26.506.1 Tech and affiliate faculty in the Department of Engineering Education and the Department of Educational Leadership and Policy Studies at Virginia Tech. c American Society for Engineering Education, 2015 Developing the Postsecondary Student Engagement Survey (PosSES) to Measure Undergraduate Engineering Students’ Out-of-Class Involvement    Abstract    A large body of literature focuses on the importance of student involvement in all aspects ofcollege for achieving

Conference Session

Examining "Big" Data

Collection

2015 ASEE Annual Conference & Exposition

Authors

Issam Wajih Damaj, American University of Kuwait; Ashley Ater Kranov, Washington State University

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Educational Research and Methods

Paper ID #12549A Framework for Measuring the Sustainability of Academic Programs in theTechnical Fields: Initial Validity Study FindingsDr. Issam Wajih Damaj, American University of Kuwait Dr. Issam W. Damaj (Ph.D. M.Eng. B.Eng.) is an Associate Professor of Computer Engineering at the American University of Kuwait (AUK). He is the Chairperson of the Department of Electrical and Computer Engineering. His University service experience is focused around assessment, quality assur- ance, program development, accreditation, and institutional effectiveness. His research interests include hardware/software co-design

Conference Session

Assessing Hard-to-Measure Constructs in Engineering Education: Assessment Design and Validation Studies

Collection

2021 ASEE Virtual Annual Conference Content Access

Authors

Madison E. Andrews, University of Texas at Austin; Priyadarshan N. Patil, University of Texas at Austin

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Articles which did not focus on McConnell and Dickerson (2017) Engineering undergraduate engineering students consider student arguments about or undergraduate engineering subject the function of external structures matter. on animals for survival. The subjects are fourth-grade students. Examine Process Articles which examined the process Purzer (2011) studied student rather than of argumentation, rather than the arguments, self-efficacy and Product products of argumentation (e.g. a individual student achievements. writing

Conference Session

Data-informed Approaches to Understanding Student Experiences and Outcomes

Collection

2020 ASEE Virtual Annual Conference Content Access

Authors

Harrison Douglas Lawson, Michigan State University; Amalia Krystal Lira, Michigan State University ; Alexandra A. Lee, Michigan State University; Minhye Lee, Daegu National University of Education; Lisa Linnenbrink-Garcia, Michigan State University; S. Patrick Walton, Michigan State University; Daina Briedis, Michigan State University

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(7.5%), Latinx (4.8%), Asian (20.9%), Multiracial (2.2%), Alaska Native (0.2%), andNative Hawaiian or Other-Pacific Islander (0.1%). The surveyed students included both studentsenrolled in engineering majors and students who, at one point, were engineering majors but wereno longer enrolled in engineering.Measures: Academic Self-efficacy. Five questions measured engineering self-efficacy [19]. Theresponses were recorded using a 5-point Likert-type scale. These measures were collectedannually over four years (T1 ⍺ = .87, T2 ⍺ = .90, T3 ⍺ =.91, and T4 ⍺ =.90). A sample item forengineering self-efficacy is “I’m certain I can master the content in the engineering-relatedcourses I am taking this semester.” Prior Achievement. Prior

Conference Session

Motivation

Collection

2017 ASEE Annual Conference & Exposition

Authors

Andrew Jackson, Purdue Polytechnic Institute; Nathan Mentzer, Purdue University, West Lafayette (College of Engineering); Jiawei Zhang, Purdue University, West Lafayette (College of Engineering); Rebecca Kramer, Purdue University, West Lafayette (College of Engineering)

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. Educational environments whichleverage these interests may be better able to attract and retain female students 9.Figure 1. Percentage of degrees awarded to women in engineering disciplines. Adapted from Yoder, B.L. (2014). Engineering bythe numbers. Retrieved from American Society for Engineering Education's College Profiles website:https://www.asee.org/papers-and-publications/publications/14_11-47.pdf.Tinkering Self-EfficacySelf-efficacy is an individual’s self-perceived ability to accomplish a goal or task 12. Self-efficacy is a domain specific measure—for example being confident in my ability to jump acertain distance says nothing of my confidence for gardening—with predictive relationships torelevant outcomes like motivation, effort, and

