Paper ID #33241Creative Self-Efficacy of Undergraduate Women Engineering MajorsDr. Christine Delahanty, Bucks County Community College Dr. Delahanty is the Area Coordinator of Science and Engineering, and Professor of Engineering and Physics at Bucks County Community College (Bucks). She worked as an electrical engineer at General Electric Co. for nine years in both military and commercial communication satellite operations. Her research interests include investigating creativity within STEM education as a factor in cultivating diver- sity. She establishes technical, college level, programs of study for modernized
materials to help facilitate rapid prototyping activities.After survey completion, student data were grouped into two categories based on response to questionsrelated to engineering self-efficacy. The highest responders on the engineering skills scales greater than 4on a 5-point Likert Scale were grouped as high-engineering self-efficacy, or high-ESE, and compared tothose responders that scored less than 4 on a 5-point Likert Scale as low-engineering self-efficacy, or low-ESE.Student perceptions towards different design activities were also measured. To examine the reliability ofthe scales for engineering self-efficacy, rapid prototyping, CAD, and 3D printing, the set of questionsassociated with each scale were assessed using Cronbach’s alpha test
.[3] May, Vicki (2014). “Broadening the Path to Engineering,” Huffington Post. http://www.huffingtonpost.com/vicki-may/broadening-the-path-to- engineering_b_4941739.html. March 2014.[4] Mamaril, Natasha A., Usher, Ellen L., Li, Caihong R., Economy, D. Ross, and Kennedy, Marian, S. (2016). “Measuring Undergraduate Students’ Engineering Self-Efficacy: A Validation Study.’ Journal of Engineering Education. Vol. 105, No. 2, pp. 366-395.[5] Hsieh, P., Sullivan, J. R., Sass, D. A., & Guerra, N. S. (2012). Undergraduate engineering students’ beliefs, coping strategies, and academic performance: An evaluation of theoretical models. Journal of Experimental Education, 80, 196–218. http://dx.doi.org
retainingwomen engineering students? Do the virtual measures foster the same levels of self-efficacy inwomen engineering students as the previously offered face-to-face interactions? Do womenengineering students feel additional isolation from their peer group and perhaps question theircareer path when faced with an increased amount of online presence and the removal of criticalprograms aimed at increasing retention?While it is impossible to know the long-term impact on women engineering students due to thepandemic, it is possible to measure the immediate change in self-efficacy, sense of belonging andconfidence in program of study. This study measured changes in self-efficacy, belonging andconfidence of undergraduate women engineering students at a
-Middle and High School Students [5]will assess students’ attitudes about STEM-related academic course work, STEM-related careers,personal interests and professional contacts, growth mindset and self-efficacy. The survey is partof a set of STEM outreach measurement resources available for educational purposes from TheFriday Institute for Educational Innovation at North Carolina State University College ofEducation.The items assessing attitudes about STEM-related academic courses ask students to rateagreement, using a 5-point Likert scale, with statements related to math courses (3 items), andscience courses (3 items). Students are also asked to indicate agreement with statements assessinginterest in activities related to engineering and
Loyola University Chicago and is currently holds the Walter P. Krolikowski, SJ Endowed Chair in the School of Education at Loyola University Chicago. He is an Associate Editor of the Journal of Counseling Psychology and his research interests span four related areas: multiculturalism, vocational psychology, social justice engagement, and applied psychological measurement. American c Society for Engineering Education, 2021 Exploring the validity of the engineering design self-efficacy scale for secondary school students (Research to Practice)Introduction and BackgroundPre-college engineering education efforts and associated research has seen a
University in Ghana. Pre and post surveys were administered tounderstand changes in students’ self-efficacy as a result of the intervention. The project scopewas to design, build, and fly a quadcopter drone to simulate surveying a mining area inZimbabwe and transporting items between two sites. This scope was significantly morechallenging than anything most of them had done before, as evidenced by less than half of thestudents reporting prior experience designing and building any product, and nearly a thirddescribing the project as “impossible” at first. Significant (p < 1.04 E-2) increases with mediumto large effect sizes (|g| = 0.653 to 1.427) were measured for five of six self-efficacy measures,capturing how students’ belief in their own
