higher self-efficacy in using ChatGPT as a learning tool in comparison with othergender identities. Furthermore, Freshmen engineering students tend to have high perceptions onusing ChatGPT as a learning tool, while junior engineering students have the lowest. Finally,freshmen engineering students tend to have high perceptions on ease of accessing ChatGPT, whilesophomore engineering students have the lowest.Keywords: ChatGPT, concerns with ChatGPT, ethical considerationsIntroductionEngineers working in Open Artificial Intelligence (OpenAI) developed the language model ChatGenerative Pre-Trained Transformer (ChatGPT). It's a kind of artificial intelligence (AI) systemthat can produce text responses to a variety of questions and prompts that seem
understanding of its structure and purpose. Below is a detaileddescription of the rubric that has been recontextualized from its original application inmanufacturing to its broader use in inclusive STEM education. The rubric is structured into threeprimary sections—Head, Heart, and Hands—each representing critical facets of the learningexperience and corresponding to cognitive engagement, emotional engagement, and activeparticipation. Our application of the 3H model[1] is rooted Piaget’s constructivist learningtheories[2], Vygotsky’s Zone of Proximal Development[3], brain-based learning like that ofSmilkstein[4], self-efficacy[5], and cultural responsive teaching[6].Head (Cognitive Engagement): This section of the rubric focuses on self-efficacy
make plans to leaveengineering after earning an undergraduate degree 11, there is a need to examine what factorscontribute engineering students’ post-graduate plans using large scale data sets. Such studentsmay help undergraduate engineering programs design interventions to keep engineering studentsin the engineering graduate programs and profession.Students’ Self-assessments of Abilities and Graduate School Plans Most research identifies academic preparedness in mathematics and science at an earlyage as one of the most salient factors influencing engineering student choice of graduate schoolin engineering5. However, Bandura argued that students aspire to careers based on not only theirqualifications but also their self-efficacy in
todemographic characteristics (underrepresented racial/ethnic minority (URM), women, URM women),college experiences (internships/co-ops, having a job, conducting research, and study abroad), andengineering task self-efficacy (ETSE) which is a respondent characteristic that may be targeted ineducational interventions (i.e., outcome indicator for evaluation of impact of an intervention). All ofthese measures were collected on the survey instrument via self-report by student respondents to fixed-choice survey questions.Table 1. Variables compared between students classified as first-generation/low-income based on definitions Demographic Characteristics URM Underrepresented racial/ethnic minority status in response to ‘racial or ethnic
-improvement and personal growth were found to be highly valued. In comparison with extrinsicgoals from the same study, further differences were found between intrinsic and extrinsicmotivation. Other studies have found that student motivation is directly linked to seeing valueand meeting goals and beliefs about the importance of a given task or subject.The value of motivation can be conceptualized through various approaches (e.g., learning vs.performance goals, intrinsic vs. extrinsic orientation, and interests); this motivational componenteffectively concerns students' motives for the completion of a task7. Self-efficacy has a majorrole in student motivation at both intrinsic and extrinsic levels. Students’ perceived self-efficacyinfluences as the
Paper ID #42415Latina Engineering Student Graduate Study Decision Processes—Developmentand Initial Results of a Mixed-Methods InvestigationDr. Bruce Frederick Carroll, University of Florida Dr. Carroll is an Associate Professor of Mechanical and Aerospace Engineering at the University of Florida. He holds an affiliate appointment in Engineering Education. His research interests include engineering identity, self-efficacy, and matriculation of Latin/a/o students to graduate school. He works with survey methods and overlaps with machine learning using quantitative methods and sequential mixed methods approaches.Dr. Janice
success in the major is evident. In 2017, women comprisedapproximately 20% of engineering graduates, up from 18% in 1997, and 15% never entered theengineering workforce. In 2019, women comprised 48% of the workforce, 34% of the STEMworkforce, and only 16% of practicing engineers, a 3% increase from 2009. In an effort to betterunderstand these disparities, this mixed methods research investigated the creative self-efficacy(CSE) of women engineering majors and their beliefs about creativity in relation to livedexperiences and explores the research question: In what ways do undergraduate womenengineering students describe their creativity and how their lived experiences influenced theirdecision to major in engineering? The researchers investigated
