of Missouri. His main research interests are program evaluation and education policy. c American Society for Engineering Education, 2017 The Role of High School Math and Science Course Access in Student College Engineering Major Choice and Degree AttainmentI. IntroductionPrevious research has documented numerous factors that impede the progress of women andunderrepresented minorities in engineering fields, which can be broadly categorized into sixfactors: “classroom and academic climate, grades and conceptual understanding, self-efficacy andself-confidence, high school preparation, interest and career goals, and race and gender” (Geisingerand Raman, 2013). While high school
Control refers to a participant’s perception that they have the ability toparticipate and succeed in entrepreneurship if they so choose, or their self-efficacy with regard toentrepreneurship (Carr & Sequeira, 2007). We measured Perceived Behavioral Control usingthree questions from Ajzen (2002) as cited in Solesvik (2013) (“If I wanted to, I could easilybecome an entrepreneur”, “As an entrepreneur I would have sufficient control over mybusiness”, “It is entirely up to me whether or not I become an entrepreneur”). Question “PBC3”from Solesvik (2013) was left out per Solesvik (2013). We believe that Perceived BehavioralControl is an important topic for research in this field, connected to self-efficacy, but it appearedthat many students
their work, andemphasizes non-confrontational feedback processes in which the presenter chooses what kind ofcritique they would like to hear 36. In terms of physical space, the chairs and tables would be setup by instructor and GTAs when students arrived, then students would be able to restructurespace according to the activity planned for the day. As in the first introductory course, studentsoften worked with their groups using supplies from the art cabinet at their tables and on thewhiteboards. Although we did not employ Gerber’s survey to measure Innovation Self-Efficacy(ISE)12, in many ways the students dispositions reflect signs of low self-efficacy. However, theISE indicators reflect the types of activities taught in the class, and
belongingness score.The growth mindset scales were obtained from the Stanford University Project on EducationResearch that Scales (PERTS) website22. It is comprised of three questions which proberespondents’ level of agreement to the fixed mindset. We implemented a 5-point Likert scale (1= strongly agree to 5 = strongly disagree). Responses to the items were found to be internallyreliable (Cronbach’s α = 0.83), and the responses across the three items were averaged to form asingle growth mindset score.Scales measuring happiness, self-perceived health, and self-efficacy were also included from thispaper. While not the immediate focus of this study, they obscured the objective of the study toparticipants.Academic performance measures were collected in
-richprograms in their classrooms is a lack of both self-efficacy and a support network to help themprepare and teach such lessons. Supporting conclusions can be found in the literature,particularly highlighting the pitfalls of teachers having only a superficial understanding of theEDP5. Working through an EDP with proper guidance gives teachers the tools and confidence topush their students outside of the comfort zone of concrete answers and encourages creativityand innovative thinking5, 6.For these reasons, every participant in this program is immediately immersed in the EDP so thatthey can become comfortable playing the role of an engineer. One of the foundational conceptsof real-world Engineering is that there is not one right solution to a problem
participation with content-specific learning10. This belief maybe more prevalent among instructors with lower self-efficacy for teaching technical andcomputational content, as will be illustrated from a modeling perspective later in this paper.In this paper, we present causal loop diagrams that serve as explanatory models for the existenceof virtuous and vicious student engagement cycles11. These models serve as a guide forproposing professional development and implementation improvements for the future.Background: Modeling and Systems ThinkingSchools are complex systems with thousands of variables, feedback loops, social networks, andintelligent agents. They are difficult to predict and even more difficult to manipulate. It isdifficult to measure the
procrastinators’distance learning outcomes. Computers & Education, 49, 2, 414–422.Simonson, M., Smaldino, S., Albright, M., & Zvacek, S. (2009). Teaching and learning ata distance: Foundations of distance education (4th ed.). Boston, MA: Pearson.Bates, R. & Khasawneh, S. (2007). Self-efficacy and college students’ perceptions anduse of online learning systems. Computers in Human Behavior, 23, 1, 175–191.Chen, A., Darst, P. W. & Pangrazi, R. P. (1999). What constitutes situational interest?Validating aconstruct in physical education. Measurement in Physical Education andExercise Science, 3, 3, 157–180.Guzley, R. M., Avanzino, S. & Bor, A. (2001). Simulated computer-mediated/video-interactive distance learning: a test of motivation, interaction
purpose is for the research team to obtain feedback on the modification process prior toimplementing the measure to approximately 1800 students across 11 middle schools in duringthe third and final year of the larger study. The purpose of the ECA-M8 will be used as oneindicator of intervention impact on student learning along with a performance assessment ofunderstanding of engineering design, forces and motion concept assessment, and assessments ofmotivational outcomes including interest and self-efficacy in STEM. Another purpose of theECA-M8 is for educators to use students’ scores to inform instructional planning, as well asgrowth in understanding.While there are established assessments for students’ motivation in STEM5,6 and
