role models in educationsettings, including Social Cognitive Theory (Bandura, 1977), Expectancy Value Theory (Eccles& Wigfield, 2002), and the Stereotype Inoculation Model (Dasgupta, 2011). Social CognitiveTheory places emphasis on self-efficacy, people’s beliefs on what they themselves can do. Indeveloping their self-efficacy, learners can adjust their own efficacy in numerous ways such asobserving the outcomes of others’ actions, particularly if the model is perceived as being similar(Cook & Artino, 2016). Expectancy Value Theory (EVT) examines the expectation of successand perceived value of accomplishing the task (Cook & Artino, 2016). The expectancy ofsuccess is shaped by motivational beliefs. Role models represent who can be
(recently) sexual minorities within higher educationSTEM programs. Likewise retention research highlighting additional corroborating factors instudent struggles, such as self-efficacy and cognitive attributes4,5,6, has informed the efforts ofsome of these support programs in affective and academic dimensions. Qualitative researchstrands that look at identity and marginalization have documented struggles from the studentperspective, noting how aspects of self can contribute to or come into conflict with one’sprogress and prosperity within a STEM major7,8,9. This research often employs a metaphor of“cultural mismatch” or “identity mismatch” to help extend the empathy and perspective ofpractitioners and those involved in the day to day of STEM in
them as diversity tokens. They emphasized the importance of social and structuralsupport to promote self-efficacy and retention for women of color. The bearings of thoseidentities cut across other interactional experiences, such as teamwork, in which students wereexpected to assert themselves and navigate unfamiliar team dynamics.Teamwork was often studied through the lens of student behaviors. Using an educationalanthropologist approach, Tonso (2006a) studied how the campus culture (categorized by studenttypes – nerds, Greeks, and academic achievers) influenced teamwork in an engineering collegeof a state-funded university in the Midwest. By observing team behaviors in situ, Tonso foundthat non-design engineering classes promote social
’ Sense of Belonging: A Key to Educational Success for AllStudents. (2nd ed.). Routledge, 2018.[5] C. Gillen-O’Neel, “Sense of belonging and student engagement: A daily study of first- andcontinuing-generation college students,” Research in Higher Education, vol. 62, no. 1, pp. 45-71,Feb. 2021.[6] M. Bong and E.M. Skaalvik, “Academic self-concept and self-efficacy: How different arethey really?,” Educational Psychology Review, vol. 15, pp. 1-40, Jan. 2003.[7] D.W. Johnson, R.T. Johnson and K.A. Smith. Active Learning: Cooperation in the CollegeClassroom. Edina, MN: Interaction Book Company, 1991.[8] M.J. Baker, “Collaboration in collaborative learning,” Interaction Studies: Social behaviourand communication in biological and artificial systems
the OR: exploring use of augmented reality to support endoscopic surgery,” in Proceedings of the 2022 ACM International Conference on Interactive Media Experiences, in IMX ’22. New York, NY, USA: Association for Computing Machinery, 2022, pp. 267–270. doi: 10.1145/3505284.3532970.[30] T. Khan et al., “Understanding Effects of Visual Feedback Delay in AR on Fine Motor Surgical Tasks,” IEEE Transactions on Visualization and Computer Graphics, vol. 29, no. 11, pp. 4697–4707, Nov. 2023, doi: 10.1109/TVCG.2023.3320214.[31] M. Menekse, S. Anwar, and S. Purzer, “Self-Efficacy and Mobile Learning Technologies: A Case Study of CourseMIRROR,” in Self-Efficacy in Instructional Technology Contexts, C. B. Hodges, Ed., Cham
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
is likelyhighly dependent on the foundation they have brought to the course. More general academicskills and attributes such as motivation, self-regulation, self-efficacy, sense of belonging andmindset also influence how students engage with the course.Existing research demonstrates the importance of math and physics preparation to studentsuccess in mechanics [1], [2], [3], [4], [5]. Problem solving skill is also clearly an importantcomponent to success [5]. The correlation of spatial abilities to broader measures of success andretention for engineering majors in general is well-established [6]. However, existing studiesexploring the importance of spatial abilities to success in mechanics courses find mixed results.Many fundamental concepts
beneficial because they help you:-make strategic decisions, plan programming, and identify gaps in the programming,-clarify and quickly communicate your plan,-demonstrate to stakeholders you have thought things through, and-make the case for funding. 4When working in the area of DEI in particular, developing a clear plan for yourinitiative and identifying intended outcomes can hold you accountable to yourvision for change and help you demonstrate that you’re doing what you hoped.For example, say you have a Bridge program for first generation students inengineering. Hopefully you have an intention behind this program, likely toimprove students self-efficacy and/or