affected.Estriegana conducted a study [8] which extended the TAM with the factors of perceivedefficiency, playfulness, and satisfaction. After analyzing the questionnaire results, theyconcluded that each newly introduced factor has a positive influence on the original TAMvariables [8].Salloum and his colleagues [17] performed an in-depth literature review on eLearning TAMextension factors in the last 12 years. The following factors showed up most frequently: systemquality, content quality, information quality, computer self-efficacy, subjective norm, enjoyment,accessibility, and computer playfulness. The pilot study and subsequent questionnaire revealedthat subjective norm has an insignificant impact on both perceived usefulness and perceived easeof use, and
2 6 17 complex systems. The Arduino kit manual was useful for learning 0 1 3 13 8 the kit basics. We received sufficient instruction on using the 0 1 4 9 11 Arduino kit to complete the final project. In the future, the class should continue using the 0 2 7 7 9 Arduino kit. Completing this course has made me well- prepared going into the 0 0 6 12 7 junior-level Mechatronics and Measurement Systems course …Self-efficacy results show some similar
Scholars’ self-efficacy, identity, and sense of belonging, and (iv) to study the impactof cross-disciplinary “engaged-engineering” projects on retention through the end of the 2nd year.Moreover, this program has the potential to benefit society in a variety of ways. It will contributeto the development of a diverse, globally competitive STEM workforce by preparing students forcareers in engineering. The program also contributes to the full participation of women andunderrepresented minorities in engineering by incorporating program features that are known toincrease the retention of these groups in engineering [9]. By measuring and studying the effects ofthe program elements and disseminating results, the research conducted will inform
significant increase in self-efficacy of the participants in the development of STEM education manuscripts. There was a 67%increase in academic publications among graduate students. The dominant theme in the qualitativeinvestigation was the "supportive and collaborative environment." Insufficient time managementpresents a barrier. Additionally, through the writing accountability group structure, there was asignificant increase in trainees’ scholarship productivity. Faculty advisers and administrators canprioritize writing groups as a cost-effective and impactful intervention to enhance academicproductivity. Further research is required to identify the most effective implementation strategies;however, integrating a writing collaboration approach seems
the EDVES, the VESAS, Carberry’sEngineering Design Self-Efficacy Scale, and the STEM-CIS were the primary contributors to itemcontent and wording in the EDVES while Eccles’ Expectancy-Value Theory grounded the attitude-focused items [3-6] [9-10]. Note that the three scales exhibited their own validity and reliabilityby their creators, and subsequently allowed us to ensure EDVES items were created withestablished, high-quality practices in mind. Upon assembling and finalizing all items, theinstrument was reviewed by two engineering faculty members and a psychometrician. Additionalrevision of the instrument was conducted upon receiving their feedback and gave rise to the currentform of the EDVES (see Appendix 1) where items measure expectancy
than those for science andengineering—three of the five students indicated a positive change on items pertaining to aninterest in mathematics on at least three survey items, and two students indicated a positivechange in interest toward subject areas and jobs associated with mathematics. There are severalfactors which may have contributed to more positive responses to mathematics questions. First,the questions contained in the “Student Attitudes” section of the survey were designed tomeasure self-efficacy, interest, and usefulness of a particular area of STEM toward their futures.In the mathematics section, all eight survey items assessed self-efficacy. In the science section,five survey items assessed self-efficacy, and three survey items
accreditation cycle. Baltimore, MD: ABET. 11. Coelho, G.L.D.H., Hanel, P.H.P, & Wolf, L.J. (2018). The Very Efficient Assessment of Need for Cognition: Developing a Six-Item Version. Assessment, online first, 1-16. 12. Cropley, D. H. (2015). Creativity in Engineering: Novel solutions to complex problems, San Diego, CA: Academic Press. 13. Cropley, D. H. and Cropley, A. J. (2016). Promoting creativity through assessment: A formative CAA tool for teachers, Educational Technology Magazine, 56:6, pp. 17-24 14. Karwowski, Maciej & Lebuda, Izabela & Wisniewska, Ewa. (2018). Measuring Creative Self-efficacy and Creative Personal Identity. The Journal of Creativity and Problem Solving. 28. 45-57. 15
,2014;Century,Cassata,Freeman,&Rudnick,2012).Inparticular,Centuryetal.defineanarrayofindividual,organizational,andcontextualfactorsthatmayinfluencewhetherindividualusers(e.g.teachers)decidetoadoptandcontinuetoutilizeanintervention.Thesefactorsincludecharacteristicsoftheinnovation,suchasitscomplexity,duration,andscope;characteristicsofindividualuserssuchasmotivation,self-efficacy,attitudestowardtheinnovationandusersperceptionsoftheeaseofusingtheinnovation;andorganizationalcharacteristicsattheschoollevelincludingsharedbeliefsandvalues,resources,andinstructionalleadership.AnindepthexplorationofallofthefactorsinfluencingSTEAMTrunkutilizationisbeyondthescopeofthispaper;however
