electrical and mechanical engineering majors. Each ofthese courses has a final team project, with varying degrees of open-endedness, in lieu of atraditional exam. Design competencies were measured in these courses, both pre- and post-experience, using self-reported surveys as well as instructor assessment of ABET learningoutcomes. The post-experience surveys as well as final project rubrics were used to measurechanges in design competencies as well as changes in self-efficacy. There was a correlationbetween the changes of self-efficacy and ABET outcomes at the end of the courses for bothmajor-specific and general education courses. Students in the general education course scoredlower in final self-efficacy compared to their peers in the major
teach and refine oral communicationskills of English language learners (ELL) at Skoltech, a Russian university. The objectivewas to develop disciplinary communication skills in English so that students could presenttheir engineering designs during a rapid prototyping project. A pre/post survey assessedchanges in self-efficacy as a measure of success in the instruction about, practice andperformance of oral presentations. The post-test survey showed a statistically significantincrease in self-efficacy for a majority of the students. Survey data combined with facultyobservation indicates that the communication pedagogy combined with practice waseffective in increasing self-efficacy and in facilitating and refining oral communication skillsfor the
university in the CM department and was run as a cross-listed (undergraduate andgraduate) elective course for the spring and fall 2015 semesters. The course met three hoursonce per week in the spring and 90 minutes twice per week in the fall.The two semesters of the course were assessed and compared against typical education metrics:enrollment, final course project grade, and course rating. A less known metric, self-efficacy wasalso discovered and utilized in the second semester to further measure the effectiveness of thiscourse. The metrics are used to measure the course design, current effectiveness of the course,and highlight areas for future improvements.A “backwards design” approach was taken for the instructional design of this course
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
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
aerospace engineering students and analyzed the students’ self-reported background factors, engineering identity, and engineering self-efficacy. Studentinformation such as GPA, retention information, demographics, SAT/ACT scores, and initialmajor of study were acquired from the university and analyzed with the self-reported data todetermine significant measures of success. The results of our investigation can inform the designand implementation of pre-college engineering programs.Introduction The workforce demand for engineers is increasing, but student retention and graduationrates are staying constant which means that soon the need for engineers in the United States willsurpass the engineering population. Only 57% of engineering
impact ofcollaborative project-based learning (CPBL) on the self-efficacy of traditionally underrepresented minoritygroups in electrical engineering courses with the support of NSF. The project goals include: 1) Improve theunderstanding of the factors that affect the self-efficacy of minority student groups in Engineering; 2) Developbetter ways to measure the impact of collaborative learning in the developmental stages of the student learningprocess in addition to the learning outcomes; 3) Design a more effective instructional system that integratescommunity inquiry to boost the self-efficacy of underrepresented minority students.Since 2013, the research effort has produced interesting results that allowed us to better understand the
Engineering Education. American Society for Engineering Education. Vancouver, B.C., Canada, June 26-2913. Selvi, E., Soto-Caban, S., Taylor, R.S. and Wilson, W.R., 2011. Similar Consecutive Bridge Design Projects for Freshmen and Sophomore Level Engineering Courses. In American Society for Engineering Education. American Society for Engineering Education. Vancouver, B.C., Canada, June 26-2914. Abramowitz, H., 2008. Basswood Bridges. In American Society for Engineering Education. American Society for Engineering Education. Pittsburgh, Pennsylvania., June 22-2515. Mamaril, N.J., 2014, Measuring undergraduate students’ engineering self-efficacy: a scale validation study, Ph.D. Dissertation. University of Kentucky. Lexington, Kentucky.16
-concepts of math ability are also examined 10,14. According toBandura16, math anxiety has an inverse relation to self-efficacy levels. Thus, increasing mathself-efficacy may decrease students’ feelings of anxiety when they perform math activities 17.There is some ambiguity concerning the possible effects of math anxiety on students, and thisambiguity is normally generated by the different ways by which math anxiety is measured. Forexample, including survey items and questions that could combine students’ perceptions of theirmath abilities with their feelings about performing math tasks can create ambiguity 13. If mathanxiety is not established and measured as an independent factor, developing a conclusion aboutits effects on students’ behavior and
