– extremely)Post survey items to measure engineering self-efficacy (response options strongly disagree – strongly agree): I will be able to achieve most of the engineering-related goals that I have set for myself When facing difficult tasks within engineering, I am certain that I will accomplish them I believe I can succeed at most any engineering-related endeavor to which I set my mind I am confident that I can perform effectively on many engineering-related tasksPost survey items to measure commitment to engineering (response options): I have no doubt that I will graduate with a degree in engineering (strongly disagree – strongly agree) It is my intention to pursue a career in engineering (strongly disagree – strongly agree
factors or sub-constructs commingle to form the self-concept of a student inengineering undergraduate education is the crux of this study. To accomplish that, a systematicreview was performed over recent studies, related to engineering education, that assessed self-concept as part of their methodology.This paper first introduces self-concept and self-efficacy, the two constructs that are often usedinterchangeably in literature, followed by a database search for recent studies measuring self-concept. Based on the results this study enlists the variables assessing either of the constructs thatwere introduced. Then a detailed analysis of the differences between the two constructs isprovided. Extensions to the current structure of self-concept and
influencing the self‐efficacy beliefs of first‐year engineering students,” J. Eng. Educ., vol. 95, no. 1, pp. 39–47, 2006.[2] M. W. Ohland, S. D. Sheppard, G. Lichtenstein, O. Eris, D. Chachra, and R. A. Layton, “Persistence, engagement, and migration in engineering programs,” J. Eng. Educ., vol. 97, no. 3, pp. 259–278, 2008.[3] J. J. Appleton, S. L. Christenson, D. Kim, and A. L. Reschly, “Measuring cognitive and psychological engagement: Validation of the Student Engagement Instrument,” J. Sch. Psychol., vol. 44, no. 5, pp. 427–445, 2006.[4] J. L. Meece, P. C. Blumenfeld, and R. H. Hoyle, “Students’ goal orientations and cognitive engagement in classroom activities.,” J. Educ. Psychol., vol. 80, no. 4, p. 514, 1988.[5] R
.” American Educational Research Journal, vol. 29, no. 3, pp. 663–676, 1992.[7] N. A. Mamaril, E. L. Usher, C. R. Li, D. R. Economy, and M. S. Kennedy, “Measuring Undergraduate Students’ Engineering Self-Efficacy: A Validation Study.” Journal of Engineering Education, vol. 105, no. 2, pp. 366–395, 2016.[8] B. W. Smith, J. Dalen, K. Wiggens, E. Tooley, P. Christopher, and J. Bernard, “The Brief Resilience Scale: Assessing the Ability to Bounce Back.” International Journal of Behavioral Medicine, vol. 15, no. 3, pp. 194—200, 2008.Appendix A: Survey InstrumentPart 1: Please read the following 12 statements regarding advising functions and select the mostrelevant response option from the 6-point scale in the drop-down box to indicate
within thefirst two weeks of class and the post-survey was administered two weeks before final exams.MeasuresThere were three items measuring outcome expectations for engineering adapted from Lent et al.[13], six items measuring intentions to stay in engineering adapted from Lent at al. [13], threeitems measuring self-efficacy adapted from Lent et al. [13], and five items measuringengineering identity adapted from Chemers et al. [33] & Estrada et al. [34]. Table 1 provides thesample survey items for all four surveys used in this study. Table 2 provides the summary ofdescriptive statistics of continuous predictors and categorical variables. The Cronbach’s alphacoefficients across all subscales were also estimated with values ranging from 0.85
national Ph.D. programs.The scope of this work is to develop a baseline of the data within a single Hispanic servinginstitution. The analysis completed to this point validates the survey instrument in measuring theidentified constructs. This validation is necessary so that this study may be expanded to a largersurvey population.Research QuestionsThis research investigates several factors that are believed to impact the identity of engineeringstudents as researchers. We seek to assess the role of research self- efficacy, researcher identity,and cultural compatibility on research persistence intentions. These variables were selected asthey have been determined to be relevant factors in prior identity studies [16], [29]–[35].Students that self
students were invited to complete the survey a secondtime early in the fall quarter of their second academic year, thus bounding their first-year collegeexperience with pre and post survey administrations. This process of survey data collection wasrepeated for each new cohort of incoming students over the course of the study. The instrumentused was an adapted version of a survey developed by the Studying Underlying Characteristicsof Computing and Engineering Student Success (SUCCESS) project [18-19], which includesitems drawn from previously validated measures of self-efficacy, identity, and sense ofbelonging related to engineering [1, 11].Unfortunately, at least in part due to impacts of the COVID-19 pandemic, response rates werelower on the post
