in a real situation or problem that needs tobe addressed and solved,…”.Mourtos8 offered the following link between the learning framework and Student Outcome 3(i)"a recognition of the need for (affective - organization), and an ability to engage in lifelonglearning (cognitive - analysis)". Thus, the potential lifelong learner must at some point in theiracademic career develop value for information that pertains his or her discipline and has a strongenough sense of self-efficacy to be intrinsically motivation to independently learn.Concomitantly, in exploring his or her discipline, the student will face new, ill-defined andchallenging tasks which require concerted, systematic and extended efforts in order to succeedand subsequently graduate
barriers facultyexperience in providing encouragement to students. Additionally, the creation and validation of atool to measure faculty perceptions of providing encouragement can be used by institutions toidentify critical areas to strengthen how we teach in engineering.Guiding FrameworkAn extensive literature review showed the Academic Encouragement Scale (AES) and theFaculty Encouragement Scale (FES) as the best instruments to guide this research [20, 21]. Bothmeasure students’ perceptions of receiving encouragement in academic settings. Findings fromboth studies indicate that receiving encouragement increases students’ self-efficacy and outcomeexpectations.The Social Cognitive Career Theory (SCCT) guided the development of the survey
be measured in terms of gradeperformance and intellectual development during the college years [22]. While ability has beenpositively associated with college persistence, commitment to the goal of completion is the mostinfluential factor in determining persistence [22]. A feeling of success and congruence in theacademic environment may lead to increased motivation to study, which may lead to betterperformance, increased academic self-efficacy, and institutional commitment [23]. Learningcommunities are a way to combine academic and social aspects of an institution to help increaseacademic performance and retention, particularly in the transition from high school to college[24]. Learning communities that include mentoring encourage personal
Asian Black White Agree Agree Agree Agree Self-Efficacy I am confident that I will be 4.7 ± 0.7 4.7 ± 0.6 4.6 ± 0.7 4.5 ± 0.9 4.7 ± 0.6 4.8 ± 0.6 4.7 ± 0.5 4.7 ± 0.7 able to transfer to a 4-year institution. Self-Efficacy I am aware of the 3.9 ± 1.1 3.9 ± 1.1 3.9 ± 1.2 3.7 ± 1.2 3.9 ± 1.1 4.0 ± 1.0 4.1 ± 1.0 3.5 ± 1.3 procedures involved in transferring to a 4-year institution. Self-Efficacy I know how I can get more 4.2 ± 1.0 4.2 ± 1.0 4.2 ± 1.0 4.1
constructs in the population. The constructs are all positively correlated, withmagnitude of correlation corresponding to the size of the bubble. This is shown by the checkedbubbles intersecting any two pairs of measures in Figure 2. It is evident that Anticipatory Cognitionis correlated and significant to several of the measures, but lacks significance against stereotypethreat, isolation, extant knowledge and future anticipation. For example, the weaker theparticipants infer the stereotype threat, the higher is their attention and focus to solving theirresearch problem. It is also evident from this Figure that Academic Self Efficacy is predominantlycorrelated
activities” (CareerExploration Skills).The SCDI has been used in studies of adolescent, college student, and post-high school youngadult career development [e.g., 27, 28, 29], including studies of the career development of NativeAmerican young people. Career exploration, as measured by the SCDI, has been positivelyrelated to interests and efficacy among Native American young people [30].The Career-Related Parent Support Scale [31] is a 27-item instrument that was used to measurestudents’ self-reports of their parents’ support in the four areas of self-efficacy information(Instrumental Assistance (IA), Career-Related Role Modeling (CM), Emotional Support (ES),and Verbal Encouragement (VE)) identified by Bandura [32]. IA is the tangible help provided
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
co-teaching, classroom technologies, active learning in the classroom, and various classroom-based affective inter- ventions targeted at fostering self-efficacy, belongingness, metacognitive learning strategies, and growth mindset affect outcomes such as student retention and success, particularly during the freshman and sophomore year. Her field of research is undergraduate engineering education. Dr. Kiehlbaugh com- pleted her BS and MS at the University of Arizona and her PhD at UC Berkeley. She is now a Research Assistant Professor in the College of Engineering at her undergraduate alma mater. c American Society for Engineering Education, 2019 1 Scalable and Practical
