Conference Session

Multidisciplinary Effects on Student Learning

Collection

2016 ASEE Annual Conference & Exposition

Authors

Tela Favaloro, University of California, Santa Cruz; Tamara Ball, University of California, Santa Cruz; Zachary W Graham, University of California, Santa Cruz; Michael S. Isaacson, University of California, Santa Cruz

Tagged Topics

Diversity

Tagged Divisions

Multidisciplinary Engineering

Paper ID #14844Facilitating Learner Self-efficacy through Interdisciplinary Collaboration inSustainable Systems DesignDr. Tela Favaloro, University of California, Santa Cruz Tela Favaloro received a B.S. degree in Physics and a Ph.D. in Electrical Engineering from the Univer- sity of California, Santa Cruz. She is currently working to further the development and dissemination of alternative energy technology; as project manager of a green building design initiative and researcher with the Center for Sustainable Engineering and Power Systems. Her background is in the development of characterization techniques and

Conference Session

Measurement and Instrumentation

Collection

2015 ASEE Annual Conference & Exposition

Authors

Anthony Bourne, Wright State University; Nathan W. Klingbeil, Wright State University; Frank W. Ciarallo, Wright State University

Tagged Topics

Diversity

Tagged Divisions

Educational Research and Methods

intervention on studentmathematics self-efficacy: Development and application of revised measurement tool Page 26.1142.2Research into the effectiveness of a mathematics intervention course for first year engineeringstudents revealed anomalous results in relation to student persistence. While previous studies ofperformance of college engineering students showed that ACT Math scores were highly linearlypredictive of student persistence outcomes, the study in question did not show similar results.The study revealed an interaction between ACT Math and high school GPA for students thatcompleted the course. The results showed an inverse relationship between ACT Math

Conference Session

First-Year Programs Division Technical Session 2A: Using Alternative Measurements to Look at Students and Their Success

Collection

2016 ASEE Annual Conference & Exposition

Authors

Nicholas Andres Brake, Lamar University; James C. Curry

Tagged Divisions

First-Year Programs

students during the first andfinal week of the semester to assess the gains in each of the mentioned categories. The surveywas comprised of questions from the questionnaire published by Mamaril19 and Carberry et al.20that are used to measure general, skills, tinkering, and design self-efficacy, and students’engineering design motivation and confidence, respectively. The first 18 items were taken fromCarberry et al.20 which uses a 11 point Likert scale ranging from 0 to 100 with ten pointincrements; and shown to have excellent internal group reliability (Cronbach alpha of 0.96 and0.95, respectively) and significantly differentiate motivation, anxiety, and confidence. Thefollowing 14 items were taken from Mamaril19, which uses a six point Likert

Conference Session

First-Year Programs Division Technical Session 5: Identity & Belonging

Collection

2024 ASEE Annual Conference & Exposition

Authors

Javeed Kittur, University of Oklahoma; Moses Olayemi, University of Oklahoma; Tierney Harvey, University of Oklahoma; Haley Taffe, University of Oklahoma

Tagged Divisions

First-Year Programs Division (FYP)

), we focus on the potential of leveraging the CPPs as a way to increase students’ self-efficacy, persistence within engineering, and sense of belonging. This study addresses thefollowing research question, “What factors influence first-year engineering students’ perceptionsof their engineering self-efficacy, design self-efficacy, intentions to persist, and sense of belongingthrough the application of community-partnered projects?”Methods1. Development of the Survey InstrumentThe survey instrument was developed during the fall of 2023 by an undergraduate student andthree faculty members. The instrument included a total of six scales (please refer Table 1). Thesurvey instrument measures the perceptions of first-year engineering students

Conference Session

Self-efficacy and Emotion: ERM Roundtable

Collection

2015 ASEE Annual Conference & Exposition

Authors

Laura Hirshfield, University of Michigan; Debbie Chachra, Olin College of Engineering; Cynthia J. Finelli, University of Michigan; Jeremy M. Goodman, Franklin W. Olin College of Engineering

