underutilized as a wellspringfor STEM workforce development planning. Page 22.1209.2 While it is useful to test SCCT using nomothetic, quantitative methods, it is valuable tocomplement such research with idiographic, qualitative methods capable of elaborating specificself and environmental percepts that could inform educational interventions. For example, priorwork on SCCT has established that social supports and barriers generally have been linked topersistence in engineering majors (largely indirectly, through their relation to self-efficacy), butthe mostly nomothetic research on this issue has focused on global aspects of supports andbarriers
learningaccording to self-efficacy theory.12Unlike typical process simulation packages (HYSYS, ASPEN, PRO/II), in ChemProV thedevelopment of the process flow diagram and the needed balance equations were left entirely tothe students and no numerical solution programming was provided. A number of othereducational software programs for material/energy balance classes have recently appeared, forexample the offerings of Sapling Learning. These tend to be overly prescriptive in the problemsolving procedure employed thus reducing the educational experience for the student. The goalof ChemProV was to provide a scaffold for learning but leave the problem solving strategyflexible enough to accommodate multiple learning styles and approaches. The intent was that
underrepresentedminorities derive greater benefit from models that involve social and networkinginformation in addition to more mechanistic career development information (e.g.,Learning to negotiate the politics of an organization as well as understanding thesteps to advancement) 11,12,8.Ongoing research on mentoring identifies and investigates a broader range ofmodels. Chesler and Chesler 6, a team comprising sociology and engineeringexpertise, investigate how existing gender roles and dynamics impact the creationof effective mentoring programs. They report that a prevalent model, the HeroicJourney, emphasizes organizational and technical information and guidance butneglect psychosocial issues such as self-efficacy or sense of belonging. This isimportant because
? What went well? Self-efficacy for Why did you want to What have you learned this week? Scientific research participate in this RET What have you been doing related to your Self-efficacy for teaching program? engineering teaching module? engineering What do you hope to get How confident are you feeling this week about General program out of the RET program? teaching your students about engineering?Table 2. Coding structure to measure RET interns’ functionality as scientific researchers.Constructs 1. Low 2. Low-Middle 3. High-Middle 4. High Internal vs
participant has transferredher camp experience into her everyday life, particularly her self-efficacy about pursuing a careerin engineering or other STEM discipline. Since our program is relatively new, this data iscurrently limited. This assessment gauges continuing STEM interest levels, and the nature ofany increase or decrease in the girls’ level of interest in pursuing a career in a science,mathematics, engineering, or technology field. These assessments are accomplished throughtracking documents emailed to the former participants and also placed on the CoP website. The “Results” level of assessment is ultimately the “bottom line” in recruiting these femalesinto engineering or related fields. Our plan is to continue to track former GRADE
requested to prioritize these factors based on theextent to which they influenced their self-efficacy beliefs. Analysis of student responsesconcerning the factors affecting confidence in success in this first-year engineering courserevealed nine categories of prominent factors: understanding or learning the material; drive ormotivation toward success; teaming issues; computing abilities; the availability of help andability to access it; issues surrounding doing assignments; student problem-solving abilities;enjoyment, interest, and satisfaction associated with the course and its material; and gradesearned in the course.In a Connecticut university, a survey was conducted on Introduction to Psychology students fromdifferent majors, including
Perceptions of teaching effectiveness under in- Section 5.2 person and online modes Learning (attitudes, Interest in online versus in-person teaching Section 5.2 knowledge and skills) Self-efficacy in online teaching skills Behaviour New teaching practice introduced to meet online Section 5.2 needs Results Likelihood for teaching online versus in person Section 5.3 in the future Likelihood for using particular instructional development opportunities in the futureIn our analysis, we used the descriptive statistics and thematic analysis for
the emotional experience of shame presentswithin a real student, outside of theory. This IPA study, true to the methodology, is intended tomake connections of theory concerning engineering education, gender identity and shame withthe real ways that shame is experienced within the student [19]. The five themes presented abovepresent a picture of the interaction between engineering culture and the individual student.Nicole’s experience of shame follows a cognitive path that is valuable for those in theengineering community who wish to see students succeed. Navigation of shame experiences isclosely linked within the literature to student’s self-efficacy [22-25]. Students who continuallyexperience pervasive shame within their academic and