Conference Session

ERM Technical Session 7: Learning and Research in Makerspaces

Collection

2019 ASEE Annual Conference & Exposition

Authors

Lee Michael Martin, University of California, Davis

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Development, vol. 72, pp. 187-206, 2001.[9] M. K. Ponton, J. H. Edmister, L. S. Ukeiley, and J. M. Seiner, "Understanding the Role of Self- Efficacy in Engineering Education," Journal of Engineering Education, vol. 90, pp. 247-251, 2001.[10] A. R. Carberry, H. S. Lee, and M. W. Ohland, "Measuring engineering design self‐efficacy," Journal of Engineering Education, vol. 99, pp. 71-79, 2010.[11] T. D. Fantz, T. J. Siller, and M. A. Demiranda, "Pre-Collegiate Factors Influencing the Self-Efficacy of Engineering Students," Journal of Engineering Education, vol. 100, pp. 604-623, 2011.[12] H. M. Matusovich, R. A. Streveler, and R. L. Miller, "Why Do Students Choose Engineering? A Qualitative, Longitudinal Investigation of

Conference Session

Student Motivation, Identity, and Resilience

Collection

2020 ASEE Virtual Annual Conference Content Access

Authors

Wonki Lee, Purdue University, West Lafayette; Jeffrey F. Rhoads, Purdue University, West Lafayette; Edward J. Berger, Purdue University, West Lafayette; Jennifer Deboer, Purdue University, West Lafayette

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their learning [1], [2]. TheMSLQ is one of the most extensively used scales designed to assess self-regulated learning [3].Pintrich and colleagues developed the MSLQ [2] to measure three components (motivation,metacognition, and behavior) of self-regulated learning [2]. It has been widely validated anddeployed in university engineering education settings. The MSLQ has two parts: Motivation and Learning Strategies. Motivation scales arecomposed of three dimensions (value, expectancy, and affective) with 31 items subdivided intosix subscales: intrinsic goal orientation, extrinsic goal motivation, task value, control beliefs,self-efficacy for learning and performance, and test anxiety. The learning strategies scalemeasures two dimensions

Conference Session

Faculty Development II: Building Community Among STEM Educators

Collection

2016 ASEE Annual Conference & Exposition

Authors

Toni Ivey, Oklahoma State University; Nicole M. Colston, Oklahoma State University; Julie Thomas, University of Nebraska, Lincoln; Juliana Utley, Oklahoma State University

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and perceptions regarding engineering.Additionally, changes in teachers’ self-efficacy of teaching engineering and students’ attitudesabout science and engineering were measured. This article discusses the value of elementaryengineering education in rural communities.Keywords: Engineering education; professional development; elementary; rural schoolsIntroduction Science education in elementary (K-6) curriculum is often lacking and leads towidespread lack of preparation and misconceptions about fundamental science ideas in middleand high school students.1 Researchers have documented that elementary classroom scienceinstruction is typically limited and of low quality.2,3,4,5 Further, results from a 2013 nationalsurvey indicated that

Conference Session

Predicting Student Success

Collection

2017 ASEE Annual Conference & Exposition

Authors

Anthony Bourne, Wright State University; Craig Baudendistel, Wright State University; Zulima Guilarte Rhodes, Wright State University; Jannet Chermi Anders

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Educational Research and Methods

) The relationship between mathematics self-efficacy and achievement in mathematics. Procedia Social and Behavioral Sciences, 1, 953-957.Bandura, A. (1977). Self-efficacy: Toward a unifying theory of behavioral change. Psychological Review, 84(2), 191-215.Barker, F.J. (2010). The effects of an engineering-mathematics course on freshmen students’ mathematics self-efficacy. (unpublished master’s thesis). Washington State University, Pullman, WA.Bourne, A.L., Ciarallo, F.W., Klingbeil, N.W. (2015) Measuring the impact of a mathematics intervention on student mathematics self-efficacy: Development and application of revised measurement tool. Proceedings 122nd ASEE Annual Conference and Exposition, Seattle WA, June 2015.Bourne, A.L

Conference Session

The Role of Peers in Promoting Learning and Persistence

Collection

2021 ASEE Virtual Annual Conference Content Access

Authors

Thien Ngoc Y Ta, Arizona State University; Gary Lichtenstein, Arizona State University; Cody D Jenkins, Arizona State University; Karl A. Smith, University of Minnesota - Twin Cities; Ryan James Milcarek, Arizona State University; Samantha Ruth Brunhaver, Arizona State University