Tagged Topics

Diversity

Tagged Divisions

Educational Research and Methods

questions. 1. Did students’ academic confidence or engineering self-efficacy improve after the project course? 2. Were there differences between the academic confidence or self-efficacy of male and female students? 3. Was there a relationship between the tasks students engaged in and their incoming confidence and self-efficacy measures? 4. Did any tasks correlate to observable changes in confidence or self-efficacy measures?Both academic self-confidence and self-efficacy have a strong effect on student motivation anddecision-making. Academic self-confidence in three particular areas (problem-solving,16 mathand science,17–19 and professional and interpersonal skills7) have been found to be importantfactors in student

Conference Session

Student Beliefs, Motivation and Self Efficacy

Collection

2014 ASEE Annual Conference & Exposition

Authors

Nora B. Honken, University of Louisville; Patricia A Ralston, University of Louisville; Kate E. Snyder, University of Louisville

Tagged Divisions

Educational Research and Methods

the current study. Of these, 495 completed the survey(98% response rate). The final sample consisted of 479 students (95% participation rate) with Page 24.579.3complete data for all measures included in the analyses. Demographic information for thesample is provided in Table 1. Of note, gender composition for our cohort is relativelycomparable to national averages, but the cohort was less ethnically diverse than the nationalpopulation of engineering students.18 Average ACT composite score for the participants was28.5 (SD = 3.16) and the average ACT math score was 29.0 (SD = 3.16). Forty-one percent ofthe students had a weighted high school GPA

Conference Session

First-year Programs Division: Self Efficacy

Collection

2018 ASEE Annual Conference & Exposition

Authors

Joshua L. Hertz, Northeastern University

Tagged Divisions

First-Year Programs

naturally uncomfortable towork on open-ended problems, because it feels risky to proceed along an ambiguous solutionpath. Nevertheless, some students seem to be more confidently uncomfortable, ready and willingto begin working on open-ended problems. We sought in this study to understand the factors thatmake a student better able to begin work on these projects without directed guidance from theinstructor. Here, this student ability is ascribed to, in part, a student’s ambiguity tolerance andself-efficacy on open-ended problems. A survey instrument to measure ambiguity tolerance and self-efficacy on open-endedproblems was created and subject to internal validation. Students taking a 2-course sequence ofrequired, foundational courses over

Conference Session

First-year Programs Division: Self Efficacy

Collection

2018 ASEE Annual Conference & Exposition

Authors

Stacey Leigh Kelly, Virginia Tech; Darren K. Maczka, Virginia Tech; Jacob R. Grohs, Virginia Tech

Tagged Divisions

First-Year Programs

has shown to be related to students’ choice to leaveengineering. Jones et al. [8] found that engineering belonging was the most significant predictor of first-yearengineering students’ intention to remain in their selected engineering major.Engineering program expectancy. Expectancy is a subjective evaluation of one’s competence in a particulardomain.19 Self-perceptions of competence are central to many theories in the field of motivation, such as self-concepttheory,20 self-efficacy theory,21 and expectancy-value theory.16 An individual’s expectancy beliefs are influenced bymany factors including past experiences (e.g. how well they performed in a high school math class), the influences ofsocializers (e.g., parents, teachers and peers) and

Conference Session

Self-efficacy and Emotion: ERM Roundtable

Collection

2015 ASEE Annual Conference & Exposition

Authors

Jenefer Husman, Arizona State University; Katherine C Cheng, Arizona State University; Krista Puruhito, Arizona State University; Evan J Fishman, Stanford University

Tagged Divisions

Educational Research and Methods

for university photovoltaics education. Paper presented and published at the 37th Institute of Electrical and Electronic Engineers, Photovoltaic Specialists Conference. Seattle, WA.[3] Suresh, R. (2007). The relationship between barrier courses and persistence in engineering. Journal of College Student Retention: Research, Theory & Practice, 8, 215–239.[4] Nelson, K. G., Shell, D. F., Husman, J., Fishman, E. J., & Soh, L. K. (2014). Motivational and Self‐Regulated Learning Profiles of Students Taking a Foundational Engineering Course. Journal of Engineering Education, 104(1), 74-100.[5] Usher, E. L., & Pajares, F. (2008). Sources of self-efficacy in school: Critical review of the literature and

