, “Measuring entrepreneurial self-efficacy to understand the impact of creative activities for learning innovation,” Intl J Mgmt Educ, 12, pp. 456-468, 2014.[9] J.H. Dyer, H. B. Gregersen, and C.M. Christensen, “Entrepreneur Behaviors, Opportunity Recognition, and the Origins of Innovative Ventures,” Strateg. Entrepreneurship J, 2 (4): pp. 317–38, 2008.[10] G. Balau, D. Faems, J. van der Bij, “Individual characteristics and their influence on innovation: A literature review,” Proceedings of the 9th International Conference on Innovation and Management, Nov. 14-16, Eindhoven, The Netherlands. Eds. G. Duysters, A. de Hoyos, K. Kaminishi, Wuhan University Press, pp. 887-901, 2012.[11] A. Bolhari, & S. Tillema
data set measures students’ social cognitions over the course of theSpring 2020 semester in a set of 8 engineering courses using the same group of students beforeand after the unexpected transition to remote learning.BACKGROUNDThis study seeks to determine if the sudden transition to remote learning impacted students’engineering self-efficacy and outcome expectations. If these social cognitions were impacted,then student’s performance, persistence, and approach/avoidance behavior may also be impacted.To understand the basis of the study, the following section reviews the relevant background onsocial cognitions.Social CognitionsBandura’s [2, 3] social cognitive theory postulates that the social cognitions of self-efficacy andoutcome
first step in leadership development. By their responses they have shown an accurateself-awareness, honesty, and self- discipline. They have demonstrated that they can lead themselves.GrowthStudent’s growth of their leadership was examined through instruments that measured theirLeadership Self-Efficacy (LSE) and Motivation to Lead (MTL). LDP students showed the mostimprovement in efficacy after one year of the program. Similarly, LDP students’ motivationappear to remain consistent throughout the program.Combining this with results from the control group, suggest that LDP students come into theprogram with higher motivation than their peers but develop higher efficacy because of theprogram. Future surveys will incorporate a retrospective pre
be increased by learning additionalmaterial concerning the specific goals and being motivated towards success8. Higher self-efficacy leads to higher achievement behaviors.Self-efficacy assessments are difficult to create because they need to have a precise measurementconsistent with the criteria tasks in order to maximize the influence of self-efficacy as apredictive power1. Validation of an instrument is important because it is used as a justificationof the adequacy of the measured values9, 10. Carberry et al. developed a self-efficacy instrumentto study people’s self-efficacy towards engineering design tasks and proved three sources ofvalidity: content, criterion-related, and construct2.Carberry’s instrument examines four task-specific
makerspaces blend new manufacturingtechnologies like 3-d printing and laser cuttings with more traditional woodworking andmachine shop tools. Little data exist, however, about what the impact of universitymakerspaces is on the students who choose to participate in those spaces. In order to betterunderstand this impact of university makerspaces, our research team is conducting a multi-university longitudinal study.To measure the impact of making environments, this study looks at different metrics such asGPA, design self-efficacy, retention, and idea generation ability and how these metrics areaffected by different levels of involvement in university makerspaces. Preliminary results (twoof four years are completed) from the longitudinal studies raised
Student Preparedness for Chemical Engineering Curricula.” Chemical Engineering Education, 52(3): 181-191 (2018).[17] Cicciarelli, B.A., Sherer, E.A., Martin, B.A., and Orr, M.K., "From Assessment to Research: Evolution of the Study of a Two-Day Intervention for ChemE Sophomores.” 2020 ASEE Virtual Annual Conference, June 2020: Paper ID #30669.[18] Mamaril, N.A., Usher, E.L., Li, C.R., Economy, D.R. and Kennedy, M.S. “Measuring Undergraduate Students’ Engineering Self‐Efficacy: A Validation Study,” Journal of Engineering Education, 105(2), 366-395 (2016).[19] LAESE survey instrument developed as part of Assessing Women in Engineering (AWE) project: www.aweonline.org; NSF Grant #0120642. Marra, R.M. and Bogue, B., 2006
programsurvey was used to probe participant ‘s abilities/confidence in research. Their results indicateddirect relationships between research skills and research self-efficacy. These researchers alsofound that research skills and self-efficacy were good predictors of career aspirations.8 However,the measures used to assess research self-efficacy were not ideal. For example, items such as “Ihave the ability to have a successful career as a researcher,” and “I have a strong interest inpursuing a career as a researcher” are reflective of the student’s career goals, but may not reflecttheir beliefs in their current research capabilities. This concern about the quality of self-efficacyitems for assessing the gains in REU programs was highlighted earlier by
