to programming.Two validated scales were used to assess changes in both computer programming andengineering self-efficacy: 1.Computer Programming Self-Efficacy Scale (CPSES): Measures programming confidence across constructs such as independence, persistence, and complex task handling [9]. 2.Longitudinal Assessment of Engineering Self-Efficacy (LAESE):Assesses confidence in engineering-related tasks, career expectations, and sense of belonging [10].The instruments were administered as pre- and post-surveys to capture baseline andpost-intervention self-efficacy data. The CPSES and LAESE surveys both used a 7-point Likertscale ranging from “not confident at all” to “absolutely confident.Preliminary
perceptions ofengineers and engineering. This impacts their self-efficacy with teaching engineering as well astheir willingness to attempt to incorporate engineering practices into their classrooms [6-8].Engineering teaching self-efficacy, which is defined as teachers’ “personal belief in their abilityto positively affect students’ learning of engineering” [7,8], directly affects the ability of teachersto engage students in engineering practices. The Teaching Engineering Self-Efficacy Scale(TESS), a survey developed by Yoon and Strobel to measure the self-efficacy of K-12 teachers,has demonstrated that the engineering teaching self-efficacy of current K-12 teachers is typicallyquite low [7,8].To provide pre-service STEM teachers with exposure to
levelof engineering interest, engineering self-efficacy beliefs, recognition as engineers, and engineeringagency beliefs. These measures were collected using a 0-4 rating scale, asking students to rate theirlevel of agreement with the survey statements. All survey data were collected during the 1.5-hoursession. A mixed ANOVA was conducted to assess changes in students’ responses to the surveymeasures before and after the activity and to determine whether they differed by gender. Data wereexamined for multivariate outliers using Mahalanobis distance; the one case that violated theassumption was removed. Univariate normality assumptions were assessed through skewness andkurtosis z-scores; all values were within an acceptable range. The
, understanding of growth mindset, and skills with cultural competence and culturallyresponsive pedagogy [7]. The CRT survey items asked participants to respond to their attitudesabout equitable teaching and culturally sensitive instruction. The first part of the survey (40items) measured teacher self efficacy in relation to teaching tasks related to CRT. The secondpart of the survey (26 items) measured how teachers associate positive student outcomes withCRT. After reviewing the survey with faculty advisors, we adapted the survey for this project byreducing the number of items to 18 and 11 respectively, with some slight wording changes tobetter reflect our participants. The response scale was also adapted to be on a 5-point likert scale,rather than a
engineeringdesign process using the Engineering Design Self-Efficacy Measure [7], and those results arepresented in Figure 2. As these students completed this survey at the start of their first semesterin college, it is not surprising to see that the majority of them (11 of 19 or 58%) rated their abilitybelow “Moderately Can Do.” These students would be considered novice learners, and so theirself-efficacy is expected to be fairly low before taking engineering courses. 6 5 4 Count 3 2 1 0
systemschallenges. The use of FPGAs and IoT boards provides multiple entry points into the material,offering a hands-on, exploratory experience that fosters self-efficacy, particularly forneurodiverse learners. This strategy ensures students gain both foundational knowledge and theconfidence to navigate the rapidly evolving field of intelligent embedded systems.This paper and poster presentation will explore the evolution of this curriculum, enriched by datacollected from Fall 2023 to Fall 2024 on students' career choices, identity, interest, outcomeexpectations, and self-efficacy in hardware engineering, AIoT, and intelligent embeddedsystems. To gauge participants' interest and perceptions, we administered both pre- and post-surveys, conducted focus
in undergraduate research working on assistive technologies without directrecruitment. We aim to use qualitative engineering education research methods developed in theNSF RIEF program, to study this unique cohort to understand supports and barriers for studentswith physical disabilities to contribute to research. Grounded in Social Cognitive Career Theorywe set out to understand factors that influence research in human-centered engineeringdesign as a support for career success for students with disabilities. The research design set outto answer the research question, What factors impact self-efficacy and career interest as a resultof a human-centered robotics design research experience?IntroductionThis supplement project is examining the
collective experience via focusgroups to provide a different perspective than the isolated experiences solicited through thesurvey instrument. Table 1. Latent variables contained within the survey. Variables Scale/Items Confidence in STEM- Confidence in Math and Science Skills (α=.80) related skills Confidence in Professional and Interpersonal Skills (α=.82) Sheppard et al. (2010) Confidence in Solving Open-Ended Problems (α=.65) Entrepreneurial Intent Entrepreneurial Intent (α=.89) Gilmartin et al. (2018) Self-Efficacy about Self-efficacy (α=.81) Graduate School
