Conference Session

The Best of First-year Programs Division

Collection

2020 ASEE Virtual Annual Conference Content Access

Authors

Campbell R. Bego, University of Louisville; Jason Immekus, University of Louisville; Jeffrey Lloyd Hieb, University of Louisville

Tagged Divisions

First-Year Programs

Research Paper examines non-cognitive predictors of first-year engineeringretention for students who received a C in their first semester mathematics course at theUniversity of Louisville. Scores across eight non-cognitive measures served as model predictors,obtained at the beginning of the first year, including: value interest in engineering, perceivedeffort, opportunity, and psychological costs, perceived belonging uncertainty, contingencies ofself-worth: academic competence, test anxiety, and self-efficacy. Using least absolute shrinkageand selection operator regression, we found that value interest and test anxiety were the strongestpredictors of C-student retention. The results from this study inform research on the decision-making of

Collection

15th Annual First-Year Engineering Experience Conference (FYEE)

Authors

Matthew Cavalli, Western Michigan University; Anetra Grice, Western Michigan University

areconsistent with values measured for similar groups of students during the Fall 2022 semester atWMU [15]. Raw scores for mindset and self-efficacy responses can range from 1-6. Raw scoresfor ICOPPE responses can range from 0-10. With the exception of the Wellness Compositescore and the ICOPPE – Physical wellness score, average responses in Table 3 are in the upperhalf of each range for all groups.Table 3: Comparison of average responses on the start-of-semester survey for beginner students enrolled in ENGR2100, beginner students in the PREP sections of ENGR 2100, and beginner students not enrolled in ENGR 2100. Surveyed Beginner Surveyed Beginner Surveyed Beginner

Conference Session

Educational Research and Methods Division (ERM) Technical Session 16

Collection

2024 ASEE Annual Conference & Exposition

Authors

Jasmine Smith, University of Florida; David J. Therriault, University of Florida; Jeremy A. Magruder Waisome, University of Florida

Tagged Divisions

Educational Research and Methods Division (ERM)

-awareness related to the dimensions of self-reflection and insight. In the literature, thedimension of self-awareness is often assessed as engineering self-efficacy. Self-efficacy is anindividual's belief in their capacity to act in the ways necessary to reach specific goals [20]. Inengineering education, studies have measured self-efficacy among engineering students relatedto engineering design [21], mathematics aptitude [22], and general and skill-specific engineering[23]. Nevertheless, self-efficacy is only one dimension of one’s overall self-awareness. We arguethat you cannot consider a single aspect of an engineer’s being, such as their efficacy, andneglect to assess how that contributes to their overall identity as an engineer (i.e., overall

Conference Session

Track 7: Technical Session 1: Agriculture & Nutrition for Girls While Encouraging Leadership & Stem-Enrichment (ANGELS) Program

Collection

2025 Collaborative Network for Engineering & Computing Diversity (CoNECD)

Authors

Sandra C Affare, University of Tennessee at Chattanooga; Marissa McElrone, University of Tennessee at Chattanooga; Rachelle Pedersen, Texas Tech University

Tagged Topics

2025 CoNECD Paper Submissions, Diversity

, particularly women ofcolor, continue to be grossly underrepresented in engineering and agrisciences [2], [3]. TheANGELS Education/ Teaching Programs were designed to support increased participation ofwomen and underrepresented minorities in STEM, with a unique focus on broadening participationthrough motivational impact for middle school girls. Affare, Pedersen, McElrone, Barbosa, and RamnarineMotivation, such as personal-professional identity, self-efficacy, and belonging, has long beenshown to play a role in interest and integration in STEM fields, particularly for women andunderrepresented minorities [4], [5]. According to a 2018 Confidence Code poll, self-confidencelevels drop by thirty percent (30%) for girls between the ages