Conference Session

Self-efficacy and Emotion: ERM Roundtable

Collection

2015 ASEE Annual Conference & Exposition

Authors

Sarah E Zappe, Pennsylvania State University, University Park; Philip M. Reeves, Pennsylvania State University, University Park; Irene B. Mena, University of Illinois, Urbana-Champaign; Thomas A. Litzinger, Pennsylvania State University, University Park

Tagged Divisions

Educational Research and Methods

Paper ID #11165A cross-sectional study of engineering students’ creative self-concepts: An ex-ploration of creative self-efficacy, personal identity, and expectationsDr. Sarah E Zappe, Pennsylvania State University, University Park Dr. Sarah Zappe is Research Associate and Director of Assessment and Instructional Support in the Leonhard Center for the Enhancement of Engineering Education at Penn State. She holds a doctoral degree in educational psychology emphasizing applied measurement and testing. In her position, Sarah is responsible for developing instructional support programs for faculty, providing evaluation support

Conference Session

ERM: Self-Efficacy, Motivation, and MORE!

Collection

2022 ASEE Annual Conference & Exposition

Authors

Jan Edwards, College of Lake County; ANA PIZANO, College of Lake County

DescriptionEach semester students are selected based on financial need, program of choice, level ofmathematic preparation and a personal essay. Once selected, these students attend weeklytutoring or advising and provide updates on their academic progress. In addition, near the start ofthe fall semester and towards the end of the spring semester the scholars along with the entireECS population will receive a survey to provide a measure of their self-efficacy relative toengineering, tinkering and design, sense of belonging, and inclusion.The CLC Baxter Innovation Lab was selected as an integral part of the expanded NSF Scholarsprogram, including team building activities with NSF Scholars, using the lab as a tutoring hub,and employing NSF scholars as

Conference Session

ERM: Self-Efficacy, Motivation, and MORE!

Collection

2022 ASEE Annual Conference & Exposition

Authors

Campbell Bego, University of Louisville; Jeffrey Hieb, University of Louisville; Patricia Ralston, University of Louisville; Thomas Tretter; Jason Immekus; Jody Zhong, University of Louisville

possible to succeed in engineering with a mid-level grade and correspondingskills. Simultaneously, the group of C-in-math students who left engineering present anopportunity for interventions; there is a whole group of capable students who decide not tocontinue but are capable. Students with a C grade in the first semester math course thereforeappear to be a potentially productive subgroup that merit further investigation for strengtheningengineering retention.In addition to math performance, several noncognitive variables such as a student’s sense ofbelonging [12] or self-efficacy [13]–[15] have been found to predict student retention. Thesefactors are interesting because not only can they be used to predict student decision-making, butthey are

Conference Session

Student Beliefs, Motivation and Self Efficacy

Collection

2014 ASEE Annual Conference & Exposition

Authors

Courtney June Faber, Clemson University; Sarah Jane Grigg, Clemson University; Adam Kirn, Clemson University; Justine M. Chasmar; Lisa Benson, Clemson University

Tagged Divisions

Educational Research and Methods

-Level MotivationsSelf-efficacyBandura's work in self-efficacy examines motivations toward short-term tasks.14 Self-efficacyspeaks to students’ specific perceptions on how they will perform on a task.15 Self-efficacy hasbeen shown to influence the use of learning strategies on tasks related to students' courses.16While self-efficacy and expectancy are correlated constructs when examining goals with thesame time scale8, self-efficacy was developed to examine short-term tasks that require a highlevel of granularity17 and makes it more useful for examining motivations toward short-termgoals.For this work, problem solving items were adapted from the Attitudes and Approaches toProblem Solving survey18 to appropriately assess student self-efficacy for

Conference Session

ERM: Self-Efficacy, Motivation, and MORE!