aligned with their STEM career). PIC is a core concept ofidentity research, emphasizing that when individuals perceive a close connection between theirself-concept and their career goals, they are more likely to maintain motivation, interest andpersist in that domain, even when they experience difficulty [22]. Further, the data suggest thatPIC leads to higher sense of belonging to the University and it’s members. Kim, London andcolleagues also demonstrate that interest in a STEM career and sense of belonging in one’sUniversity both predicted STEM self-efficacy among students (confidence in one’s ability tomanage STEM academic tasks). STEM self-efficacy in turn predicted higher STEM achievementin classes through students’ second year of college
real-world problems. When students work on real-world problems,they are more motivated because real-world problems usually have proximal and tangible goalswhich often lead to higher self-efficacy and control among students. The pedagogy in this courseachieved the goal because the real-life-based design project and related activities were implicatedin personally meaningful tasks.On the other hand, students were not highly motivated by being able to connect information fromdisparate contexts and make reflective judgments through critical thinking. Nowadays, engineersare required to be flexible and creative with a good understanding of human-centered design andan ability to work in multidisciplinary contexts. In school, design and other
ensure they receiveeffective instruction when resources, especially time, were limited? The answer was to betterutilize an existing resource – the GTAs who assessed student work.Evolution of GTAs and Writing in EngineeringIn the last fifty years, the literature on GTA training has evolved from non-existent to discipline-specific, with the need for such training undisputed but the content of the training of moreinterest lately [5-9]. In addition, GTA self-efficacy, which involves “beliefs in one’s capabilitiesto organize and execute the courses of action required to produce given attainments” [10], hasalso been the subject of research [11-12]. Additional research has been done in training GTAs toteach writing in composition courses [13-15] and
college students, particularly in enhancing self-efficacy and career aspirations [8].Bureaucratic processes at four-year institutions add another layer of complexity, potentiallybecoming obstacles to academic progression [9]. Recommendations from research include theutilization of tools such as the Transfer Guide Modified (TGM) for a more in-depth explorationof student experiences, especially focusing on those with varying scores within the TGM'sdifferent factors [1].Navigating academia requires not only academic resilience but also adapting to newsociocultural environments. These experiences often reshape student identities, making themmore resilient and prepared for future challenges. The nuances of race and ethnicity in transferexperiences
quantitative measures may not beassessed until decades later, e.g., when a 2nd grader eventually chooses to pursue a STEM majorin college. Qualitative aspects can include analyses of interviews and free response survey datato ascertain improved sense of belonging, self-efficacy, or access to educational opportunitiesamong the target population. They could also include an increased understanding of gender orrace/ethnicity in STEM opportunities, skills development in becoming an equity advocate, and adeepening passion for DEI in STEM. They could also include subtle data-driven shifts in cultureor practice, e.g., creating groups for class assignments where female students are not isolated,sustaining near peer-mentor networks, or sustainability and
taxonomy of motivation theorieswhich captures the breadth of motivation in educational research. Eccles and Wigfield groupedtheories into four categories 1) expectancy (e.g., belief about the difficulty of a task and a person’sability to perform it successfully); 2) reasons for engagement; 3) integrating expectancy and valueof a task; and 4) integrating motivation and cognition. This systematic review found that over halfof the articles found did not have a specified framework for their study. Of the papers that used aframework, three were most prevalent including Bandura’s self-efficacy construct68, Deci andRyan’s self-determination theory69, and Eccles and Wigfield’s expectancy-value theory70. Self-efficacy is one’s belief in his or her ability
while maintaining students’ satisfaction levels [66].For a holistic understanding of CS support programs’ impact on affective outcomes, we will alsoinclude measures that have been previously associated with persistence in STEM, such astechnical confidence [31], [32], [36], [69], [70] and professional role confidence [34], [63], [71].Further, we will be interested in how social capital influences the relationship between students’perceived performance/competence in CS and persistence. Performance/competence is theorizedto be an advanced measure of self-efficacy [36] – also linked to student retention in CS [72] –and shown to have a direct effect on students’ interest and persistence in CS [36]. Finally, wewill also add social-benefit interest