Conference Session

The Best of Design in Engineering Education

Collection

2009 Annual Conference & Exposition

Authors

Oenardi Lawanto, Utah State University; Scott Johnson, University of Illinois

Tagged Divisions

Design in Engineering Education

they have enough knowledge (i.e., declarative,procedural, and conditional knowledge) to respond to such task. Self-appraisal includes“judgments about one’s personal cognitive abilities, task factors that influence cognitivedifficulty or cognitive strategies that may facilitate or impede performance.”4, p. 17 Self-appraisal has a motivational aspect. Students’ motivational components, such as Page 14.1089.3intrinsic goal orientation, self-efficacy, task value, and learning beliefs play an important role inself-directed learning. In this study, the self-appraisal aspect was identified by students’ self-confidence and self-efficacy to

Conference Session

Making, Hacking, and Extracurricular Design

Collection

2018 ASEE Annual Conference & Exposition

Authors

Victoria Bill, New York University, Tandon School of Engineering; Anne-Laure Fayard, New York University, Tandon School of Engineering

Tagged Divisions

Design in Engineering Education

.[11] Carberry, A. R., Lee, H. S., & Ohland, M. W. (2010). Measuring engineering design self‐efficacy. Journal ofEngineering Education, 99(1), 71-79.[12] Martinez, L. J., & Sullivan, P. A., & Pines, E. (2017, June), Integration of Engineering Capstone within aMakerspace Environment Paper presented at 2017 ASEE Annual Conference & Exposition, Columbus, Ohio.[13] Nickols, F. (2003). Communities of practice. A start-up kit.

Collection

ASEE Zone 1 Conference - Spring 2023

Authors

Abdullah Konak, Pennsylvania State University, Berks Campus; Sadan Kulturel-Konak, Pennsylvania State University, Berks Campus; Haibin Liu, Northeast Normal University

, vol. 6, no. 1, pp. 60-86, 2023.[10] C. C. Chen, P. G. Greene, and A. Crick, "Does entrepreneurial self-efficacy distinguish entrepreneurs from managers?," Journal of Business Venturing, vol. 13, no. 4, pp. 295- 316, 1998.[11] T. M. Fernandez, G. Sliva Coutinho, M. D. Wilson, and S. R. Hoffmann, "Development of entrepreneurial attitudes assessment instrument for freshman students," 2015.[12] P. B. Robinson, D. V. Stimpson, J. C. Huefner, and H. K. Hunt, "An attitude approach to the prediction of entrepreneurship," Entrepreneurship Theory and Practice, vol. 15, no. 4, pp. 13-32, 1991.[13] Y. Shou and J. Olney, "Measuring Risk Tolerance across Domains: Scale Development and Validation," (in English

Conference Session

K-12 Programs (Co-sponsored by K-12 Division)

Collection

2007 Annual Conference & Exposition

Authors

Jeanne Hubelbank, WPI Evaluation Consulting; Chrysanthe Demetry, Worcester Polytechnic Institute; Shelley Errington Nicholson, Worcester Polytechnic Institute; Stephanie Blaisdell, Independent Consultant; Paula Quinn, Independent Consultant; Elissa Rosenthal, Marketing Research Consultant; Suzanne Sontgerath, Independent Consultant

Tagged Divisions

Women in Engineering

chosen in the random lottery (controlgroup). Results indicate that, in comparison to the control group, Camp Reach participants weresignificantly more likely to attend a public high school specializing in mathematics and scienceand also more likely to enroll in elective math and science courses in high school. While a higherfraction of the Camp Reach group chose engineering majors upon college entry, the differencedid not reach statistical significance. Grouping all STEM-related majors together, choices of theCamp Reach and control groups were not significantly different. Furthermore, there were nosignificant differences in the engineering self-efficacy and other measures of efficacy betweenthe Camp Reach and control groups.Introduction and

Conference Session

Making, Hacking, and Extracurricular Design

Collection

2018 ASEE Annual Conference & Exposition

Authors

Ethan Hilton, Georgia Institute of Technology; Megan Tomko, Georgia Institute of Technology; Wendy C. Newstetter, Georgia Institute of Technology; Robert L. Nagel, James Madison University; Julie S. Linsey, Georgia Institute of Technology