attitude included several stereotypicalstatements that could indicate students’ level of understanding of basic job functions. Nofield of engineering was specified in the attitude survey. Then the study asked students toidentify 5 types of engineers and state one example of the work that type of engineer did.Less than 5% of the 300 plus students included in the survey were able to correctlyidentify 5 types of engineers. Close to half of the students had no opinion of engineers’involvement in business decisions or how much time engineers spent in the lab.16There are many studies that explore differences in perceptions by ethnicity or gender.These studies generally fall into either aspirational studies or self-efficacy studies. Inother words, why do
personal characteristics (e.g. gender, race) to influence career behaviors,confidence in one’s ability to do research (research self-efficacy), and the outcomes oneexpects from a research career (career self-efficacy). These factors, in turn, predict one’sinitial or sustained interest in a research career pathway. This theoretical framework isimportant because it recognizes the role of personal agency and personal characteristicsin the career development process. The authors suggested that interventions to increasethe number and effectiveness of researchers in an academic environment be focused on1) reducing role conflicts imposed by multiple environments, 2) providing continuity oftraining efforts, 3) creating a positive and rewarding mentoring
self-efficacy, sense of belonging, identification and identityintegration. Often, negative experiences are the result of subtle bias or schemas that all studentsbring with them into their teams, and occur despite the employment of best practices in teamformation.This paper presents a summary of a contemporary understanding of this phenomenon aspresented by several individual researchers covering the fields of stereotype threat, engineeringdesign, teamwork, motivation, and race, gender and their intersections. The content of this paperwas generated by collecting the individual responses of each researcher to a set of promptsincluding: • examples of how students can be marginalized in engineering teamwork and what governing
inOctober 2021. Twenty-five (100%) students completed the survey and will complete the samesurvey in Fall 2022 to assess gain and satisfaction of program elements.The survey instrument had three sections. The first section was based on the LongitudinalAssessment of Engineering Self-Efficacy (LAESE). (see http://aweonline.org/efficacy.html)LAESE is designed to identify longitudinal changes in the self-efficacy of undergraduatestudents studying engineering. The LAESE undergraduate instrument has been tested andvalidated on male and female engineering students. The LAESE questions will be administeredeach fall to determine if self-efficacy increases as they progress through school.The second section was based on the questions in the Clance Imposter
longitudinal changes in the self-efficacy of undergraduatestudents studying engineering. The LAESE undergraduate instrument has been tested andvalidated on male and female engineering students. The LAESE questions will be administeredeach fall to determine if self-efficacy increases as they progress through school.The second section was based on the questions in the Clance Imposter Phenomenon Scale [54].The Clance Impostor Phenomenon Scale was designed to measure the concept that individualsare successful by external standards but have an illusion of personal incompetence. Thequestions assess components of the phenomenon such as ideas about self-doubt and achievingsuccess by chance.The third section asked questions about the student’s advisors
, student self-assessments are used to gauge self-efficacy and quizzes are used to assess competency. What isinnovative about the approach is the automation of the process for students and faculty. Studentscomplete a worksheet online and receive a copy of their responses by email with the option togenerate a PDF version of their responses. Subsequently, the student submits the PDF version toBrightspace for review by the instructor. After submitting the worksheet, students complete aself-assessment survey to assess student’s self-efficacy with content covered in class andreinforced in the worksheet. Worksheets coupled with self-assessments provide insight onstudent’s data visualization capacity levels.The goals of the worksheets are to enable
pathway metaphor into an ecosystem. The ecosystemapproach suggests more complex aspects of a system be recognized by offering a holisticunderstanding of educational experiences [22]. Lord et al. argue that the ecosystem approachoffers insights into contextual factors such as multiple influential actors, gatekeepers, powerrelations, tacit knowledge, knowledge transmission, and disciplinary cultures. Much like thispaper, we plan to apply network analysis techniques to makerspaces to provide richer insights.A survey measuring student participation in makerspaces and students’ self-efficacy for designrelated tasks [23] was deployed at Georgia Tech. The results of the study showed that studentswho are voluntary involved (not class-related) in the