components: a) assessing student self-efficacy, i.e., their perception of theirown ability to perform certain tasks, and b) perceived effectiveness of instructional techniquesused in the class. Survey questions include: A) Self-efficacy (“I am confident that …”) Scale: Strongly disagree (1), Disagree (2), Neutral (3), Agree (4), Strongly Agree (5) 1. I can program and use MATLAB to solve problems 2. I can use MATLAB to control LabJack 3. I can solve DC electric circuits problems 4. I can solve general engineering problems 5. I can write good quality reports B) Effectiveness of instructional techniques Scale: Complete waste of time (1), Not helpful (2), Neutral (3), Somewhat helpful (4), Very
“weed out” course. In the larger project of which thisstudy is a part, we utilize the constructs of engineering identity and self-efficacy as proxies toexamine future attrition. In this study, we focus on fine-tuning our instructional interventions toincrease students’ sense of community. Results from this initial iteration reveal usefuldifferences in the role instructors and students play in the course as well as the impact thosechanges have on students’ sense of community. Over time, we believe an increase in a sense ofcommunity among the students will have a positive impact on both their engineering identity andself-efficacy, and thus their continuation as engineering majors, as they continue in theirprograms.References[1] Blickenstaff
Task Value (TV) 4, 10, 17, 23, 26, 27Expectancy Components Control of Learning Beliefs (CLB) 2, 9, 18, 25 Self-Efficacy for Learning and Performance (SE) 5, 6, 12, 15, 20, 21, 29, 311 There are 31 questions within the motivation scale of the MSLQ.2.4. Data CollectionWe collected pre- and post-test surveys during the spring 2016 semester. The pre- and post-testsurveys were both administered through Qualtrics (Provo, UT), with the pre-test collectionoccurring during week eight of the semester, and the post-test collection occurring during week16. This pre- vs. post-test design allowed us to measure changes in students’ motivationorientation relative to
women from choosing STEMmajors and careers take shape early in a girl’s life. These factors include poor science identity,low self-efficacy in math, gender stereotypes and stereotype threat, lack of role models,misalignment between perception of STEM careers and personal values, and low interest inSTEM subjects. For example, VanLeuvan (2004) found that girls’ interest in math and sciencedropped by about 15% between middle and high school. Moreover, low confidence and self-efficacy in STEM subjects form as early as grade six (Heaverlo et al., 2013). Early interventionto mitigate negative influences can ultimately have an effect on a women’s choice to enterSTEM (Young, Ortiz, & Young 2017; Bieri Buschor, Berweber, Keck Frei, & Kappler
Affective/Non- Measure of student experience, interest, self-efficacy, or similar, typically Cognitive using a survey Achievement or Measure of factual, conceptual knowledge or of practices, including Learning standardized examsQuantitative methods Disaggregation Compares sub groups (male/female; White/nonwhite students, etc.) Control or Compares an experiential or intervention group top a control or Compare comparison group Pre Includes a pre-test Post Includes a post-testDelayed Post test Includes a delayed post-testQualitative Methods Details how analysis was done, such as by coding data or interaction Analysis analysis
[Portions of this paper in the review of the literature and research design have been reprintedfrom the 2016 ASEE Poster Session Papers, which provide preliminary material for the reader.]1There is a growing national concern over decreases in science achievement in middle and highschool. Paired with it are challenges associated with workforce declines in STEM-relatedcareers. In response, in a recent PCAST report2 recommendations for recruitment of scienceand engineering students and corresponding recommendations for increased attention to strategicSTEM-related instruction and teacher professional development have emerged. A significantchallenge facing urban science teachers is a low sense of self-efficacy in teaching STEMcontent.3 Additionally, a
. Specifically, there seems tobe a misalignment between teachers’ lessons and what the STIR is intended to measure, namely, afull scientific investigation. Furthermore, our observations also highlighted the challenge that highschool STEM teachers’ face in integrating nanotechnology into their classroom. While each of theclassroom lessons that we observed included a nano-component, the teacher’s primary focuscorresponded with something students were expected to know per state mandates and with respectto state tests. More time spent on nanotechnology, especially a full nano-lab would, we think,detract from what the teachers were expected to cover.Third, we did not find any changes in students’ STEM self-efficacy as measured by the S-STEMconstructs
like-minded peers, female college students, faculty, and practicing engineers in order to provide acritical mass of role models and begin developing a professional support network - both of whichhave been shown to improve retention and self-efficacy of women in STEM fields.The university assesses learning outcomes via a pre-test and post-test covering topics withinvarious engineering disciplines. Participants are asked to provide both qualitative andquantitative feedback regarding the camp experience in an exit survey on the final day of camp.All assessment is completed anonymously; however, archival data are not available for eachyear. This paper highlights qualitative and quantitative findings from the past decade.Introduction and