Tagged Topics

Diversity

Tagged Divisions

Design in Engineering Education

Makerspaces," presented at the International Symposium on Academic Makerspaces, Cleveland, USA, 2017.[8] M. Tomko, R. L. Nagel, M. W. Aleman, W. C. Newstetter, and J. S. Linsey, "Toward Understanding the Design Self-Efficacy Impact of Makerspaces and Access Limitations," in 2017 ASEE Annual Conference & Exposition, 2017.[9] R. Morocz, B. D. Levy, C. R. Forest, R. L. Nagel, W. C. Newstetter, K. G. Talley, et al., "University Maker Spaces: Discovery, Optimization and Measurement of Impacts," in ASEE Annual Conference and Exposition, Seattle, WA, 2015.[10] E. C. Hilton, M. Tomko, A. Murphy, R. L. Nagel, and J. Linsey, "Impacts on Design Self- efficacy for Students Choosing to Participate in a University

Conference Session

Women in Engineering Division Technical Session 2

Collection

2019 ASEE Annual Conference & Exposition

Authors

Behzad Beigpourian, Purdue University, West Lafayette ; Matthew W. Ohland, Purdue University-Main Campus, West Lafayette (College of Engineering)

Tagged Topics

Diversity

Tagged Divisions

Women in Engineering

the analysisFigure 1. Adaptation of the PRISMA flowchart for described search process [12] ResultsWe analyzed the remaining 18 articles that investigated race and gender in engineeringteamwork at U.S. institutions. Two of these articles studied race [13], [14], and ten paperswere related to gender [15]–[24]. Another six papers investigated both race and gender [25]–[30]. For better understanding papers’ results, we categorized them and each differentcategory describing one facet of teamwork covered by papers: collaboration, communication,leadership and self-efficacy, peer evaluation, perceptions of professors and students, teameffectiveness and outcome, and team formation. We extracted any

Conference Session

Environmental Engineering Division Technical Session 3

Collection

2018 ASEE Annual Conference & Exposition

Authors

Bettina Jeanine Casad, University of Missouri, St. Louis; Monica Palomo P.E., California State Polytechnic University, Pomona; Natalie Mladenov, San Diego State University

Tagged Topics

Diversity

Tagged Divisions

Environmental Engineering

American Chemical SocietyAnnual Spring Meeting, and at the international Dresden Nexus Conference in Germany .(3)MeasuresThe pre- and post-questionnaires included the following quantitative measures.Academic self-efficacy. An 8-item measure (Chemers et al., 2001) assessing students’ beliefsregarding their ability to successfully achieve their academic goals was rated on a scale from 1(Very Untrue) to 6 (Very True). Items included statements such as, “I know how to study toperform well on tests” and “I usually do very well at school and at academic tasks.” The scalehad adequate internal consistency (Time 1 or T1 Cronbach’s α = .70, Time 2 or T2 α = .94).Items were averaged so that higher scores indicated higher levels of academic self

Conference Session

Educational Research and Methods Division (ERM) Technical Session 29

Collection

2024 ASEE Annual Conference & Exposition

Authors

David Paul Harvie, Embry-Riddle Aeronautical University ; Kimberly A. Luthi, Embry-Riddle Aeronautical University ; Monica Surrency, Embry-Riddle Aeronautical University ; John K. Wilson, Embry-Riddle Aeronautical University

Tagged Topics

Diversity

Tagged Divisions

Educational Research and Methods Division (ERM)

, vol. 15, no. 2, pp. 7-15, 2014.[7] S. B. Wilson and P. Varma-Nelson, "Small Groups, Significant Impact: A Review of Peer- Led Team Learning Research with Implications for STEM Education Researchers and Faculty," Journal of Chemical Education, vol. 93, pp. 1686-1702, 2016.[8] S. B. Wilson and P. Varma-Nelson, "Implementing Peer-Led Team Learning and Cyber Peer-Led Learning in an Organic Chemistry Course," Journal of College Science Teaching, vol. 50, pp. 44-50, 2021.[9] J. E. Klobas, S. Renzi and M. L. Nigrelli, "A scale for the measurement of self-efficacy for learning (SEL) at univeristy," Bocconi University, 2007.[10] K. Wilson, K. Luthi, D. Harvie and M. Surrency, "Strategies for Engagement of Non- Traditional Students