, 1995, Generalized Self-Efficacy Scale. In J. Weinman, S. Wright, and M.Johnston, Measures in health psychology: A user’s portfolio. Causal and control beliefs (pp. 35-37). Windsor, UK:NFER-NELSON.10 Cohen J., 1988, Statistical Power Analysis for the Behavioral Sciences (2nd ed.), Lawrence Earlbaum Associates,New Jersey.11 Shi, W. and K. J. Min, 2014, “Product Remanufacturing: A Real Options Approach,” IEEE Transactions onEngineering Management, Vol. 61, pp. 237-250, 2014.12 Shi, W. and K. J. Min, 2014, “Product Remanufacturing and Replacement Decisions Under Operations andMaintenance Cost Uncertainties,” The Engineering Economist – Special Issue on Engineering Economics inReliability, Replacement and Maintenance, Part 1, Vol. 59
, 2016Changes in Undergraduate Engineering College Climate and Predictorsof Major Commitment: Results from Climate Studies in 2008 and 2015Abstract This paper presents results of two cross-sectional investigations of educational andinterpersonal climate in a college of engineering at a large mid-western university. In 2008 andin 2015 we deployed a survey ("Project to Assess Climate in Engineering”) to undergraduateengineering students. In each survey year, just over 1000 eligible students participated andresponded to items contributing to scales rating their professors, teaching assistants, collegeresources, confidence (self-efficacy) in engineering, student interactions, perceptions ofengineering, and commitment to an engineering major
, including student scoreon the pretest three-dimensional modeling self-efficacy (3DSE) assessment, gender, age, andwhether or not the student had a parent with professional engineering backgrounds. The three-dimensional self-efficacy instrument consisted of nine questions, each being a 7-point Likerttype item, designed to measure students’ self-efficacy related to modeling three-dimensionalobjects [11]. Logistic regression could not identify for which subgroups of students the variableswere most significant. For these reasons, machine learning analytics software was used toexamine the predictors, and their interactions, that led to persistence in engineering degreeprograms. Machine learning has gained popularity over recent years due to its ability
join our GTA training.Program EvaluationAligned with the goals of the program to improve teaching ability and based on the assumptionthat students may not see the connection between teaching and transferable professional skills,this program evaluation was designed to: 1) measure changes in students’ perceptions of theirconfidence in teaching and 2) estimate changes in students’ viewpoints toward teaching as anopportunity to enhance transferable professional skills. To these ends, we administered twosurveys before and after the course: the STEM GTA Teaching Self-Efficacy Scale 5 and a modifiedskills perception inventory. 6 This section discusses the demographics of the students whoparticipated in this evaluation and their responses to the
, extrinsic goal orientation, task value, control of learning beliefs, self-efficacy forlearning and performance, critical thinking, and metacognitive self-regulation; 2) the Change-Readiness Assessment [10] which assess 7 subscales, including adventurousness, confidence,adaptability, drive, optimism, resourcefulness, and tolerance for ambiguity; 3) PersistenceMeasures [11] which measures 3 responses including graduate study, career, and intent to changemajor; and 4) the Longitudinal Assessment in Engineering Self-Efficacy [12] which providesresults in six subscales, including self-efficacy, sense of belonging, and career expectations. Allof the questions are related to the course and/or learning environment. These questionnairesemploy 7-point Likert
. Instead, the researchers are customizing a University Seminar (US 1100) section, whichis an introduction to the university freshman seminar course, specifically for engineering andengineering technology majors while exploring research questions related to the development ofstudent design self-efficacy. This paper presents this work in progress including preliminaryresults from pre- and post-project engineering design self-efficacy measures of the initial cohort,lessons learned, and plans for future work.BackgroundThe Texas State STEM Rising Stars project is using a three-sided organizing framework, asshown in Figure 1, to guide the interventions and its associated research plan. This framework isbased upon Swail’s geometric model for student
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
associated with a variety of student outcomes. Additionally, modified versionsof previously validated instruments were used to measure teachers’ motivation for participatingin the K12 InVenture Prize program [15] and teachers’ self-efficacy for teaching engineering andentrepreneurship [16]. Participants A total of six teachers from our focal region began the survey. Of these, two discontinuedthe survey during the demographics and teaching background sections; a total of fourrespondents completed the survey. All four teachers who completed the survey are women, andall four teachers are White. For all four teachers, the 2018-2019 school year was their first yearimplementing the K12 InVenture Prize program. Two teachers implemented in a
