environment in terms of support, organizational climate, incivility, microaggressions, and work-family conflict? 1a. Are there differences across Latino men and Latina women on perceptions of the workplace? 1b. Are there changes in these measures across time? 2. What are their perceptions of their self-efficacy and outcome expectations in domains of engineering tasks, organizational skills, and multiple roles? 2a. Are there differences across Latino men and Latina women on self-efficacy and outcome expectations
the psychological constructs are shown in Table 2. Eachconstruct was measured with at least one instrument, but in some cases several such instrumentswere used. For example, we defined self-efficacy as the belief that one is capable of performinga certain task or tasks in order to achieve a desired goal. From this definition, it is apparent thatany measure of self-efficacy would be highly dependent on the tasks and goals in question. AsTable 1 indicates, we were interested in assessing students’ self-efficacy surrounding both designand life-long learning. A review of the literature failed to produce validated instruments foreither objective. Consequently, we developed our own instrument based on the work of AlbertBandura.9 As Table 2 shows
different demographic groups.ResultsThe lowest reliability within this data set, seen in Table 2, is observed in the ‘Test Anxiety’ and‘Help Seeking’ scales. This could suggest that these are less important within the Southeast Asiancontext. Data represented by Pintrich [20] align with the ‘Help-Seeking’ aspect, displaying asimilar alpha coefficient of 0.52. However, on the ‘Test Anxiety’ scale, there is a significantdifference between the study’s 0.56 and Pintrich’s 0.80. That could suggest that test anxiety is notimportant within this region or it has become less important over the last 30 years since theappearance of the MSLQ. Self-efficacy is shown to be a reliable construct, with a measured 0.96alpha coefficient, which is higher in comparison
engineeringstudents at two Midwest universities, the University of Illinois at Urbana Champaign and theUniversity of Illinois at Chicago. The goal is to gain a comprehensive understanding of theinformation sources and decision-making strategies used by these students, with the hope ofimproving the major selection process for all students.Theoretical FrameworkThe study is rooted in the Social Cognitive Career Theory (SCCT), which posits that students'evolving career interests are shaped by their self-efficacy expectations. This theory has beensupported by multiple research studies, which have established a positive correlation betweenself-efficacy and career interests. [2][3][4]. SCCT asserts that self-efficacy acts as a driving forcefor career choice.To
2006-1354: THE CHEMICAL ENGINEERING ENVIRONMENT: CATALYST ORINHIBITOR TO STUDENTS' CONFIDENCE IN SUCCESS?Deborah Follman, Purdue University Deborah K. Follman is an Assistant Professor in the Department of Engineering Education at Purdue University. She received a B.S. in Chemical Engineering from Cornell University in 1994 and a Ph.D. in Chemical Engineering from North Carolina State University in 2000. Her research interests include engineering education and gender equity, specifically regarding self-efficacy, issues of gender on student cooperative learning teams, and curriculum development.George Bodner, Purdue University George M. Bodner is the Arthur E. Kelly Professor of Chemistry, Education
) framework to provide undergraduate students with morepractice in tissue characterization. The framework involves structuring a multi-week lab thatintegrates theoretical foundations, bioinstrumentation background, experimental design, and dataanalysis. The goal of the framework is to enhance lab-based learning by providing opportunitiesfor students to incorporate multiple levels of Blooms Taxonomy. By consolidating theseopportunities into a multi-week module, we hypothesized that students would experience morereinforcement and thus self-efficacy with these experimental methods. For this study, we focusedon the development of a TDA module to measure apoptosis in tissue constructs using real-time,reverse transcription polymerase chain reaction (RT-PCR
evaluation measures were altered every1 The challenge of increasing diversity in STEM has been with us for more than two decades. Despite effort andtime, little has been achieved in changing the representation in STEM. The paradigm that exposure to STEMgenerates STEM degrees and drives the STEM workforce does not appear to work. Exposure to STEM is necessary,but it is not sufficient to diversify the STEM workforce. The PREP program focuses on activities that will increaseSTEM self-efficacy, STEM career awareness, and grit. This was accomplished by including activities led byyear. The modality of collecting data also changed throughout the years (paper and pencil,SurveyMonkey, Google Forms, and REDCap7,8) As such, it should be noted the remainder