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of URG students [13],[14].We hypothesize that PLSGs will effectively provide engineering transfer students with socialsupport that, in turn, promotes institutional and major persistence in ways consistent with socialcognitive career theory (SCCT).Study DesignTreisman’s approach has been implemented at several institutions [15], [16], [17]. Our projectdiffers in four critical ways: we (1) utilize the PEERSIST model in an engineering context, (2)extend beyond student achievement to also measure self-efficacy beliefs, (3) employ a virtualplatform to accommodate the unique work and personal circumstances of transfer students and(4) compare PLSG results to a TA-led study group.After piloting the method with four students in Spring 2020, the

Conference Session

Classroom Practice III: Student-Centered Instruction

Collection

2016 ASEE Annual Conference & Exposition

Authors

Matthew Reyes, University of Oklahoma; Diana Bairaktarova, Virginia Tech; Anna Woodcock, California State University San Marcos

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Educational Research and Methods

whenselecting a test.6, 19, 21, 22, 23, 24, 25, 26 While each test measures a slightly different aspect of the broadtopic of spatial skills, many of them correlate highly with one another. Since this study calls for ameasure of general spatial skills, the authors chose a revised version of the PSVT:R test to assessparticipants’ spatial skills.Authors’ Previous Work Previous work by the authors indicates that individuals’ spatial ability differ by gender,age, and ethnicity.27 However, differences were not found on variables such as a student’sclassification (or year in school), early life experiences, and college major. Motivational factors,particularly domain-specific self-efficacy, are positively correlated with individuals’ spatial

Conference Session

Communication and Literacy

Collection

2015 ASEE Annual Conference & Exposition

Authors

Christina Kay White, Massachusetts Institute of Technology; Lori Breslow, Massachusetts Institute of Technology; Daniel E. Hastings, Massachusetts Institute of Technology

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self-efficacy are well equipped to educate themselveswhen they have to rely on their own initiative. One of the goals of teaching communicationskills is to develop students who feel competent and confident in the use of those skills [13]. Ourstudent survey is designed to measure the extent to which students at our study sites havedeveloped a sense of self-efficacy for communication.The survey lists the sub-skills we have identified, both from the literature and from experience inteaching communication skills, that student must master in order to successfully create anddeliver oral presentations, write, develop and use visual literacy skills, and participate inteamwork. For example, for oral presentations, we asked students about their

Conference Session

Motivation, Identity, and Belongingness

Collection

2018 ASEE Annual Conference & Exposition

Authors

Jonathan D. Stolk, Franklin W. Olin College of Engineering; Yevgeniya V. Zastavker, Franklin W. Olin College of Engineering; Michael D. Gross, Wake Forest University

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/perceived confidenceand interest/values in STEM has progressed over the past two decades, studies of students’motivational orientations (intrinsic versus extrinsic) in STEM are quite limited.Perceived confidence and self-efficacy strongly influence academic motivations [44] and serveas mediators of learning engagement and persistence [8]. As such, STEM educators areconcerned with how learners cultivate a strong sense of efficacy and expectations of success.Indeed, measurement of self-efficacy and perceived competence represents an area of notableprogress in STEM education research. Gendered patterns in learners’ perceived competence andself-efficacy within gender-role stereotyped domains such as mathematics and engineering arewidely reported [45

Conference Session

Engineering Cultures and Identity

Collection

2016 ASEE Annual Conference & Exposition

Authors

Anita Patrick, University of Texas, Austin; Maura Borrego, University of Texas, Austin

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ASEE Diversity Committee, Diversity

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Educational Research and Methods

isevident and supported by Table 2. Despite this lack of coherence, these studies have beenimportant first steps in exploring specific aspects of identity development in engineering. Closely related to identity but not explicitly stated, others have provided a review andanalysis of existing research on the measurement of the characteristics of engineering students inorder to illuminate factors that affect college enrollment and retention.12 The authors, Li,Swaminathan, and Tang, found that many researchers are specifically looking at the factors thathelp or hinder the matriculation of underrepresented groups into engineering. Marra, Rodgers,Shen, and Bogue conducted a multi-institution study on self-efficacy and women engineeringstudents.36