Collection

2022 ASEE Annual Conference & Exposition

Authors

Robert Nagel, James Madison University; Bethany Popelish, James Madison University; Melissa Aleman, James Madison University; Tobias Reynolds-Tylus, James Madison University

%), followed byAsian (6.9%), Black or African American (5.6%), Hispanic/Latino (3.1%), and Native American(0.6%). The ratios of male to female and White to non-White in the sample is comparable to thetotal population. Participants reported working on anywhere from 1 to 25 projects (M = 4.87, SD= 3.12, Median = 4, Mode = 3), reported an average number of 2.84 of projects involvingmaking (SD = 2.68, Median = 2, Mode = 3, Range = 0-25).All items were measured on a 7-point Likert scale (1 = corresponds not at all to 7 = correspondsexactly). See Table 1 for a zero-order correlation matrix for study variables. The current studyused a modified version of the basic needs satisfaction scale [18]. Autonomy was measured withsix items (e.g., “I feel like I am

Conference Session

First-year Programs Division: Self Efficacy

Collection

2018 ASEE Annual Conference & Exposition

Authors

Brenda Read-Daily, Elizabethtown College; Kurt M. DeGoede, Elizabethtown College; Stacey L. Zimmerman, Elizabethtown College

Tagged Divisions

First-Year Programs

] [7].Other tools that are helpful in developing self-awareness are the Myers-Briggs Type Indicator(MBTI), the DiSC profile, and the Kolb Learning Style Inventory. These inventories all measuredifferent aspects of an individual; CSF measures natural talent, MBTI measures preferred modesof psychological processing, DiSC measures behavioral style, and Kolb measures individuallearning styles [8]. Our campus chose to utilize the CSF as our primary tool because of Gallup'sspecific focus on college students with their StrengthsQuest platform. This platform utilizes thesame inventory (CSF), but the information provided after taking the inventory is geared towardstudents.Within the Engineering education community, MBTI has been widely used in team

Conference Session

Student Division Technical Session 5: Self- Efficacy

Collection

2024 ASEE Annual Conference & Exposition

Authors

Xinyi Ma, University of Toronto; Janet Lam, University of Toronto

Tagged Divisions

Student Division (STDT)

still suggested to apply parametric tests if both groupshave sample sizes larger than n=15 even when some test assumptions are not met [16].When data collection from the mid-term and end-of-course surveys are completed, we propose touse two-way mixed ANOVA to measure how the two groups of students’ programming attitudesand self-efficacy evolve over the semester. Ordinal logistic regression might also be conducted totake more factors that could affect attitudes and efficacy levels into account. Besides, qualitativeanalysis will also be performed on the courses they have taken and the courses they think thathave prepared them for the lab activities to provide additional information on the findings.ResultsAccording to the survey data, previous

Conference Session

Student Beliefs, Motivation and Self Efficacy

Collection

2014 ASEE Annual Conference & Exposition

Authors

Micah Stickel, University of Toronto; Siddarth Hari, University of Toronto; Qin Liu, University of Toronto

Tagged Divisions

Educational Research and Methods

questions on a 7-point Likert scale were asked to students toinvestigate their level of confidence in various aspects of the course materials and studyingengineering. Those related to Engineering Self-Efficacy were taken directly from theLongitudinal Assessment of Engineering Self-Efficacy instrument 20. Through factor analysisusing polychoric correlation, three factors were derived. Those questions and related factors arereported in Table 7.Table 7. Cronbach's Alpha and Loaded Factors of Measuring Self-Efficacy Cronbach’s Alpha Factors Traditional Cohort Inverted CohortSelf-efficacy related to explaining course

Conference Session

Student Beliefs, Motivation and Self Efficacy

Collection

2014 ASEE Annual Conference & Exposition

Authors

Adam Kirn, Clemson University; Courtney June Faber, Clemson University; Lisa Benson, Clemson University

Tagged Divisions

Educational Research and Methods

-1055950).References [1] Adam R. Carberry, Hee-Sun Lee, and Matthew W Ohland. “Measuring Engineering De- sign SelfEfficacy”. In: Journal of Engineering Education (2010), pp. 71–79. URL: http: / / onlinelibrary . wiley . com / doi / 10 . 1002 / j . 2168 - 9830 . 2010 . tb01043 . x / abstract. [2] A. Bandura. “Guide for constructing self-efficacy scales”. In: Self-efficacy beliefs of ado- lescents. Information Age Publishing, 2006, pp. 307–337. URL: http://books.google. com/books?hl=en\&lr=\&id=Cj97DKKRE7AC\&oi=fnd\&pg=PA307\&dq=GUIDE+FOR+ CONSTRUCTING+SELF-EFFICACY+SCALES\&ots=cF-Zx\_vHu5\&sig=onq0GKyPXkXj80f6IoboGeGDuYc. [3] MA Hutchison et al. “Factors influencing the self-efficacy beliefs of