”). We excluded these because they do not appear to be directly measuring factors thatmight lead to the pursuit of STEM in the future. Another group of papers measured contentlearning that occurred during outreach (such as math skills or geophysics concepts). While thismay influence self-efficacy measures and/or better prepare students should they choose to enterSTEM, it is not directly measuring factors that most authors focus on as proxies for change toeducational and career paths. We have not included tests of content knowledge in thedescriptions of the outreach evaluation.Table 3: Examples of commonly referenced constructs in the papers, and our definitions.Construct DefinitionsAttitude What an individual
senior mathe- matics education majors during their student teaching.Dr. Elizabeth Dianne Johnson, The College of New Jersey Page 22.1044.1 c American Society for Engineering Education, 2011 Math anxiety and math teaching beliefs of a K-5 integrated-STEM major compared to other teacher preparation majorsAbstract:In this work math anxiety, math teaching self-efficacy (SE) and math outcomes expectancy(OE) are measured on a large sample of K-5 teacher candidates, where the teacher candidatesvary among several STEM and non-STEM majors. One of the STEM-oriented majors,referred to as the Math
in 1993to evaluate the efforts to improve engineering education at the University of Pittsburgh. “ThePFEAS was constructed to measure many of Seymour and Hewitt’s primary reasons studentsleave engineering. The PFEAS attitudinal subscales were administered to assess students’attitudes about engineering” [17]). Seven factors identified by the original authors werepostulated to underlie the attitudinal items: general impressions, financial influences,contributions to society, perceptions of work, enjoyment of math and science, engineering asexact science, and family influences. The LAESE (longitudinal assessment of engineering self-efficacy) instrument was usedto measure the self-efficacy of women studying engineering, including feelings
achievement and engineering interest [33,34]. Self-efficacyfigures prominently in Social-Cognitive Career Theory (SCCT) [7] to explain achievement andcareer-related choices. The authors of the theory suggest that contextual factors are particularlyinfluential for underrepresented groups, and have successfully employed the theory to understandengineering interest and goals [35,36,37], adjustment [38], satisfaction [39], and persistence [40] amongcollege engineering students. Other researchers have employed the framework to understandpersistence of ethnic minority women in engineering [41,42].Marra and colleagues [43] developed the Longitudinal Assessment of Engineering Self-Efficacy(LAESE) to measure self-efficacy, feelings of inclusion, and outcome
into the targeted course in the Spring 2021semester, chosen as a baseline condition. Two survey instruments to measure self-efficacy andengineering identity were chosen based on the literature [1,2]. Both surveys were implementedat the beginning and end of the Spring 2021 semesters. On the other hand, six randomlyselected students, stratified by gender, were interviewed at the beginning and end of theSpring 2021 semester to determine reactions to the instructional design and instructionalevents and materials. This content analysis helped the project team identify challenges,difficulties, and gains of adopting this approach to the engineering program and provide anappraisal of student outcomes, including cognitive and affective responses.Up-to
“illustrating quantitative results withqualitative findings” [25, p. 68]. Quantitative data from the surveys were analyzed to measurethe students’ self-efficacy in targeted writing skills. In addition, quantitative data from theassessed student writing samples were analyzed to measure improvements from draft to final,and from control to intervention. The qualitative data from students’ reflections supported thequantitative results.BME Laboratory Course, Writing Assignment, and Intervention BackgroundEntering BME students enroll in the laboratory course during their first year; for fall semesterstudents, it is one of their first university courses. Unlike the engineering undergraduates studiedin [12]-[13], most students in this study had not completed a
Appendix A.2.Innovation Self-Efficacy (ISE.5) – This self-efficacy construct involves specific behaviors thatcharacterize innovative people and is designed to measure a students’ confidence in his/herability to innovate. The included items are adapted from Dyer, Gregersen, and Christensen(2008). The original Dyer items were piloted and factor-analyzed as part of the EMS surveydevelopment process. The emergent five factors corresponded to Dyer’s innovative behaviordomains of questioning, observing, experimenting, and idea networking, as well as the relateddomain of associative thinking. These items each have a Likert scale of (0-4), have an acceptableCronbach 𝛼 (.78), and have been averaged to form the ISE.5 construct variable (Schar,Gilmartin
