of a physical prototypehas been shown to improve basic engineering skills, viz. spatial visualization, and increasestudent interest and retention in the discipline. FYE courses are frequently taught in large-enrollment settings, which adds logistical complexity to supplying and supervising hands-onprototyping across a large number of students. Lastly, engineering design challenges must bethoughtfully scaffolded in FYE courses to help novice students navigate complex, longer-termprojects in a team-based setting. Prior work by our group and others [Authors 2018, 2019,citation redacted for review] have shown unequal distribution of tasks on team-based projects,caused in part by differences in self-efficacy and prior experiences. This effect can
(Evaluation).” 2017 ASEE Annual Conference & Exposition Proceedings, doi:10.18260/1-2--28122.[12] Blotnicky, Karen A., et al. “A Study of the Correlation between STEM Career Knowledge, Mathematics Self-Efficacy, Career Interests, and Career Activities on the Likelihood of Pursuing a STEM Career among Middle School Students.” International Journal of STEM Education, vol. 5, no. 1, 2018, doi:10.1186/s40594-018-0118-3.[13] Prima, E C, et al. “STEM Learning on Electricity Using Arduino-Phet Based Experiment to Improve 8th Grade Students’ STEM Literacy.” Journal of Physics: Conference Series, vol. 1013, 2018, p. 012030., doi:10.1088/1742-6596/1013/1/012030.[14] Herger, Lorraine M., and Mercy Bodarky. “Engaging
eliminating the time and cost of travel, this project will enable populations thatmight otherwise be limited in attendance such as professional-track faculty, teaching focused faculty,community college faculty, adjunct faculty.IntroductionThe Skillful Learning Institute (SLI) is preparing a virtual short course experience for 25-30 engineeringeducators to expand the explicit engagement of engineering students in their metacognitive development,which is currently lacking. Metacognition is instrumental in being able to independently assess and directone’s learning - a lifelong skill to propel ongoing growth and development. As such, metacognition isimportant for engineers because it empowers them (i.e., builds their agency and self-efficacy) to
, vol. 103, no. 1, pp. 206–222, 2011, doi: 10.1037/a0020743.[15] M. Syed et al., “The Role of Self-Efficacy and Identity in Mediating the Effects of STEM Support Experiences.” PsyArXiv, Oct. 11, 2018. doi: 10.31234/osf.io/ctr8d.[16] J. Lave, “Situating learning in communities of practice.,” in Perspectives on socially shared cognition., L. B. Resnick, J. M. Levine, and S. D. Teasley, Eds. Washington: American Psychological Association, 1991, pp. 63–82. doi: 10.1037/10096-003.[17] A. Sfard and A. Prusak, “Telling Identities: In Search of an Analytic Tool for Investigating Learning as a Culturally Shaped Activity,” Educational Researcher, vol. 34, no. 4, pp. 14–22, May 2005, doi: 10.3102/0013189X034004014.[18] E. D. Tate
capacity to be good at it. Grades bothimplicitly and explicitly signal to students whether they belong within a course or major inaddition to dictating their ability to progress in their career-of-choice. Paradoxically, grades maydetermine whether students can participate in meaningful academic and extracurricularopportunities, high-impact practices that are usually associated with better student academic andcareer outcomes due to their tendency to increase feelings of belonging and self-efficacy[43]–[45].2.3. Grades Reflect Situational FactorsLastly, a growing body of evidence suggests that grades may be best described as a reflection ofa students’ circumstances, the time and resources they currently or historically have had todevote to their
students;the positive results of internships may even be contingent on certain qualities of the experience.For example, Raelin et al 2014 showed that the increase in student self-efficacy in internshipsdepends on students feeling as though they have made an impact on their organization, had theopportunity to work in teams, and were able to apply knowledge from their majors [21].Informal evaluation and inflexibility in internships may form a barrier to student learning goals,and students are not always fully prepared for their internships [16], [22]. This is particularly aproblem since internships may be formally integrated into curricula or even take the place ofcapstone projects [23], [24].Yet despite these difficulties, internships enjoy
interest, but they are still severely underrepresented in the field of engineering. Priorliterature demonstrated that various factors contribute to students’ engineering career interests,such as self-efficacy and social support. Previous research also explained that students’ earlyengineering interest was the most influential predictor of their engineering major and careerchoice. Therefore, it is necessary to examine students’ engineering career interest trajectoriesprior to college to better understand how students develop or hinder their interest in anengineering career. This study answers the following research question: “Which social agentsand what communicative messages influence female students’ intentions to choose engineeringas a career at
