and together,providing further nuance into how Hispanic/Latina/o/é/x students might differ between transferand non-transfer. Much of the present literature focuses exclusively on Hispanic/Latina/o/é/x ortransfer students (e.g.,[34]-[35]), and we build on the present insights within literature to bettersupport Hispanic/Latina/o/é/x Transfer students (HLT) (e.g., [36]-[39]).MethodsAt a large southeastern university in the United States, 152 students (n=152) in Dynamics (afundamental engineering course) completed entry and exit surveys in the Spring 2024 semester.The questions were the same at the beginning and end of the semester to assess students’ self-reported perceptions of pedagogical practices, SRL, motivation (measured by self-efficacy
the perceived challenges of live streaming as an informal learning opportunity forcomputer science students?Through this work, we aim to understand and evaluate whether or not live streaming impacts anundergraduate student’s perceived self-efficacy in software or game development, RQ1 . Toquantitatively measure self-efficacy, we have adapted questions from Ramalingam andWiedenbeck’s Computer Programming Self-Efficacy Scale and Hiranrat et al.’s surveymeasurements for software development career [41, 42]. As we allow the students to choose theirown projects and set their own goals, we expect there to be some division among the participantson how quickly they believe themselves to be improved based on the gravity of the goals they setfor
the course, before initiating the thesis portfolio. Studentscomplete the Survey about Collaboration Skills (SCS) and Senses on Belonging and Self-Efficacy Survey (SBSS) to establish baseline data during this session. The second activity(Activity 2) is conducted in Week 14, following the academic recess in Week 13, ensuring itdoes not interfere with other evaluated course activities. This session focuses on conflictresolution and teamwork, complemented by reflective discussions. Finally, the third activity(Activity 3) takes place in Week 17 during the course's closing session. This final sessionintegrates a continuous improvement exercise and a second application of the SCS and SBSSsurveys to measure changes and outcomes across the semester
necessary to success in their careers. The course provides an excellent first-yearexperience, measures belonging and self-efficacy to the engineering profession, increasesstudents’ confidence in their professional goals, as well as tracks the success of engineeringstudents.III. RESULTS1. Contextualized BridgeIn 2022, the qualitative and quantitative outcomes of the first Bridge cohort were assessed throughsurveys and case study interviews supplemented with retention, persistence, transfer, and degreecompletion rates.[17] The outcomes showed that the established framework overwhelminglyincreased belonging and self-efficacy. All participants who completed the Bridge eliminated up totwo years of math remediation, and 54% were directly placed in
diverse public and private schools in Nigeria.Data were collected using validated instruments: the Mental Rotation Test (MRT) and SpatialOrientation Test (SOT) to measure spatial reasoning; a Physics Achievement Test Survey (PATS)(based on WASSCE papers) to assess physics performance; and the Students' Attitudes TowardPhysics Questionnaire (SATPQ) to measure personal, teacher, and self-efficacy factors related tophysics learning.The penalized regression analyses revealed several significant predictors of spatial reasoning.School type emerged as the strongest predictor, with private school students demonstratingsignificantly higher spatial reasoning scores than their public school counterparts. Physicsperformance also showed a robust positive
for each time point to measure changes overtime. Preliminary quantitative analysis included the use of two-tailed t-tests to compare pre- andpost-survey construct scores. ANOVA was conducted to explore differences among students ofdifferent genders within pre- or post-survey data.ResultsThe t-test results showed that there was a statistically significant increase (p = 0.0002 < 0.01) interms of self-efficacy between pre- and post-survey data, underscoring a marked increase instudents’ self-efficacy in the engineering field after taking the course. Further analysis for eachgender group showed a statistically significant increase in self-efficacy for both male (p = 0.0196< 0.05) and female (p = 0.0067 < 0.01) students, while no change
biometric, measure the duration of exercise activities such asrunning or brisk walking, detected by the Garmin device [30]. Aerobic exercise research supportsthe use of intensity minutes in studying well-being. It is well-established that physical exercisepositively affects psychological well-being [31]. For instance, a study on problem-solvingconfidence found that students who exercised regularly had higher self-confidence when solvingproblems [32]. A study on self-efficacy in exercise also showed that belief in one's ability to engagein physical activity significantly predicted perceived wellness [33]. Furthermore, exercise has beenlinked to higher self-care, gratitude, and increased physical activity, showing a positive feedbackloop between
and other socialidentities in team effectiveness is described below.Self-EfficacyBandura defined self-efficacy as an individual’s belief that they can successfully complete a taskor endeavor [8]. Self-efficacy beliefs are recursive; student self-efficacy is often informed byprior performance feedback and stereotypes/expectations, and future academic performance hasbeen shown to be influenced by self-efficacy, with negative self-efficacy resulting in “reducedinterest and engagement during learning” [9]. Recent research has shown that women reportlower self-efficacy than men in STEM subjects such as physics, chemistry, and mathematics intheir first year of engineering studies [9]. Furthermore, Whitcomb et al. identified“discipline-dependent