Conference Session

Improved Pathways to Graduate Studies

Collection

2019 ASEE Annual Conference & Exposition

Authors

Jacques C. Richard, Texas A&M University; So Yoon Yoon, Texas A&M University; Maria Claudia Alves , Texas A&M University; Vikram K. Kinra, Texas A&M University

Tagged Topics

Diversity

Tagged Divisions

Graduate Studies

experiences, and overall program experiences.The format of the measures varied, including open-ended questions, ranking, and seven-pointLikert scales, ranging from 1 (strongly disagree) to 7 (strongly agree). Among several measures,we analyzed four common measures in both pre- and post-surveys, aligned with the NSF REUprogram objectives, such as (a) career goals after graduation, (b) self-efficacy in decision-makingtoward graduate school, and (c) perceptions of research knowledge, skills, and engineeringcareer paths, and (d) research expectations and experiences that enabled us to explore thedifferences of the impact of the REU programs on national versus international students.D. Data AnalysesFirst, we applied descriptive statistics for frequency

Conference Session

Women in Engineering Division Technical Session 7

Collection

2020 ASEE Virtual Annual Conference Content Access

Authors

Denise Wilson, University of Washington

Tagged Topics

Diversity

Tagged Divisions

Women in Engineering

study. All participation was voluntary, and students were informed that theirsurvey responses would remain confidential. In several courses, students were incentivized witha nominal amount of extra credit for the course in which they were recruited. All studentscompleted an electronic survey online and outside of class. Surveys were collected withidentifying information so that duplicates could be removed before aggregating data for analysis.All results were cross-sectional. Students reported their perceptions of various items related toengagement, belonging, effort, peer harassment, task value, self-efficacy, TA and facultyinteractions, and measures of course achievement as well as responding to demographic items.Data AnalysisThe data were

Conference Session

Engineering Education Research and Assessment III

Collection

2005 Annual Conference

Authors

Daniel Bailey; Andrew Ricke; David Spurlock; Susan Murray

,intrinsic motivation to accomplish, and intrinsic motivation to experience stimulation.In addition, we selected six other personality traits to measure that seemed highly relevant in thiscontext: need for cognition (Cacioppo & Petty9, 1982), organization (International PersonalityItem Pool10, 2001), activity level (International Personality Item Pool10, 2001), socialconnectedness (Lee & Robbins11, 1995), social assurance (Lee & Robbins11, 1995), andgeneralized self-efficacy (Schwarzer & Jerusalem12, 1995). Need for cognition refers to the needto think, learn, and analyze. Organization refers to one’s tendency to plan, control, and orderone’s available resources to accomplish one’s goals. Activity level refers to one’s tendency

Conference Session

Curricular Issues in Computing and Information Technology Programs II

Collection

2017 ASEE Annual Conference & Exposition

Authors

Vetria L. Byrd Ph.D., Purdue University; Camilo Vieira, Purdue University, West Lafayette (College of Engineering)

Tagged Topics

Diversity

Tagged Divisions

Computing & Information Technology

research instrument: self-efficacy, research skills, and scientificleadership. The sections below describe survey questions from each of these survey sections. Atotal of 17 questions are provided: 5 from General Self-Efficacy, one (1) from Research Skillsand Knowledge, and 11 from Scientific Leadership.General Self-Efficacy Feedback from students on general self-efficacy addresses student confidence in theirability to perform each of the activities listed in Table 5. Students select the rating that bestdescribe their degree of confidence by using the following scale: Strongly Agree (5), SomewhatAgree (4), Neutral (3), Somewhat Disagree (2), and Strongly Disagree (1).Table 5. General Self-Efficacy Student Survey 2015 Post Questions