Conference Session

First-year Programs Division: Self Efficacy

Collection

2018 ASEE Annual Conference & Exposition

Authors

Tanya Dugat Wickliff, Texas A&M University; So Yoon Yoon, Texas A&M University; Jacques C. Richard, Texas A&M University; Noemi V. Mendoza Diaz, Texas A&M University

Tagged Topics

Diversity

Tagged Divisions

First-Year Programs

. AcknowledgementThis work was conducted under the auspices of the National Science Foundation (NSF) undergrant number EEC-1640521. However, any items expressed in this paper do not necessarilyrepresent the views of NSF or its affiliates.ReferencesBandura, A. (1977). Self-Efficacy: Toward a Unifying Theory of Behaviorial Change. Psychological Review, 84(2), 191-215.Bandura, A. (1982). Self-efficacy mechanism in human agency. American Psychologist, 37(2), 122-147.Engineering Accreditation Commission (2015). Criteria for accrediting engineering programs: Effective for reviews during the 2016-2017 accreditation cycle. Baltimore, MD: ABETFantz, T. D., Siller, T. J., & DeMiranda, M. A. (2011). Pre-collegiate factors influencing the self

Conference Session

Student Division Technical Session 5: Self- Efficacy

Collection

2024 ASEE Annual Conference & Exposition

Authors

Jeffrey Luke Morrison, University of South Florida; Chris S Ferekides, University of South Florida; Dhinesh Balaji Radhakrishnan, Purdue University

Tagged Topics

Diversity

Tagged Divisions

Student Division (STDT)

Paper ID #44125Examining Imposter Syndrome and Self-Efficacy Among Electrical EngineeringStudents and Changes Resulting After Engagement in Department’s RevolutionaryInterventionsMr. Jeffrey Luke Morrison, University of South Florida Jeffrey Luke Morrison is an undergraduate student pursuing his bachelors in Electrical Engineering at the University of South Florida with focuses in wireless circuits and nano-scale systems. He is an IEEE member and also a member of the USF Honor’s College. In addition to pursuing his EE degree, he is also pursuing a BS in Quantitative Economics and Econometrics.Dr. Chris S Ferekides, University

Conference Session

Student Division Technical Session 5: Self- Efficacy

Collection

2024 ASEE Annual Conference & Exposition

Authors

Karen Elizabeth Nortz, Cornell University; Allison Godwin, Cornell University; Linda DeAngelo, University of Pittsburgh; Danielle V. Lewis; Kevin Jay Kaufman-Ortiz, Purdue University; Charlie Díaz, University of Pittsburgh; Carlie Laton Cooper, University of Georgia

Tagged Topics

Diversity

Tagged Divisions

Student Division (STDT)

Their Own Words: How Aspects of Engineering Education Undermine Students’ Mental Health,” in 2022 ASEE Annual Conference & Exposition Proceedings, Minneapolis, MN: ASEE Conferences, Aug. 2022, p. 40378. doi: 10.18260/1-2–40378.[33] N. Mamaril, E. Usher, C. Li, D. Economy, and M. Kennedy, “Measuring Undergraduate Students’ Engineering self‐efficacy: A validation study,” J. Eng. Educ., vol. 105, no. 2, pp. 366–395, Apr. 2016, doi: 10.1002/jee.20121.[34] K. J. Jensen and K. J. Cross, “Engineering stress culture: Relationships among mental health, engineering identity, and sense of inclusion,” J. Eng. Educ., vol. 110, no. 2, pp. 371–392, Apr. 2021, doi: 10.1002/jee.20391.[35] S. Farrell, A. Godwin

Conference Session

Student Division Technical Session 5: Self- Efficacy

Collection

2024 ASEE Annual Conference & Exposition

Authors

David Myers, Rowan University; Matthew Currey, Rowan University; Luciano Miles Miletta, Rowan University; Darby Rose Riley, Rowan University; Kaitlin Mallouk, Rowan University

