changes in studentinterest and self-efficacy as they relate to cybersecurity.Measuring change in student interest gives us an indication of how well a given course ismotivating students to pursue further knowledge or work in this sub-field. 22 Building long-termstudent interest is vital within a new, fast-changing, field such as cybersecurity. Self-efficacy isdefined as “...a person’s belief in his or her capability to perform a task,” 8 Measuring studentself-efficacy is important because it has been linked with outcomes such as persistence on task,academic success and long-term career success. 4,19 Studies have shown that students with higherself-efficacy in fields such as mathematics are more willing to discard faulty strategies and reworkmore
learningsituations and the impractical, difficult-to-measure level of transient situations within one course[9, 13, 23]. By focusing on the roles of both motivation and cognition during learning, the MSLQreflects the research on self-regulated learning, which emphasizes the interface betweenmotivation and cognition [14-15]. Prior research using the MSLQ has found relationshipsbetween constructs on its motivational subscales such as: intrinsic goals, extrinsic goals, taskvalue, control of learning beliefs, self-efficacy, and test anxiety, and constructs on its use oflearning strategies subscales such as: rehearsal, elaboration, organization, critical thinking,metacognitive self-regulation, time and study environment, and effort regulation [16 - 17
self-efficacy are well equipped to educate themselveswhen they have to rely on their own initiative. One of the goals of teaching communicationskills is to develop students who feel competent and confident in the use of those skills [13]. Ourstudent survey is designed to measure the extent to which students at our study sites havedeveloped a sense of self-efficacy for communication.The survey lists the sub-skills we have identified, both from the literature and from experience inteaching communication skills, that student must master in order to successfully create anddeliver oral presentations, write, develop and use visual literacy skills, and participate inteamwork. For example, for oral presentations, we asked students about their
motivational itemssuch as perceived instrumentality and self-efficacy beliefs. We must note that this pilot study alsoserved to test the instrument. Future studies will gather data regarding prior training related tospatial visualization skills. 3.2 Data Analysis: To analyze the findings from the self-report questions, exploratory factor analysis (EFA)was used with the measures of motivational factors such as perceived instrumentality and self-efficacy beliefs. Based on the literature, we expected that individuals who were exposed in theirearly childhood and later on in live to experiences related to the manipulation of objects viasectional cuts, three dimensional rotations, and other mental operations will have higherperformance score on
and thosestudents who were interested in a “socially oriented” (non-profit) career outcome. The theoreticalframework used for modeling these groups was Social Cognitive Career Theory (SCCT).Logistic regression analysis was conducted using a multi-measure survey that assessed cognitive,motivational, behavioral influences.Results show that students who are Starters tend to be “new seeking” and “iconoclastic”, andhave higher “domain self-efficacy”, compared with students who are Joiners. Further, studentswho are interested in Socially Oriented career outcomes are more “socially altruistic,” and have astronger sense of “personal morals” and a more hopeful future about their “quality of life”compared with their Market Oriented peers. Gender was an
large gains over pre-vious curricula 39 . Jara found that students in Automatics and Robotics at the Universityof Alicante significantly improved their efficacy and performance following a “learning bydoing” approach using a remote robotic laboratory called RobUALab 42 . Cannon positivelyreviewed a University of Minnesota robotics day camp for middle school youth designed toinspire minorities and women to pursue careers in STEM through hands-on learning 24 . Thiswork aims to provide additional support for these findings. This work is based on the hypothesis that in addition to engagement, the proposed ap-proach will also positively affect students’ academic success by boosting self-efficacy, theperceived ability to complete a task and reach
sensing.” Journal of NeuroEngineering and Rehabilitation. 2(4), 1-7.8. Berzowska J. (2005). “Electronic Textiles: Wearable Computers, Reactive Fashion, and Soft Computation.” Textile. 3(1), 2-19.9. Lam Po Tang, S. (2007). “Recent developments in flexible wearable electronics for monitoring applications.” Transactions of the Institute of Measurement and Control, 29 (3-4), 283-300.10. Raelin, J. A., Bailey, M. B., Hamann, J., Pendleton, L. K., Raelin, J. D., Reisberg, R., and Whitman, D. (2011). “The Effect of Cooperative Education on Change in Self-Efficacy among Undergraduate Students: Introducing Work Self-Efficacy.” Journal of Cooperative Education and Internships. 45(2), 17-35.11. Chubin, D. E., May, G. S., and