studentswith greater mindfulness (trait mindfulness) and was more evident when the task demandedsignificant working memory resources [15]. Another study [16], including 75 students in anintroductory solid mechanics course, measured students' self-reported trait mindfulness at thetime of completing the mindfulness instruments. This study did not conduct mindfulness trainingwith the students. However, the self-reported mindfulness measures revealed that traitmindfulness does not correlate with students' final grades or mechanics self-efficacy butpositively correlates with business skills self-efficacy. The study further suggests thatmindfulness-based classroom activities may help broaden the engineering education experience.Some research results suggest
shows a student performing an experiment using one of the devices developed in the ECPproject. By adopting ECP, students were able to have a better understanding in the course (COSC243 – Computer Architecture) and other STEM subjects that are part of the project.Figure 6: Students setting up the experiment.The Motivated Strategies for Learning Questionnaire (MSLQ) developed by Pintrich, Smith,García, and McKeachie [15] was used to measure key constructs associated with students’ success,such as motivation, epistemic and perceptual curiosity, and self-efficacy. The effectiveness of theimplementation of ECP was evaluated using the MLSQ measure, which consists of a learninggoals scale that is further divided into cognitive and resource management
explored in an effort tomeasure the effectiveness of the intervention. In the RCT reported here, participants weredivided into two treatment groups, one that had access to the entire CareerWISE website, onethat had access to all site content with the exception of the interactive video simulations, and await-list control group (WLC). The WLC group was given access to the entire online resource ata later time, which allowed those participants to also gain any associated positive impacts. Outcome measures for the RCT included self-reported knowledge of and self-efficacy ininterpersonal communication skills and ability to apply key interpersonal communication skills.Comparisons based on outcome measures were made both between the two treatment
groups in computer science programs and careers have been suggested. Lackof access to computing technology, inadequate K-12 preparation, lack of role-models, stereotypethreat, and lower self-efficacy have all been identified as reasons non-majority students do notenter or eventually leave computing programs [8]-[19]. Specifically in STEM fields anddisciplines, non-majority students’ sense of belonging is imperative to their retention and successwithin STEM programs and is associated with a variety of positive outcomes for individualsincluding: increased GPA, increased self-reported health and well-being, and increased academicscores [20], [21]. Yet, in direct opposition to non-majority students cultivating this sense ofbelonging, or fit, in
elementary school students’ situational interest, self-efficacy, and achievement emotions,” Int. J. STEM Educ., vol. 5, no. 1, p. 43, Dec. 2018, doi:10.1186/s40594-018-0129-0.
B. A. Montelone, “KS-LSAMP pathways to STEM: A system approach to minority participation in STEM,” in Proceedings of the American Society for Engineering Education Annual Conference, Seattle, WA, USA, June 14-17, 2015. Available: https://peer.asee.org/24389[2] C. S. H. Kamphoff, Bryant I; Amundsen, Scoot A, Atwood, Julie A, "A motivational/empowerment model applied to students on academic probation". Journal College Student Retention, vol. 8, no. 4, pp. 397-412, 2006.[3] A. Bandura, Self-efficacy: The exercise of control. New York: Freeman, 1997.[4] W. Glasser, Reality therapy in action. New York: HarperCollins, 2000.[5] J. L. Bloom, and N. A. Martin, “Incorporating appreciate inquiry into academicadvising
. However, point values wereincreased for the second Cohort and the data remained collapsible.Finally, it is possible that the measures used in the present investigation are not actuallypredictive of persistence in an engineering program, and therefore the null result we founddepicts the true state of reality. There are myriad components to self-regulation beyond thesubset chosen for this study. For example, self-efficacy, or the personal belief that one can orcannot accomplish particular tasks in particular domains, has been linked to academic outcomes[16], as have implicit theories regarding the source of one’s intelligence in subsequentimplications for outcomes [17, 18]. Nelson and colleagues incorporated knowledge building andclass goal
engineers do. These questions were crafted as the authors had previously observed thatmiddle school students abandoned the idea of becoming an engineer either because of lack ofself-confidence in succeeding as an engineer or lack of understanding of what engineers do (e.g.,more than build bridges, make cars, and work at chemical plants). The survey began with a set ofLikert-type statements to determine students’ interest and self-efficacy in engineering with thechoices: yes, a lot; yes, a little bit; not sure; probably not; and no way (see Appendix B). Thenext question was open-ended and directed students to list as many types of engineering as theycould. The last question consisted of a list of 14 things and instructed students to answer