otherhands-on learning opportunities increase student self-efficacy and have positive effects onretention of minority students, particularly into postgraduate studies. Here we focus on assessingthe short-term effects of “Making” activities. Assessment included pre- and post-student self-efficacy surveys with three distinct areas of measurement: general self-efficacy, self-efficacy incourse outcomes, and self-efficacy in EM-related constructs.Preliminary data suggests that inclusive PSS activities resulted in positive student motivationalresponses comprising high levels of identified regulation and external regulation, with moderatelevels of intrinsic motivation. Relative to the average motivational response of the entire class,underrepresented
. [15]We hypothesize that increased participation in co-curricular activities, especially engineeringstudent organizations, will provide positive experiences that will be a driving force to pursuemore activities and more responsibilities. The more students experience positive outcomes whenperforming responsibilities could lead to increased self-efficacy and increased academic success.[16] The compounding reward system proposes that participation in co-curricular activitiesincreases self-efficacy and academic success in college. Student GPA, time to degree completion,and internships will be used to measure student success. A survey and case study interview willbe used to assess self-efficacy. Figure 1 shows the possible scenarios between self
given the NILA’s leadership framework and curriculum focus onthe development in these areas. The average mean for leadership self-efficacy increased from 4.0to 4.3. The increase was significant, and it shows that NILA had a measurable positive effect.Nevertheless, the effect may or may not be sustainable. Most of the change was explained by thelower values (pre-test minimum=2.6, post-test minimum=3.0), which is reflected in a smallerstandard deviation for the post-survey. This shows that the effect may be larger for those whocome in with lower self-efficacy than those who are already confident in their abilities. While thesample size was small, the EFA analysis is statistically significant to tentatively support ourhypothesis. However, this can
CT awareness among leaders andpractitioners, builds traction by relating CT to local goals, educational initiatives, or reformefforts, connects teachers to help them explore grade-appropriate implementation, and createsopportunities to practice CT learning activities.Related WorkMalallah investigated complications associated with adopting a U.S.-based STEM outreachprogram into the Kuwaiti educational system. The program focused on teaching CT viaArduino and Scratch to students in grades 6–9. Malallah used pre-post self-efficacy surveys todetermine increased CT awareness. Survey results revealed that, although students wereconfused about some CT concepts, their overall CT knowledge improved after the STEMoutreach program [19]. In a
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
Attrition: Lessons from Four Departments. The Journal of Higher Education, 76(6), 669–700. https://doi.org/10.1080/00221546.2005.11772304Holbrook, A., Shaw, K., Scevak, J., Bourke, S., Cantwell, R., & Budd, J. (2014). PhD candidate expectations: Exploring mismatch with experience. International Journal of Doctoral Studies, 9, 329–346.Holloway-Friesen, H. (2019). The Role of Mentoring on Hispanic Graduate Students’ Sense of Belonging and Academic Self-Efficacy. Journal of Hispanic Higher Education, 153819271882371. https://doi.org/10.1177/1538192718823716Jaeger, A. J., Mitchall, A., O’Meara, K. A., Grantham, A., Zhang, J., Eliason, J., & Cowdery, K. (2017). Push and pull: The influence of race
instrumentality in the motivationliterature [2]. Both of the frameworks in this study measure different aspects of students' beliefsabout their abilities in math and engineering and are utilized as they can shift due to educationalexperiences [20], [21]. The operationalization of these constructs, along with our population andstudy design, are outlined below.Research QuestionBy building off the body of available literature about student mathematics and the role ofengineering in fostering positive beliefs, we sought to implement an integrated engineering,science, and mathematics unit and answer the following research question:How do 5th-grade students' mathematics and engineering self-efficacy and perceived usefulnessfor abstract mathematics concepts
