Using asimilar approach of measuring cultural consumption and preferences by proxy, we examinestudent music genre preference as a potential mediating factor in engineering students’ disciplinechoice.We situate our examination in the context of self-efficacy, which has been shown to have asignificant impact on student behavior, including major choice. Self-efficacy, the belief in one'sabilities, plays a central role in the achievements of individuals throughout their careers.Differing levels of self-efficacy has been documented to impact student behavior from academicachievement to the success in a job search.2 Furthermore, self-efficacy has been shown to have asignificant impact on students’ decisions to major in engineering
the understanding of concepts taught in class. Many of these traits are notcognitive, but rather psychological in nature, such as self-efficacy, curiosity, perseverance (grit),and creativity. These and other psychological constructs are often measured and correlated totraditional aspects of student performance1. In contrast, they are seldom measured to determinewhether they are influenced by specific academic interventions. For example, the literature onactive learning, problem-based learning, and peer learning are rife with claims that they eithercultivate or depend upon curiosity and creativity, yet we are unaware of any direct assessmentsthat demonstrate that this is so. In engineering education, pre-post quantitative comparisons ofthese
to measure difference aspects ofstudents’ self-efficacy12. For this research we utilized three different subscales of the LAESEinstrument: Engineering Self-Efficacy 1 (ESE1), Engineering Self-Efficacy 2 (ESE2) and MathOutcome Expectations (MATH). Tables 4 through 6 show comparisons of these subscales fordifferent groups of students that we assessed as part of this work.Table 4 shows the differences in the Self-Efficacy measurements for the three aforementionedsubscales, comparing the Project-Based and Math-Focused sections of the fall 2013 course.Students in the Math-Focused sections scored lower for each of the three subscales, with only thedrop in the Engineering Self-Efficacy 2 (ESE2) shown to be statistically significant using
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
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
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
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
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
Metacognitive Self-regulation Intrinsic Goal Orientation Extrinsic Goal Orientation Task Value Control of Learning Self-efficacy Test Anxiety Time/Study Management Effort Regulation
self-efficacy, sense of belonging, identification and identityintegration. Often, negative experiences are the result of subtle bias or schemas that all studentsbring with them into their teams, and occur despite the employment of best practices in teamformation.This paper presents a summary of a contemporary understanding of this phenomenon aspresented by several individual researchers covering the fields of stereotype threat, engineeringdesign, teamwork, motivation, and race, gender and their intersections. The content of this paperwas generated by collecting the individual responses of each researcher to a set of promptsincluding: • examples of how students can be marginalized in engineering teamwork and what governing
financial pressures). Hutchison, Follman, Sumpter, and Bodner6found that student retention was greatly impacted by students’ self-efficacy, which in turn wasimpacted by factors such as motivation, understanding of material, and social influences(including peers and faculty). Finally, Bernold, Spurlin, and Anson3 found that persistence inengineering is related to both student learning styles and study habits, as well as teachingmethodologies.Adding to the existing body of literature, ASEE’s publication on best practices in engineeringretention1 highlighted the wide range of programs that universities have developed in reaction tothe various issues that affect student persistence. Almost half of the universities profiled in thepublication had some
strongly related to learner-centered practices (r=.45), withmathematics achievement running a close second (r=.34). Grades as an outcome show a muchlower relationship (r=.25). Affective/motivational variables showed higher association, typically,than cognitive outcomes. Student participation, for example, is strongly related to learner-centeredness (r=.55), closely followed by satisfaction (r=.44), drop-out prevention (r=.35), self-efficacy (r=.35), positive motivation (r=.32), and social connection/skills (r=.32). Given these affective/motivational variables are causally and reciprocally related tostudent achievement in mathematics and science4, we propose that faculty learner centeredattitudes and practices put in place a positive
Vogt illustrates “time expending the necessary mental effort.” Vogt continued inher study to show that student self-efficacy had “very strong effects on effort and criticalthinking where academic confidence had insignificant effect.” What she meant by this was that a Page 26.237.2students’ view that they could accomplish the work in a class was a greater factor in a students’effort and in the critical thinking that they did in a class than was their general academic skill3.Students need to be actively engaged in their chosen professions as soon as possible. A recentprogram review at UT Tyler indicates that students who are in exciting active
