be increased by learning additionalmaterial concerning the specific goals and being motivated towards success8. Higher self-efficacy leads to higher achievement behaviors.Self-efficacy assessments are difficult to create because they need to have a precise measurementconsistent with the criteria tasks in order to maximize the influence of self-efficacy as apredictive power1. Validation of an instrument is important because it is used as a justificationof the adequacy of the measured values9, 10. Carberry et al. developed a self-efficacy instrumentto study people’s self-efficacy towards engineering design tasks and proved three sources ofvalidity: content, criterion-related, and construct2.Carberry’s instrument examines four task-specific
environment all play important roles in an individual’s academic and careerchoices16. SCCT expands on SCT by providing a model for understanding the choices thatindividuals make with respect to academic and career pathways. The SCCT framework arguesthat these choices are influenced by three main factors: self-efficacy (the degree to which onebelieves that one can succeed at a given activity), outcome expectations (one’s beliefs about theoutcomes of certain behaviors), and personal interest (i.e., intentions). Brown and Lent17 foundthat people choose not to follow certain career paths because of faulty beliefs they may holdabout their own self-efficacy or faulty outcomes expectations. They found that modifying self-efficacy and outcome expectations
incorporate a wide array of contributing factors;modern theories most relevant to engineering pertain to goals, values, and expectations 4.Expectancy x Value models of motivation 5, in particular a model refined by Eccles et al. 6, positthat expectations of success and the value placed on success determine motivation to achieve,and directly influence performance, persistence, and task choice. Expectancy of success isdefined as one’s beliefs about competence in a domain; it is not necessarily task-specific.Aspects of instrumentality capture how students perceive the importance of what they are doingin class relative to their future careers 7–9. Students’ expectancy is based partly on their self-efficacy 10, in addition to their perceptions about the
linkbetween program impacts on student motivation and self-efficacy and ultimate graduate rates.The Wright State ModelIt is well known that student success in engineering is highly dependent on student success inmath, and perhaps more importantly, on the ability to connect the math to the engineering1-6.However, first-year students typically arrive at the university with virtually no understanding ofhow their pre-college math background relates to their chosen degree programs, let alone theirfuture careers. And despite the national call to increase the number of graduates in engineeringand other STEM disciplines7 , the inability of incoming students to successfully advance past thetraditional freshman calculus sequence remains a primary cause of
. Thisquestionnaire is based on an expectancy-value theory for motivation and measurescontrol beliefs, extrinsic motivation, intrinsic motivation, self-efficacy, task value, and Page 23.895.3test anxiety. MSLQ • Tutorial on osmosis (or Northern Lights), including pre and post tests Task Value • Tutorial on Northern Lights (or osmosis), including pre Manipulation and post tests • ReBlection on task value • Tutorial on
bioengineering plans employedEvaluators their bio- concentration concentration Measurement ofFunding from medical # of students en- Increase secondary Self efficacy forNSF courses rolling into single students under- STEM and Career Workshop courses of the standing and inter- aspirations (for sec- material for concentration est in STEM ca- ondary and post- secondary # of students reers secondary students) school teach- Improved and Plan to replicate or
expectations related to their majors and experiences.An encrypted numeric ID (privy only of the program support assistant and destroyed at the endof the program) is created for each participant with the main purpose of analyzing the genderrelated questions.MATERIALSSURVEY CONTENT: The survey instruments were chosen to collect program evaluationresponses and to measure beliefs, expectation/perceptions of engineering and science careers,self-efficacy, and other constructs. From the surveys, specifically the NSF-funded AssessingWomen and Men in Engineering (AWE) project at Penn State University provided several ofthe instruments used in this study [7]. After a review of the literature, an assessment plan wasdeveloped to focus on career, confidence
analyzing school, teacher, and classroom effects on student learning out- comes. Dr. Bagaka’s has also been involved in studies utilizing hierarchical linear modeling to identify the value-added indicators of school and teacher effectiveness on student achievement. His recent work on the role of teacher characteristics and practices on upper secondary school students’ mathematics self- efficacy was published in the International Journal of Science and Mathematics Education. Dr. Bagaka’s is a recent African Regional Research Fulbright Program scholar to Kenya where he conducted research on teacher beliefs and practices on high school mathematics self-efficacy.Dr. Matthew W Roberts, University of Wisconsin, Platteville Dr
motivation and subsequent academic achievement, we are assessingstudents’ perceived competence in and interest/value for engineering. Perceived competence isbeing measured using the 5-item self-efficacy scale from the Patterns of Adaptive LearningSurvey (PALS).21 A sample item includes ‘I’m certain I can master the skills taught in myengineering courses.’ Interest/value is being assessed in terms of students’ enjoyment and valuefor engineering using an 8-item interest/value scale developed Linnenbrink-Garcia andcolleagues.22 Sample items include ‘Engineering is exciting to me’ (enjoyment) and ‘Engineeringis practical for me to know’ (value). Pilot data obtained from Duke undergraduates indicated thatitems from both scales are highly reliable
III institution, CSULA has a large number of students from minoritygroups and low income families. Many students have low self-efficacy due to their lack ofacademic preparation. In the past two years, we have been continuously improving theimplementation of CPBL to address the learning issues for students from minority groups. In thispaper, we will share what we learned in our practice on how to effectively embed inquiry basedlearning through in-class and after class projects. Examples will be presented to show how todesign a project to complete a natural learning cycle and strategies will be described on how toconduct remote CPBL to ensure the achievement of learning outcomes for underpreparedstudents. Although the presented projects were
solving process. Motivation: including mastery goal for self-actualization (i.e., personal pursuit of well- being and passion); self-efficacy for maintaining optimal emotion and overcoming frustration due to failure; and persistency in valuable task until achieving goals; Metacognitive knowledge: including awareness of one’s beliefs regarding learning and creativity, and metacognitive knowledge of the following interrelated parts: (a) knowledge of one’s own cognitive and creative process; (b) conceptual knowledge about the specific cognitive and creative strategies that might be used for various learning and creativity tasks; and (c) procedural knowledge of when and where to use the
generation college students and other underrepresented groups such as genderand ethnicity8, 23, 24. Results of Flores23 show that traditional versus non-traditional contextualvariables influenced the strength of the linkage between interests, career self-efficacies, and Page 23.429.5career choices for Mexican Americans. Research specific to supports and barriers includes workconcerning coping efficacy versus barriers relative to the process variables for obtaining outcomeexpectations25 and a comparison of Bandura’s model to SCCT for contextual support andbarriers in engineering majors26. Qualitative research using SCCT includes research onengineering
”, Commissioned by the NCSU Friday Institute, 2007, http://www.tdhah.com/site_files/Teacher_Resources/MUVE/MUVE%20Documents/Dede_21stC- skills_semi-final.pdf36. Gardenfors, P. and Johansson, Cognition, Education, and Communication Technology, Routledge, 2005.37. Marra, R. and Bogue, B., “Women Engineering Students Self Efficacy – A Longitudinal Multi- Institution Study”, http://www.x-cd.com/wepan06/pdfs/18.pdf38. Akl, R., Keathly, D., and Garlick, R., “Strategies for Retention and Recruitment of Women and Minorities in Computer Science and Engineering”, http://www.cse.unt.edu/~rakl/AKG07.pdf39. Tindall, T., and Hamil, B., “Gender Disparity on Science Education: The Causes, Consequences, and Solutions”, Education, Vol. 125, Issue 2