Camp Wilson, T. Telling more than we can know: Verbal reports on mental processes. Psychological Review 84(3)., 231-259, 1977.19. Eraut, M. Informal learning in the workplace. Studies in Continuing Education 26(2), 247- 273, 2004.20. Lave, J., & Wenger, E. Situated learning: Legitimate peripheral participation. Cambridge, England: Cambridge University Press, 1991.21. Knowles, M. The adult learner: A neglected species (3rd Ed). Houston, TX: Gulf Publishing, 1984.22. Bandura, A. Self-efficacy: Toward a unifying theory of behavioral change. Psychological Review 84, 191-215, 1977.23. Carberry, A., Lee, H., & Ohland, M. Measuring engineering design self-efficacy. Journal of Engineering Education 99(1), 71-79, 2010.24
related problems. For students specifically, makerspaces provide opportunities for hands‐on experience in problem solving, design, prototyping, and manufacturing. Given the collaborative‐learning nature of makerspaces, and how prevalently they’re used by students, the question posed is how does makerspace involvement impact student performance. In this longitudinal study, student performance is qualified by experimental measurements of idea generation ability and engineering design self‐efficacy (EDSE). Method The data presented here is a part of a 5‐year longitudinal study (removed). In this paper we focus impact to idea generation. The participants of this study were freshman and senior undergraduate students from
Community and Self-Efficacy Building of Civil Engineering StudentsIntroductionThe Citadel, a regional, residential military college, is currently engaged in a multi-year NSF S-STEMproject to encourage persistence of academically-talented, low-income civil engineering students. OurExcellence in Civil Engineering Leadership (ExCEL) scholarship program builds on a prior program (ofthe same name) that included 34 scholarship recipients, of which 85% graduated with a STEM degree and65% met the academic requirements to graduate as an ExCEL scholar [1]. The current ExCEL programseeks to retain several community-building and support services that were highly valued by our formerstudents, including: (1) funding to attend the
section included questions designed to assess participants’ self-efficacywith teaching engineering using 2 constructs: content knowledge self-efficacy and engagementself-efficacy. Content knowledge self-efficacy measured participants’ self-efficacy as it relates toknowledge about engineering, while engagement self-efficacy measured participants self-efficacy with engaging students in engineering practices [9],[10].A total of 41 students enrolled in 5 different VolsTeach courses completed the survey. The mostcommon majors among the survey participants were mathematics (41%) and biology (20%),although many STEM fields, including engineering, were represented. 61% of the participantswere either third or fourth year students, while 39% were first or
importance in relation to other identities in the self-concept), suggest that the design Fellows are unclear regarding the extent to which their identityas an engineer is one of the more important identities they have. The five items at the bottom ofthe table which measure identity salience (or the likelihood that the identity is activated acrosscontexts) however reflect somewhat higher scores. This suggests the Fellows’ identities asengineers are relevant within their social interactions across multiple contexts. As can be seen in Table 4, the Design Fellows on average reported a moderately highlevel of engineering self-efficacy with an overall mean of 5.44 across all scale items. Thissuggests that the fellows on average “Somewhat Agreed” or
data set is collected over the comingsemesters. Table 1. Mean and standard deviation for each measure of problem-solving self-efficacy. Civil Engineers (n=34) Non-Civil Engineers (n=36) Mean Standard Mean Standard Deviation Deviation Problem definition (/100) 81.6 9.0 83.3 10.4 Representation & 82.0 10.1 82.6 12.0 Organization (/100) Calculations (/100) 87.3 10.0 84.6 11.1 Evaluate Solution (/100) 87.9 8.4
Designing andConducting Mixed Methods Research by J.W. Creswell & V.L. Plano Clark, 2007.ParticipantsThis study will focus on the experiences of first-year engineering students. These students areable to inform our research questions because they are the least removed from their precollegeengineering experiences and from the transition to college engineering programs. To the extentthat self-efficacy is important to persistence in engineering4, the mastery experiences of first-yearstudents will be more closely tied to their precollege experiences, whereas the masteryexperiences of upper-level engineering students will be derived from their college engineeringexperiences.Qualitative Data CollectionWe administered a survey on students’ demographic
, fostering diverse learningenvironments, and promoting multi-disciplinary teams. We will also investigate the potential ofmaker spaces to positively influence females and minorities and thereby broaden participation inengineering.Impact will be measured through engineering design self-efficacy; retention in the engineeringmajor; and idea generation ability. Impacts will be measured at two levels. The first level of theproject will use a randomly assigned experimental design to assess the impact of early makerspace engagement on females and minorities through longitudinal measurements. In the secondlevel, we compare segment snapshots and longitudinal measurements between extensive makerspace users and those with minimal exposure. We will also
