expectations toward performance and acquisition of skills. Eachstudent’s perception of engineering identity and engineering self-efficacy seems to influencehow students measure their performance and standing within the discipline which in turninfluences their overall development of their particular engineering identity. This cyclical loopof expectations and identity development also seems to affect the navigational pathways thatstudents plan to take as undergraduate engineering students, for better or worse.Suggestions for future workWhile the information obtained from these interviews has shed light onto the field ofengineering identity formation in relation to student expectations, there is much more work thatcould be done to better understand this
previous educational experiences and “enter with lower self-efficacy beliefs aboutpersonal academic skills than the traditional student.”10 In addition to this barrier, manynontraditional students experience “feelings of isolation and not fitting in, lack of access toresources, scheduling conflicts, lack of course availability and course times, financial difficulties,and the lack of catering to nontraditional students detracted from the overall college experience.”11Additionally, the challenge of balancing work, school, and life can create pressures for the adultlearner. “According to the resource scarcity theory, going back to school creates another roledomain that competes for limited resources: the student’s time, energy, and finances.”12
persistence in an academic area is primarily influenced by twothings: expectancy for success and subjective task value. It has been a relatively consistentfinding that expectation for success (confidence or self-efficacy) will predict children’sachievement, while subjective task value (usefulness or enjoyableness) will predict children’spersistence and selection in any given subject.20In one application, Simpkins et al.21 explored the relationship between students’ interest andpersistence in science classes and students’ interest and understanding of science careers.Researchers concluded science activity predicted expectancy and subjective task value (confidentstudents also considered science careers) and proposed that exposure might increase
the interrelationship among individual, environmental, andbehavioral variables that have key impacts on academic and career choice5. Additionally, TPBsuggests that any behavior, like STEM choice and performance, can be explained by a person’sintentions to engage in the behavior. The predictors of a behavior are an evaluation of thebehavior, perceived social pressure to perform the behavior (viz, teamwork) self-efficacy inrelation to the behavior, also known in TPB as behavioral control, and intention to perform thebehavior6. SCCT, self-efficacy, outcome expectations, and goals operate together with personalcharacteristics and environmental contexts to help shape academic and career development7.While it is claimed that SCCT is comprised of
the role of engineer starters’ early academic experiences,including participation in project-based courses, on retention. Future work will broaden bothpredictors and outcomes. In particular, we plan to assess engineer starters’ attitude toward STEM(e.g., interest, self-concept, self-efficacy) and academic performance and retention. Future workwill include pre-tests and post-tests to control for pre-existing differences in attitude and interestby course enrollment. We will also examine the impact of other early academic experiences onretention, including research experiences and participation in other courses with hands-onlearning components.IntroductionIn order to remain competitive in science, technology, engineering, and mathematics (STEM
diminishes female confidence (stereotype threat) [13-15],• females have an inborn disposition for ‘caring’ or ‘humanities’ jobs [16], and• female secondary students have lower self-efficacy and interest in engineering [17].In addition to under-representation there is an unequal distribution of female enrolmentamongst the disciplines (See Figures 1 and 2). Understanding what draws a higherpercentage of female students to disciplines such as chemical engineering, may revealstrategies to increase female enrolment in other disciplines.Within this multi-stage research project, we will use survey research methods to betterunderstand the reasons for this under-representation. We hypothesize that one reason for theunder
shared understanding by organizational members regarding organizationalgoals, values, and general structures and procedures. When members are acculturated, theyusually have accepted the general goals and values of the organization, and are willing tointegrate into the culture. Familiarity with other individuals from the organization (i.e., get toknow the colleagues and establish relationships with members) can foster relationships (in bothmicro and macro-levels) bond individuals to their organizations, and become a way to increaseperceptions of self-efficacy and commitment toward the organization (Cheney et al, 2014).Recognition from others (i.e., perceiving one’s value to the organization and feeling recognized)can also link to job satisfaction
