the Workplace 2023," McKinsey & Company, 2023. [Online]. Available: https://www.mckinsey.com/featured-insights/diversity-and-inclusion/women-in-the- workplace[11] 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.[12] S. A. Shields, M. J. Zawadzki, and R. N. Johnson, "The impact of the Workshop Activity for Gender Equity Simulation in the Academy (WAGES–Academic) in demonstrating cumulative effects of gender bias," Journal of Diversity in Higher Education, vol. 4, no. 2, p. 120, 2011.[13] M. Leonard, "Everyone Knows Girls Are
analyses provided additional information about the effectiveness of the intervention.A comparison of the pre-intervention responses of male and female participants (Table 2) showedthat there were some differences in attitudes. Of the four dimensions on which the difference wasstatistically significant, males ascribed higher importance to math for getting a good job (D1).However, females exhibited higher self-efficacy in math (D2) and good aptitude for science (D3).Females also indicated that the use of flight simulator in learning math and science can be helpful(D5).A comparison of the post-intervention responses of males and females showed a higher impact ofthe intervention on females (Table 2). Females had a higher recognition of the usefulness
Evaluating the performance of Lithium ion Chemistry-H Challenge batteries under cold environment (Grosse Pointe)3. Increase in RET-OU participant self-efficacy to teach engineering. Participants completedpre (n=33) and post surveys (n=30) asking about their self-efficacy to teach engineering in asecondary school setting. Surveys were given on the first day of the summer program and againon the final day of the program. The survey had nine items measuring teacher beliefs about theirpedagogical skills to teach engineering. The survey asked teachers to indicate their level ofagreement on a six point scale (Strongly Disagree
students (n=79) at a Hispanic-Serving Institution(HSI) through a semester-long group project. Life cycle assessment (LCA) and life cycle costanalysis (LCCA) were used to analyze the environmental and economic impacts of energyrecovery, water reuse, and nutrient recycling processes from a small-scale agriculturalwastewater treatment system in rural Costa Rica. Students’ ability to solve problems and producesolutions that accounted for environmental, economic, and social factors were evaluated usingdirect measures of student performance on specific assignments (e.g., final report, final videopresentation) and indirect measures using a self-efficacy questionnaire. Direct measures weregraded by the instructor of the course and an in-country partner
researchershave studied various factors for their ability to influence the performance of a student in anintroductory programming course discussed below.1.1 Factors of SuccessA wide range of factors spanning from a student’s gender to their experience with video gameshave been studied in the context of student success in programming courses. Some of the mostcommonly analyzed factors include gender [3], [4], [5], [6], prior programming experience [3],[5] – [9], and previous math or science courses [3], [8]. Other factors include self efficacy [6],[8], comfort level [3], [6], [10], motivation [10], and attributions [6], [8].There is currently little evidence that gender plays a major role in student success. Quille et al.[4] conducted a multi-institutional
. This finding is consequential to policy makerslooking at the implications for practice and will be discussed later in the paper.2. EPBEL as an Effective Tool for Increasing Self-Efficacy and MotivationEPBEL provides a particularly engaging experience for students, but another important questionis how it develops self-efficacy. Bandura describes self-efficacy as the measure of “convictionthat one can successfully execute the behavior required to produce the outcomes” desired. 31 TheAcademic Pathways of People Learning Engineering Survey (APPLES) found that high levels ofmotivation and confidence are important indicators for success in engineering and that studentswho participate in extracurricular activities are more likely to have high levels
completing an engineering degree.[4] The “leak in the pipeline” phenomenonexplains women’s tendency to quit their engineering jobs or studies.[5] Furthermore, femalesface many challenges as a result of their gender.[6] These themes are studied to overcome“machismo”, traditional culture, and the false truth that women cannot pursue careers that menhave traditionally dominated. With evidence demonstrating no gender differences formathematical skills or other engineering-related abilities, [7] women feel less able to pursue thesecareers and even think they have many barriers and obstacles to achieve them.[8]To understand social constructs that influence women, an increased interest in concepts as self-efficacy and the feel of competence have emerged in