,students followed a set of directions to build their heat engines provided by the instructor; next,students redesigned their heat engines with the goal of increasing the device’s efficiency. At theend of the class, students completed some questions to help them reflect on the activity and itsconnection to efficiency, the design process, and the operation of power plants, and the instructorled a brief discussion during which participant groups shared their results.Analysis and Discussion Several assessment methods were implemented to determine the effectiveness of the E-GIRLprogram with respect to the students’ technical skill, self-efficacy, perceptions of engineering,and interest in engineering. Pre- and post-surveys were conducted asking
Citizens Engineering Students preparedness for working globally Evaluation of learning programsIt should be noted that developing assessment and evaluation methods in this area is inherently complex,given the list of areas to be investigated, including ethics, social norms, global difference along withstudents own biases based on culture, racial and ethnic position, socio-economic status etc. [12] Thereare also research philosophy and methodological issues to consider, most qualitative measures of globalpreparedness or awareness are by nature, self-efficacy which may call into question the level of ability ofstudents to self-assess given their respective levels of experience. As an example, a recent study into theEWB-USA chapter at
faculty and administrators will require a cognizant understanding ofwho these students are, -- the challenges they face, how they handle stress, their levels of self-efficacy, and their development of an engineering identity, -- if they are to successfully designand implement programs specifically targeted at this demographic.The semistructure interview and design protocols have resulted in large amounts of datacollected. Work continues to explore the intricacies of who these students are. The aim is to havelarge enough numbers that results can be generalized and broadly applied. Future work willdwell into adult learners’ level of preparedness and their student-faculty relationship.AcknowledgementsThis material is based upon work supported by the
gala after the class whichseems to indicate that the structure is boosting the student’s entrepreneurial skills andaspirations. This is linked with the heightened feeling of both self-efficacy and also reflexiveengineer [20,21]. In this research we take a deeper look into what kind of preferences thestudents have regarding the starting points for innovation to reach an impactful outcome.Innovation for ChangeInnovation for Change (IfC) is a five month long impact innovation program that providesentrepreneurial education for interdisciplinary teams who tackle global challenges that areproposed by big industry/entities and use latest technology from research centres as aninspiration. The program is a collaboration between CERN who provides access
asked students about their research self-efficacy and torate themselves on their research ability. Questions included ability to manage a team, identifyresearch problems, and communicate their findings. Qualitative data were collected from theGlobal Engineering Competency Activity (Jesiek, 2011) an open-ended question that askedrespondents to consider themselves as a working engineer in an international location. Therespondent in this imagined role was asked to consider how they needed to be prepared to enterinto this international work situation and list five capabilities and/or things they would need toknow. Given the low number of participants we were not able to run detailed statistical analyses.Descriptive statistics were used to compare
Study 4 and Study 5 into a singleprotocol. See below.Study 5: Frame-of-reference training makes participants better team membersPurpose of study: This study explores the effect of cognitive model development (measured by aknowledge test as in Study 2) on team performance and team-member effectiveness. Trainingmembers of teams to develop a more accurate cognitive model of teamwork should increaseteam performance, team cohesion, team self-efficacy, and satisfaction, and reduce team conflict.Status of study: Participants were recruited to the experimental and control groups at UNCCharlotte and Purdue University for lab studies, and the results of that work are being published.A significant research protocol was designed, developed, and launched at
moderatelyhigher (p < 0.05) than their non-FGCS peers. Indicating that, on average, FGCS enter engineeringwith higher confidence in understanding engineering, feeling like they can perform well on examsthan their non-first-generation college student peers. First-generation college students’ high self-reported measures of performance/competence is directly related to their self-efficacy andperception of themselves in relation to their chosen field, in this case engineering35. Theimportance of students’ self-confidence and self-efficacy for persisting in science and engineeringhas been further articulated in a literature review by Geisinger and Raman49. This study examinedliterature on engineering students’ attrition, while not explicitly focused on FGCS
study is an adaptation of the Laanan-transfer students' questionnaire (L-TSQ)1,2,3,4 plus a compilation of survey items extracted from the following multi-institutionalresearch studies that investigated transfer student experiences in STEM: Prototype to Production:P2P5 and Measuring Constructs of STEM Student Success Literacy: Community CollegeStudents’ Self-Efficacy, Social Capital, and Transfer Knowledge.6,7The final survey instrument, the “Engineering Transfer Student Survey”, was developedspecifically for this project and is comprised of six sections that include a mix of multiple choiceand open-ended questions. Multiple survey items are embedded in 16 of the 45 questions. Ahigh level summary for each section of the survey is provided as
), 525-548.[4] Mamaril, N. A., Usher, E. L., Li, C. R., Economy, D. R. & Kennedy, M. S. (2016). Measuring undergraduate students' engineering self-efficacy: A validation study. Journal of Engineering Education, 105(2), 366–395.[5] Thaler, R. & Sunstein, C. (2008). Nudge: Improving decisions about health, wealth and happiness. New Haven, CT: Yale University Press.