Beliefs about engineering Methods integration (BEI) Collaboration 3 Self-efficacy for integrating Elementary Science Methods + Fluid engineering (SEI) MechanicsInstrumentsTwo survey instruments were used to assess the variables of interest. The Attitudes Surveymeasured PSTs’ beliefs about integrating engineering into their future teaching. The instrumentwas adapted from existing scales [22], [23], incorporating elements of social cognitive theory[24] to measure PSTs’ beliefs about engineering integration (BEI) and self-efficacy forintegrating engineering (SEI). Beliefs refer to one’s mental representations of reality that
of future engineers at universities and willhave a significant impact on female engineering students.When developing an instrument to measure self-efficacy, it is also important to understand theperspectives of practitioners. Bandura1 states that the first step in creating items for a self-efficacy instrument is to draw on expert knowledge about what a person must be able to do inorder to be successful in a given pursuit. This can be done through a variety of means such asopen-ended surveys, interviews or questionnaires. The work being presented here utilized anopen-ended survey and discussions with engineers.Tinkering and Technical Self-efficacyTinkering self-efficacy refers to one's experience, competence, and comfort with manualactivities
Services in the NASA Center for Success in Math & Science at Estrella Mountain Community College, she utilizes her academic preparation and extensive engineering background to prepare students for successful careers in the science, technology, engineering and mathematics fields through student internships and summer research experiences. Page 13.1289.1© American Society for Engineering Education, 2008 Tinkering Self-Efficacy and Team Interaction on Freshman Engineering Design TeamsIntroductionIn the book Talking about Leaving, Seymour and Hewitt interviewed hundreds of
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
5 1.8% Missing 7 2.6%2.2 Survey Design and Key VariablesThe research team worked closely with the course teaching team to align the pedagogical goals,milestones, strategies, and assignments to the survey measures and questions. The surveyinstrument addressed three general topics related to: 1) education and career pathways; 2)innovation, entrepreneurship, and design self-efficacy measures; 3) the learning experience ofthe course. This paper primarily addresses the first two areas.Education and Career Pathways (31 survey items)One major challenge faced by our research team was how to efficiently ask about the careerpaths and plans that students have pursued since
), Salvadorian (onestudent), and Mixed (one student). Additionally, 17% of respondents noted they were of Hispanicor Latino origin or descent. Of the total sample, 52% identified as Male, 45% identified asFemale, and 2% as Non-Binary, with 1 student preferring to not identify their gender for thestudy.A. Data Collection Data collection for the study took place at two points in time, pre and post intervention.Pre-intervention data collection included a student demographic survey recording studentrace/ethnicity, gender, etc. Measures of science interest (Science Motivation Questionnaire II;[18]), career decision self-efficacy (Career Decision-Making and Self-Efficacy Brief Decisionalscale; [15]), and knowledge of engineering technician careers
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
learningsituations and the impractical, difficult-to-measure level of transient situations within one course[9, 13, 23]. By focusing on the roles of both motivation and cognition during learning, the MSLQreflects the research on self-regulated learning, which emphasizes the interface betweenmotivation and cognition [14-15]. Prior research using the MSLQ has found relationshipsbetween constructs on its motivational subscales such as: intrinsic goals, extrinsic goals, taskvalue, control of learning beliefs, self-efficacy, and test anxiety, and constructs on its use oflearning strategies subscales such as: rehearsal, elaboration, organization, critical thinking,metacognitive self-regulation, time and study environment, and effort regulation [16 - 17
neutralprime condition where participants were informed we were interested in generalexperiences while participating in FIRST. Length of Time Manipulation. To examine if length of time while participating inFIRST influenced participants’ social networking skills, we administered the survey atthe beginning of the FIRST robotics season and again at the end of the season. Theseason started in mid-January and ended in mid-April; thus there were approximately 3-4months from the beginning of the season to the end of the season. Self-Efficacy Measure. To see if participating in FIRST influenced self-efficacy, orthe belief that one is capable of performing in a certain manner to attain certain goals, wemeasured their academic and social self