, 1995, Generalized Self-Efficacy Scale. In J. Weinman, S. Wright, and M.Johnston, Measures in health psychology: A user’s portfolio. Causal and control beliefs (pp. 35-37). Windsor, UK:NFER-NELSON.10 Cohen J., 1988, Statistical Power Analysis for the Behavioral Sciences (2nd ed.), Lawrence Earlbaum Associates,New Jersey.11 Shi, W. and K. J. Min, 2014, “Product Remanufacturing: A Real Options Approach,” IEEE Transactions onEngineering Management, Vol. 61, pp. 237-250, 2014.12 Shi, W. and K. J. Min, 2014, “Product Remanufacturing and Replacement Decisions Under Operations andMaintenance Cost Uncertainties,” The Engineering Economist – Special Issue on Engineering Economics inReliability, Replacement and Maintenance, Part 1, Vol. 59
, 2016Changes in Undergraduate Engineering College Climate and Predictorsof Major Commitment: Results from Climate Studies in 2008 and 2015Abstract This paper presents results of two cross-sectional investigations of educational andinterpersonal climate in a college of engineering at a large mid-western university. In 2008 andin 2015 we deployed a survey ("Project to Assess Climate in Engineering”) to undergraduateengineering students. In each survey year, just over 1000 eligible students participated andresponded to items contributing to scales rating their professors, teaching assistants, collegeresources, confidence (self-efficacy) in engineering, student interactions, perceptions ofengineering, and commitment to an engineering major
. Instead, the researchers are customizing a University Seminar (US 1100) section, whichis an introduction to the university freshman seminar course, specifically for engineering andengineering technology majors while exploring research questions related to the development ofstudent design self-efficacy. This paper presents this work in progress including preliminaryresults from pre- and post-project engineering design self-efficacy measures of the initial cohort,lessons learned, and plans for future work.BackgroundThe Texas State STEM Rising Stars project is using a three-sided organizing framework, asshown in Figure 1, to guide the interventions and its associated research plan. This framework isbased upon Swail’s geometric model for student
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
, orconcentration—a “learning experience”—and other SCCT constructs: Innovation Self-Efficacy(ISE) and Career Goals: Innovation Work (CGIW).The EMS institutional sample represents a stratified quasi-random sample of ~350 U.S.engineering schools. Schools were stratified on the basis of: 1) research university or non-research university, 2) size of engineering school as measured by number of engineering degreesawarded, and 3) presence of an undergraduate business major on campus. This resulted in a2x2x2 scheme. Institutions within each stratification “cell” were “quasi” randomly sampled inthat schools were flagged as “Epicenter affiliated” or “not Epicenter affiliated”, and, wherepossible, roughly equal numbers were randomly selected from each group
1.4 Missing 4 .8Instrumentation The 2014 version of the STEM IQ consisted of 71 items. 13 were demographic, 58attitudinal items related to students’ experiences, teamwork, learning experience, hands on activelearning, and career. The study focuses on only attitudinal items with a high reliability Cronbachalpha (α=.83). The items in the questionnaire are based on 100 scale. Further, the attitudinalitems are divided into three components. First component aims to measure STEM-related self-efficacy, like a student’s ability to complete academic milestones and to overcome performancehurdles. Students are asked to indicate their confidence to perform successfully
workforceonce they have arrived.Self-efficacy, grit, and leaning in; are these the keys that distinguish female students who willthrive in ECS not only as college students but also as career professionals? Arguably, Bandura,Duckworth, and Sandberg were a perfect storm of women’s empowerment theories. In ourSPARK assessments, we decided to quantify the first two items and qualitatively assess how –and if – our students were “leaning in”.In addition to measuring self-efficacy, we administered surveys to assess the students’ grit,perseverance, ambition, problem-solving abilities, resilience, self-confidence, and GPAs. Weincluded questions about their satisfaction with the various SPARK activities we organizedthroughout the years. We also asked open ended