Tagged Divisions

Student Division (STDT)

Paper ID #42380The Effect of Ego Network Structure on Self-efficacy in Engineering StudentsDavid Myers, Rowan UniversityMatthew Currey, Rowan UniversityLuciano Miles Miletta, Rowan UniversityDarby Rose Riley, Rowan University Darby Riley is a doctoral student of engineering education at Rowan University. She has a special interest in issues of diversity and inclusion, especially as they relate to disability and accessibility of education. Her current research is focused on the adoption of pedagogy innovations by instructors, specifically the use of reflections and application of the entrepreneurial mindset. Her previous

Conference Session

ERM: Self-Efficacy, Motivation, and MORE!

Collection

2022 ASEE Annual Conference & Exposition

Authors

Kai Jun Chew, Virginia Polytechnic Institute and State University; Holly Matusovich, Virginia Polytechnic Institute and State University

to complement tests.Keywords: Test, Exams, Assessment, Instructor, BeliefsIntroduction Tests have been a default form of assessment in concept-heavy fundamental engineeringcourses (Lord & Chen, 2015; Sheppard et al., 2009). Situating tests in the expansive assessmentliterature, tests play important roles in the learning process, such as the “testing effect” in whichstudents retain information after multiple testing (Roediger et al., 2011). However, tests alsocome with various disadvantages, such as being not appropriate for measuring conceptual change(Streveler et al., 2008) and decreasing motivation to learn (Tan, 1992; Vaessen et al., 2017).Thus, tests being the go-to assessments may not be an ideal way of assessing and helping

Conference Session

Biomedical Engineers and Professional Development - June 23rd

Collection

2020 ASEE Virtual Annual Conference Content Access

Authors

William H. Guilford, University of Virginia

Tagged Topics

Diversity

Tagged Divisions

Biomedical Engineering

be a better mediator of affect – how one feels about a task – while thelatter is a better mediator of academic achievement [4]. Further, self-concept may positivelyinfluence self-efficacy.We hypothesized that BME students’ self-concepts and feelings of self-efficacy might relate totheir unusual career goals (relatively speaking, among engineering fields). We therefore soughtto explore BME students’ career self-concept as engineers and as clinicians, and the relationshipof those self-concepts to engineering design self-efficacy [5]. Both constructs are measured viainstruments that rely on self-declarations – also known as explicit measures. Self-declarations, orexplicit measures, of self-concept carry with them the concern of unreliability

Conference Session

Relationships Between Skills and Knowledge Domains

Collection

2020 ASEE Virtual Annual Conference Content Access

Authors

Zhen Zhao, Arizona State University; Samantha Ruth Brunhaver, Arizona State University

Tagged Topics

Diversity

Tagged Divisions

Liberal Education/Engineering & Society

interpersonalskills are less likely to pursue a career in engineering (vs. in a non-engineering field) thanstudents with lower self-confidence in these skills [6, 10]. However, only one of the abovestudies [9] investigated the connection between engineering undergraduates' self-efficacy in theircommunication skills and their perceived importance of these skills directly, despite a suggestionfrom Riemer [4] that they might be related. Further, none of the above studies developedinstantiated items with which to measure communication skills. They instead relied on genericterms such as verbal communication skills, written communication skills, or presentation skills,suggesting that engineering students may not have a true understanding of what is involved ineach

Conference Session

First-Year Programs: Metacognition, Self-Efficacy, and Motivation #1

Collection

2020 ASEE Virtual Annual Conference Content Access

Authors

Vanessa Svihla, University of New Mexico; Pil Kang, University of New Mexico; Yan Chen, University of New Mexico; Chen Qiu, University of New Mexico; Jordan Orion James, University of New Mexico