/post surveys and audioreflections and facilitated a focus group discussion at the end of each internship program.Following some refinement early in the project, the pre/post survey included measures adaptedfrom validated instruments including the Engineering Design Self-Efficacy Instrument [9], theShort Instrument for Measuring Students’ Confidence with Key Skills [10], and the STEMProfessional Identity Overlap measure (STEM-PIO-1) [11]. These measures assess teens’ self-efficacy in engineering and the design process and their self-perceptions as engineers. Based onthemes that emerged from the project’s first two years, the team added a retrospective (post-only) survey in the project’s third year to assess changes in teens’ understanding of
Experiences and Outcomes in the E3 ProgramThe E3 program was designed to enhance high school teachers’ ability and confidence to teachethical principles in STEM. Feedback from the participating teachers, collected through pre- andpost-program surveys, provides a clear picture of the program’s impact. A Likert scale was usedto measure their responses to various aspects of the program. The scale ranged from 1 to 5, with 1indicating "Strongly Disagree" and 5 indicating "Strongly Agree." This method was employed toevaluate the teachers' confidence, preparedness, and perceptions both before and after the program,providing a quantitative measure of its effectiveness.The E3 program had a notable influence on teachers’ self-efficacy in teaching engineering
students, after which they discussed their thoughts and how they would implementit in their classrooms.2.3 Measurements and data collectionPre- and post-workshop surveys were conducted to investigate the impact of flow-based musicprogramming environments on teachers’ self-efficacy, interest, and attitudes toward teachingprogramming. Table 1 outlines the specific survey questions, all rated on a five-point Likert scale.For example, the post-survey #1 has “Much more confident/more Confident/Equallyconfident/Less confident/Much less confident”. The pre-workshop survey established a baselineof participants’ confidence, interest in programming, and perspectives on teaching programming,while the post-workshop survey assessed changes in these
participation in engineering. Recent investigationshighlight that participation in makerspaces correlates with improved innovation self-efficacy andgreater academic and professional confidence (Andrews et al., 2021). However, most priorresearch has focused on engineering students already committed to the field. There is a gap inunderstanding how multidisciplinary makerspace experiences shape identity trajectories amongstudents with varying levels of prior exposure to engineering. Although the link between makerspaces and skill development is established (Forest etal., 2014; Wilczynski, 2015), more research is needed on how multidisciplinary makerspacecourses shape engineering identity dimensions holistically, particularly regarding recognition
-belonging-at-Imperial-College-London-scale.pdf. (Accessed Sept 1, 2024)[13] N. Mamaril, E. Usher, C. Li, D. Economy, and M. Kennedy, “Measuring Undergraduate Students' Engineering Self-Efficacy: A Validation Study. Journal of Engineering Education.” 105. 10.1002/jee.20121. 2016.
science in high school. Teacher outcomes (N=68) include improved QISTknowledge and pedagogical self-efficacy. This project is a replicable model of university-basedQIST outreach to inspire the next generation quantum workforce in industry, research, andacademia.Introduction and BackgroundRecent reports have called for increased teaching, learning, and awareness of quantuminformation science and technology (QIST) principles and skills in precollege educationalsettings. Federal initiatives including the National Strategic Overview for Quantum InformationScience have emphasized the need to develop the future quantum workforce through K-12partnerships between academia and government agencies [1]. The Quantum Information Scienceand Technology
foster deepcollaboration and build a strong community of effective community college teaching faculty witha shared vision and purpose. This aims to ensure that students transfer to the four-yearenvironment equipped with a well-developed engineering identity, self-efficacy, sense ofbelonging, and the T-shaped skills – combining breadth and depth of knowledge - needed to makethe most of their new university environment. This project will thus revolutionize student-centeredinclusive teaching practices and lead to cultural, structural and organizational change at all levels,ultimately impacting high-tech workforce development in the state. One major aspect of the projectis to design and effectively deliver three required engineering courses at the