think like one. The factor of an advancedengineering degree is focused on students' intentions to pursue graduate studies in engineering.The factor of academic engineering confidence relates to students’ performance in coursework,exams, and comprehension. The factor of DEI components is associated with discussions ondiversity, equity, and inclusion among instructors and students. Later in this paper we willexamine how strong each factor is and how well the items measure the factors. The six factorsalign with Tinto’s four key elements of student motivation and persistence, serving assubcomponents of intensity and clarity of goal to graduate, self-efficacy, sense of belonging, andcurriculum perception, as illustrated in Figure 2
9 Senior / 4th 28 19 9 0 7 Total 256 199 (78%) 54 (21%) 3 (1%) 32 (12%)Survey items (Appendix A) considered participant demographics, questions regarding identity asa maker and self-efficacy for conceptual design and prototyping, and questions regardinginteractions with both the makerspace teaching assistants (TAs) and other student users in themakerspace. Survey items came from a previously validated measure [26,27] with items relatedto self-efficacy in conceptual design and prototyping (i.e., “tinkering”) with terminology relatingto space identification [31]; The survey also included questions regarding participant
majority of respondents in the analytic sample identified asmen (n=92, 67.2% men; n=41, 23.0% women; n=1, 0.7% non-binary; n=3, 2.2% not reported).Both tenure stream/track (n=108, 78.8%) and non-tenure stream/track (n=29, 21.2%) facultywere represented. Among the tenure stream/track faculty, varying ranks were represented (n=23,21.3% assistant professor; n=11, 10.2% associate professor; n=73, 67.6% full professor; n=1,1.0% not reported).Instrument. A survey instrument was used to understand the ways that faculty take upresponsibility for driving DEIB changes, as well as their self-efficacy and readiness for change..The instrument included 7 scales (see Appendix) measuring various aspects of facultyperceptions of DEIB policies and practices
,including a hypothesis to test, equipment to use, and data that they propose to collect. GraduateTeaching Assistants (TAs) and the laboratory manager review the proposals and either approve themor require further development. Once their proposal is approved, students use the remaining weeksto complete their study and write a full technical report, which they submit using an assignedpseudonym. The project finishes with each student conducting a single-blind Peer Review of astudent’s work from another lab section. Grading is based on the TA’s assessment of the report andthe Peer Evaluation.Pre- and post-surveys of the students measure their self-efficacy, among other aspects of theirexperience with the course, to evaluate the effectiveness of this
collectively account for 48.9% of thevariance within the dataset, with the variable PA0 contributing the largest portion of 19.1%.The factor of greatest significance (PA0) is a latent variable which measured Intrinsic Motivation,Task Value, Learning Beliefs, Self-Efficacy, and Extrinsic Motivation. This latent variable couldbe termed: “Motivation and Perceived Ability”. This latent variable represents a student’s innatedesire to perform well in the course, combined with their own perceived ability to succeed inaccomplishing this goal. The second factor (PA1) is a latent variable that measures CriticalThinking, Peer Learning, and Help-Seeking. We term this latent variable: “CollaborativeCognition”. This latent variable suggests that students who engage
these questions, the study employs a mixed-methods approach. Pre- and post-eventsurveys measure shifts in students’ STEM interest and self-efficacy, while observational metrics,such as task engagement, peer collaboration, and facilitator interactions, provide qualitativeinsights. Knowledge checks and thematic analysis of feedback from participants, parents, andeducators further enrich the evaluation of the fair’s impact. Preliminary findings highlight howculturally and socially relevant STEM activities can inspire and educate underrepresentedstudents, fostering both technical skill development and sustained interest in engineering fields.By contributing to the broader discourse on diversity and inclusion in STEM education, thispaper underscores
group gender composition on girls’ motivation and engagement. Dr. Robinson is a PI and Co-PI on several NSF sponsored grant projects which focus on teacher professional learning and self-efficacy with implementing culturally relevant engineering education, connecting to place and community, and centering culture and Indigeneity within STEM education. Dr. Robinson has over twenty years of K – 12 teaching experience, including seven years as a teacher leader of professional development in the Next Generation Science Standards, the Common Core State Standards in Mathematics, and in elementary science and engineering pedagogy.Dr. Frank M. Bowman, University of North Dakota Dr. Frank Bowman is Thomas C. Owens Endowed
, 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
a more sustainableand equitable approach. As we prepare for the next iteration of the course, including a February run, we haveidentified several opportunities to enhance our research and gather more comprehensive data. Akey area for improvement is the direct assessment of students' self-efficacy beliefs inengineering, which will be addressed through the implementation of pre- and post-coursesurveys. These surveys will measure changes in self-efficacy and provide valuable insights intothe course's effectiveness in building students' confidence in their engineering abilities. Our primary focus will be on introducing and evaluating modifications to the coursestructure and content, accompanied by preliminary observations of their