Conference Session

Faculty Development

Collection

2017 ASEE Annual Conference & Exposition

Authors

Hye Sun You, New York University; Vikram Kapila, New York University

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Educational Research and Methods

of technology use. Mishra and Koehler23 used a surveyto track changes in teachers’ perception of their TPACK understanding over a course thatincorporated educational technology. Moreover, Archambault and Crippen47 developed 24 surveyquestions to measure teachers’ understanding of various instructional and conceptual issues. Thiseffort adapted a widely used self-efficacy TPACK instrument46,48 for our PD program, whichemploys robotics to teach classroom science and math. Moreover, in our study, we reformulatedthe TPACK survey instrument,46,48 guided by the self-efficacy research,49,50 to establishparticipant’s confidence, motivation, outcome expectancy, and apprehensiveness for each of theseven components of the TPACK framework.3. Research

Conference Session

Career Decisions and Faculty Development

Collection

2018 ASEE Annual Conference & Exposition

Authors

Trevion S. Henderson, University of Michigan; Katie A. Shoemaker, University of Michigan; Lisa R. Lattuca, University of Michigan

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social pressure tosucceed in engineering. Students were asked to respond on a 5-point Likert scale (1=StronglyDisagree and 5=to Strongly Agree)to the survey item that read, “I would be embarrassed if Ifound out that my work in my science or engineering major was inferior to that of my peers.”Finally, since Ajzen argued that perceived behavioral control is highly compatible withBandura’s concept of perceived self-efficacy, we measured perceived behavioral control using asubscale of our engineering self-efficacy measure. Items in the subscale of Engineering MajorConfidence were measured on a five-point Likert scale (i.e., Strongly Disagree to StronglyAgree). Example items included, “I can succeed in an engineering major” and “Someone like mecan

Conference Session

Experiences of Underrepresented Students in Engineering

Collection

2020 ASEE Virtual Annual Conference Content Access

Authors

Manuel Jimenez, University of Puerto Rico, Mayaguez Campus; Luisa Guillemard, University of Puerto Rico, Mayaguez Campus; Sonia M. Bartolomei-Suarez, University of Puerto Rico, Mayaguez Campus; Oscar Marcelo Suarez, University of Puerto Rico, Mayaguez Campus; Aidsa I. Santiago-Roman, University of Puerto Rico, Mayaguez Campus; Nayda G. Santiago, University of Puerto Rico, Mayaguez Campus; Carla López del Puerto, University of Puerto Rico, Mayaguez Campus; Pedro O. Quintero, University of Puerto Rico, Mayaguez Campus; Nelson Cardona-Martínez, University of Puerto Rico, Mayaguez Campus

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shapeinterventions aimed at impacting SCCT factors and studying their effect on LIATS success.Success in our case is defined by the student ability to complete an engineering degree within133% of the nominal program time and inserting into the grad school or the engineeringworkforce during the first-year post-graduation. Metrics to measure students’ advancementtowards such a goal include retention, time-to-graduation, completion rates, and post-graduationchoices.The main question driving this research is: How effective is the L-CAS model at improvingengineering LIATS success as a consequence of developing awareness of their career paths,improving self-efficacy beliefs, developing leadership skills, and going through a sequence ofcourses designed to develop

Conference Session

ERM Technical Session 24: Studies on Socioeconomic Status

Collection

2019 ASEE Annual Conference & Exposition

Authors

Emily Bovee, Michigan State University; Amalia Krystal Lira, Michigan State University; Harrison Douglas Lawson, Michigan State University; Daina Briedis, Michigan State University; Lisa Linnenbrink-Garcia, Michigan State University; S. Patrick Walton, Michigan State University

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portion of my expenses. Please list approximate percentage of expenses covered (1 to100%)).” Students only saw the second scholarship question if they answered yes to the firstquestion. Motivation. Five questions measured engineering self-efficacy (⍺ = .88). A sample itemfor engineering self-efficacy is “I can do a good job on almost all my engineering coursework ifI do not give up.” Five questions measured engineering interest (⍺ = .91). A sample item forengineering interest is “Engineering is exciting to me.” Five questions measured attainment value(⍺ = .85). A sample item for attainment value is “Being good in engineering is an important partof who I am.” Finally, four questions measured utility value (⍺ = .87). A sample item for