during her doctoral studies, but also helped to remind her of her self-efficacy as astudent. She explained that conversations with her counselor helped her to realize herconfidence in her abilities, as well as recognize that her self-worth is not determined by theacquisition of the doctorate degree. With this insight from her counselor, Brandi (CTC) wasable to approach graduate school stressors with a clearer mind and continue on with thecompletion of her degree. The ways in which counseling helped three of the participants to make persistencerelated decisions is another testament to its usefulness amongst graduate WOC in STEM.Although women in STEM graduate programs are more likely to have experiences withinthat environment that threaten
students stillhave access to help if they need it. Logistics of group work in an online class will need to becarefully considered using video conferencing software.References[1] M. Holdhusen. “A “flipped” statics classroom,” presented at the 122nd ASEE Annual Conference and Exposition, Seattle, WA, June 14-17, 2015. Paper ID #12162.[2] M. Radu. “Applying the Flipped Classroom Pedagogy in a Digital Design Course,” presented at the 126th ASEE Annual Conference and Exposition, Tampa, FL, June 15-19, 2019. Paper ID #25080.[3] H. Ozyurt and O. Ozyurt. “Analyzing the effects of adapted flipped classroom approach on computer programming success, attitude toward programming, and programming self- efficacy.” Comput
six broad factors drive students to leave engineering: classroom and academicclimate, grades and conceptual understanding, self-efficacy and self-confidence, high schoolpreparation, interest and career goals, and race and gender. They also noted that studies suggestthat retention can be increased by addressing one or more of these factors [3].In order to address the factors that persistently cause so many students to leave engineering, andto develop a lower-division curriculum that will engage and retain Electrical Engineering majors,particularly those from underrepresented groups, California State University San Marcos, proposesto implement this study to improve retention. This paper will address two of the retention issuesthat Geisinger and
. However, the COVID-19 protocolsimpacted the implementation of these lessons in a VR environment. The lessons were thereforeimplemented such that students could experience them on their computer screens at any time andfrom anywhere. The software platform allowed interaction with the 3D environment usingmouse/cursor controls. The methodology of the development of a VR lesson and links to the VRlessons are included in the paper. Attitude surveys were administered to students before and afterthe implementation of these interactive lessons. Results from these surveys are shared. Thispaper is based on an exploratory project funded by the NSF HBCU Target Infusion Projectsprogram.IntroductionLow self-efficacy associated with challenges in understanding
engineering classes. Institutions might also discover theneed for introductory computational thinking courses that previously were not included in thecurriculum.ECTD results will also allow instructors to understand how their student cohorts function acrossthe broad areas of computational thinking. By using the results, the instructors can focusclassroom and assessment activities to help students mature computational thinking factors thatare less developed. The long-term impact would be classroom instruction that helps increasestudent self-efficacy and improve student enculturation into the engineering profession. ReferencesCattell, R. B. (1966). The scree test for the number of factors. Multivariate
pandemic potentially impacted the results ofthis survey. It is also possible that an established survey on self-efficacy in technical writing forengineering students has already been developed. Using a validated survey could provide morethorough and nuanced results than those obtained in this research.It is also important to note that faculty advising practices may need to be adjusted, to furtherencourage sophomore students to enroll in the ENGR 291 Experimental Design and TechnicalWriting course as sophomores, rather than waiting until they are upperclassmen. While increasinga student’s comfort with technical writing is a desirable outcome, increasing their technicalcommunication skills is the primary objective. Faculty should reinforce the
of our PD program in terms of the design of our courses and Saturday workshopsbased on feedback from the teachers. There will also be efforts in facilitating and sustaining acommunity of practice for the teachers.AcknowledgementsThe authors would also like to acknowledge the other collaborators on the project and teachingassistants and instructors of the two summer courses and the Saturday workshops. This workwas supported by the National Science Foundation under grant no. 1837476.ReferencesPeteranetz, Markeya, Shiyuan Wang, Duane Shell, Abraham E. Flanigan, and Leen-Kiat Soh. 2018. “Examining the Impact of Computational Creativity Exercises on College Computer Science Students’ Learning, Achievement, Self-Efficacy, and Creativity
students assigned no mentor. A survey was sent out at threepoints throughout the year to monitor the students’ experiences and a fourth survey was sent oneyear after the program ended. The survey measured self-efficacy, feelings of threat andchallenge, and career goals. College transcripts also were collected to monitor students gradesand retention information. The study concluded same-gender peer mentoring increasesconfidence, motivation, and retention for women in engineering. Pairing a female student with afemale mentor had a greater impact with 100% retention than pairing a female student with amale mentor with 82% retention. However, there was no indication that the mentoring programincreased average GPA’s. Although there is limited