Conference Session

Faculty Development Division (FDD) Poster Session

Collection

2023 ASEE Annual Conference & Exposition

Authors

Ha Pho, University of Massachusetts Lowell; Yanfen Li, University of Massachusetts Lowell; Hsien-Yuan Hsu, University of Massachusetts Lowell

Tagged Divisions

Faculty Development Division (FDD)

with sixsubscales measuring six competencies: Maintaining Effective Communication (4 items),Aligning Expectation (4 items), Assessing Understanding (3 items), Fostering Independence (3items), Addressing Diversity (3 items), Promoting Professional Development (4 items). Therevalidated scale is called MCA-21 to distinguish it from the original MCA-26 [36].Newly Developed Instruments for Added Modules in EM As the NRMN Mentor Training Core expanded the EM curriculum by adding additionaltraining modules, they developed scale items to assess the training outcomes of these modules.For the self-efficacy training module, the instrument (Promoting Mentees’ Self-Efficacy – table1), which consisted of five items on a 7-point Likert scale, aims to

Conference Session

Engineering Design Graphics Division Technical Session 3 - Spatial Visualization Topics

Collection

2019 ASEE Annual Conference & Exposition

Authors

Hannah Budinoff, University of California, Berkeley; Audrey Ford, University of California, Berkeley; Sara McMains, University of California, Berkeley

Tagged Topics

Diversity

Tagged Divisions

Engineering Design Graphics

canbetter devise pedagogical strategies targeted at improving self-efficacy and retention of femalestudents.The objective of this study is to determine if women do in fact put more effort into anintroductory engineering graphics class, and to determine if this extra effort can compensate fortheir lower average spatial visualization ability, resulting in equal course outcomes such as examand homework grades. We hypothesize that: 1) female students put more effort (measured asquiz scores, time spent on homework, attendance, and homework scores) into engineeringgraphics courses; and 2) that this greater effort by female students results in roughly equalaverage course and exam grades for men and women. While other studies have observed

Conference Session

Biomedical Engineering Division (BED) Technical Session 1: Sense of Self in Biomedical Engineering Students

Collection

2023 ASEE Annual Conference & Exposition

Authors

William H. Guilford, University of Virginia

Tagged Topics

Diversity

Tagged Divisions

Biomedical Engineering Division (BED)

. ©American Society for Engineering Education, 2023 Clinician-engineer self-concept in biomedical engineering students and its relationship to race, first-generation status, and mode of deliveryIntroduction and abstractRetention, recall, comprehension, and measurable skills are mainstays of the scholarship ofteaching and learning, and yet they represent only a fraction of what engineering educators hopeto achieve through education. The development of self-efficacy, for example, is a common goaland is often measured as a psychological construct. Less commonly measured constructs that arenonetheless commonly valued by educators are the development of creativity, perseverance(grit), and self-concept.Self-concept is particularly interesting in

Conference Session

Graduate Studies Division (GSD) Technical Session 1: Recruitment and Support in Engineering Graduate Programs

Collection

2023 ASEE Annual Conference & Exposition

Authors

Alyssa V. B. Santos, Pennsylvania State University; Sarah J. Boehm, Pennsylvania State University; Fadi Castronovo, California State University, East Bay; Tiffany A. Mathews, Pennsylvania State University

Tagged Topics

Diversity

Tagged Divisions

Graduate Studies Division (GSD)

opportunities? Modified Measure of Engineering Identity Student's Survey (MEI) survey scientific Modified Sense of Belonging Scale (SoBS) 3. Did students find the identity, survey program to stimulate their sense of Modified General Self-Efficacy Scale (GSE) scientific identity, sense of belonging, Measuring Undergraduate Students' belonging, and self-efficacy? and self- Engineering Self-Efficacy Survey (MUSES) efficacy Modified Student

Conference Session

Entrepreneurship & Engineering Innovation Division Technical Session 1

Collection

2019 ASEE Annual Conference & Exposition

Authors

Magdalini Z. Lagoudas, Texas A&M University; So Yoon Yoon, Texas A&M University; Rodney Boehm, Texas A&M University