diminishment of learning core engineeringconcepts.17 While the case study experience did not significantly change entrepreneurial careerintentions it did grow students’ perceived entrepreneurial self-efficacy (as measured byconfidence in business skills), which can be a precursor to changing career intent.4. Research HypothesesThe intent of this curriculum is to introduce entrepreneurial concepts in the context of entry-levelengineering curriculum in the hope that it would have a positive impact on the students’entrepreneurial career intent. Therefore, our research hypothesis is: The incorporation of entrepreneurial content into core engineering curriculum will have a positive impact on engineer students’ entrepreneurial
sought to measure the same thing, the studentsunderstood the questions differently. Finally, the survey and interview results suggest that theCES|CS program is having a positive impact on identity development.Related WorkThis work builds on a body of literature focused on student persistence and success as well asdisciplinary identity.Self-efficacy, Retention, and Academic SupportPerez et al. [3] discuss the impact that professional identity has on retaining students in STEMfields in college. Graham et al. [4] introduced a “persistence framework” that underscores theconnection between persistence (especially in STEM fields) with motivation and confidence(self-efficacy [5]). They discuss three factors that form the persistence framework: (i
Model to increased student motivation and self-efficacy, none has attempted to fullyquantify the impact of the associated restructuring of the curriculum. As a result, the currentpaper describes a detailed analysis of the Wright State Model using the Curricular Analyticsplatform (https://curricularanalytics.org/), which provides new and significant insight into therelative roles of curricular complexity and centrality on the success of the Wright State Model.In particular, results suggest that while the Wright State Model has had only a negligible impacton the overall complexity of the engineering curriculum, it has measurably reduced thecomplexity and dramatically reduced the centrality of the required calculus sequence. Moreover,the relative
post empathy surveys atthe beginning and at the end of the semester. The pre/post-tests consisted of three empathysubscales that served as proxies to assess the cognitive, affective, and behavioral components ofempathy. Two subscales (perspective taking and empathic concern) were taken from theInterpersonal Reactivity Index (IRI) [15] and one subscale (interpersonal self-efficacy) was takenfrom Hess et al. [16]. The full survey instrument is included as an appendix.The IRI is a tool that measures empathy using a multi-dimensional approach [15] and waschosen because it is the standardized tool that is widely used and accepted among scholars whomeasure empathy. Empathic concern assesses "other-oriented" feelings of sympathy and concernfor others
sense of ownership, competency and belonging that allows students to growfurther as they enter new research experiences. References1. Byars-Winston, A.M., Branchaw, J., Pfund, C., Leverett, P., and Newton, J., 2015, —”Culturally diverse undergraduate researchers’ academic outcomes and perceptions of their research mentoring relationships.” International Journal of Science Education, Vol. 37, No. 15, pp. 2533-2554.2. Carpi, A., Ronan, D. M., Falconer, H. M., & Lents, N. H., 2017, —”Cultivating minority scientists: Undergraduate research increases self-efficacy and career ambitions for underrepresented students in STEM,” Journal of Research in Science Teaching, Vol. 54, No. 2, pp
unlabeled axes. Aquestion form of this inquiry could be “Do students interpret and recognize characteristics ofpotentially misleading bar and line graph axes?” The methods employed included havingsubjects draw conclusions based on complete or incomplete bar and line graphs and provide theconfidence in their answer. Sub-questions included “Do students accurately measure theirconfidence and self-efficacy regarding their ability to interpret and recognize characteristics ofpotentially misleading bar and line graph axes?” and “What, if any, differences exist betweenstudents from Maine and the general population regarding ability to interpret and recognizecharacteristics of potentially misleading bar and line graph axes?”Study of factors influencing
theirstatus in engineering.Course data is used to assess academic performance and institutional data is used to tracepersistence. Enrollment data is collected to track students in the upper-level engineering coursesequence as well as major declaration compared to non-PLTL groups. Focus groups, peer leaderjournals, classroom observations, and faculty surveys are used to assess commitment toengineering and engineering identity. Non-cognitive factors that have a promising effect oncommitment such as motivation, self-efficacy, and confidence are measured using pre- and post-survey instruments [7].Peer Leader TrainingThe first step in this work was the development of a 10-hour self-paced peer leader trainingcourse. This course consists of three modules