academic competency but also comfortability, self-efficacy,and awareness [6]. Early exposure to different STEM career paths increases the chance of astudent choosing STEM as their career destination. More specifically, Dou et al. found thatinformal STEM experiences including “science consumption” through STEM activities at homeand conversations with family and friends about science “were predictive of STEM identity incollege” [7]. Further, research shows that social capital is key to broadening participation inSTEM; Saw suggests that a student’s social capital is “derived from families, peers, teachers, andprofessional networks” and supports their academic performance in STEM subjects as well astheir career trajectory in STEM pathways [8
. 2. 2006.[8] A. Godwin, “The Development of a Measure of Engineering Identity,” 123rd Am. Soc. Eng. Educ. Annu. Conf. Expo., p. 15, 2016.[9] Z. Hazari, G. Sonnert, P. M. Sadler, and M.-C. Shanahan, “Connecting high school physics experiences, outcome expectations, physics identity, and physics career choice: A gender study,” J. Res. Sci. Teach., vol. 47, no. 8, p. n/a-n/a, 2010.[10] R. M. Marra, K. A. Rodgers, D. Shen, and B. Bogue, “Women Engineering Students and Self-Efficacy: A Multi-Year, Multi-Institution Study of Women Engineering Student Self- Efficacy,” J. Eng. Educ., vol. 98, no. 1, pp. 27–38, 2009.[11] E. Seymour and N. M. Hewitt, Talking about Leaving: Why Undergraduates Leave the Sciences. Westview
adaptation of theLaanan-transfer students' questionnaire,13,14,15 a survey from the NSF-funded Prototype toProduction study,16 and Measuring Constructs of STEM Student Success Literacy: CommunityCollege Students’ Self-Efficacy, Social Capital, and Transfer Knowledge.17,18 For a fulldescription of the survey development process, steps that were put into place to support constructvalidity, and individual campus customization procedures, please see our work in progress paperfrom the 2015 Frontiers in Education (FIE) Conference titled Transfer Student Pathways toEngineering Degrees: A Multi-Institutional Study Based in Texas.19 Table 1. Project four-year institutions and partner community colleges. Four-Year Institution
camps arepositioned to reduce these challenges by offering girl participants more opportunities to directlycontribute to STEM related components of the project.Prior research has provided insight into girls’ attitudes towards STEM and methods forencouraging their persistence (Microsoft, 2018; Mosatche, Matloff-Nieves, Kekelis, & Lawner,2013; Dasgupta & Stout, 2014; McGrath, 2004, Hughes, 2013, Seron, 2016). Although thestudies identified the need to improve self-efficacy and a sense of belonging with efforts such asproviding female role models and opportunities for teamwork, these studies did not address girls’perception of belonging in STEM teamwork activities. SEEK insights suggest differentperceptions exist between girls and boys
-4.2 Other 0.3 0 -0.3Analysis of Survey DataStudent survey data demonstrate many positive impacts including changing student self-perception,self-efficacy, and career and educational plans. Faculty survey data indicate positive outcome rangingfrom improved ability to supervise and advise students in research, improved teaching skills andcredibility, and new research opportunities.Staff survey results indicate interest in working with the faculty and students from diverse backgroundsand no presence of bias. Staff indicate a variety of benefits from expanding their own research 17portfolios to learning about the ability of faculty
students’ agentic engagement, self-efficacy, growth mindset, and other related aspects. 1In recent years, there has been increasing attention paid to students’ epistemic beliefs and theirimpact on learning efficacy. Epistemic belief, which reflects students’ views on the nature ofknowledge and knowing, plays a crucial role in the cognitive, metacognitive, and affectivedimensions of students’ learning. Research has demonstrated that interventions targeting epistemicbeliefs can significantly enhance learning outcomes (Greene et al., 2018). Epistemic cognition -mostly measured in terms of belief (Greene et al., 2018) – is identified as the apex of
discipline-based educational research, including design self-efficacy, project-based learning, critical reflection in ethics, and high-impact practices.Lauren Christopher, Indiana University-Purdue University Indianapolis Dr. Lauren Christopher attended Massachusetts Institute of Technology, where she received her S. B. and S. M. in Electrical Engineering and Computer Science in 1982, specializing in digital signal processing and chip design. She worked at RCAˆa C™s David SaChristine Krull, Indiana University-Purdue University IndianapolisEric W Adams, Indiana University-Purdue University IndianapolisShahrzad Ghadiri, Indiana University - Purdue University IndianapolisRichard Vernal Sullivan, Indiana University-Purdue University