still suggested to apply parametric tests if both groupshave sample sizes larger than n=15 even when some test assumptions are not met [16].When data collection from the mid-term and end-of-course surveys are completed, we propose touse two-way mixed ANOVA to measure how the two groups of students’ programming attitudesand self-efficacy evolve over the semester. Ordinal logistic regression might also be conducted totake more factors that could affect attitudes and efficacy levels into account. Besides, qualitativeanalysis will also be performed on the courses they have taken and the courses they think thathave prepared them for the lab activities to provide additional information on the findings.ResultsAccording to the survey data, previous
Paper ID #44125Examining Imposter Syndrome and Self-Efficacy Among Electrical EngineeringStudents and Changes Resulting After Engagement in Department’s RevolutionaryInterventionsMr. Jeffrey Luke Morrison, University of South Florida Jeffrey Luke Morrison is an undergraduate student pursuing his bachelors in Electrical Engineering at the University of South Florida with focuses in wireless circuits and nano-scale systems. He is an IEEE member and also a member of the USF Honor’s College. In addition to pursuing his EE degree, he is also pursuing a BS in Quantitative Economics and Econometrics.Dr. Chris S Ferekides, University
Their Own Words: How Aspects of Engineering Education Undermine Students’ Mental Health,” in 2022 ASEE Annual Conference & Exposition Proceedings, Minneapolis, MN: ASEE Conferences, Aug. 2022, p. 40378. doi: 10.18260/1-2–40378.[33] N. Mamaril, E. Usher, C. Li, D. Economy, and M. Kennedy, “Measuring Undergraduate Students’ Engineering self‐efficacy: A validation study,” J. Eng. Educ., vol. 105, no. 2, pp. 366–395, Apr. 2016, doi: 10.1002/jee.20121.[34] K. J. Jensen and K. J. Cross, “Engineering stress culture: Relationships among mental health, engineering identity, and sense of inclusion,” J. Eng. Educ., vol. 110, no. 2, pp. 371–392, Apr. 2021, doi: 10.1002/jee.20391.[35] S. Farrell, A. Godwin
Paper ID #42380The Effect of Ego Network Structure on Self-efficacy in Engineering StudentsDavid Myers, Rowan UniversityMatthew Currey, Rowan UniversityLuciano Miles Miletta, Rowan UniversityDarby Rose Riley, Rowan University Darby Riley is a doctoral student of engineering education at Rowan University. She has a special interest in issues of diversity and inclusion, especially as they relate to disability and accessibility of education. Her current research is focused on the adoption of pedagogy innovations by instructors, specifically the use of reflections and application of the entrepreneurial mindset. Her previous
organizations including the Society of Women Engineers(SWE), the Society of Hispanic Professional Engineers (SHPE), the Society of Asian Scientists andEngineers (SASE), the National Society of Black Engineers (NSBE) and ten times Outstanding ChapterAwardee, the American Chemical Society-Wright College Chapter. Doris promotes collaboration betweenK-12 schools, other community colleges, 4-year institutions, non-profit organizations, and industries.Doris’ current research is to design and implement practices that develop Community of Practice (CoP),Professional Identity, and Self-Efficacy to increase diversity in Engineering and Computer Science and tostreamline transfer from community colleges to 4-year institutions. ©American
1980s.THE SMART goal framework, published by George Doren, states that goals should be Specific,Measurable, Attainable, Realistic, and Timely [17]. This overlaps with Latham and Locke’s goal-setting theory but is much more detailed and seems to diverge from their suggestion that goals bedifficult, rather than stating that goals should be both attainable and realistic instead of lofty ordifficult. If we are to follow Bandura’s self-efficacy model, students need “mastery experiences,”which should be somewhat challenging but attainable. The ideal degree of difficulty is likelyindividualistic, but the experience itself can be small or large.Several papers have noted the effect of goal setting on students and engineers [16-22]. However,only two papers
SystemsTheory recognizes that variation in individuals’ development “exists across time within contexts,and across contexts within time;” as a result, “differences in time and place constitute vitalcontributors to plasticity across the life span” [13]. Given the variations by time and place, weexpect a diverse range of pathways of individuals who are on their way to the engineeringprofession.The Social Cognitive Career Theory (SCCT) [14] posits that one’s learning experiences caninfluence their self-efficacy and outcome expectations, which in turn influences their interests,goals and, ultimately, career choice actions; these learning experiences are affected by personinputs (such as predispositions, gender and race) and contextual affordances (such as
institution in theSoutheast United States. Given the exploratory nature of the study, a novel survey tool wascreated that focused on: residual time, club participation, design skills before and after clubparticipation, design self-efficacy, and demographic information, see Appendix A. This researchstudy was approved by the IRB at Duke University (protocol #2023-0178). 1) Survey DesignFor the purpose of transparency, we defined engineering clubs as a subset of clubs whosemembership is primarily engineers, the subject matter is technical, and/or they are a pre-professional organization for engineers. The engineering school at Duke University gives clubsthis designation. We divide engineering clubs into three categories: competition design teams