an undergraduateengineering program at a large southwestern university. Students were invited to respond toonline surveys using a link sent to their university email address. Participants were surveyedthree times during their first year: prior to entering the engineering program (Survey 1), at theend of their first semester (Survey 2), and at the end of their second semester (Survey 3).Students were given time during summer orientation and during class to complete these surveys.In total, a sample of 2473 participants was used to develop and validate a 5-item engineeringidentity measure, with Surveys 1, 2, and 3 consisting of 1900, 1083, and 481 respondents,respectively.MeasuresEngineering identity and engineering self-efficacy, the belief
). “The role of interest in understanding the career choices of female and male college students,” Sex Roles, vol. 44, pp. 295-320. 2001.National Academy of Engineering. (2004). “The Engineer of 2020: Visions of Engineering in the New Century,” National Academies Press, Washington, D.C, 2004.Ponton, M. K., Edmister, J. H., Ukeiley, L. S. & Seiner, J. M. (2001). “Understanding the role of self- efficacy in engineering education,” Jnl of Engineering Education, vol. 90, no. 2, pp. 247-251, 2001.Priniski, S. J., Hecht, C. A. & Harackiewicz, J. M. (2017). “Making Learning Personally Meaningful: A New Framework for Relevance Research,” The Jnl of Experimental Education, vol. 86, no. 1, October 18, 2017
in the project: identification and self-efficacy. Further,it presents results responses from approximately 2,000 first-year engineering students at a largepublic institution. The paper addresses two questions: 1) How do engineering students respond totwo scales related to identity frameworks; and 2) What has been learned by giving these twoscales to first-year engineering students.IntroductionThe importance of increasing the number and diversity of B.S. graduates with degrees in science,technology, engineering, and mathematics (STEM) has been highlighted in several nationalreports1,2 . Increasing retention of students, including retention of students traditionallyunderrepresented in engineering is one approach to addressing this challenge
a pathway to recruit students to robotics and engineering careers.IntroductionPre-college robotics programs are common precursors to majoring in engineering [1]. However,gender disparities persist across engineering disciplines. The fact that girls do not participate inpre-college robotics at the same rate as boys has been proposed as a bottleneck for girls enrollingin engineering majors [2]. When girls are not part of extracurricular robotics programs, they missvital opportunities to develop tinkering self-efficacy and join engineering majors includingmechanical and electrical engineering [3]. Alternatively, bioengineering and biomedicalengineering (BME) programs graduate ~40% women students each year [4]. Diversity in BME iswell studied
surveys provide a quantitative measure of students’ GRIT, general self-efficacy,engineering self-efficacy, test anxiety, math outcome efficacy, intrinsic value of learning,inclusion, career expectations, and coping efficacy. Qualitative data from the focus group andindividual interview responses are used to provide insight into the quantitative survey results.Surprisingly, a previous analysis of the 2017 cohort survey responses revealed that students wholeft engineering had higher baseline values of GRIT, career expectations, engineering self-efficacy, and math outcome efficacy than those students who retained. Hence, the 2018 cohortsurvey responses were analyzed in relation to retention and are presented along with qualitativeresults to provide
outcomes [14, 15]. In somecases, self-efficacy is seen as a significant predictor of academic outcomes [16-18]. However,just as in other areas, a universal measure of self-efficacy is not appropriate to determine ethicsself-efficacy [19, 20]. Some domain specific self-efficacy scales include general engineering [21]and software engineering [22]. This work presents a survey instrument that attempts to measureethical self-efficacy.Whereas a general self-efficacy instrument would contain questions such as, “I can alwaysmanage to solve difficult problems if I try hard enough” or “I can solve most problems if I investthe necessary effort” [23], an instrument related to the design domain would include questionssuch as “I can identify a design need
, Discipline-Based Education Research: Understanding and Improving Learning in Undergraduate Science and Engineering. 2012.[5] American Educational Research Association, American Psychological Association, and National Council on Measurment in Education, Standards for Educational and Psychological Testing. 2014.[6] R. J. Jenson, A. N. Petri, A. D. Day, K. Z. Truman, and K. Duffy, “Perceptions of Self- Efficacy among STEM Students with Disabilities,” Journal of Postsecondary Education and Disability, vol. 24, no. 4, pp. 269–283, 2011.[7] Şe. Purzer, “The Relationship Between Team Discourse, Self-Efficacy, and Individual Achievement: A Sequential Mixed-Methods Study,” Journal of Engineering Education, vol. 100, no. 4, pp. 655
increases in short and long-term student learning are mediated by experiences thathelp students identify needs and develop design solutions (i.e., developmentally instigativebehaviors). These experiences in turn enhance students’ valuation of engineering, beliefs aboutcapabilities, and identification as an engineer; motivating future behaviors. Like a cyberneticsystem then [29], these processes repeat and are self-regulating. Several basic hypotheses will beused to assess both the validity of the scales used to measure engineering values, self-efficacy,and identity and the plausibility of this theoretical framework. Students who engage in moreengineering related activities (e.g., attending an engineering conference, facilitated study group,or