approaches students spend extended time (oftenmultiple semesters) working with engineering professionals outside the classroom [1]. These“co-op” experiences can have positive impacts on engineering students’ academic performanceand future compensation [2], [3], as well as strengthening self-efficacy, career development andpractical engineering skills [4]–[6]. Undergraduate research is another form of experientiallearning that allows students to engage in problem solving and investigative processes in alaboratory or with a research group. Undergraduate research is a “high impact” learningexperience [7], [8], although its value depends in part on how well students are integrated withand supported in the research setting [9]–[12].At a large research
], [28].Flipped classroom pedagogies, including POGIL, effectiveness on student outcomes has beendemonstrated thoroughly in the literature through longitudinal studies [18], STEM classes [15],[19], and quantitative studies of exam performance [20]-[25]. The literature shows increases instudent outcomes, student perceptions [12], even in self-efficacy with regards to complicatedsubject matter [25]. The flipped classroom pedagogy equalizes opportunities for students,especially for students of lower socioeconomic status and first-generation students. Incomparison to advantaged students who may have support systems in place to help completehomework and projects with tutors or advice from previous generations of how to navigatehigher education
scales included in the survey, the Inventory of Graduate Writing Processes and theGraduate Concepts of Academic Writing surveys developed and validated by other researchers.Inventory of Graduate Writing Processes [26]. The Inventory of Graduate Writing Processesscale asks multiple questions using a Likert scale regarding the student’s approach to the writingprocess. Results from the questions were sorted into their factors and averaged with the other in-factor items to find each student’s primary and secondary approaches. The factors are describedbelow. Elaborative—writing is a personal investment and part of knowledge creation Low Self-Efficacy—lack of confidence in ability to articulate thoughts No Revision—avoids or resists
study following over 23,000 students from 2009 to 2016.The data were analyzed using multiple regression analyses to correlate high school,demographic, academic achievement factors from the 2009 and 2012 data collection waves to astudent’s likelihood of attending college and majoring in a STEM field. The high school levelfactors that were found to be significant predictors for college STEM major declaration includethe student’s family background, high school STEM GPA, and measures for math/scienceidentity. The findings are mixed and suggest further research is needed, particularly indisaggregating the math/science self-efficacy, identity, and utility measures, as well as ininvestigating potential differences in major choice by field separately
providedby the agency to develop educational self-efficacy, responsibility, and empathy for others.Inclusive: Educators are aware of and responsive to the ways that students are marginalized by ourcurrent education system. Educators (and all individuals in the building) actively and lovinglyaddress negative bias and integrate affirmations to promote social-emotional growth and well-being for all individuals in the classroom and school.Relevant Students experience “relatedness” with their teachers and a learning relevant to their livesthrough direct connections to their community, their country, and the world.The Engineering CurriculumPI Bayles co-developed the INSPIRES Curriculum (Figure 3)which was designed to specificallytarget three Standards for
). Assessing college students’ satisfaction with their academic majors. Journal of Career Assessment, 15(4), 446 – 462.[10] Goodwin, A. (2016). The development of a measure of engineering identity. Retrieved from: https://www.asee.org/public/conferences/64/papers/14814/view.[11] Mamaril, N. J. A. (2014). Measuring undergraduate students’ engineering self-efficacy: A scale validation study. Retrieved from: http://uknowledge.uky.edu/cgi/viewcontent.cgi?article=1020&context=edp_etds[12] Williams, D. (2006). On and off the ‘net: Scales for social capital in an online era. Journal of Computer-Mediated Communication, 11(2), 593 – 628.