/perceived confidenceand interest/values in STEM has progressed over the past two decades, studies of students’motivational orientations (intrinsic versus extrinsic) in STEM are quite limited.Perceived confidence and self-efficacy strongly influence academic motivations [44] and serveas mediators of learning engagement and persistence [8]. As such, STEM educators areconcerned with how learners cultivate a strong sense of efficacy and expectations of success.Indeed, measurement of self-efficacy and perceived competence represents an area of notableprogress in STEM education research. Gendered patterns in learners’ perceived competence andself-efficacy within gender-role stereotyped domains such as mathematics and engineering arewidely reported [45
preparedness10. Workshop(s) on product commerciali- 1 2 - 2 3 4 2zation Table1: Ratings of the overall summer bridge experienceStudent self-efficacy was assessed using the Engineering Skills Self-Efficacy Scale [6]. The scalewas developed to assess the different dimensions of self-efficacy for undergraduate studentsacross various engineering-related disciplines. The measure reports three sub-scales:Experimental Skills, Tinkering Skills, and Design Skills. To assess the effectiveness of theadditive manufacturing project-based experiences, the project evaluator wrote four itemsmodeled on the existing items on the Engineering Skills Self-Efficacy Sub-Scales
environment as an intern/co-op”(Atwood et.al, 2021). However, only 41.5% of historically marginalized populations completedan internship (Atwood et.al, 2021) by graduation. Similarly, only 47.6% of first-generationstudents completed an internship (Atwood et.al, 2021). Lack of internship or co-op can lead tounderemployment and significantly less lifetime earnings. Lack of internship also could beattributed to the student’s lack of social capital. According to NACE, first-generation studentsreceive lower salary offers compared to their continuing-generation counterparts (Eismann,2016). Additionally, self-efficacy is crucial for the individual’s ability to complete a task(Huang, 2003).MethodsHaving explicit instruction around communication skills
specified). In addition, we assessed social cognitive variables related to educationaland career decision making, including engineering self-efficacy, expectations for the field ofengineering, commitment to major and degree completion. In 2019, students were asked if theyidentified as a member of the LGBTQ+ community, allowing for a better understanding of thesestudents’ experiences. Data from all three survey years were combined to investigate trends oncritical measures related to persistence in engineering. We found that students’ assessment of theeducational environment (professors and student interactions) were relatively stable, while otheraspects of the environment (experiences of stereotyping and harassment) significantly increasedacross the
other courses includingvideo content and be less resistant to this form of instruction.To get insight into the effects of the courses focus on learning and applying design theory, aninstrument was used to measure participant engineering design self-efficacy. The instrumentwas designed and validated by Carberry et al [20]. The tool measures individual’s self-efficacytowards engineering design tasks. Self-efficacy is an individual’s belief in their ability tocomplete a specific task [21]. This instrument examines four aspects of an individual’s self-efficacy: 1) Confidence, 2) Motivation, 3) Expectation of Success and 4) Anxiety towardscompleting engineering design [20]. The instrument was administered at the beginning and endof the Hybrid2
uniqueresearch experiences must be identified for 100 students in laboratories across campus.Furthermore, the arrangement of internships depends upon strengthening and expanding thenetwork of regional industries, companies, and health services organizations. This requiresconsiderable work, however, our extensive faculty network and alumni have been supportive inproviding resources and opportunities for current WISE students.Preliminary FindingsTo measure the effectiveness of the new WISE curriculum in meeting its goals, incomingfreshmen (N = 58) were surveyed at the end of the fall semester in 2017. Baseline data werecollected to explore the following research question: How does participation in the WISEcurriculum impact students’ self-efficacy, career
). After the completion of the summer program, teachers completed a post-survey (n =7-8 ) ontheir self-efficacy for teaching engineering during the Fall to measure any perceived changes inbeliefs as a result of the summer program. The results of the pre-post survey are found in Table3.Table 3: Teachers reported self-efficacies in teaching engineering pre-post summerprogram. Strongly Moderately Slightly Slightly Moderately Strongly Disagree Disagree Disagree Agree Agree Agree 1. I can discuss PRE how given 20% 10% 20% 0% 40% 10% N=10