comparative judgment, integrated STEM learning, Technology & Engineering Design learning, and self-directed learning. I have taught at the middle-school, high school, and collegiate levels and am dedicated to strengthening Technology & Engineering Education.Mr. Andrew Jackson, Purdue Polytechnic Institute Andrew Jackson is currently pursuing a PhD in Technology through Purdue’s Polytechnic Institute, with an emphasis on Engineering and Technology Teacher Education. His research interests are engineering self-efficacy, motivation, and decision making. Andrew is the recipient of a 2015 Ross Fellowship from Purdue University and has been recognized as a 21st Century Fellow by the International Technology and
: they believe in innate talents. Thegrowth mindset is considered an important component in promoting positive learning behaviorsand dispositions, because it promotes success through effort.Dweck also found that students with the growth mindset adopt a mastery goal orientation, inwhich they strive to master an academic subject whereas students with the fixed mindset adopt aperformance goal orientation in which they aim only to earn a grade or to perform better thanpeers8. Mastery goal orientation has been associated with positive outcomes such as self-efficacy,persistence, preference for challenge, and self-regulated learning, whereas performance goalorientations has been associated with maladaptive patterns of cognition, affect, and behavior 9
application in clinical physiological measurement,” Physiol. Meas., vol. 28, no. 3, p. R1, 2007.[6] O. Hoilett, “PulseFit - DIY Heart Sensor With Auto-Adjusted Threshold and Heart-Shaped LED Heartbeat Indicator,” Instructables.com. [Online]. Available: http://www.instructables.com/id/Heart-Sensor-With-AutoAdjusted-Threshold-and-Heart/. [Accessed: 23-Mar-2017].[7] T. Knapp, B. Fisher, and C. Levesque-Bristol, “Service-Learning’s Impact on College Students’ Commitment to Future Civic Engagement, Self-Efficacy, and Social Empowerment,” J. Community Pract., vol. 18, no. 2–3, pp. 233–251, Aug. 2010.[8] C. Levesque-Bristol, T. D. Knapp, and B. J. Fisher, “The Effectiveness of Service-Learning: It’s Not Always what you Think,” J. Exp
initially associatesvalue with a behavior, and then begins to engage in that behavior, until becoming fully motivatedto act out the behavior in everyday life16.Existing Motivation Assessments. A number of established assessment instruments exist withconstructs related to motivation. The Motivated Strategies for Learning Questionnaire (MSLQ),developed to measure learning strategies and academic motivation used by college students,identifies motivation constructs for extrinsic motivation, intrinsic motivation, self-efficacy, taskvalue, and control expectancy20The Intrinsic Motivation Inventory (IMI), a multidimensional measurement to assess students’subjective experience in laboratory experiments, includes constructs for attainment, utility
"soft skills" (a.k.a."essential skills") as advocated by ABET 2000. A more recent example is provided by Boylan-Ashraf who includes hands-on lab activities as part of an arsenal of active strategies applied in anintroductory solid mechanics course (based on presented topical coverage the course would serveas a course in statics). Indicated advantages of active strategies include their increasedlikelihood (compared to lecture-based activities) to provide experiences that are significantenough to build connections as well as a strong association with improved self-efficacy. It isfurther suggested that hands-on learning may promote student retention.Developing contextual knowledge for the "machines" topic In spite of the potential advantages