Tagged Divisions

First-Year Programs

baselinegroup in a first-year chemical engineering course at a Hispanic-serving research university in thesouthwest United States. Students completed measures of design self-efficacy, explicit designknowledge, and implicit design framing knowledge as a pre/post course measure. Usingexploratory factor analysis, we identified two explicit design knowledge factors ill-structuredness and framing. Using repeated measures ANOVA, we found that students in bothbaseline and implementation groups reported moderate design self-efficacy, with post-coursescores slightly but significantly higher. No difference was found by group or timepoint onstudents’ explicit knowledge of design. Compared to the baseline, the implementation groupshowed more growth in implicit

Conference Session

Pedagogical Issues in Computing

Collection

2011 ASEE Annual Conference & Exposition

Authors

Chia-Lin Ho, North Carolina State University; Dianne Raubenheimer, North Carolina State University

Tagged Divisions

Computers in Education

AC 2011-993: COMPUTING-RELATED SELF-EFFICACY: THE ROLESOF GENDER, ACADEMIC PERFORMANCE, AND COMPUTATIONALCAPABILITIESCHIA-LIN HO, North Carolina State University Chia-Lin Ho is a doctoral student in Industrial/Organizational Psychology at North Carolina State Uni- versity. She received a B.S. in Psychology and a Bachelor of Business Administration at the National Cheng-Chi University in Taiwan in 2002 and her Masters in I/O Psychology at the University of North Carolina at Charlotte in 2005. Her research interests include measurement and evaluation issues, individ- ual differences, leadership, cross-cultural studies, work motivation, and the application of technology on human resources management.Dianne Raubenheimer

Conference Session

Issues of Cooperative Education I

Collection

2008 Annual Conference & Exposition

Authors

Joe Raelin, Northeastern University; Jerry Hamann, University of Wyoming; David Whitman, University of Wyoming; Rachelle Reisberg, Northeastern University

Tagged Divisions

Cooperative & Experiential Education

careers haveresulted in fewer women entering these fields. Since then, empirical studies have supported thistheory, finding that college-aged women’s self-efficacy for traditionally female occupations wassignificantly higher than their self-efficacy within male-dominated fields.17, 18Conceptual FrameworkThis study seeks to develop a theory that examines the effects cooperative education as well asother factors (demographics, contextual supports) have on self-efficacy beliefs. It includes well-established measures of science/ math/ engineering academic self-efficacy and of career self-efficacy while introducing a new construct, work self-efficacy. Figure 1 displays the conceptualframework for the study, depicting the relationships among

Conference Session

What Are We Learning About Co-op and Experiential Education Experience?

Collection

2012 ASEE Annual Conference & Exposition

Authors

Rachelle Reisberg, Northeastern University; Joseph A. Raelin, Northeastern University; Margaret B. Bailey, Rochester Institute of Technology; David L. Whitman, University of Wyoming; Jerry Carl Hamann, University of Wyoming; Leslie K. Pendleton, Virginia Tech

Tagged Divisions

Cooperative & Experiential Education

of the data summary and discussion given below will be appearing in aparallel publication.1 The immediacy with which the preliminary data has seen publicationspeaks, we believe, to the broad interest which this study has gained. In particular, theintroduction and demonstration of the work self-efficacy measure has the potential to provide asignificant new instrument to academic, government, and industry researchers.The overarching model for the study proposes that retention is shaped by self-efficacy, which, inturn, is based on the impact of students’ demographic characteristics, the effect of workexperience -- in particular cooperative education, and the contextual support provided by theuniversity as well as by others, such as parents and

Conference Session

Educational Research and Methods Poster Session

Collection

2012 ASEE Annual Conference & Exposition

Authors

So Yoon Yoon, Purdue University, West Lafayette; Miles Griffin Evans; Johannes Strobel, Purdue University, West Lafayette

Tagged Divisions

Educational Research and Methods

. Page 25.466.1 c American Society for Engineering Education, 2012 Development of the Teaching Engineering Self-Efficacy Scale (TESS) for K-12 TeachersTo teach engineering in K-12 classrooms means, for most teachers, to teach something for whichthey are not adequately prepared: pre-service teacher training does not require learningengineering and there are no teaching licenses for engineering teaching1. There is, however, alarge movement to provide in-service teachers with professional development to help themintegrate engineering into their classrooms2,3. A well-established construct to measure teachers’preparedness and effect on students’ achievement is “teacher self-efficacy towards