. c American Society for Engineering Education, 2019 Model Building in Engineering Education This paper reports on research that is part of a lager project taking place at a mid-sizedpublic HBCU funded through the National Science Foundation’s Revolutionizing Engineeringand computer science Departments (RED) program. The purpose of the RED program is toencourage and support innovation projects that develop new, revolutionary approaches andchange strategies that enable the transformation of undergraduate engineering education [1]. Avital component of this particular RED project involves the development and validation ofsurvey-based measures of Engineering Values, Self-Efficacy, and Identity: and a model thatcombines
use in K-12classrooms. A new course model was created that utilized a hybrid community of practice wherestudents learned about engineering education and worked together to support local K-12 schoolsby engaging in service learning. This project explored the ways in which participation in thiscourse impacted pre-service teachers’ perceptions of engineering and engineering teaching self-efficacy. We first administered a survey designed to measure engineering teaching self-efficacyto pre-service teachers at the beginning and end of the course. In addition, pre-service teachersalso completed reflective journals throughout the course in which they were asked to reflect onhow specific aspects of the course impacted their understanding of the nature
, andpersistence (Table 1). We used the framing agency survey [6, 7], which incorporates research-based measures of design self-efficacy [8, 9] and engineering identity [1, 10].Table 1. Survey questions and constructs measured Construct Items (7-point scale, with ends named in question) Individual consequentiality How responsible or not responsible have you felt: The extent to which an • for making decisions personally? individual reports that the • for coming up with your own ways to make progress on the problem changed, or their design project? understanding changed as a • for the outcomes of the design project? result of decisions made
]. Students who ultimately leave engineeringbefore their second year often begin their engineering journey with unrealistic views of theirability and the difficulty of the journey. Typically, they underestimate the demands of the major(and career) and overestimate their ability to succeed in the major with little extra effort [2], [3],[5]. This paper compares pre- and post-measures of characteristics believed to be influential orrelated to academic success and student retention in STEM fields for three cohorts (2017, 2018,and 2019) of the AcES program.2.0 MethodologyThree survey instruments: the Grit assessment [6], [7], the Longitudinal Assessment ofEngineering Self-Efficacy (LAESE) survey [8], [9], and the Motivated Strategies for
Efficacy Scale (TSES) survey is a set of questionnaires developed byTschannen-Moran at College of William and Mary and Woolfolk Hoy at the Ohio State University[4]. It is designed to help people gain a better understanding of the kinds of things that createdifficulties for teachers in their school activities. Similarly, teachers are asked to indicate theopinion about each question by marking from 1 to 9. There are two forms of this survey. The longform has 24 questions and the short form has 12 questions. These questions measure efficacy inStudent Engagement, Instruction Strategies, and Classroom Management. TSES has been used inmany teachers’ self-efficacy studies. 2.2 Bandura’s Instrument Teacher Self-efficacy Scale Bandura’s instrument on
summerresidential program geared towards providing high school teachers with insights into the latest inmanufacturing research. The goal was to improve their beliefs and attitudes regarding STEMeducation so that they would feel more capable to impart similar technical information to theirstudents.The next section of this paper (Literature Review) provides an overview of several paperspublished in the area of teaching self-efficacy, its relationship with STEM education, and theinstruments that have been used for its measurement. The Research Design section describes indetail the methodology and instruments used for the purpose of this study. The Data Analysissection provides a description of the data used for this study and the results of the
organize and execute the courses ofaction required to produce given attainments” [6](p. 3), is a critical form of motivation and basisfor evaluating persistence. It is one of the strongest predictors for undergraduate studentachievement [7],[8] and a lack of self-efficacy has been shown to foreshadow a change of majorsand leaving engineering for underrepresented students [9],[10]. For engineering students, self-efficacy predicts interest, achievement and persistence in the major [11],[12],[13]. Self-efficacyis most likely to drop during the first two years a student spends at a university [14].This paper reports on a field study of student self-efficacy and persistence across a semester forthree groups taking general chemistry laboratory for