, scientists, designers, and architects.As Wirkala and Kuhn (2011) explain, most research on PBL has focused on adult students inmedical schools, and results have not been conclusive regarding PBL’s effectiveness. In K-12and post-secondary settings, implementation papers are more common than reports thatempirically demonstrate PBL's effectiveness. However, in the limited number of publishedstudies conducted at the middle school level, PBL has been shown to increase achievement incomprehension of instructional concepts (Wirkala & Kuhn), science achievement (Liu, Hsieh,Cho, & Schallert, 2006), science self-efficacy (Liu et al. , 2006), and transfer of problem-solvingskills (Pedersen & Liu, 2003). Kolodner et al. (2003) also describe results
friendlyand easily accessible to teachers. This project also fosters strong collaborations between in-service teachers, and engineering and STEM education faculty.Program participants for yr2 included seven teachers, one male and six females. Of the seventeacher participants four identified as African American, two identified as white, and oneparticipant identified as biracial. Surveys instruments included the Project Knowledge Scale, thePatterns of Adaptive Learning Scales (PALS), Computer Self-Efficacy Scale, and the TeacherSelf-Efficacy Scale all used to measure teachers’ knowledge, attitudes, computer, and teachingself-efficacy changes pre and post surveys were disseminated to program participates during thesummer 6-week professional development
measures to determine mismatches between how efficacious a woman in engineeringthinks she is versus the strategy she chooses and if it depends on the type of HC or who thecommunicator of the HC is. Our future work will compare the strategies used by people withother gender identities in engineering to see how:(1) others work to overcome HC inengineering, and (2) see how different others’ strategies are to those that women employ. We alsoplan to analyze responses to a self-advocacy item to determine how women extend their self-efficacy into advocating for themselves and others in engineering. With these findings, we aredeveloping professional development workshops to support women engineers’ advocacymentoring capacity within engineering
and taskorientation in first-year engineering design courses. In Frontiers in Education Conference (FIE),2014 IEEE (pp. 1-4). IEEE.[38] D. Baker, S. Krause, and S. Y. Purzer, “Developing an instrument to measure tinkering andtechnical self-efficacy in engineering,” presented at the 2008 ASEE Annual Conference andExposition, 2008.[39] Ohland, Matthew W., et al. "The comprehensive assessment of team member effectiveness:Development of a behaviorally anchored rating scale for self-and peer evaluation." Academy ofManagement Learning & Education 11.4 (2012): 609-630.[40] Basadur, G. Graen, and M. Wakabayashi, “Identifying individual differences in creativeproblem solving style,” J. Creat. Behav., vol. 24, no. 2, pp. 111–131, Jun. 1990.
DiscussionDuring instrument development, sections of questions were developed using data gathered fromthe ethnographic observations and interviews in combination with SCCT themes. Thesequestions, combined with those from the literature, form the basis of the following sections ofanalysis: student self efficacy, outcome expectations, goals, and barriers and support. In anothersection of the survey (separate from the Likert items), we asked students to indicate the variousreasons to attend or not to attend graduate school by selecting applicable items from a list. Adiscussion of these results will follow at the conclusion of this section.A. Student Self Efficacy Regarding Graduate SchoolSeveral items were developed to measure student self efficacy as it
AC 2009-2070: UNDERGRADUATE ENGINEERING STUDENT ATTITUDESTOWARD ENTREPRENEURSHIPAndrew Borchers, Kettering UniversitySung Hee Park, Kettering University Page 14.1289.1© American Society for Engineering Education, 2009 Entrepreneurial Self Efficacy, Locus of Control and Intent to Start a Business: An Expanded Study in an Engineering SchoolsAbstract This study extends the authors prior work on student attitudes towards entrepreneurship in a Midwestern US engineering school. Based on prior work by Chen (1998) and Rotter (1966), the study measures entrepreneurial self-efficacy (ESE) with 22 items, locus of
retention rates, degree attainment, and grade point averages, additionalliterature suggests that students’ efficacy beliefs may be an important measure of courseeffectiveness5. Self-efficacy, as first described by Bandura6, can positively or negativelyinfluence behavior based on a person’s perception of his abilities to successfully complete a task.Self-efficacy beliefs of undergraduate students in STEM (i.e. Science, Technology, Engineeringand Mathematics) majors have been linked to success and persistence within these fields7.Additionally, self-efficacy beliefs have been shown to affect interest, expectations, and choicesof engineering students8-9.Previous work examined self-efficacy beliefs of students in relation to their expectations