not absolute characteristics,and the Felder-Silverman model accounts for “balanced,” “moderate,” and “strong” preferenceswithin each dimension. However, because learning styles describe the cognitive processesinvolved in problem solving, it may be argued that individuals with more balanced learningstyles will be better problem solvers. Originally, our study focused on the correlation betweenstudent learning styles, problem solving strategies, self-efficacy, attitudes/perceptions, andperformance in an introductory undergraduate chemical engineering course at a largeMidwestern university, in an effort to better understand our student population and provide abasis for curricular development. We were interested in understanding whether there
ECD Self-efficacysurvey measures teachers’ engineering curriculum design self-efficacy. This new scale consistsof eight subscales that are rated on a 6-point Likert type agreement scale (Strongly Disagree,Disagree, Slightly Disagree, Slightly Agree, Agree, Strongly Agree). A three step process wasused to develop and validate the survey. First the constructs and associated items were defined.A literature review resulted in the selection of eight factors that are pertinent in engineeringcurriculum design: (1) K-12 Engineering Content, (2) Industry Engineering Content, (3)Engineering Design Process, (4) Project-based Learning, (5) Student Learning, (6) IntegratedLearning, (7) Teaching Coherence and (8) Curriculum Planning (see Appendix A for
outcomes of their project-based communityservice learning based on collected students’ learning data, this paper reveals impacts of thescaffolding through different delivery approaches on students’ perceptions on creativeproblem solving, self-efficacy, identity, and application of creativity strategies. It alsoconfirms the correlation among application of prompts and students’ learning process andlearning outcomes, and compares the available results of data analysis from twoimplementation years. The results from data analysis indicate that scaffolding creativeproblem solving through freshmen’s project-based service learning may in general enhancestudent’s self-efficacy, strategies application, and interest in engineering. Among threeintervention
(pre = 63.33 ± 5.77, post = 83.33 ± 5.77). There areno significant differences between the majors (Mechanical Engineering n = 4, Applied Math n =1, Electrical Engineering n = 2).Lastly, students were asked whether they changed their views of pursuing graduate degrees aftergraduation. There is no significant difference between the pre-self-efficacy measures andchanges in views towards graduate school, F (2,7) = 0.48, p > 0.789. This may indicate that self-directed opportunities during the undergraduate curriculum can be viewed as supplemental, butnot necessarily as a way to introduce graduate research habits. Since the students were notworking with any graduate students. Figure 3 shows students’ self-efficacy scores before andafter
to receive high grades had been eliminated.8 In addition aformative assessment may have a negative impact on students’ self-efficacy (individualjudgment about being able to perform an activity) and therefore their motivation to learn.9 If thegoal is learning, are there ways that we can continue to monitor and measure learning so thatstudents don’t feel under pressure and can see the value in grading?We were interested in exploring how to incorporate more formative assessment into a largeIntroduction to Environmental Engineering class. While both summative and formativeprocesses are complementary and both address “what has the student learned” more significantlearning gains can be made when formative assessment results are used to inform
-regulated dimension highlights self-initiated actions and processes aimed at acquiring and applying information or skills that involve settinggoals, self-monitoring, managing time, and regulating one's efforts as well as physical and socialenvironment for goal fulfillment12. However, the most robust factors for motivation and learning Page 26.1172.3strategies could be self-efficacy and effort regulation. Motivational strategies are closely related to thegrades of university students.Research methodology:Participants: The targeted population included male and female freshmen, sophomores, juniors and seniorsfrom both private and
University of Colorado Boulder.Twenty-five survey items were used to measure four sub-components of sustainable engineeringmotivation, single items were used to measure global interests and interdisciplinary value, andnine items evaluated consideration for others. Sustainable engineering self-efficacy, value, andnegative attitudes were similar among students in all three majors. Environmental engineeringstudents had higher scores than civil and architectural engineering majors in sustainableengineering affect and overall motivation. Interest in working on projects outside the U.S. washigh, without significant differences between environmental, civil, and architectural engineeringstudents. Interdisciplinary value was the higher among environmental
a measure of self-efficacy (1 = not at all true, 4 = exactly true). The final sectionasks students about their career plans and uses the same scale as the second section. Theinstrument was developed by the Georgia Tech Office of Assessment and uses an externallyvalidated General Self-Efficacy Scale to assess an individual’s ability to cope with stressful lifeevents.405.0 ResultsMean scores from the GITIIS were computed for both programs, and independent anddependent samples t-tests were conducted in order to assess between and within group meandifferences, respectively. The complete results are reported in the appendix, but this paper willfocus on the student responses to items measuring perceived level of preparation at the end oftheir