Institutional Review Board at each university, with anapplication package including the survey instruments and informed consent letters for teachersand students. In addition to quantitative measures of participation and diversity, the assessmentincludes attitudinal measures of problem-solving and self-efficacy.8,9,10 Also, qualitativereflections completed by teachers, Young Scholars, and middle school students are collectedonline at the completion of each activity. Mentors and ERC precollege staff perform Page 15.969.6longitudinal follow-up electronically. This follow-up itself may have a positive effect onprecollege participants, helping them see
Implications for STEM Education Researchers and Faculty," Journal of Chemical Education, vol. 93, pp. 1686-1702, 2016.[8] S. B. Wilson and P. Varma-Nelson, "Implementing Peer-Led Team Learning and Cyber Peer-Led Learning in an Organic Chemistry Course," Journal of College Science Teaching, vol. 50, pp. 44-50, 2021.[9] J. E. Klobas, S. Renzi and M. L. Nigrelli, "A scale for the measurement of self-efficacy for learning (SEL) at univeristy," Bocconi University, 2007.[10] K. Wilson, K. Luthi, D. Harvie and M. Surrency, "Strategies for Engagement of Non- Traditional Students in Engineering-Related courses," in 16th Annual Mentoring Conference, Albuquerque, NM, 2023.[11] K. Luthi, D. Harvie, K. Wilson and M. Surrency, "Peer support
engineering confidence, but this percentage reached 50% when the camp was male-only (figure 1). Figure 1 Engineering Self-efficacy Self Reports* n for female only = 35 participants, n for male only = 8 participants, n for co-ed = 7 female, 8 male studentsThe final camp session was male-only. STEPS student responses from this session compared tothe mixed-gender session indicates that the absence of female campers led to male self-efficacyincrease of 100%. The study was not designed to measure the effect of female participation onmale student self-efficacy. And while the data sample is small, this is an interesting observation.While having
engineering professionals.Factor analysis of survey items resulted in five analytical constructs: mathematics self-efficacy,design self-efficacy, engineering interest, communication skill, and creativity. Comparisonsbetween students enrolled in PBL and traditional versions of introductory civil engineering arereported elsewhere (Marshall et al., 2017), and survey results are used here primarily to supportfindings from interview data. Epistemological theorists and researchers note the closerelationship between identity and epistemology (Boaler & Greeno, 2000; Danielak, Gupta, &Elby, 2014; Hofer & Pintrich, 1997), and factors of the Engineering Attitude Survey pertaining tostudents’ identities and perception of their own competences within
elements of affect. For example, feelings can often beconsidered to be measured by a students’ physiological state [20]; and one contributor to self-efficacy (an aspect of a student’s affect) is physiological state [5]. If a student has an upsetstomach or dizziness – in other words, symptoms of anxiety – they may experience reduced self-efficacy. Whereas if they experience an elevated heart rate or increased blood rush to the head,symptoms that can be associated with being excited, they may experience an increase in self-efficacy. In other words, a student’s most basic feelings will both be influenced by and, in turn,influence, their self-efficacy.Therefore, while it is recognized that it is important to study how different elements of
measure will be used to explain retention rates and not as an outcomemeasure. Table 6: Engineering Toy FUN-damentals Student Efficacy (Fall 2009-Spring 2010). Pre-Survey Post-Survey Engineering Efficacy Scale α M SD α M SD t(138) 1 Communication Self-Efficacy .86 7.62 1.49 .83 8.02 1.25 -3.24** 2 Coping Self-Efficacy .76 4.83 .78 .71 4.89 .70 -1.14 Engineering Career Success .85 5.06 .67 .88 5.13 .67 -1.50 Expectations2
, students completed consent forms,academic and health histories (necessary for risk-management purposes, as EPICS students visitthe university), and provided parental contact information before completing a series of measures(see Table 1). The measures were aimed at capturing students’ attitudes and behaviors towardengineering. The main measures of interest include Engineering Identity (see Table 2) and DoingEngineering (see Table 3) designed by Terence J. Tracey, a counseling psychologist andTirupalavanam G. Ganesh, an engineering education researcher [17]. These measures weredesigned based on James Marcia’s theory [18], [19] and building upon Betz and Hackett’s [20]work in studying self-efficacy. Based on Marcia’s theory [18], [19], that identity
supports students in building self-efficacy in their abilitiesas electricity and electronics students. 1IntroductionActive learning is a teaching pedagogy which has gained traction in higher education as aneffective method for engaging learners in the process of attaining new knowledge [1]. It movesthe student from a passive role in hearing and absorbing information, to an active participant inconstructing new knowledge, typically through hands-on exercises. Active learning is an umbrellaterm used to describe many different types of practices, including role playing activities, pairprogramming, project-based learning, and many others [2].Many introductory electricity and electronics courses are ripe