/20281.8. Burwell-Woo, C., Lapuz, R., Huang, T., and Langhoff, N. (2015, June), Enhancing Knowledge, Interest, and Self-Efficacy in STEM Through a Summer STEM Exploration Program Paper presented at 2015 ASEE Annual Conference & Exposition, Seattle, Washington. 10.18260/p.23998.9. Enriquez, A., Hum, D., Price, B, Woo, C., Redding-Lapuz, D., and Camacho, A. (2013)., Creating Accelerated Educational Pathways for Underprepared STEM Students through an Intensive Math Placement Test Review Program, Proceedings: 2013 American Society of Engineering Education PSW Conference, Riverside, CA, April 18-20, 2013, pp 314-328.10. Camacho, A. M., & Hum, D. (2016, June), Measuring the Effectiveness of an Intensive Math Preparation Program to
Nvivo: 1000 most frequently used words with minimum length of ten.3.5 Deductive Thematic AnalysisDeductive thematic analysis was conducted by applying the conceptualization of motivation to learnresulting from three factors: self-efficacy, seeing value, and a supportive environment [3, 4]Self-efficacy describes one’s confidence in the ability to complete a performance-based task. Severalparticipants emphasized an increase in self-efficacy by referencing skill development, and by respondingwith a capacity to apply new tools and strategies. Example quotes are provided here: • The PhotoVoice did bring a nice mix of image, essay, and engineering. I will use this in all my research projects.” • “PhotoVoice is a great new assessment
”responses related to strategies students realize they were not using effectively.A single researcher scored the responses; thus our study did not have the benefit of a more robustreview of the data or the benefit of inter-rater reliability.Conclusion and Implications for Future ResearchWe propose that a course environment that focuses on increasing metacognitive awarenessthrough self-directed learning in individual and collaborative settings may positively impactstudents’ self-efficacy. As students focus on attaining goals that are important to them, in settingswhere the challenge is not beyond their capability, in a social setting that supports persistence,students’ self-efficacy should be enhanced [16]. This is an area ripe for future
(rather than individuals) and help withan overview of the differences and similarities between groups of individuals.Research is emerging that is examining the potential of quantitative tools for measuring theoutcome of maker activities on youth. In a recent project, Chu et al. developed a series of surveyinstruments to measure youth’s interest, self-efficacy and self-identity with respect to makingand science [2]. The survey tools measured maker identity, self-efficacy and interest, as well as,science self-efficacy and interest. Additionally, the researchers measured the students’ STEM-career possible selves and interest. In a year-long study with 121 middle-school students (ages 8-11) who participated in weekly maker activities, they found that
these experiments were visualized in real-time.To measure the key constructs associated with students’ success (motivation, epistemic andperceptual curiosity, and self-efficacy), data collection was done pre-and post-implementation ofthe experiments using the Motivated Strategies for Learning Questionnaire (MSLQ) developed byPintrich, Smith, García, and McKeachie, in 1991. Also, the Classroom Observation Protocol forUndergraduate STEM (COPUS) was employed to characterize the simultaneous activities ofinstructors and learners during class sessions. More so, students’ understanding of the course andthe application of knowledge gained were evaluated using signature assignments.Data analysis was conducted using Statistical Package for Social
making. 1 The SCCT model posits thatperson-centered variables of domain-specific self-efficacy coupled with interests and realisticoutcome expectations about the field propel individuals to pursue particular careers. Careerchoice is further influenced by a combination of supportive and inhibiting contextual factors.Supportive factors associated with pursuing computing include: early exposure, access to highquality learning experiences, supportive parents, and peer groups.2, 3 Inhibiting factors includelimited access, subtle and not-so-subtle racism and sexism, geographic location, and lower socio-economic status.3, 4 Importantly, SCCT incorporates gender and race/ethnicity explicitly in its model, whichrenders it appropriate for work with
. Three research questions are asked:RQ1: How does student STEM SC relate to their design performance in parametricbuilding design? In this study, “design performance” refers to the ability of students to generatesolutions that have good performance in quantitative metrics such as low energy usage. Previousresearch shows that student self-efficacy and performance are positively related both outside ofSTEM [11] and in STEM [12]. However, this study evaluates performance specifically in abuilding design exercise with quantitative goals that are simulated within a parametric designtool. This relationship can reflect potential student effectiveness in technical building design, butit does not fully reflect student behavior. The extent of their
IntroductionThere is substantial evidence that most K-12 science and math teachers who aim to incorporateengineering design processes into their courses acquire these skills through extracurricularprofessional development (PD) programs or self-directed learning [1-4]. Research has shownthat PD programs are valuable in increasing teachers' engineering self-efficacy and thelikelihood of implementing engineering processes in the classroom [5-7]. These programs offerflexibility in introducing engineering design to teachers in diverse formats (e.g., in-person versusvirtual) [8], using various theoretical frameworks [9]. They often provide participation incentivessuch as stipends [9, 10]. However, despite the value of these PD programs, teachers areusually