2015In total, 25 papers were nominated by 21 divisions and four Zones for consideration for BestDiversity Paper, 2015. There were six finalists invited to present; these papers were from the K-12, First Year Programs, Liberal Education/Engineering and Society, Mechanical Engineering,Entrepreneurship and Engineering Innovation, and Multidisciplinary Engineering Divisions. Thetop papers presented at the conference included an exploration of changes in Latinx adolescents’perceptions of engineering self-efficacy and of engineering during a community-basedengineering design experience [3], a baseline study on how engineering students identify asengineers and how they view the importance of diversity in engineering, [4], anautoethnographic study of
characterize STEM careers as unworthy of literate andcreative individuals [2]. Does she have a good point? During the last two decades substantial efforthas been expended towards reconciling developing students with what can be broadly defined asSTEM identities. Considerable recent research broadly on STEM identities [e.g. 3-21], includingseparate considerations of science, engineering and math identities, has focused on the identitiesof groups and intersectionalities underrepresented in STEM disciplines and careers. But, someresearch also suggests that merely inserting a STEM label, e.g. science or scientist, into adiscussion unleashes implicit biases of gender, race and ethnicity in middle school children [14].Surveys to assess self-efficacy and
, were factored intothe statistics. [4] GPA was a greater predictor of retention and eventual graduation for malestudents than female students. Meanwhile, moderate to high levels of achievement increasedlevels of confidence in females but accentuated female students’ social discomfort as a minority,making self-doubt and social discomfort better predictors of graduation rate for females thanGPA. This trend was valid when women were both a numerical minority in classes and werestereotyped, as women often are in engineering programs. [4]The existing literature suggests that factors other than just GPA impact a female student’sdecision to remain in and eventually graduate from an engineering program. For example, self-efficacy, or a specified level
financial pressures). Hutchison, Follman, Sumpter, and Bodner6found that student retention was greatly impacted by students’ self-efficacy, which in turn wasimpacted by factors such as motivation, understanding of material, and social influences(including peers and faculty). Finally, Bernold, Spurlin, and Anson3 found that persistence inengineering is related to both student learning styles and study habits, as well as teachingmethodologies.Adding to the existing body of literature, ASEE’s publication on best practices in engineeringretention1 highlighted the wide range of programs that universities have developed in reaction tothe various issues that affect student persistence. Almost half of the universities profiled in thepublication had some
education, vol. 6, p. 184, 2015. 11. N. McDonald, A. Akinsiku, J. Hunter-Cevera, M. Sanchez, K. Kephart, M. Berczynski, and H. M. Mentis,“Responsible computing: A longitudinal study of a peer-led ethics learning framework,” ACM Transactions on Computing Education (TOCE), vol. 22, no. 4, pp. 1–21, 2022. 12. G. C. Graber and C. D. Pionke, “A team-taught interdisciplinary approach to engineering ethics,” Science and engineering ethics, vol. 12, pp. 313–320, 2006. 13. A. R. Carberry, H.-S. Lee, and M. W. Ohland, “Measuring engineering design self-efficacy,” Journal of Engineering Education, vol. 99, no. 1, pp. 71–79, 2010.14. P. R. Pintrich and D. H. Schunk, “Motivation in education: Theory, research, and
-Atlantic private college. This exploratory study includes the perceptionsof two engineering faculty members and one educational support staff using mastery-basedteaching and assessment in a project-based engineering program. A semi-structured interviewwith multiple open-ended questions were used to prompt participants to share their experienceswith assessment in relation to their self-efficacy around teaching and their perceptions ofassessment in relation to their students’ failure mindset, metacognition (awareness of learningprocesses), and agency (ownership of learning). Directed content and thematic analysis wereused to identify codes and develop themes in relation to how participants described certainfeatures of assessment in their engineering
modelintegrated elements from Lent's Social Cognitive Career Theory (SCCT) [7] and Tinto'sDeparture model [8] into a hybrid structure aimed at boosting success metrics among LIATS.Figure 1 reproduces the structure of interventions underpinned by the L-CAS model [9]. Figure 1: LIAT college access and success model [9].L-CAS activities followed a longitudinal path consonant with student development, withobjectives ranging from boosting their sense of belonging and self-efficacy beliefs to propellingthem into actions and immersing them into real-life contexts [10]. Context scenarios targeted thedevelopment of collaborations and interactions in communities of practice that led students todevelop practical skills for becoming future