institutional data analyst. As a psychometrician, she revised the PSVT:R for secondary and undergraduate students, developed the TESS (Teaching Engineering Self-efficacy Scale) for K-12 teachers, and rescaled the SASI (Student Attitudinal Success Inventory) for engineering students. As a program evaluator, she evaluated the effects of teacher professional development (TPD) programs on elementary teachers’ attitudes toward engineering and students’ STEM knowledge through a NSF DRK-12 project. As an institutional data analyst, she is investigating engineering students’ pathways to their success. c American Society for Engineering Education, 2016 Enculturation of Diverse Students to the
,” showeda drop of 1.75 (P value < 0.00001 using an unranked T-test), from an initial 6.36 to a final 4.61.Interestingly, the place of these scores almost exactly reverses Q2, going from the highest initialscore to the lowest final score. We have not seen previous studies on this drop in self-efficacy ata time of increasing knowledge in the literatures of writing or communication. We understandthis shift as a clear indicator of a transition stage between novice and expert, and as a step inprofessionalization.We also saw a small increase (+ 0.35, P value 0.0193 using an unranked T-test) in Q8, “Iunderstand how to reflect on the communication choices I make in light of context, purpose, andaudience.” These terms were used consistently in workshops
77 college students chose to continue to the next more demanding firstcourse intended for CS majors, CS61A.Research MethodsFormative, mixed-method research was conducted to test out the effectiveness of Beauty and Joyof Computing (BJC) curriculum as implemented in UC Berkeley’s CS10, in attracting historicallyunderrepresented students. To gain a comprehensive analysis into the socio-curriculareffectiveness of the BJC curriculum as the first class in a student’s CS trajectory, it wasbenchmarked against CS61A—the first class for majors, and increasingly, for non-majors aswell.Survey instruments were developed to measure participants’ self-reported efficacy along severaldimensions. To determine the role of identity and self efficacy; as well as
of measuring impacts of theiruniversity Makerspace "through engineering design self-efficacy, retention in the engineeringmajor; and idea generation ability."Halverson and Sheridan31 in their comparative case study on different Makerspace invokedwork by Papert and Dewey as the theoretical underpinning of the Maker movement and itsrelation with education.Figure 4. Educational and developmental theoryEducational and developmental theoryThe allusion to the theories of thinking and development in the academic research literatureencourages our inquiry into these theories and how they are and can potentially be related tothe educational aspects of Makerspaces. Figure 4 shows these connections in the form of aconcept map.Papert’s32 theories on
anycorrelations between student learning styles, self-efficacy, attitudes/perceptions, andperformance in an undergraduate material balances course, in an effort to better understand ourstudent population and provide a basis for curricular development. We categorized the learningstyles engaged by exam problems of five instructors in their presentation and solution. While wediscovered several instances where students of one learning style preference either outperformedor underperformed relative to others, we made an even more interesting observation whilecategorizing the learning styles exploited by exam problems of different instructors. In mostcases, there was little variation between the learning styles exploited by individual instructorsover the course
college personnel and students in both educationalvenues. Forty-one interviews were conducted with 10+ at each CC site during the first semesterof our research. These data, along with a careful review of documents and websites availablefrom each CC and applicable higher education literature as a comparison informed therefinement of the CPPI which was developed, and tested in our previously described STEMcommunity college study.3The Refined College Pedagogical Practice Inventory (CPPI-R): Refinement, testing, and use ofthe CPPI has been informed by measurement research of educational psychologicalresearchers.31 Specifically, the inventory was initially designed with the intent of enabling us toexplore relationships among the dependent and
projects focusing on engaging stakeholders in forest management issues, surveys on public values of cultural ecosystem services, and psychographic market segmentation of sustainable tourism.Dr. Denise Wilson, University of Washington Denise Wilson is a professor of electrical engineering at the University of Washington, Seattle. Her research interests in engineering education focus on the role of self-efficacy, belonging, and other non- cognitive aspects of the student experience on engagement, success, and persistence and on effective methods for teaching global issues such as those pertaining to sustainability. c American Society for Engineering Education, 2016 Cross-Validation of a
dissociation from engineering but is more a measure of one’s “fit”14. FGS students may seetheir salient identity as separate from engineering, but they choose to associate (major in)engineering and thus take on engineering’s group affiliation. Social identity serves as theoverlying structure guiding our work. This theory serves to potentially bridge the gap betweenengineering identity and belongingness to engineering. Additionally, the role of social capitalfalls into this theory as it serves to moderate entrance into the engineering group and thedevelopment of feelings of belongingness in engineering. Identity, belongingness, and socialcapital will be used to measure the students’ engineering social identity for this study. Explicitframing of how we