. This programincludes complex tasks such as testing the tensile strength of 3D-printed parts. Students mustiteratively use the results of the tensile strength measurement to adjust the 3D printing parametersettings and improve the quality of the print through multiple cycles. TeleopLab preserves theinteractivity and real-world complexity of these processes, allowing students to conduct multiplecycles of testing and adjustment critical to manufacturing training. The educational impact ofTeleopLab was evaluated using the Motivated Strategies for Learning Questionnaire (MSLQ),with pre- and post-use data collected from six students. The results showed an improvement of25% in self-efficacy, 27% in motivation to re-engage, and a reduction of 13% in
Participants, while those who selected Never and Rarely were categorizedas Non-Participants.In addition to participation frequency, the survey included Likert scale questions aimed atmeasuring motivation and sense of belonging. The Motivation Questionnaire II (SMQ-II) [16]was used to assess underlying aspects of motivation, including self-determination, intrinsicmotivation, career motivation, and goal motivation. The New General Self-EfficacyQuestionnaire [17] was used to measure the additional motivation factor, self-efficacy. Threequestions designed by our team were used to assess students’ sense of belonging: I feel acceptedat UC San Diego, I feel comfortable at UC San Diego, and I feel supported at UC San Diego.These questions were designed to
Sample Item for Applicants Recruiters Self-Efficacy A student’s perception I am confident at I can effectively develop of their competence presenting myself a recruiting timeline. participating in the through a resume. recruitment process Expectancy A student’s expectation Based on my statement Based on my abilities to for Success that they can achieve of interest, I am likely screen applicants, I am their goal in the to move forward to the likely to find good recruitment process. next recruitment stage
: Workshops such as #IamRemarkable, a global movement that empowersparticipants by fostering self-efficacy and resilience. The program’s focus on creating a sense ofbelonging within the tech community has led to increased perceptions of family support, culturalinclusivity, and recognition of computing’s societal contributions.Research MethodologyThe LIFT program evaluated its impact using retrospective pre/post surveys from 2022 to 2024,consolidating findings from the 2022-2023 and 2023-2024 reports. Designed by MDC, RebootRepresentation, and Creative Research Solutions, the surveys measured self-reported changes insense of belonging, social impact awareness, technology access, instructor inclusiveness, self-efficacy, computing interest, and cultural
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
Non-URM ContGen First Gen All (n=45) Male (n=25) URM (n=15) (n=20) (n=30) (n=24) (n=21) Pre 3.9148 4.16 3.6084 3.8889 3.9667 4.0174 3.7977 Post 3.9889 4.13 3.8125 4.0583 3.85 4.0104 3.9643Self-efficacy: There were no significant changes in students’ perceived self-efficacy in bothmastery experiences and verbal persuasion measures over the semester, although a slight declinewas noted across most demographic subgroups. There were no significant differences betweenstudents’ self-efficacy (mastery) by gender, URM, or first-generational status at
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
interact with undergraduate STEM students.Data were passively collected from students via the online learning management system (LMS)every year of implementation (2021-22, 2022-23, 2023-24). Data included time spent in the LMSand number of role model videos viewed. Additional data collected includes measures of studentalgebra proficiency (i.e., graded rubrics of student work) and pre-post survey instruments(measuring math self-efficacy, STEM interests, STEM outcome expectations, and STEM choicegoals). Interviews with 25 students were collected using a semi-structured protocol to capturereasons for electing to participate, barriers to participation, and reactions to the role model videosand field trips. Finally, external evaluators characterized
reports persistencerates for engineering degree programs as 91%, measuring persistence as progressing from oneyear to the next [7]. They also report a persistence rate for engineering programs of 84.4%.PRISM journal from The American Society For Engineering Education (ASEE) reports anational first-year persistence for engineering bachelor’s degree at 92.8% and a retention rate of86.4% [8] Factors such as academic self-efficacy, access to resources, and the ability to applycourse concepts to real-world scenarios are crucial predictors of success, particularly forfirst-generation students [3]. Programs designed to enhance self-regulation and reduce anxietyare especially beneficial for this demographic, providing a foundation for their academic
of these affective characteristics include a growth mindset,STEM identity, a sense of belonging, and academic self-efficacy. It can be helpful to characterizethese for a particular population of students. Interventions such as research participation,tutoring, or internships can then be more readily identified, which might help to improve thesefeelings and attitudes among the students, leading to greater success in STEM retention anddegree completion.It is possible to quantify some of these student beliefs and attitudes through validated instrumentsthat have been developed to measure specific characteristics. These instruments frequently takethe form of survey-like questions that can be given to students. These instruments can be used
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
% Sexual Identity Heterosexual 401 85.9% LGBQ+ 56 12.0%There is no widely agreed-upon sample size requirement for latent class analysis, but previousresearch has indicated that common fit statistics perform adequately when N ≈ 300–1000. Modelsthat use fewer indicators and sufficiently well-separated classes may still produce acceptableresults with a sample size of less than 300 [9].Measures of Help-Seeking Mechanisms and Help-Seeking IntentionFive mental health help-seeking mechanisms (attitude, perceived norm injunctive, perceived normdescriptive, self-efficacy, and perceived control) were assessed in