in the invertedsection of Engineering 82 were allowed access to the videos.MeasuresStudents in both sections of each course were administered a pretest and posttest attitude survey.The pretest survey contained a total of 28 selected items from established instruments includingfrom the Research on the Integrated Science Curriculum (RISC), Motivated Strategies forLearning Questionnaire (MSLQ), Metacognitive Awareness Scale (Schraw & Dennison), and theSTEM Questionnaires developed by the STEM team at the Higher Education Research Institute(HERI). A factor analysis was conducted on the pretest survey questions to determine whichquestions were most appropriate to represent the various constructs of interest including self-efficacy for
entrepreneurial action.With respect to entrepreneurial interest, Lent, Brown, Sheu, Schmidt,and Brenner posited that aperson’s interest in a given activity is based on two concepts: 1) self-efficacy or beliefs aboutone’s own personal capabilities; and 2) outcome expectations or beliefs about the outcomes ofengaging in a particular course of action.10 We propose that alumni who have shown highinterest are more likely to pursue entrepreneurship, since interest will result in a higherlikelihood of entrepreneurial action.We hypothesized that alumni who have expressed high intentions to pursue entrepreneurialactivities are more likely to seek out these activities. This included constructing a model toidentify which are the important factors that predict
, and sexual harassment. Second, this base of discrimination may influenceidentified behavioral and attitudinal barriers such as women faculty’s lower self-efficacy andconfidence, lower productivity, and higher risk-aversion. Third, discrimination and attitudinalbarriers come into play when considering the differences women experience navigating work-lifebalance such as marriage and parenting, and inclusion in critical networks. Finally, taking all ofthe listed factors into consideration, a picture emerges around why women faculty in engineeringare not participating in academic commercialization education and training at the same rate astheir male counterparts
not be surprising. There are a total of15 subscales in the MSLQ, but each subscale can be used alone or in conjunction withany other scale depending on need. The subscales of interest in the present study are asfollows: ● Intrinsic goal orientation (a measure that focuses on learning and mastery) ● Control of learning beliefs (beliefs that outcomes are the result of effort rather than luck) ● Self-efficacy (beliefs about competence and ability)Ideally, as the semester progress students will increase intrinsic goal orientation – thebelief that outcomes are the result of effort rather than luck, and increase self-efficacy.The Academic Entitlement Scale17 is also used as an assessment tool. Even with therecent development of
individually and in small groups.Students spend up to six hours a day for five days working on improving their math skills. Veryseldom do students get the opportunity to concentrate all of their efforts on math during theregular semester. To that end, in an effort to describe the effect of Math Jam on participant self-efficacy (the participant’s belief in their capability to complete specific tasks or goals) a self-efficacy instrument was administered as part of the pre- and post-program surveys. Studentswere asked 18 of the 34 question Mathematics Self Efficacy Scale developed by Nancy Betz andGail Hackett to measure student self-efficacy related to math both at the very beginning of MathJam and again on the last day of the program. The questions
by the endof the semester.Results for Student Ranking of Class ActivitiesIn addition to the diversity and engineering identity survey questions, students rated classactivities to better understand what pedagogical practices fostered self-efficacy and engineeringidentity (see Tables 5-8).Students in the grand challenges course indicated that the visit with Steve Swanson (NASAastronaut) was the most helpful course activity in developing student self-efficacy and interest.Students also suggested that discussions about engineering and interacting with professors washelpful in developing self-efficacy while discussion of engineering challenges helped to fosterinterest. Students in the civil engineering course indicated that learning practical
from a social cognitive perspective10,11 thatconsiders the multiple environments central to one’s life and work. Relevant to thisproject, the authors advocated that attention be given to the multiple environments ofresearch, academia and home/family life that create numerous and often competingexpectations and demands on one’s work life. These multiple environments interactwith personal characteristics (e.g. gender, race) to influence career behaviors,confidence in one’s ability to do research (research self-efficacy), and the outcomes oneexpects from a research career (career self-efficacy). These factors, in turn, predict one’sinitial or sustained interest in a research career pathway. This theoretical framework isimportant because it