students' motivation topursue a career in microelectronics differ after this limited curriculum intervention?Literature ReviewThe Role of Interest in Career DevelopmentSocial Cognitive Career Theory (SCCT) [9] is an overarching conceptual framework that guidesall of the decisions of the Scalable Asymmetric Lifecycle Engagement (SCALE) project. SCCTemphasizes the role of relevant interests in career development. Within SCCT's Choice Modeland Interest Model, interest directly links self-efficacy, outcome expectations, and career-relatedchoices [9]. Because of this, many studies seeking to affect student's interest in engineeringcareers focus on increasing student self-efficacy and outcome expectations. In SCCT, interestsdirectly relate to choice
SWE member who zealously engages in community service work. ©American Society for Engineering Education, 2023 Full Paper: Impact of Inclusion of Makerspace and Project Types on Student Comfort with Additive Manufacturing and Three-Dimensional Modeling in First-Year Engineering ProgramAbstractThe following evidence-based practice study investigates the impact of utilizing a makerspace onthe exposure to additive manufacturing and three-dimensional modeling practices for first-yearstudents. This document builds upon recent literature which illustrated statistically significantgains in a plethora of self-efficacy and sense of belonging metrics over an academic year inwhich a makerspace was
Model to increased student motivation and self-efficacy, none has attempted to fullyquantify the impact of the associated restructuring of the curriculum. As a result, the currentpaper describes a detailed analysis of the Wright State Model using the Curricular Analyticsplatform (https://curricularanalytics.org/), which provides new and significant insight into therelative roles of curricular complexity and centrality on the success of the Wright State Model.In particular, results suggest that while the Wright State Model has had only a negligible impacton the overall complexity of the engineering curriculum, it has measurably reduced thecomplexity and dramatically reduced the centrality of the required calculus sequence. Moreover,the relative
dropoutrates and improving student success.Keywords: AI, data mining, dropout, engineering, first-year students, higher educationIntroductionOver the years, many studies have been conducted to understand why students leave theirstudies in Science, Technology, Engineering, and Mathematics (STEM) disciplinesprematurely. Research has delved into sociocognitive factors that play a critical role in studentpersistence in university. For instance, sense of belonging [1, 2], self-efficacy [3, 4], identity[5, 6], and intrinsic motivation [7], which are vital to student persistence in university. Forinstance, Andrews et al. [8] researched how the incorporation of makerspaces impactsstudents' self-efficacy and sense of belonging concerning design, engineering
concepts Compare students who took HCE courses with those on the concepts than students on standard prerequisite pathway. the standard prerequisite pathway.4. Sense of Correlate self-efficacy and perceptions as measured by the Key activities, support belonging adapted version of the Longitudinal Assessment of mechanisms, and programs Engineering Self-Efficacy survey (AWE, 2009) to activities, identified. support mechanisms, and programs that students participated in (self-report and tracking of certain programs such as First-Year Summer
]. Metacognitive and self-regulation strategies can help students be moreeffective learners. The affective element of learning refers to student attitudes and mindsets thatcan influence their thinking and behaviors, ultimately impacting their learning and academicperformance.Learning and persistence in higher education, and engineering education specifically, areinfluenced by many internal and external factors [5], [6], [7]. For example, Geisinger and Raman[7] identify six factors driving students to leave engineering: classroom and academic climate,grades and conceptual understanding, self-efficacy and self-confidence, high school preparation,interest and career goals, and race and gender. The first three items are fundamental to theclassroom experience