selection of initial experiments toadapt, the modifications made, and resulting changes in the course delivery. Preliminary resultsusing measures of key constructs associated with student success, such as motivation,engineering identity, and self-efficacy are provided. This project is conducted at a historicallyblack college/university and most participants are from groups historically underrepresented inSTEM.IntroductionAccording to National Science Foundation data, African American students comprise 2% of theB.S. degree recipients in the geosciences, 2.6% in physics and 3.9% in engineering, while Blackscomprise 14.9% of the college-aged population [1]. Thus, there are opportunities to increase therepresentation of African American students in
implementation withnumerous student cohorts. The methods used for tracking and comparing student sentiment,confidence, beliefs, skill development, and technical skill performance include: (1)demographics, (2) assessments of conceptual knowledge (i.e., two concept inventories and threefaculty-developed proficiency exams), (3) a survey that assesses design self-efficacy and othercourse-specific assessments, (4) written design skills tests that measure design problem framingability, and (5) student observations and interviews. These assessment methods are distributedand administered throughout the four-year degree program. This paper outlines and describesthese assessment tools and methods and how they are used to measure outcomes. The analysis ofsome of
learning experiences [1 - 4], positive self-reflections are important parts of the theoryof motivation and self-efficacy [35]. When answering Question 5, the students liked “the processof seeing and creating parts from scratch,” “how much detail the MoonRay can print,” “objectsrising like Phoenix,” “upside down grown parts,” and “the quality and accuracy of the process.” 14 12 10 8 6 4 2 0 1 2 3 4 5 Q1 Q2 Q3 Q4Figure 8. Students’ 3D Printing Attitudes and Perception Survey Results: Questions 1 – 4
Sciences, vol. 1483,no. 1, pp. 80-97, 2021.[5] C. Elliott, C. Mavriplis, & H. Anis, “An entrepreneurship education and peer mentoringprogram for women in STEM: mentors’ experiences and perceptions of entrepreneurial self-efficacy and intent,” International Entrepreneurship and Management Journal, vol. 16, no. 1,pp. 43-67, 2020.[6] D.A. Erlandson, E.L. Harris, B.L. Skipper, & S.D. Allen, Doing naturalistic inquiry: A guideto methods, NY: Sage, 1993.[7] N.K. Denzin, “The logic of naturalistic inquiry,” Social Forces, vol. 50, no. 2, pp. 166-182,1971.[8] E. Blair, “A reflexive exploration of two qualitative data coding techniques,” Journal ofMethods and Measurement in the Social Sciences, vol. 6, no 1, pp. 14-29, 2015.[9] S. Hennessy, C. Howe
set of findings emerging frommotivation research that sought to better understand K-12 students’ choice and pursuit of STEMcareers [7], [8]. This body of work has indicated consistently that underrepresented children andyouth are less likely to develop STEM identities or pursue career pathways than non-minoritystudents, especially in the field of engineering [9], and the choices made by children, especiallyunderrepresented children, to pursue various STEM disciplines are strongly associated with theirperceptions of self-efficacy, competence, interest, social support, and the discipline’s costs andbenefits [10], [11], [12]. Yet, despite the recognition of this issue, limited research has beenconducted on young children’s motivation in
heart of the model is the idea that expectancy and value lead to student motivation whichis a key ingredient for learning and cognition. This theory suggests that both expectancies forsuccess and subjective task values directly influence the choice of activity, the persistence in it,and the final result (i.e., student performance). Expectancy describes one’s expectation ofsuccess, often framed in terms of self-efficacy. Value represents subjective task value andincludes intrinsic value (i.e., interest and enjoyment), attainment value (i.e., importance), utilityvalue (i.e., usefulness of the task), and relative cost.In order to catalyze changes in student’s attitudes toward data science and explore the hypothesisdriving this research (i.e
technical contributors [2, 7-10]. Connections to mentors andexperience with real-world problems that connect the dots between STEM academic content andthe industry practice can also enhance students’ competencies and preparation for future careers[11]. These are all critical components in the development of a STEM identity. Engineering self-efficacy and engineering/STEM identity are both characteristics predictive of success inengineering majors and careers [8]. As alluded to above, this is especially important for studentstraditionally underrepresented in STEM fields and is therefore key to addressing diversity issuesessential for organizational innovation [12].Finally, the benefits of apprenticeships and the application of relevant research
education andbuild capacity for student success. This project will use a data-driven and evidence-based approachto identify the barriers to the success of underrepresented minority students and to generate newknowledge on the best practices for increasing students’ retention and graduation rates, self-efficacy, professional development, and workforce preparedness. Three objectives underpin thisoverall goal. The first is to develop and implement a Summer Research Internship Programtogether with community college partners. The second is to establish an HSI Engineering SuccessCenter to provide students with academic resources, networking opportunities with industry, andcareer development tools. The third is to develop resources for the professional