Tagged Topics

Diversity

Tagged Divisions

Entrepreneurship & Engineering Innovation

large Southwestern publicuniversity. The program implementation component included program data associated withcurriculum content and format, recruiting approach, and participant data from five cohorts. Dueto the delayed employment of the assessment, the evaluation component included findings fromtwo cohorts using pre- and post-quizzes on knowledge of entrepreneurship terms and pre- andpost-surveys that captured changes in perceptions of entrepreneurship and customer interview.The results of this study indicated that while student interest on entrepreneurship remainedconstant, there were significant improvements of participants in three areas of self-efficacy: (a)entrepreneurship, (b) marketing and business planning, and (c) customer interview

Conference Session

NEE Technical Session - the Best of NEE

Collection

2022 ASEE Annual Conference & Exposition

Authors

Sarah Wodin-Schwartz, Worcester Polytechnic Institute; Kimberly Lechasseur, Worcester Polytechnic Institute; Adam Powell, Worcester Polytechnic Institute; Yihao Zheng, Worcester Polytechnic Institute; Sneha Prabha Narra, Carnegie Mellon University

?” The five items related to self-efficacy are: “Enthusiasm forengineering,” “Interest in taking or planning to take additional engineering classes,” “Confidencethat you understand the material,” “Confidence that you can do statics work,” and “Your comfortlevel in working with complex ideas.” Response options were a five-point Likert scale from “nogains” to “great gains.” These five items are moderately to highly positively correlated with eachother (see Table 1) and have high internal reliability, with a Cronbach’s alpha of .93; togetherthese suggest the items can be combined to constitute a single measure that is a stronger signal ofself-efficacy than each individual item.Table 1. Correlations of Items in Self-Efficacy Measure Item

Conference Session

CoNECD Session : Day 3 Slot 8 Technical Session 1

Collection

2021 CoNECD

Authors

Jill Davishahl, Western Washington University

Tagged Topics

CoNECD Paper Submissions, Diversity

Social & Emotional SkillsPhysical Space • Layout • Confidence • Collaboration • Self efficacy • Open • Innovation • Sense of • Safe • Creativity belonging • Accessible • Partnerships The bad news… Women and minoritized students are underrepresented Tension

Collection

2021 ASEE Midwest Section Conference

Authors

Kam Yuen Cheng; Rebecca Yang

].Another personality characteristic that helps women succeed in the construction industry isconfidence or self-efficacy. Academic capacity articulated that vocational preferences, and avariety of perceived career opportunities are all linked to self-efficiency [17]. Women who workin a non-traditional profession have the highest degree of career self-efficacy [18]. Another findingreinforced that their primary source of trust came from inside, followed by the influence of peoplethey interacted with mentors , and eventually, the additional education to help female feel moreconfident in their positions [11].Work experience has been recognized as another good indicator of job success. The positiverelationship between career success and work experience

Collection

2016 Spring ASEE Middle Atlantic Section Conference

Authors

Abdullah Konak; Sadan Kulturel-Konak

have a negative experience with teamwork (reverse coded) • I would rather work on team projects than on my own • I like to participate in teamwork • I am usually motivated to participate in teamworkIn order to measure their teamwork self-efficacy, students are asked to rate themselves usingfour-level Likert scales (1= Very Unconfident, 2=Unconfident, 3=Confident, 4= Very confident)with respect to the following teamwork skill, knowledge, and abilities. • Establishing specific team goals • Evaluating team progress toward each team goal • Providing feedback on the team or individual performance • Accepting feedback and criticism positively • Making adjustments based on the feedback • Defining tasks and clear task

Conference Session

Impact of Community Engagement on Students

Collection

2014 ASEE Annual Conference & Exposition

Authors

Chris Swan, Tufts University; Kurt Paterson P.E., James Madison University; Timothy Henry Hellickson, Tufts Center for Engineering Education and Outreach