Process: An Expert Study of Advanced Practicing Professionals, in Proceedings of ASEE Annual Conference & Exposition. 2005, ASEE: Portland, OR. p. 1-27.55. Carberry, A.R., H.S. Lee, and M.W. Ohland, Measuring engineering design self‐ efficacy. Journal of Engineering Education, 2010. 99(1): p. 71-79.56. Nocito-Gobel, J., et al., Are Attitudes Toward Engineering Influenced by a Project-Based Introductory Course, in Proceedings of ASEE Annual Conference and Exposition: The Changing Landscape of Engineering and Technology Education in a Global World. 2005, ASEE: Portland, OR. p. 693-706.57. Sheppard, S., et al., Exploring the Engineering Student Experience: Findings from the Academic Pathways of People
advancement of engineering education. CAEE-TR-10-02. 2010, Center for the Advancement of Engineering Education: Seattle, WA, USA.7. Seymour, E., & Hewitt, N. M., Talking about leaving: Why undergraduates leave the sciences, 1997, Boulder, CO,USA: Westview Press.8. Marra, R. M., Rodgers, K. A., Shen, D., & Bogue, B., Women engineering students and self-efficacy: A multi-year, multi-institution study of women engineering student self-efficacy, Journal of Engineering Education, 2009, Vol. 98, No. 1, pp. 27-38.9. Lord, S. M., Layton, R. A., & Ohland, M. W., Trajectories of electrical engineering and computer engineering students by race and gender, IEEE Transactions on Education, 2011, Vol. 54, No. 4, pp. 610
implicitlearning.There has been little to no work done to understand how learners learn in Makerspaces, andto find or develop tools to assess this learning. In the recent ASEE conference Morocz et al.11 presented plans of measuring the impacts of a university makerspace “through engineeringdesign self-efficacy, retention in the engineering major; and idea generation ability".A study by the Maker Ed Open Portfolio Project 12 strengthens the promise of our proposal toemploy self-reflection to assess learning in Makerspaces. This work presents self-reporteddata by Makerspaces all over the United States about their alignment with nationaleducational initiatives. Most sites reported themselves as being aligned with STEM (94%)(Science, technology, engineering, and
of the academic rigor and transition issues they are facing. Thecombination of rigorous coursework, the freedom to try and fail, and significant peer and staffsupport allows for the failure and mastery experiences needed to develop self-efficacy and agrowth mindset.19, 24Other aspects of RESP were also designed based on a number of best practices in the field.Research demonstrates study groups are a crucial aspect of success in undergraduate STEMprograms.25 Because most students in RESP were among the most capable in their high school,few arrive at Rice having worked extensively in groups of equally capable peers. Additionally,students from groups traditionally underrepresented in STEM fields may resist asking for help soas not to confirm
concept of persistence as amanifestation of motivation, while Graham et al 14 view motivation as a driver of studentengagement. Self-efficacy or confidence is one among several constructs underlying motivation.Additionally, our research included a consideration of the learning style preference amongst thedifferent genders and ethnic groups. In brief the following is what research suggests. First, intraditional science and engineering institutions, individual personnel success is highly regarded.However, women and underrepresented minorities commonly place high value on people andgroup-oriented activity 15. Pearson & West suggest that the traditional classroom structure isdesigned to foster independent, non-collaborative thinking and is most
mathematics (STEM) graduates1, and education and psychology research hasshown that motivation has an effect on student success in STEM fields2–4. As described by theFuture Time Perspective (FTP) theory, motivational attributes have been shown to positivelyaffect student achievement and persistence5. Additionally, Self-Regulated Learning (SRL) hasbeen positively linked with increased self-efficacy of undergraduates6. FTP and SRL have oftenbeen researched separately, but previous literature has reported that there is a link between thesetwo areas2,7–11. We seek to observe the student experience in terms of FTP and how FTP affectsstudent task-specific behavior in terms of SRL, thus investigating this link for engineeringstudents. This paper describes a
influence the persistence or resilience of STEM students to stay focused and engaged in pursuitof their personal academic goals.Of particular importance to Packard’s STEM mentorship program development are three factorsshe labels “capacity”, “interest” and “belongingness.” Capacity refers to a student’s ability to learnand demonstrate requisite performance. Mentors can help students improve their personal capacitythrough various practice opportunities and timely, effective feedback. More importantly, suchmentoring can improve a student’s self-efficacy of confidence which Packard indicates is often abetter predictor of future performance than demonstrated capability. A student’s interest in STEMcan be expected to wax and wane as they pursue their
