. Students were asked questions aboutthese feelings regarding each step of the engineering design process as well as open-endedquestions inquiring about feelings towards the project.BackgroundEngineering and technology fields encompass complex problem-solving skills and one’s abilityin executing different ways of thinking when applying them to projects and tasks. Theengineering design process itself instills problem-solving and real-world skill sets for those whowish to pursue these topics professionally. Developing these skills has been successful throughthe measurement of self-efficacy in first-year engineering courses and programs. Several studiesinvestigate engineering design thinking, teaching, and learning which target strategies to
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
.” 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
of studying engineering, self-efficacy, and contingencies of Academic Competence, Academic Competence subscale. Example items and references for each of these scales are provided in Table 1, and 5. Retention, defined as enrollment in the engineering school in the fall of the second year.AnalysisTwo machine learning techniques were investigated in this work: a neural network and a decisiontree. A neural network works to learn patterns via an iterative process of trial and error to classifydata into categorical outputs [11], and the results are black box (it is not possible to tell why aclassification was made without the aid of explainable methods). For the neural network analysis, Table 1: EVT
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
StudentsAbstractThis Complete Research Paper presents changes in data from a combined wellness, self-efficacy,and mindset survey for new students in the College of Engineering and Applied Sciences(CEAS) at Western Michigan University (WMU) during their first semester. Correlationsbetween individual survey factors and student retention and success are explored. The generalstructure of a first-year experience course focused on various dimensions of wellness is alsodescribed.Two electronic surveys (start-of-semester and end-of-semester) were created in Qualtrics basedon the Perceived Wellness Survey (PWS), the Interpersonal, Community, Occupational,Physical, Psychological, and Economic (ICOPPE) wellness scale, mindset, and self-efficacy. Thecombined surveys were
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
undergraduate research experiences impacts theirengineering identity and self-efficacy developments [4-7]. In addition, enhanced self-efficacypositively impacts engineering identity [4-6]. Other research explores the impact of a sense ofbelonging and community building on student development [8-11]. This paper examines theimpact of building a community of practice conceptual framework on both engineering identityand self-efficacy development of engineering students who participated in 10-week summerresearch experiences focusing on the engineering grand challenges as identified by NAE.Through building a community of practice, students experience a sense of belonging which webelieve adds to the engineering identity and self-efficacy
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
]. 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
which included experiences with faculty, course learning, andstigma as a transfer student [1]. Some articles simplified these factors describing them asacademic counseling, perceptions of the transfer process, experiences with faculty, andlearning/study skills [25], [27], [28]. Building on Laanan’s research, Moser [29] added severalwidely accepted constructs to the transfer student capital theory: staff validation at communitycollege, faculty validation at community college, faculty mentoring at community college,financial knowledge, active coping style, social coping style, motivation and self-efficacy, socialsupport at the four-year university, and formal collaboration with faculty at the communitycollege.Theoretical Frameworks The
complete autonomy to organize, schedule, and run the program as they seefit. The upper layers of the program – the graduate student and the faculty member – providesupport, advice, and resources, but the undergraduate students are the ones iterating and formingthe program. Through these means, the program has evolved in several ways, including theintroduction of group meetings and a semesterly service project, which were the directimplementations of student ideas. This focus on student voice and agency enables students tobuild self-efficacy and make meaning from their experiences with the mentorship program.IntroductionThis paper describes a mentorship program for undergraduate engineering students at a publicurban research university, and it will
students to be more reflective in later courses?IntroductionThis work in progress paper assesses whether a first-year ePortfolio experience promotes betterreflection in subsequent engineering courses. While reflection is vital to promote learning,historically, reflection receives less attention in engineering education when compared to otherfields [1]. Yet, cultivating more reflective engineers yields several important benefits includingbuilding self-efficacy and empowering student agency. Through continued practice, engineeringstudents can develop a habit of reflective thinking which increases students’ ability to transferknowledge across contexts. The adoption of ePortfolios is becoming an increasingly popularstrategy to improve student learning