evaluation instruments were built from psychometrically sound instrumentsand scales that include the Career Interest Questionnaire and Modified STEM Semantics Survey(Tyler-Wood et al., 2010), Entrepreneurial Self-Efficacy and Intention (Wilson et al., 2007),Student Attitudes toward STEM Survey (Mahoney, 2010); STEM Semantics Survey (Tyler-Wood et al., 2010), Sources of Self-Efficacy Scale (Britner & Pajares, 2006), and a 21st CenturySkills Assessment/Rubric. Specifically, the process evaluation was designed to measure both quality and intensity ofSTEM-Inc activities in order to monitor the short-term and formative results of activities andservices, validate program components, and determine whether activities were of sufficientquality and
no effect on faculty members’ self-efficacy related toculturally responsive classroom management (CRCMSE) and engineering pedagogy (TESS).Faculty reported moderately high self-confidence on all CRCMSE measures (range: 2.06-2.50 on0-3 pt Likert), and there were no statistically significant gains in these measures from pre- topost-workshop. Similarly, faculty also had moderately high self-confidence on TESS measures(range: 3.33-4.72 on 0-5 pt Likert); and pre- vs. post-workshop gains were reported for two of 15survey items. Specifically, faculty reported gains in confidence related to their ability to guidestudents in the engineering design process or scientific method (d=1.15, p=0.009, n=18) and self-confidence in encouraging critical
attended the Bridge remotely, still found the experiencetransformational. In a case study interview conducted by Ruxton Consulting, one student attributedtheir success to the Bridge saying, “I really think I wouldn't be here. I wouldn't be studyingengineering without the creation of the Bridge program.” (Ruxton Consulting Evaluation Reportpresented to the PI, 2022).Students also reflected on how their effort, within the structure of the Bridge, contributed to theirimproved self-efficacy in math. As one student shared, “It's not a test of your finances, or yourbrains. It's a test of how hard you can work, and I think that's a great factor to measure someoneby.” Another student acknowledged how much work was ultimately needed in order to be readyfor
isevident and supported by Table 2. Despite this lack of coherence, these studies have beenimportant first steps in exploring specific aspects of identity development in engineering. Closely related to identity but not explicitly stated, others have provided a review andanalysis of existing research on the measurement of the characteristics of engineering students inorder to illuminate factors that affect college enrollment and retention.12 The authors, Li,Swaminathan, and Tang, found that many researchers are specifically looking at the factors thathelp or hinder the matriculation of underrepresented groups into engineering. Marra, Rodgers,Shen, and Bogue conducted a multi-institution study on self-efficacy and women engineeringstudents.36
engineering careers and on developing theircontent knowledge in select grade-appropriate science and mathematics content areas. Pre-posttesting was conducted with sixty-five students of diverse backgrounds in grades six through eightto measure their self-reported engineering-related self-efficacy, knowledge of engineering careers,and motivation to pursue future engineering classes and careers. In addition, interviews wereconducted to examine any changes in middle school camp participants’ affective characteristics ofmotivation, self-efficacy, and self-determination.Introduction The attraction and retention of students in science, technology, engineering, andmathematics (STEM) disciplines along the full length of their education is a national
, to estimate the expected total numberof delayed months, including: 1-3 months, 4-6 months, 7-9 months, 10-12 months, and morethan one year. In terms of the career outcome, we evaluated students’ job search self-efficacy byasking three questions [25]: “Since the COVID-19 outbreak occurred, how confident have youbecome in finding (1) the job for which you are qualified? (2) a job in a company/institution thatyou prefer? (3) the job for which you are prepared?” The 5-point Likert scale was from -2 (muchless confident) to 2 (much more confident). The Cronbach’s alpha for these three job search self-efficacy items is .906. The measure for mental health outcome, which focused on symptoms ofdepression and anxiety, asked students if in the last 7
state finals in Spring, 2016. Allteachers were invited to participate. Components of this survey relevant for the current workinclude demographics, information about teachers’ backgrounds, and also several constructs:self-efficacy for teaching engineering, self-efficacy for teaching entrepreneurship, and teacherperceptions of the program’s effects on students. Some of these constructs were assessed throughvalidated instruments, while others were measured with internally developed items. Teaching Engineering Self-Efficacy Scale Self-efficacy for teaching engineering was measured with the Teaching Engineering Self-Efficacy Scale (TESS), which was developed and validated by Yoon Yoon et al., 201411. Theseauthors “define teaching