an issue not only with competency,but also with a lack of self-efficacy in math, science, and engineering which creates anxiety. According to Beck-Winchatz and Riccobono (2007), the majority of students with VI arefollowing general education curricula. However, less than 30 individuals with VI earned ascience and engineering research doctorate on average each year from 2001 to 2009 compared to25,600 people without a disability on average per year during the same time period (NSF, 2012).Lack of higher level degrees in the science and engineering fields do not reflect the fact thatstudents with VI have the same spectrum of cognitive abilities as sighted peers (Kumar,Ramasamy, & Stefanich, 2001) and with appropriate accommodations can
. Theinitiative was assessed by participant engagement with the topics and qualitative journalresponses to the discussion prompts.Our effort for this project consists of two main goals: Goal 1: To encourage female students to remain in STEM fields through supportivedialogue. Goal 2: To promote collaboration, self-efficacy and leadership while providing strategiesfor females to change the culture.Each of these goals are in line with new ABET criteria focused on educating the “wholeengineer.” To measure our progress toward these goals, we have begun to capture studentengagement via qualitative journal responses. In the future, we plan an additional survey and alimited number of interviews about the project. Journal data is derived from
“grit”, self-determination and social cognitive careertheories are used to explore self-efficacy, goal orientation and perception of institutionalculture as mediators of academic achievement. A significant part of this paper analyzesresponses to interventions designed to support retention of students lacking the mathbackground to “hit the ground running” upon entering a large, public predominantlywhite institution (PWI)’s college of engineering, with a disproportionate number ofminorities in the underprepared category. Targeted retention interventions for first yearstudents yielded statistically significant improvement in math course progression,particularly for minority students. Overall attrition decreased by 10% in two successiveyears
and diversity,equity, and inclusion (DEI). The authors described how these subcategories would need to becategorized properly in future revisions, but the idea is they heavily dictated a student’sconfidence and sense of belonging.Summarizing this listing, we concluded with a motivational category list of interventionsubcategories as follows: task-value interventions (e.g., utility-value, communal value), framinginterventions (e.g., self-efficacy, belonging), personal value interventions (e.g., valueaffirmations), mitigating stereotype threat, and changing attributions, as shown in Table 1.Donker et al (2014) conducted a meta-analysis on teaching strategies that help studentmetacognition and self-regulation to find which specific tactics
motivation to usethe tools they learned, and specific behaviors learners adopted after attending a Carpentriesworkshop.We compiled existing instruments measuring computer self-efficacy [14], Java programmingself-efficacy [15], Python and computational ability [16], self-efficacy towards FLOSS projects[17], and student-instructor relationships [18]. Assessment specialists on staff and from ourinstructor community used a rubric to vote on whether to omit questions, keep them as-is, oradapt them for the purposes of our data collection. Rather than focusing on learners’ skills withrespect to particular tools, we wanted to focus on assessing learner confidence, motivation, andadoption of good research practices [19], as these elements represent the
report using the search term “STEM outreach”[2].Despite efforts to recruit more underrepresented students to engineering, overly difficultengineering tasks and courses can serve as a barrier to recruiting students to the engineeringworkforce. Research shows that negative STEM experiences such as “weed out” courses, orcourses that are purposefully difficult, cause low STEM persistence in first-generation collegestudents [3]. A separate study on outreach events geared towards female elementary schoolstudents stated that decreases in STEM self-efficacy occur around young elementary age [4]. Tomitigate negative experiences, there is a need to focus on creating positive STEM experienceswhich can increase student engagement and increase the likelihood
for Engineering Education, 2017 The Influence of Gender Grouping on Female Students’ AcademicEngagement and Achievement in Engineering and Biology: A Case of Small Group Work in Design-Based Learning (Work in Progress) IntroductionDuring the past 30 years, much attention has been drawn to the lack of women in STEMfields and the need to attract and retain them in these fields. In the relevant literature, theinfluence of gender grouping on variables such as female students’ interest, self-efficacy,participation/engagement and achievement in STEM subjects has been a salient line ofresearch. However, researchers have arrived at mixed findings. Also, while researchers haveinvestigated the influence of
work.Comparing the effectiveness of virtual learning events with personal workshops would provideinsights into the advantages and challenges associated with each format as well as their overallimpact.References[1] Stewart, A. J., Malley, J. E., & LaVaque-Manty, D. (Eds.). (2007). Transforming scienceand engineering: Advancing academic women. University of Michigan Press. [2] Ford, A. Y., Dannels, S., Morahan, P., & Magrane, D. (2021). Leadership programs foracademic women: building self-efficacy and organizational leadership capacity. Journal ofWomen’s Health, 30(5), 672-680. [3] Eagly, A. H., & Carli, L. L. (2007). Through the labyrinth: The truth about how womenbecome leaders. Harvard Business Review Press [4] Eagly, A. H., & Carli, L