professional skills,” Int. J. Eng. Educ., vol. 29, no. 1, pp. 85–98, 2013.[18] P. L. Yorio and F. Ye, “A meta-analysis on the effects of service-learning on the social, personal, and cognitive outcomes of learning,” Acad. Manag. Learn. Educ., vol. 11, no. 1, pp. 9–27, 2012, doi: 10.5465/amle.2010.0072.[19] L. Dent, P. Maloney, and T. Karp, “Self-Efficacy Development among Students Enrolled in an Engineering Service-Learning Section,” Int. J. Serv. Learn. Eng. Humanit. Eng. Soc. Entrep., vol. 13, no. 2, pp. 25–44, 2018, doi: 10.24908/ijsle.v13i2.11483.[20] Litterati, “Litterati - The Global Team Cleaning The Earth,” 2021. https://www.litterati.org/ (accessed Jun. 21, 2021).[21] J. M. Wolfand, K. A. Bieryla, C
belief as to how well one will perform in a givenactivity or task [11]. Competency beliefs are frequently grounded in self-efficacy theory [14],which mediates the connection between positive feedback and better academic achievement [15].While competency beliefs focus on a person’s ability to do a task or engage in an activity, valuebeliefs focus on an individual’s desire to engage (or the relevance of engaging) in an activity ortask. Key retention barriers associated with value beliefs include perceptions of attainment value,utility value, and interest value, which is the motivational construct under investigation in thisstudy. In the current study, interest refers to “student beliefs related to the enjoyability,significance and/or usefulness 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
Companion to Science and Engineering Indicators 2014. Alexandria, VA: National Science Board.20. Association of College Research Libraries (2007). The First-Year Experience and Academic Libraries: A Select, Annotated Bibliography.21. Pascarella, E. T., & Terenzini, P. T. (2005). How college affects students (Vol. 2): A third decade of research, Jossey-Bates San Francisco.22. Schreiner, L. A., Louis, M. C. & Nelson, D. D. (2018) Thriving in Transitions: A Research-Based Approach to College Student Success. 2nd Ed. Stylus, Sterling ,VA 27-4623. Eileen McBride, E., Vashlishan Murray, A. & Duggan, M.. (2021). Academic Self-Efficacy, Student Performance, and Well-Being in a First-Year Seminar. Journal of The First-Year
benefits of peer-enhanced learning, moredeveloped evaluative skills, a greater sense of belonging, improved self-efficacy beliefs, andhigher levels of intrinsic academic motivation. The merging of the two evidence-basedassessment approaches promises a scalable assessment modality hybridizing the pedagogicaldimensions of the former two assessment practices. Our study of students’ surveyed perceptionsabout peer oral exams offers perspectives on the qualities and potential role of peer oral exams ineducational practice and suggests directions for future educational research.IntroductionThe rapidly evolving professional ecosystem of the Fourth Industrial Revolution is placing highdemands on STEM education at an unprecedented rate [1], [2]. Principle
. 11[6] AIChE. "Spreadsheet related resources as part of the AIChE Academy." https://www.aiche.org/academy/search/spreadsheet (accessed July, 2020).[7] K. Stratvert. "Kevin Stratvert Master Technology YouTube channel." https://www.youtube.com/@KevinStratvert (accessed January, 2023).[8] L. Gharani. "Leila Gharani Advance Your Career YouTube Channel." https://www.youtube.com/@LeilaGharani (accessed January, 2023).[9] M. D. Miller, Minds Online: Teaching Effectively with Technology. Harvard University Press, 2014.[10] A. Singh, V. Bhadauria, A. Jain, and A. Gurung, "Role of gender, self-efficacy, anxiety and testing formats in learning spreadsheets," Computers in Human Behavior, vol. 29, no. 3
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
performance [35]; • working project design and oral presentation [36], post-quiz and post-design [37]; • direct assessment (course design notebook, oral presentations, etc.) or indirect assessment (class feedback forms, process checks) [38, 39]; and • third party evaluation [40].Surveys, standard student evaluation or adapted evaluation tools [41] or anonymous [42] wereconducted to evaluate students’ group dynamics with open-ended questions [43], provide postinterventions [44], determine students gain in learning and self-efficacy [45], etc. Individualinterviews and focus group discussions were conducted to identify successful practices andlessons learned in cross-disciplinary virtual teams [46], as well as to assess the effectiveness
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
Zamboanga, Ross A Thompson, and Larissa A Schmersal. Extra credit as incentive for voluntary research participation. Teaching of Psychology, 32(3):150–153, 2005.[16] Tracy B Henley and Indy L Savage. Who earns extra credit these days? The Journal of psychology, 128(3):311–314, 1994.[17] Anya Goldina, Peter Licona, and Patricia Likos Ricci. Creating extra credit assignments that challenge, inspire, and empower students. HAPS Educator, 2020.[18] Jennifer Barrows, Samantha Dunn, and Carrie A Lloyd. Anxiety, self-efficacy, and college exam grades. Universal Journal of Educational Research, 1(3):204–208, 2013.[19] Gary Stark, Stacy Boyer-Davis, and Melissa J Knott. Extra credit and perceived student academic stress. Journal of