, unlike the other measures, there was much more room forgrowth. However, there was no significant change detected. Thus, we cannot conclude that thelab kit and curriculum relate to self-beliefs.Table 4. Self-Efficacy results (N = 39) Initial Change Mean: 3.17 Change Mean = 0.17 Standard Deviation: 1.16 Change Standard Deviation =1.40 Conclusion and Future Directions Overall, the lab kit and neuroscience curriculum were most successful in the area ofimproving science aspirations for diverse students. Additional changes need to be made in futureiterations to the curricular materials
]. 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
captured by SHPE’s long-term NRP throughout the year.While several internal components of McCormick’s model have been validated, NILA’scurriculum serves as a unique opportunity to measure self-efficacy, a challenging aspect tomeasure [47-50], and validate in the context of Hispanic STEM professionals.Figure 2. McCormick’s Social Cognitive Model of Leadership [38], reproduced with permission from the publisher.3. SHPE’s Leadership and Chapter Programming Mapping to McCormick’s Model3.1 NILA’s Curriculum Mapped to Leader Cognitions Figure 3 shows the concept mapping of NILA’s 2019 curriculum to the leader cognitionportion of McCormick’s model [48]. Following the OGSM model presented in Section 2.1,NILA’s objective is captured by McCormick’s
; Tutwiller, 2017; Komarraju, Swanson, & Nadler, 2014). AmongSTEM students, self-efficacy predicts engagement, recruitment, and retention of STEM students(Lent et al., 2003; Wang, 2013).STEM self-efficacy is often measured using a modified 5-item scale originally created byMidgley et al. (2000) as a measure of academic self-efficacy. Participants answer on a 1(Strongly Disagree) to 7 (Strongly Agree) scale with sample items that include: “I can do almostall the work in my STEM classes if I don’t give up” and “I am certain I can figure out how to dothe most difficult class work in STEM.” This scale has been used in recent empirical workcharacterizing how psychosocial variables influences STEM outcomes (Lytle & Shin, 2020; Shinet al., 2016
demographics were effect coded as dichotomous variables:gender (female = 1 vs. male = -1; other genders were present in very small numbers and wereeliminated from the analysis) and international status (U.S. citizen or permanent resident = -1 vs.international student = 1). Instructional modality was also effect coded as a dichotomous variable(remote = -1 vs. traditional = 1).Additional scales used in this study included those associated with task value, self-efficacy,participation, TA support, faculty support, and positive emotional engagement. Sample items,primary scales as well as the source of these scales are noted in Table 1.Table 1: Independent and Dependent Variables(𝛼 =Cronbach's Alpha measure of internal consistency) References Primary
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
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
science teacher fellows. Gunning presents her research on science teacher self-efficacy, vertical learning communities for teacher professional develop- ment and family STEM learning at international conferences every year since 2009 and is published. She is the Co-Director and Co-Founder of Mercy College’s Center for STEM Education.Dr. Meghan E. Marrero, Mercy College Dr. Meghan Marrero is a Professor of Secondary Education at Mercy College, where she also co-directs the Mercy College Center for STEM Education, which seeks to provide access to STEM experiences for teachers, students, and families. Dr. Marrero was a 2018 Fulbright Scholar to Ireland, during which she implemented a science and engineering program for
domain during the pre-college yearsthat is one of the strongest predictors of intent to pursue or persist in a STEM major in college.This exploratory case study examined the lived experiences of eight high school girls whoexhibited strong STEM identities. This work reports on the role that all-female STEM spacesinfluenced participants’ intent to pursue STEM majors in college. Eight junior and senior girlswere interviewed over the course of an eight-week period during fall 2019 regarding theirperceived feelings of self-efficacy, their feelings of recognition in STEM, and their interest inSTEM domains. This qualitative research was framed using Godwin’s 2016 Engineering IdentityFramework, adapting it to accommodate a broader STEM Identity and
constructs in the population. The constructs are all positively correlated, withmagnitude of correlation corresponding to the size of the bubble. This is shown by the checkedbubbles intersecting any two pairs of measures in Figure 2. It is evident that Anticipatory Cognitionis correlated and significant to several of the measures, but lacks significance against stereotypethreat, isolation, extant knowledge and future anticipation. For example, the weaker theparticipants infer the stereotype threat, the higher is their attention and focus to solving theirresearch problem. It is also evident from this Figure that Academic Self Efficacy is predominantlycorrelated