enhancing collaboration between peers andpotentially easing the difficulty of the engineering curriculum for some students. Strategies thathave been found to be effective for learning in engineering classrooms and promoting community-building amongst students include cooperative learning activities, model-eliciting activities,problem-based learning, inquiry-based laboratories, and learning communities.3 The use of studentself-assessment tools can help students to increase self-efficacy and confidence in theirengineering-related abilities.11 Many universities are currently utilizing multi-pronged approachesthat include improvements to mentoring and academic advising, the development of a communityof belonging, and improvements to teaching in the
J. E. Pizzolato, P. Chaudhari, E. D. Murrell, S. Podobnik, and Z. Schaeffer, “Ethnic Identity, Epistemological Development, and Academic Achievement in Underrepresented Students,” Journal of College Student Development, vol. 49, no. 4, pp. 301–318, 2008.18 J. E. Pizzolato, “Assessing self-authorship,” New Directions for Teaching and Learning, vol. 2007, no. 109, pp. 31–42, 2007.19 Masi, Barbara, “Impact on Freshman Design Experiences on Self-Efficacy in Engineering,” in the Proceedings of the 2009 ASEE Annual Conference, Session 2314. Austin, TX. Jun-2009.AppendixA1. Course content and structure Fall 2013 and 2014 Style Fall 2013 Style
-19 Volume 3, 20023. Veenstra, Cindy P., Dey, Eric L., Herrin, Gary D., "A Model for Freshman Engineering Retention", AEE, Volume 1, Issue 3, Winter 20094. Meyers, Kerry L., Silliman, Stephen, E., Gedde, Natalie, L., Ohland, Matthew, W., "A comparison of engineering students’ reflections on their first year experiences.", J. Engineering Education, April 20105. Hutchison, Mica A., Follman, Deborah K., Sumpter, Melissa, Bodner, George M., "Factors influencing the self- efficacy beliefs of first year engineering students", J. Engineering Education, January 20066. Landis, R. B., "Student Development: An Alternative to 'Sink or Swim'", Proceedings of 1994 ASEE Annual Conference, June 19947. Lotkowski, Veronica A., et al. "The Role of
motivating modern learners indicates that it is important to enable“the millennials” to overcome anxiety and believe that they can learn content and achieve theoutcomes; they must build self-efficacy and take responsibility for their own learning.According to Pryce, some of the best ways to motivate the millennial student are through guidedpractice, repeated and distributed practice, and early and frequent “low stakes formativeassessment with developmental feedback, as well as repeated and distributed practice built intothe course structure.”10 Thus, the development of appropriate class components and assessmentsis essential, especially for a course aimed at first-year students. The assessments must: 1) beperceived as both relevant and valuable to
Education, pp. 267-274, July 2002.4. R. Talbert, “Learning MATLAB in the Inverted Classroom,” Proceedings of the ASEE Conference, San Antonio, TX (2012).5. K. M. Kecskemety, B. Morin, “Student Perceptions of Inverted Classroom Benefits in a First-Year Engineering Course,” Proceedings of the ASEE Conference, Indianapolis, IN (2014).6. M. Stickel, S. Hari, Q. Liu, “The Effect of the Inverted Classroom Teaching Approach on Student/Faculty Interaction and Students’ Self-Efficacy,” Proceedings of the ASEE Conference, Indianapolis, IN (2014). Page 26.1698.127. N. K. Lape, R.L. Levy, D. H. Yong, K. A. Haushalter, R. Eddy, N
, developed the TESS (Teaching Engineering Self-efficacy Scale) for K-12 teachers, and rescaled the SASI (Student Attitudi- nal Success Inventory) for engineering students. As a program evaluator, she has evaluated the effects of teacher professional development (TPD) programs on K-6 teachers’ and elementary students’ attitudes to- ward engineering and STEM knowledge. As an institutional data analyst, she is investigating engineering students’ pathways to their success, exploring subgroup variations.Dr. Monica M Cortez, Texas A&M University Monica M. Cortez, Ph.D., is the Director of the Texas A&M Engineering Academy and Workforce De- velopment Programs at Texas A&M University. She received her Ph.D. and M.S
studentswith a higher probability of failure) reduce attrition through improving self-efficacy and skilllevel in mathematics. Moses et al.6, in an article devoted to math readiness and personality, stressthe need to examine math readiness to in order to improve retention of first-year students. Thisstudy consisted of participation from 129 freshman engineering majors, and used logisticregression as a means of evaluating the data. Moreover, research in engineering education has indicated that pre-university assessment of“student readiness” might be used to inform best practices in teaching first-year engineeringcourses. A substantial portion of the literature considered in this paper was devoted to theevaluation of mathematical and other pre