. ‘Non-persisting’ students are those leaving engineering because of the academic climate, grades, self-efficacy, high school preparation, career goals, and gender or race [20]. Moreover, students leave STEM because of a lack of belonging [3], [24], “chilly” climate [25], microaggressions [26], conflicting identities [26]–[28], and not identifying with the field [29]–[31]. This literature on student perceptions highlights how their decisions are influenced by how they see themselves as being capable. This suggests how students’ perceptions affect their decisions which can be influenced by several cognitive and non-cognitive factors. Therefore, students’ observations in school inform the actions they take, and what they see as
second-year STEM courses. Theworkshop is designed to promote active learning and strategies to reduce student resistance toactive learning [16]. We developed student and instructor surveys to assess the workshops’ impact. Thestudent survey focuses on instructors’ use of active learning, instructors’ use of the associatedstrategies to reduce student resistance, and students’ responses to active learning [17]. Theinstructor survey measures instructors’ intentions and motivation (value and self-efficacy) forusing active learning as well as strategies to reduce student resistance to active learning [18]. We assessed three pilot offerings of the workshop by measuring instructors’ attitudestoward active learning before and after
Learning Questionnaire (MSLQ) is a self-report instrumentdesigned to assess college students’ motivational orientation and their use of different learningstrategies for a college course. According to [14], the instrument is a measure of student self-efficacy, intrinsic value, test anxiety, self-regulation, and use of learning strategies. Constructsfrom this survey center on measures of the types of learning strategies and academic motivationused by college students. This instrument uses 44-items with a 7-point likert-type scale withstatements focused on student motivation, cognitive strategy use, metacognitive strategy use, andmanagement of effort. Additionally, a number of researchers have also utilized the MSLQ toexamine whether there is a
students interests towards pursuing a graduate degree.The physical and psychological impacts of student involvement, such as attending social events,giving oral presentations, being part of a group, club, organization, etc., have been studied widelyby scholars [31][32][33][34]. They have shown a major role in students’ self-efficacy andpersistence and positively impact students’ academic autonomy, career, and lifestyle planning[32][35][36][37]. “Academic involvement, involvement with faculty, and peer involvement” arethe three most powerful involvement forms according to the literature [31]. Likewise, learning ina group is an effective practice in promoting greater academic achievement, promising attitudestoward learning, and increasing
Puentedura’s SAMR (Substitution - Augmentation -Modification - Redefinition) framework [1], examining the results of primary research withinstructors and students experiencing these tools and kits, in a Winter 2021 course in theStanford University department of Aeronautical and Astronautical Engineering. The instructorswho developed the course were interviewed using a structured set of questions, and the resultsanalysed through qualitative coding of the transcribed interview content to find common themes.Students studying the course were invited to participate in a pre-and post- course surveydesigned to evaluate and describe their self-efficacy and experiences with the course’s tools andkits. We note that the supplied kits were just one piece of
students’ digital literacies and assessment. Recently, Dr. Hsu has received a seed grant at UML to investigate how undergradu- ate engineering students’ digital inequalities and self-directed learning characteristics (e.g., self-efficacy) affect their learning outcomes in a virtual laboratory environment during the COVID-19 pandemic. Dr. Hsu’s research interests include advanced quantitative design and analysis and their applications in STEM education, large-scale assessment data (e.g., PISA), and engineering students’ perception of faculty en- couragement and mentoring.Dr. Yanfen Li, University of Massachusetts Lowell Yanfen Li is an Assistant Teaching Professor at the University of Massachusetts Lowell. She received
permission to work with PhD Balance and their posts for this project. Werecognize her support and assistance in moving this project forward.Bibliography[1] Nature Editorials, “Being a PhD student shouldn’t be bad for your health,” Nature, vol. 569, no. 7756, pp. 307–307, May 2019.[2] K. Levecque, F. Anseel, A. De Beuckelaer, J. Van der Heyden, and L. Gisle, “Work organization and mental health problems in PhD students,” Res. Policy, vol. 46, no. 4, pp. 868–879, May 2017.[3] C. Liu et al., “Prevalence and associated factors of depression and anxiety among doctoral students: the mediating effect of mentoring relationships on the association between research self-efficacy and depression/anxiety,” Psychol. Res
Employment Counseling, vol. 39, pp. 12–21, 2002.[7] K. J. Downing, “Self-efficacy and metacognitive development,” International Journal of Learning, vol. 16, no. 4, pp. 185–200, 2009.[8] E. Seymour and N. M. Hewitt, Talking about leaving: why undergraduates leave the sciences. Boulder, CO: Westview Press, 1997.[9] M. W. Ohland, S. D. Sheppard, G. Lichtenstein, O. Eris, D. Chachra, and R. A. Layton, “Persistence, engagement and migration into engineering programs,” Journal of Engineering Education, vol. 97, no. 3, pp. 259–278, 2008.[10] P. A. Gore, “Academic self-efficacy as a predictor of college outcomes: two incremental validity studies,” Journal of Career Assessment, vol. 14, pp. 92–115, 2006.[11] J. B. Biggs, “The role of