advised section was perhaps due torepetitive brainstorming during the weekly team meetings, while the advised section wasdeprived of this activity. Work by others suggests that repetitive brainstorming improves self-efficacy 8,9 – people’s beliefs in their capacities to produce desired effects through their actions 10.We hypothesize that the construct of self-efficacy is covariate with actual process knowledge,and that process knowledge is improved through brainstorming. The latter may be tested bymeasuring whether knowledge of processes other than engineering design can be covertlyinfluenced by brainstorming, but without overt instruction on that process.These data are consistent with a previous study showing that the mode of instruction
students.In Texas, students were measured over a six-year period. From 2006 – 2010, enrollmentquadrupled and participants increased 18,686 individuals (4498 in 2006 to 23184 in 2010)9.Female participation increased 586% and Hispanic students increased 507%. This study alsoshowed a high impact on students enrolling in higher education (62.1%) compared to their non-PLTW counterparts (58.4%)9. In addition, post-secondary enrollment was slightly greater forfemales (63.5%) compared to their non-PLTW peers (63.1%).Several studies have examined self-efficacy of females for math and science subjects whenparticipating in PLTW10,11,12. Exposure to engineering through PLTW has shown to havesignificant impact on self-efficacy and underrepresented students10. The
current approach to entrepreneurship education. As engineering educationseeks to recruit and retain diverse groups of students, it is important to consider the influence ofentrepreneurship education environments on women. To date, the few entrepreneurship education studies specific to engineeringentrepreneurship programs are usually multi-institutional and focus on individual studentparticipant characteristics, attitudes, outcomes,12 and interests13. Individual characteristics, suchas a person’s sense of self-efficacy and agency, certainly contribute to one’s interest andcapability for success in entrepreneurship and innovation. Yet, the nature of the environment onechooses to participate in also plays a critical role in initial student
decisions. Identifying the decision making behaviors ofparticipating and non-participating students can also help uncover barriers to entry ofextracurricular engineering activities, particularly any barriers affecting underrepresented groupsof engineering students.Another topic for investigation is self-efficacy trends as they relate to extracurricularparticipation. Self-efficacy development was an emerging construct of this study, however sinceself-efficacy was not intentionally investigated for this study, a sufficient understanding of self-efficacy as it relates to extracurricular participation was limited by the research design of thisstudy. Future work should focus primarily on self-efficacy theory and measurement. A possibledirection of this
. Students used the same 5-pt. Likert-type scale to rate theiragreement with items such as: 1) I consider several ways to solve the problem before I answerand 2) I know how well I did after solving the problem.Results Across the two courses, 530 students consented to participation and served as ourresearch sample. In addressing the research questions, comparisons of changes within-subjectsfrom pre to posttest were assessed via paired t-test. Between groups comparisons involved ananalysis of covariance (ANCOVA) with the pretest values for each measure as the covariate. For the first semester course, the treatment group had initially higher levels of self-efficacy, confidence in their math and science abilities, prior exposure to project
and metacognition. Thus this response is surprisingwhen looking at the clustering alone. The literature suggests a few possible reasons why thisresponse occurred. First, self-efficacy and test anxiety may play a more distinct role in gradeperformance than many of the other factors investigated in this particular study [12, 13]. Cluster3 participants reported higher levels of self-efficacy, lower levels of test anxiety when comparedto cluster 1. Future work will further investigate how these factors play a role in performance.Second, many SRL theorists believe that participants may have difficulty accurately assessingtheir levels of SRL skills [14-16]. A call for qualitative measures as well as studies conducted intrue learning contexts may
. The program seeksto improve students’ competence and self-efficacy in science and engineering, stimulate an interestin pursuing STEM-related careers, and provide engaging “hands-on/mind-on activities.” Theprogram is divided into two initiatives which include an academic year and weekend academy. Atotal of 45 middle school students have participated in a 1-week Girls in Science Lab Camp andfive half-day Girls in Science and Engineering Weekend Academy activities. For the Girls inScience Lab program, the participants were divided into teams and assigned an environmentalscience and engineering themed case study to solve during guided laboratory experience. Studentswere taught how to collect and analyze water samples using university laboratory