Asian peers [4]. This underrepresentation highlights the critical need for targetedinterventions and support programs to bridge the gap and promote persistence in STEM highereducation and careers. We contend that a critical factor in promoting persistence in STEM fields is how studentsperceive their ability to approach academic and career challenges, such as their self-efficacy [5],as well as their level of engagement—behaviorally, cognitively, emotionally, and socially—within relevant learning communities [6]. Although researchers have proposed differentstrategies to improve student retention (e.g., learning communities, supplemental instruction), forURM students, two key factors stand out: financial assistance for college expenses [7
rates betweenintervention and control groups, specifically examining improvements for first-generation andminority students. Engagement and Belonging: Using learning index measures (Engaged LearningIndex) and a custom "sense of belonging" questionnaire, along with psychometric tools (GeneralSelf-Efficacy Scale, Academic Self-Efficacy Scale, Psychological Sense of Belonging, GrowthMindset Scale), to compare mean scores between groups using t-tests.Internship/Job Offers: Comparing the rate of internship offers between the two groups.b) Impact on Teaching Curriculum:This will involve investigating the differences between CTE & HE courses and conventionalcourses.Figure No.2 shows an improvement in sense of belonging to their major in the
students’sense of identity and self-efficacy within STEM majors [3,4], which in turn are well known tosupport persistence. This paper presents preliminary results on the academic performance,graduation, and placement of the first two cohorts of RISE Scholars.RISE Program OverviewThe program is funded by a $999,999 Track 2 S-STEM grant [2] and has supported a total oftwenty Scholars in three cohorts entering the university in 2019, 2020, and 2021. The Scholars’majors include Engineering (6), Biology (4), Marine Biology (4), Computer Science (3), andForensic Science (3). Key features of the program include: • A $10,000 annual scholarship for each Scholar, renewable for up to four years. • A weeklong residential summer bridge experience intended to
, academicallytalented, 2-year CC transfer engineering students as well as retaining and graduating them. Majorelements of this effort are: provide need-based financial assistance to academically talented engineeringstudents; enhance transfer engineering students’ math proficiency through a Summer Math Boot Camp(SMBC); enhance Students’ Self-Efficacy, Growth Mindset, and Engineering Identity throughmetacognition- and cohort-based activities; and assess students’ academic performance using dataanalytics. The key preliminary findings indicate S-STEM financial support is the top-rated element of theprogram followed by professional preparation, community building, and progressive growth of scholarsin various aspects of engineering identity.Introduction and
construction, critique, andrevision (Baumfalk et al., 2018). BACKGROUNDIntegrating engineering design into K-12 science education, driven by initiatives such as the NextGeneration Science Standards (NGSS) (NRC, 2013), highlights the need to effectively prepareteachers to teach the iterative and flexible nature of design. Research indicates that interventionscan enhance teachers' pedagogical self-efficacy in engineering; however, challenges persist,including fostering confidence in students’ abilities to succeed (Coppola, 2019). Hands-on,practical experiences in engineering design significantly enhance teachers' efficacy andunderstanding, as shown in studies where interventions positively impacted preservice
thestorytelling process. Writing stories enabled participants to reflect deeply on their STEMjourneys and develop communication skills, while listening to peers’ narratives fostered empathyand a sense of shared experiences. Many participants noted that performing their stories publiclysignificantly bolstered their self-confidence and self-efficacy, helping to counter feelings ofimpostorism. However, challenges such as public speaking and language barriers led someparticipants to experience heightened impostor feelings. These findings highlight the need fortailored coaching and practice opportunities to enhance the performance phase of theintervention.Audience measures from public storytelling performances revealed significant changes inaudience
to be retained inengineering into the second college year [4] and that women students who receive theintervention may have more positive self-efficacy [5].To expand on understanding the impacts of the intervention on students, we have recently begunto examine how students experience the intervention, if they remember it, what they rememberabout it, and what they feel they gained from it. In this paper, we provide an overview of ourfindings in this area using data collected from surveys of one first-year engineering programmingcourses at one study institution and focus groups and interviews with students at a second studyinstitution where the intervention is being implemented within second-year courses in specificengineering majors.Project