method.Theories that look at the intersection of motivation and cognition include self-regulation13,14 andthe theory of intentional conceptual change3, which guides our overarching study. While thesetheories differ in the type of motivation-related constructs they examine and how they relate tocognition, within each framework motivation, cognition, and learning are interconnected. Forexample, the core of the model for intentional conceptual change is the idea that a student’smotivation for conceptual change will shape the way they approach learning. This model startswith a primary categorization of students’ motivation under Achievement Goals (e.g., mastery,performance) then considers Other Motivational Beliefs (e.g., interest, self-efficacy) and
Paper ID #12383Factors of Group Design Decision MakingMr. Andrew Jackson, Purdue University, West Lafayette Andrew Jackson is currently pursuing a Master of Science in Technology Leadership and Innovation in Purdue University’s College of Technology. His previous middle school teaching experience informs his role as a graduate teaching assistant for an introductory course in design thinking. His research interests are engineering self-efficacy, creativity, and decision making.Prof. Nathan Mentzer, Purdue University, West Lafayette Nathan Mentzer is an assistant professor in the College of Technology with a joint
it requires critical thinking and writing skills, which are difficult toexplain in a traditional classroom setting. In prior work, it was found to be among the mostmentally demanding for novices.6 Performance in this stage could be improved by smallerwriting assignments along the way, which we plan to implement in the future.From our surveys, it was possible to measure the shift in student self-efficacy in performing Page 26.1685.9iSLR and its perceived usefulness, as shown in Table 4. Shift is measured by assigning unitchange if the answers changed between neighboring categories. For example, change fromNeutral to Strongly agree gives a “+2
cooperation scaffolding might hinder students’ cooperation inlearning. The impacts of scaffolding on students' learning dispositions measured by MSLQ 23 wereexamined by comparing results between the post-test and the pre-test in terms of size effect, asshown in Table 10. According to the comparison, Group B enjoyed the increase in self-efficacy, intrinsic value, cognitive strategy use and self-regulation, but suffered intensified testanxiety. Group C, similar to Group D, experienced increase in self-efficacy and reduced testanxiety, but failed to develop in intrinsic value cognitive strategy use and self-regulation.However, Group D enjoyed the boldest increase in self-efficacy and largest decrease in testanxiety, but they suffered the largest
in a variety of STEM fields and were fromeither 4-year or 2-year institutions. Among the eight REU students, five were females and threewere males.REU Research ProjectsThroughout the 10-week summer program, REU students conducted four research projects,including 1) developing a self-regulation survey instrument for problem solving in engineering;2) studying students’ meta-cognitive strategies when learning engineering with computersimulation and animation; 3) studying students’ self-efficacy, perception of engineering, andengineering interest in the context of Mathematics Engineering Science Achievement (MESA)22 ; and 4) developing an instrument for exploring engineering design knowing and thinking.These four projects are briefly described
trainingorganization.Results22 undergraduate engineering students participating in the 2014 semester-long class participatedin pre- and post-class surveys. As mentioned above, self-efficacy has been shown to be anexcellent tool for measuring students for our key objectives. Figure 5 shows the results of the2014 semester-long class in comparison to the 2011, 2012, and 2013 fieldtrip classes and thecontrol group. Table 4 summarizes the improvements in the student survey’s following theclasses. Table 5 shows the standard deviation for each question and year. No, Not at All Yes, Definitely 3.4
course offered in Fall 2014 collaborating on designing, building, andtesting autonomous waste sorters. Teams from one section of 38 mechanical, aerospace, electrical,and chemical engineering students are paired with those of the other section with 43 computerscience, informatics, software engineering, computer systems engineering, industrial engineering,and engineering management students. While the teams from each section focus on differentaspects of the design, inter-disciplinary collaboration and system integration is required for asuccessful final product.The impact of this experience on students’ knowledge and self-efficacy of the engineering designprocess, their technical communication skills, and teamwork has been measured. A
of pre-CI scores. Interestingly,looking at the concept inventory scores for the top and bottom 20% of students measured byparticipation as presented in Table 2, the top 20% students for each cohort showed greaterimprovement when compared with the bottom 20%. For the small cohort, the percentageimprovements in CI scores were 64.9% and 72.9% for the bottom and top 20%, respectively. Forthe large cohort, the percentage improvements in CI scores were 9.1% and 47.3% for the bottomand top 20%, respectively. Thus the small cohort displayed greater performance gains overallregardless of participation level, while the gains for the large cohort showed greater difference onthe basis of participation level.Results from the qualitative self-efficacy