affects students in these majors negatively.Instructor characteristics such warmth and encouragement are associated with a strong sense ofbelonging [30] and these are typically absent in the traditional teaching methods employed inengineering [7]. Additionally, sense of belonging is directly related to a student's self-efficacy tosucceed and their value of their coursework [30]. In return this lack of value in their curriculumcan support the perception of a poor campus climate as they feel as they are not supported tosucceed.In terms of the elements related to diversity and inclusion, engineering students showed a higherknowledge of campus programs, policies, and efforts than the other two groups; however, theyhad a significantly lower levels of
biomedicalengineering. After cleaning up with attention checks, we have in total 158 Japanese engineeringstudents (7 female, 149 male, mean age = 19.96) and 209 American engineering students (80female, 128 male, 1 other, mean age = 24.3) who have completed the survey. Amongst theAmerican participants were White American: 56%, African American: 10%, Latino American:14% , Asian American: 27%, Native Americans: 2 and Pacific Islander: 1. Based on a singlesubjective socioeconomic status measure (0 - worst off to 10 - best off), we retrieved the subjectivesocioeconomic status, which was comparable between Japanese participants (mean = 6.39, SD =1.94) and American participants (mean = 6.35, SD = 1.72). The participants took the survey in2020 after the COVID-19
for analysis. All results were cross-sectional.InstrumentsThe instrument used to collect data for this study was a survey which asked students to reporttheir perceptions of various items related to peer support, engagement, belonging, peerharassment, task value, self-efficacy, TA and faculty support, and TA and faculty interactions aswell as multiple demographic items. The survey also included five short answer questions whichasked students to identify their primary expectations for faculty support (one question), TAsupport (one question), and peer support (three questions). Two of these short answer questionswere included in this analysis.The four Likert scale items used to measure peer support (Table 2) included elements ofinformational
arcade game [19]. Fig. 12. Pictures of Student Projects or Presentations for Final DayFor professional development, students were polled in the areas covered by the program beforeand after the program on a Likert scale to evaluate students’ self-efficacy. The results indicatesignificant improvement for various abilities such as: resume building, networking,communication, usage of campus resources, awareness of career paths, academic capabilities,and self-awareness in their areas of improvement to remain competitive for jobs.The number of weeks can be tuned by organizers depending on the pace, content, studentcommitment, school system, etc.Students participating in the virtual program were eager to explore both technical andprofessional
with COVID-19 guidelines of BISD. Videoand audio data were collected for the focus groups. Each focus group followed a semi-structuredformat where mentors ask a pre-defined sequence of questions regarding Making andManufacturing, diving deeper into questions based on participants’ responses. We asked threetypes of questions to initiate the discussion on the Making and Manufacturing, along withidentity-focused questions to gauge students’ self-efficacy. Qualitative data analysis wasconducted on transcribed video data and notes. Qualitative coding followed a grounded theoryapproach as employed by Charmaz and Strauss [62]. The coding procedure was conducted by ateam of three coders. After completion of open coding by a single coder, the other 2
is Power Award” [3].Post-event media coverage and following through with opportunities are the primary wayshackathons can create material benefits towards these issues and for participants [3]. Therefore,eliminating single winners can reduce solutionist mindsets and increase self-efficacy for moreparticipants, ideally increasing access to resources to those who may also be impactedstakeholders. Experiential prizes over monetary ones sponsored by corporations, nonprofits, andfoundations can also help further dialogue and offer opportunities such as presenting at aconference that may be inaccessible otherwise [3]. With increased awareness on the topic oftenbeing a large takeaway, it is crucial for hosting institutions with more influence to
material is consistent with their future career (Wigfield, 1994; Wigfield &Eccles, 2000). The interest component is based on how students perceive course topics andinstructional methods, interesting (Hidi & Ann Renninger, 2006; Renninger, Hidi, Krapp, &Renninger, 2014). Further, the success component is formed on expectancy for success(Wigfield, 1994; Wigfield & Eccles, 2000). This component reflects students’ self-efficacy aboutthe coursework (Bandura, 1986). The caring component is based on students believes thatinstructors care about their success and well-being (Noddings, 1992).Motivation can be perceived as a student’s intention and engagement in learning as student’saction (Christenson, Reschly, & Wylie, 2012). In other