Next Steps for Design ToolsIntroductionSketchtivity is an intelligent tutoring software that aids in student learning of sketchingfundamentals through providing individualized feedback to freehand sketching activities [1]. Theproject has explored the role of freehand sketching in engineering design education and has foundthat learning with the software can improve spatial visualization skills [2], creative problemsolving [2], and self-efficacy [3], through enhancing students 2-point perspective freehandsketching skills. A study investigating a sketch-based game ZenSketch also indicated that studentswith improved sketching skills were more adept at idea generation and exhibited higherengagement in the design process [4]. Recent work launched
component rate statements 1: Motivated 38 statements On a 5-point scale: Strategies for Factors: “value” with subfactors “intrinsic goals” and “task value”; “not at all true of me“, Learning “expectancy” with subfactors “self-efficacy” and “control of “a little true of me“, learning”; and “self-regulation” with sub-factors “metacognitive “partly true of me“, regulation“ and “effort regulation“ “mostly true of me“, and Example: “When I get confused about something I’m learning in my “very
, 2011, doi: 10.5703/ 1288284314639.[13]M. Perkins Coppola, “Preparing preservice elementary teachers to teach engineering: Impact on self‐efficacy and outcome expectancy,” Sch. Sci. Math., vol. 119, no. 3, pp. 161–170, Mar. 2019, doi: 10.1111/ssm.12327.[14]J. Radloff and B. M. Capobianco, “Investigating Elementary Teachers’ Tensions and Mitigating Strategies Related to Integrating Engineering Design-Based Science Instruction,” Res. Sci. Educ., vol. 51, no. S1, pp. 213–232, Sep. 2021, doi: 10.1007/s11165-019-9844-x.[15]B. M. Capobianco, J. Radloff, and J. D. Lehman, “Elementary Science Teachers’ Sense-Making with Learning to Implement Engineering Design and Its Impact on Students’ Science Achievement,” J. Sci. Teach. Educ
. 2022, doi: 10.1080/08923647.2022.2029090.[7] K. Malanson, B. Jacque, R. Faux, and K. F. Meiri, “Modeling for Fidelity: Virtual Mentorship by Scientists Fosters Teache r Self-Efficacy and Promotes Implementation of Novel High School Biome dical Curricula,” PLoS ONE, vol. 9, no. 12, p. e114929, Dec. 2014, doi: 10.1371/journal.pone.0114929.[8] V. Minces, A. Khalil, and A. Booker, “Listening to Waves: Engaging Underrepresented Students Through the Science of Sound and Music,” Connect. Sci. Learn., vol. 3, no. 4, Jul. 2021.[9] E. Chow, L. Li, N. Akshay, A. Barron, S. Yonezawa, and V. H. Minces, “Improving Teachers’ Attitudes Toward Sound and Waves Through the Connections with Music,” in 2024 ASEE Annual Conference &
/10.1080/17439760.2019.1651889Tang, H., Gumina, S., & Wang, S. (2021). Building design thinking into an authentic Internet of Things instruction. 2021 Tenth International Conference of Educational Innovation through Technology (EITT), 24–27. https://doi.org/10.1109/EITT53287.2021.00014Tsai, M.-J., & Wang, C.-Y. (2021). Assessing young students’ design thinking disposition and its relationship with computer programming self-efficacy. Journal of Educational Computing Research, 59(3), 410–428.Wang, B., Zheng, P., Yin, Y., Shih, A., & Wang, L. (2022). Toward human-centric smart manufacturing: A human-cyber-physical systems (HCPS) perspective. Journal of Manufacturing Systems, 63, 471–490
alignment with the Michigan Teacher Leader Preparation Standards [9]. Theproject also seeks to align Fellows’ teaching practices with the Next Generation ScienceStandards [10]. Evaluation data sources will include annual leadership knowledge/self-efficacy[11]; NGSS teaching practice surveys [12]; and annual interviews focused on leadershipopportunities, program experiences, program strengths, and areas for improvement. Additionally,micro-teaching observations will be conducted and Fellows’ participatory action researchprojects and classroom artifacts will be collected and assessed using rubrics. These data will helptriangulate the survey data to determine the extent that Fellows are growing in teacher leadershipand NGSS aligned teaching. Project
2024 calendar year have included ateam-based pitch development program, scholar participation in an externally facilitatedcertificate course in business startup logistics, and the integration of scholar’s product ideas intothe Project-Based Learning curriculum of the host department. This paper describes each of theseprogram highlights. As the scholars progress in their degrees with some nearing the Flight phaseof the program, the dynamics of integrating the scholars’ work into their degree curricula areaddressed. Pre- and post-year surveys assessing scholars’ perception of their entrepreneurial self-efficacy are summarized, showing a positive trajectory.Keywords: NSF, Scholarship Program, Entrepreneurship, Project Based Learning (PBL
modules, both for Dartmouth courses and for courses at colleges anduniversities across the United States. The modules are available for download and use in apermanent repository [2]. We have analyzed the impact of the modules on student data scienceinterest, beliefs, career aspirations, and self-efficacy [3] using a validated survey instrument [4].We also assessed the impact of two workshops on the module development process on thirtyfaculty participants from across the country [5], finding growth in their skills, confidence andself-efficacy.In addition to these early data science modules, a crucial element of the DIFUSE project ispairing students with practice in data science skills through experiential learning opportunities.To meet this need