year of UUR, a survey instrument was developed which assessed eachstudent’s interest and self-efficacy in STEM 23. The assessment was influenced by related STEMassessments, such as the STEM semantics survey and the STEM Career interest Questionnaire 20.The assessment asked questions regarding students understanding of STEM principles, interest inSTEM topics, careers, and fields of study. According to Wright, in that first year of study,quantitative data received from the surveys did not reveal that the ROV activity had made anystatistically significant impact on student interest in STEM areas. Researchers still believed,however, based on observations, and on teacher, student, and administrative feedback, that theROV program had potential to
Capstone Design: Inductively Enhanced”, Proceedings of the ASEE 2011 Annual Conference, 22.1562.1 - 22.1562.112. Elmer Grubbs and Martha Ostheimer (2001), “ Real World Capstone Design Course”, Proceedings of the ASEE 2001 Annual Conference, 6.835.1 – 6.835.73. Joanna Dulap (2005), “Problem-Based Learning and Self-Efficacy: How a Capstone Course Prepares Students for a Profession” - Educational Technology Research and Development, March 2005, Vol. 53, Issue 1, pp 65-83.4. Randolph Jones (2000), “Design and implementation of computer games: a capstone course for undergraduate computer science education, Proceedings of the thirty-first SIGCSE technical symposium on Computer science education, Pages 260-264, ACM New York
: http://www.ncca.ie/uploadedfiles/JuniorCycleReview/ESRIComment.pdf23. Bandura, A. (1997). Self-Efficacy: The exercise of control. New York: W.H Freeman24. Puccio, G. J., Wheeler, R. A., & Cassandro, V. J. (2004). Reactions to creative problem solving training: Does cognitive style make a difference. The Journal of Creative Behavior, 38, 192-216.25. de Bono, E. (1970). Lateral thinking. London: Penguin Group26. State Examinations Commission. (2009). Chief examiners report on materials technology Wood. Athlone: State Examinations Commission.27. Houtz, J. C., & Krug, D. (1995). Assessment of creativity: Resolving a mid-life crisis. Educational Psychology Review, 7(3), 269-30028. McAuley, E., Duncan, T., &
the pre- and post-surveys ask “What do you think it means tobe an engineer?” and the difference in answers allow researchers to determine if theirunderstanding of what an engineer is/does has changed after attending the camp.An additional note on the research surveys involves the ranking questions. The researchquestions draw from the NSF project “Assessing Women and Men in Engineering” 10. Theranking questions are identical from the pre- and post-surveys in order to determine if significantchanges in self-efficacy were made. These questions include, “I consider myself to be good atscience” and “I consider myself to be good at math”. However the camp does not focus onteaching any specific aspects of these subjects or explicitly building self
Efficacy and BeliefInstrument or STEBI during the first week of the program and again in December of 2015.34Both the MTEBI and STEBI collect information about the teachers’ self-efficacy and expectedstudent outcomes.34 For the 2015 cohort changes in the Math and Science teachers’ self-efficacyand expected student outcomes were not significant at the 0.05 level.Results of the evaluations obtained as of January 2016 were mapped to the detailed programobjectives and are summarized below. Recommendations for adjustments are included at the endof each objective summary.Objective A: Teach engineering concepts to over 1,000 K-12 students over the project period,including students from schools with a significant minority population: Participants
, students often lack formal preparation for the meta-professional skillsrequired of faculty to be successful in their roles1,3. Insufficient preparations for faculty careersresults in low self-efficacy in students and can affect doctoral students’ performances as futurefaculty5.One way to potentially improve preparation of future faculty through engineering doctoraleducation is doctoral students’ participation in professional development seminars that allowsthem to explore different dimensions of faculty work. Professional development seminars canprovide formal opportunities for students to socialize themselves into faculty roles, receiveguidance from faculty and professional speakers on various aspects of faculty life, and becomeaware of the
engineering; what it takes to be successful inthe engineering program; and their advice to incoming minority students. A fourth questionasked for their assessment of the effectiveness of seven academic support program components.Major student responses were coded for thematic content or tabulated and then entered intoregression equations against four measures of achievement, including students’ GPA, longevityin the program, average SAT/ACT scores of minority students in the school of matriculation, andtheir school's effectiveness in graduating minority students as assessed by 6-year graduationrates. Responses positively associated with achievement indices were then factor analyzed toisolate common clusters associated with success in engineering
theimpact of PFX on students’ prototyping awareness. In this study, students at a large Mid-Atlantic university were taught three prototyping lensesbased on the PFX methodology: (1) Prototyping for Viability, (2) Prototyping for Feasibility, and(3) Prototyping for Desirability. This paper presents preliminary findings on the relationshipbetween these three prototyping lenses and students’ prototyping awareness, which we define asstudents’ ability to identify their mental models during the prototyping process. We useprototyping awareness as a proxy to measure adoption and implementation of PFX methods. ThePrototyping AWareness Scale, or PAWS was created for this study, and we discuss its internalconsistency and future iterations. Data were