to selectedstudents. In addition to the scholarship funds, S-STEM programs offer additional activities andresources [1]-[4]. For example, Southern Methodist University provided their S-STEM studentswith weekly seminars and block scheduling which positively impacted the students and theirability to excel academically. While various academic and support resources are included in theimplementation of the S-STEM Program discussed here, this paper’s focus is the impact ofweekly lunches on our students.Student retention is typically influenced by feelings of self-efficacy and inclusion in engineeringspaces [5]-[6]. Reasons for attrition include classroom and academic climate, grades andconceptual understanding, self-efficacy and self-confidence
organizational success. Given that the majority of engineeringgraduates have only extensively been in the educational system [15], it is vital to identifyapproaches that allow them to better thrive in the workplace. Katz found that engineering studentswho had directly engaged with the professional engineering environment through interviews, co-op assignments, and seminars had “expectations [of their workplace responsibilities]…that muchmore closely matched the expectations of the professionals than…the students who had not”engaged with the professional world [29]. Similarly, problem-based learning through a capstonedesign course was shown to increase software engineering students’ confidence in their technicalabilities and improve their self-efficacy
Retention Problem and Gauging Interest in Interdisciplinary Integration into Undergraduate CurriculumAbstractUnderrepresented minorities (URMs) leave the engineering field at a rate significantly higherthan average. Researchers conclude that low self-efficacy, lack of support, and hostile andbenevolent discrimination are contributing causes. We contend that URMs’ lack of retention inengineering is due to a push by these causes, as well as a pull towards fields that more closelyalign with their identity. To explore further, a Qualtrics survey instrument was developed tounderstand the experiences of people who have fully or partially left the engineering field. Wesurveyed 47 URM and 38 non-URM participants at
, doi: 10.1111/jcal.12130.[9] C. J. Fong et al., “Meta-Analyzing the Factor Structure of the Learning and Study Strategies Inventory,” The Journal of Experimental Education, pp. 1–21, Jan. 2022, doi: 10.1080/00220973.2021.2021842.[10] M. K. Khalil, S. E. Williams, and H. G. Hawkins, “The Use of Learning and Study Strategies Inventory (LASSI) to Investigate Differences Between Low vs High Academically Performing Medical Students,” Medical Science Educator, vol. 30, no. 1, p. 287, Mar. 2020, doi: 10.1007/s40670-019-00897-w.[11] J. Broadbent, “Academic success is about self-efficacy rather than frequency of use of the learning management system,” Australasian Journal of Educational Technology, vol. 32
. F. Tang, and A. Y. N. Cheng, “Preservice teacher education students’ epistemological beliefs and their conceptions of teaching,” Teach. Teach. Educ., vol. 25, no. 2, pp. 319–327, Feb. 2009, doi: 10.1016/j.tate.2008.09.018.[18] H.-J. Kim and S. Im, “Preservice Physics Teachers’ Beliefs about Learning Physics and Their Learning Achievement in Physics,” Asia-Pac. Sci. Educ., vol. 7, no. 2, pp. 500–521, Dec. 2021, doi: 10.1163/23641177-bja10038.[19] B. Baki̇ oğlu, “Teacher candidates’ teaching-learning conceptions and self-efficacy in organizing out-of-school trips: The mediating role of lifelong learning,” Res. Pedagogy, vol. 11, no. 2, pp. 483–500, 2021, doi: 10.5937/IstrPed2102483B.[20] D. Hardjito, “The Use of
Retention Model Based on Factors that Most Influence Student Success,” Journal of the Scholarship of Teaching and Learning, vol. 21, no. 1, Art. no. 1, May 2021, doi: 10.14434/josotl.v21i1.30273.[17] S.S. Whorton, "Academic self-efficacy, academic integration, social integration, and persistence among first-semester community college transfer students at a four-year institution" (Doctoral dissertation, Clemson University), 2009.[18] L. C. Freeman, "Social Network Analysis: Definition and History," Encyclopedia of Psychology, vol. 7., A. E. Kazdin, Ed., New York, NY, US: Oxford University Press, 2000, pp. 350-351.[19] A. Erkan, "Effects of social capital on academic success: A narrative synthesis
. Differences in self- efficacy among women and minorities in stem. Journal of Women and Minorities in Science and Engineering, 21(1), 2015.[20] Francesca Dupuy, Elliot P Douglas, and Paul G Richardson. Isolation, microaggressions, and racism: Black engineers in technology companies. In 2018 ASEE Annual Conference & Exposition, 2018.[21] Ebony O McGee and Danny B Martin. “you would not believe what i have to go through to prove my intel- lectual value!” stereotype management among academically successful black mathematics and engineering students. American Educational Research Journal, 48(6):1347–1389, 2011.[22] Thomas F Pettigrew. Intergroup contact theory. Annual review of psychology, 49(1):65–85, 1998.[23] John F Dovidio
Culture in US Higher Education: Navigating Experiences of Exclusion in the Academy. Routledge, 2022.[17] J. Maloy, M. B. Kwapisz, and B. E. Hughes, “Factors influencing retention of transgender and gender nonconforming students in undergraduate stem majors,” CBE—Life Sciences Education, vol. 21, no. 1, p. ar13, 2022. [Online]. Available: https://doi.org/10.1187/cbe.21-05-0136[18] E. Kersey and M. Voigt, “Finding community and overcoming barriers: Experiences of queer and transgender postsecondary students in mathematics and other STEM fields,” Mathematics Education Research Journal, pp. 733–756, 12 2021. [Online]. Available: https://doi.org/10.1007/s13394-020-00356-5[19] J. A. Miles and S. E. Naumann, “Science self-efficacy in