studies to validatetheir results due to the short length of their research or small classroom size. In addition, many ofthese studies do not measure student attitudes, such as self-efficacy, or the difference in timespent out of class on coursework.The objective of this research is to determine the effectiveness of the flipped classroom system incomparison to the traditional classroom system (TC) in a large mechanics of materials course.Specifically, it aims to measure student performance, student self-efficacy, student attitudes onlecture quality, motivation, attendance, hours spent out of class, practice, and support, anddifference in impact between high, middle, and low achieving students. In order to accomplishthis, three undergraduate
SurveyThe MATES62 was developed and revised66 to measure middle school students’ attitudes towardmathematics, science, especially engineering, and their knowledge about careers in engineering(i.e. what engineers actually do). In addition to all over attitudes toward mathematics, science andengineering, six subscales have been identified to measure Interest in engineering: stereotypicaspects (Stereotypic), Interest in engineering: non-stereotypic aspects (Nonstereotypic), Negativeopinions (Negative), Positive opinions (Positive), Gender Equity (Gender) and Self-Efficacy forProblem Solving and Technical Skills (i.e. skills needed for engineering).The MATES also measures knowledge about careers in engineering with a multi-part open-endedquestion that
the course had a small effect on students’ intrinsic values, and mediumeffects on students’ feeling of inclusion and expectation of success in engineering design.However, it is worth mentioning that the pre-survey was conducted during the middle of thesemester. If measured for a whole semester, the data may have shown relatively larger effectsizes on students’ engineering motivation and design self-efficacy. Longitudinal data will becollected to investigate the influence of the course on students’ attitudes toward and learning ofengineering. Figure 19: Comparison of student engineering motivations Figure 20: Comparison of student design self -efficacyConclusionFeedback from industrial partners indicates
student preference 3,4 , self-efficacy5 and studentengagement6 . Although most studies have found no differences in measured learning gains 4,7,8 a fewhave9,10 .Although our previous work showed no differences in learning gains as measured by final exam scores 4 ,we wondered if a flipped classroom could create a more motivating classroom climate. One motivationtheory11 states that a student’s motivation to learn is based on three levers. The first levers is value. Dostudents see value in the content? The second lever is self-efficacy. Do students believe they can do wellin the class? Specifically, if a student has high efficacy expectancies, they believe that they are “capableof identifying, organizing, initiating and executing a course of action
research paper examines first-year student performance and retention within engineering. Aconsiderable body of literature has reported factors influencing performance and retention,including high school GPA and SAT scores,1,2,3 gender,4 self-efficacy,1,5 social status,2,6,7hobbies,4 and social integration.6,7 Although these factors can help explain and even partiallypredict student outcomes, they can be difficult to measure; typical survey instruments are lengthyand can be invasive of student privacy. To address this limitation, the present paper examineswhether a much simpler survey can be used to understand student motivations and anticipatestudent outcomes.The survey was administered to 347 students in an introductory Engineering Graphics
have a negative experience with teamwork (reverse coded) • I would rather work on team projects than on my own • I like to participate in teamwork • I am usually motivated to participate in teamworkIn order to measure their teamwork self-efficacy, students are asked to rate themselves usingfour-level Likert scales (1= Very Unconfident, 2=Unconfident, 3=Confident, 4= Very confident)with respect to the following teamwork skill, knowledge, and abilities. • Establishing specific team goals • Evaluating team progress toward each team goal • Providing feedback on the team or individual performance • Accepting feedback and criticism positively • Making adjustments based on the feedback • Defining tasks and clear task
forLearning Questionnaire (MSLQ), Metacognitive Awareness Scale (Schraw & Dennison), and theSTEM Questionnaires developed by the STEM team at the Higher Education Research Institute(HERI). A factor analysis was conducted on the pretest survey questions to determine whichquestions were most appropriate to represent the various constructs of interest including self-efficacy for learning, metacognitive self-regulation, peer learning, and help seeking behavior.Based on these data, a truncated scale was administered to students at posttest. Items used as partof the posttest include 14 items from the MSLQ and 4 items from the Metacognitive AwarenessScale (MAS). The posttest also included additional items from the HERI questionnaire as well ascourse