, including student scoreon the pretest three-dimensional modeling self-efficacy (3DSE) assessment, gender, age, andwhether or not the student had a parent with professional engineering backgrounds. The three-dimensional self-efficacy instrument consisted of nine questions, each being a 7-point Likerttype item, designed to measure students’ self-efficacy related to modeling three-dimensionalobjects [11]. Logistic regression could not identify for which subgroups of students the variableswere most significant. For these reasons, machine learning analytics software was used toexamine the predictors, and their interactions, that led to persistence in engineering degreeprograms. Machine learning has gained popularity over recent years due to its ability
, extrinsic goal orientation, task value, control of learning beliefs, self-efficacy forlearning and performance, critical thinking, and metacognitive self-regulation; 2) the Change-Readiness Assessment [10] which assess 7 subscales, including adventurousness, confidence,adaptability, drive, optimism, resourcefulness, and tolerance for ambiguity; 3) PersistenceMeasures [11] which measures 3 responses including graduate study, career, and intent to changemajor; and 4) the Longitudinal Assessment in Engineering Self-Efficacy [12] which providesresults in six subscales, including self-efficacy, sense of belonging, and career expectations. Allof the questions are related to the course and/or learning environment. These questionnairesemploy 7-point Likert
specified). In addition, we assessed social cognitive variables related to educationaland career decision making, including engineering self-efficacy, expectations for the field ofengineering, commitment to major and degree completion. In 2019, students were asked if theyidentified as a member of the LGBTQ+ community, allowing for a better understanding of thesestudents’ experiences. Data from all three survey years were combined to investigate trends oncritical measures related to persistence in engineering. We found that students’ assessment of theeducational environment (professors and student interactions) were relatively stable, while otheraspects of the environment (experiences of stereotyping and harassment) significantly increasedacross the
, to estimate the expected total numberof delayed months, including: 1-3 months, 4-6 months, 7-9 months, 10-12 months, and morethan one year. In terms of the career outcome, we evaluated students’ job search self-efficacy byasking three questions [25]: “Since the COVID-19 outbreak occurred, how confident have youbecome in finding (1) the job for which you are qualified? (2) a job in a company/institution thatyou prefer? (3) the job for which you are prepared?” The 5-point Likert scale was from -2 (muchless confident) to 2 (much more confident). The Cronbach’s alpha for these three job search self-efficacy items is .906. The measure for mental health outcome, which focused on symptoms ofdepression and anxiety, asked students if in the last 7
participants to report these findings. The remainder of theanalyses focused on gender.Similar rates of persistence existed for women and men, even though when they began theprogram there were statistically significant difference between mean scale scores for freshmenwomen and men on some measures of self-efficacy. For the Self-Efficacy Scale II, t(66) = 2.63,p = .011; Career Success Scale, t(66) = 3.03, p = .004, and Math Scale t(66) = 2.49, p = .015,men averaged higher scores than women (see Table 2 for averages). Although men scored higherthan women on the Self-Efficacy I Scale and Coping Self-Efficacy Scale, these results were notsignificantly different. Women and men scored similarly on the Inclusion Scale. The means onself-efficacy scales at the
students to enter graduate school. Quantitative measurableoutcomes will include increased student retention; increased cohort self-efficacy and identitystatistics; higher-than-average graduation rate for the cohorts through evidence-based programs;and successful placement in industry or graduate school. CREATE will have a broad impact onlow-income, academically talented students in two key ways (1) Support of 32 students withscholarships; and (2) Implementation and assessment of academic and professional developmentsupport mechanisms that are tuned to the needs of these students. Both impacts achievestate/federal strategic workforce diversification goals. Qualitative measurable outcomes willinclude attaining academic and personal goals; increased