Tagged Divisions

Community Engagement Division

instruments to explore theimpacts of CE on engineering students’ learning; specifically, traditionally technical attributes(e.g., ABET Criteria 3a-e) as well as a mix of non-technical attributes (e.g. global awareness,social context of problems, self-efficacy, identity, civic development, intercultural sensitivity,and psychosocial well-being). The two major components of the study consisted of semi-annualrounds of administering an on-line survey (for all participants) and telephone interviews(conducted with a sub-set of participants). An additional instrument to measure interculturalsensitivity was administered to the interview sub-set on an annual basis. Overall, the projecthad an initial, total participant number of over 250 (including 120

Collection

2001 Annual Conference

Authors

Barbara Greene; Connie Dillon; Billy L. Crynes

correlations of the approaches to learning variables with pretest and the two achievement measures (final examination score and total course points) are reported. From Table 6 we can see that among the motivation variables; learning goals, future goals, and self-efficacy have the highest correlations with final exam scores and percentage of course points. The variables asking about confidence in the mathematics and chemistry prerequisites both correlated with percentage of course points. The variable measuring degree of self-regulation was correlated with percentage of course points while the variable measuring degree of shallow engagement with the course material was moderately and

Conference Session

Thermodynamics, Fluids, and Heat Transfer-Part I

Collection

2010 Annual Conference & Exposition

Authors

Simin Hall, College of Engineering at Virginia Tech; Catherine Amelink, Virginia Tech; Sam Conn, Virginia Tech

Tagged Divisions

Mechanical Engineering

the 45 students enrolled in the course, 35 (29 men, 6 women) students completed the survey.Mean scores were computed for each item on the survey. Factor analysis was used to developthree scales for the three constructs measured by the survey. Chronbach alpha scores were usedto ensure reliability for the three scales. The mean age for the 35 students were 20.5 (SD=.92).C. Results from Survey:C.1. Self-EfficacyThe mean of self-efficacy in problem solving was 4.23 (SD=.54) for all 35 students with areliability coefficient of 0.82. Therefore, they were confident about their general problem solvingskills in engineering courses, revealing a high degree of self-efficacy. The mean and standarddeviation for each item that comprised the scale is shown

Conference Session

Equity in Engineering: Uncovering Challenges and Championing Change in STEM Education

Collection

2024 ASEE Annual Conference & Exposition

Authors

Lindsay Harley, Dartmouth College; Vicki V. May P.E., Dartmouth College; Rebecca Holcombe

Tagged Topics

Diversity

Tagged Divisions

Culture & Social Justice in Education Division (EQUITY), Equity

previous research shows thatconfidence or self efficacy greatly impacts perseverance in the major [6]. If underrepresentedstudents in particular say that assessment and reporting practices negatively impact theirconfidence and are not always accurate representations of their learning, then these studentsmight be discouraged from persisting in the engineering major, thus further perpetuating thediversity problem that already exists in the profession.This paper explores how students describe the effect of assessment practices on their perceivedsense of efficacy. Specifically, it examines whether students report differences in their sense ofself-efficacy in response to different kinds of assessment (eg. tests vs. hands-on projects) andreporting of

Conference Session

NSF Grantees Poster Session

Collection

2011 ASEE Annual Conference & Exposition

Authors

Larry J. Shuman, University of Pittsburgh; Mary E. Besterfield-Sacre, University of Pittsburgh; Tuba Pinar Yildirim, University of Pittsburgh; Karen M. Bursic, University of Pittsburgh; Natasa Vidic, University of Pittsburgh

Tagged Topics

NSF Grantees

assessment instruments to bet- ter understand and measure the educational benefits of using MEAs. Specifically, we are tri- angulating across three assessment instruments, two of which we developed: (1) pre- and post- concept inventories to assess gain, (2) an online reflection tool to assess process, and (3) a grading rubric to assess the resultant artifact (general model and specific solution). We have also developed an instrument to measure students‟ self-efficacy scale related to their Page 22.314.3 modeling skills. Assessing the MEA motivated problem solving process: Through the use of various data col- lection tools