declare their major on the entrance to theirfirst year.I. IntroductionThe experiences accumulated by students during their first year in college have a lastingimpact on the rest of their academic lives [1]. The sense of career and institutional belonging,as well as the self-efficacy beliefs of students, have been identified as crucial factors for theirpersistence and success [2] [3]. We argue that both these factors are affected by the awarenessfirst-year students have about their chosen field of study. This is particularly true forinstitutions admitting students into a specific major since their first college year.An assessment of the reasons reported by first- and second-year students in the host institutionfor choosing an engineering major
the competitive climate experienced in STEM classes, increased reports of loss of confidenceincluding among high-performing female students who switch out of STEM, and problemsfinancing college. Seymour also notes that students with socio-economic disadvantages are atrisk of leaving their institution following just one DFWI grade in a severe STEM gateway courseeven when their grades in other courses place them in good academic standing [4]. This body ofliterature suggests that for many students, particularly women, minoritized individuals, andstudents from disadvantaged backgrounds, issues related to competitive/individualistic climate,lack of fit, lack of interest, and loss of self-efficacy can be significant drivers of attrition
studyparticipants were 18 years or above and in their first year of engineering education. In addition toparticipant demographics, the survey collected data about participants’ sense of belonging,engineering identity, and perceived stress.The survey incorporated a measure of a sense of belonging [11] that assessed two constructs:three items each on general belonging in the engineering major and belonging in the engineeringclassroom.The assessment of engineering identity in the survey included a professional identity scale [14]that is based on social cognitive theory focusing on self-efficacy beliefs and outcomeexpectations, as proposed by [20]. This scale comprised three constructs, each with three itemsrelated to recognition by others and interest, and
theindustry professionals are too removed from the first-year student experience to be helpful [19].The mentorship program at West Virginia University transitioned away from industry mentorsfor first-year students as they reflected that first-year students were not yet ready to interact withexperienced industry professionals [11]. Success in the early mentorship programs is often evaluated with surveys for self-efficacy,identity, social community, and/or sense of belonging [2,3,5,7,8,20], or with analysis ofacademic grades or retention in the program [5,8,16]. While mentorship programs are often totedas successful anecdotally, the data is not always as clear to indicate the benefits when comparedto those students not participating. Sense of
Education, vol. 34, no. 4, 2012.[40] J. E. Dowd et al., “Student learning dispositions: Multidimensional profiles highlight important differences among undergraduate stem honors thesis writers,” CBE Life Sci Educ, vol. 18, no. 2, Jun. 2019, doi: 10.1187/cbe.18-07-0141.[41] M. Sumpter, D. Follman, and M. Hutchison, “2006-1812: WHAT AFFECTS STUDENT SELF-EFFICACY IN AN HONORS FIRST-YEAR ENGINEERING COURSE? What Affects Student Self-Efficacy in an Honors First-Year Engineering Course?,” in ASEE Annual Conference and Exposition, 2006.[42] S. Conrad, S. S. Canetto, D. Macphee, and S. Farro, “What attracts high-achieving, socioeconomically-disadvantaged students to the physical sciences and engineering?,” Coll Stud
systematically controlling for student motivation, self-efficacy, interest in science, or other variables that might influence performance. Thus,examining the effectiveness of bridge programs solely based on student’s academic success,persistence or retention could be insufficient [9]. There exists a need to examine a broader arrayof student outcomes.Instead of focusing only on academic outcomes to evaluate the effectiveness of summer bridgeprograms, we propose to consider an examination based on the transformative nature of theprograms in order to provide a holistic view of the effectiveness of the programs. Indeed, thetransformative learning theory posits that thought-provoking experiential activities or scenarios(also referred to as “disorienting
learning and academic identity. CUREs provideauthentic learning experiences, raise the level of expectations for all students, and support thedevelopment of a community of learners – all critical for students who have been historicallyunderrepresented in STEM [11] [12] [13] [14]. These experiences support development of self-efficacy, interest and identity in STEM [12] [15], contribute to improved course outcomes [16],and generally result in higher retention and persistence for participating students [17].Place-Based Learning CommunityThe term “learning community” refers to a purposeful restructuring of curriculum to link two ormore courses from different disciplines to emphasize connections and provide coherence in thecurriculum [18]. They are a