Conference Session

Cooperative and Experiential Education Division (CEED) Technical Session 4

Collection

2024 ASEE Annual Conference & Exposition

Authors

Kimberly LeChasseur, Worcester Polytechnic Institute; Fiona Levey, Worcester Polytechnic Institute; Ahmet Can Sabuncu, Worcester Polytechnic Institute; Alireza Ebadi, Worcester Polytechnic Institute; John McNeill, Worcester Polytechnic Institute

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Diversity

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Cooperative and Experiential Education Division (CEED)

sustained critical investigation; and develop ideas.4.2.3 Self-efficacyFive survey items using the same prompt were used to create a composite score measuring self-efficacy. These items included: feelings that your ideas are valuable, feelings that you could“make a difference,” ability to take responsibility for your own learning; ability to succeed inbusiness or industry, and ability to function effectively in the “real world.”4.2.4 Career PreparednessSurvey respondents were asked, “How well did your project experience at WPI prepare you foryour current career?” Response options were a five-point bi-directional Likert scale from verypoorly (1) to very well (5), with an option to indicate “not applicable” if the respondent was notworking.4.2.5

Conference Session

NSF Grantees Poster Session

Collection

2024 ASEE Annual Conference & Exposition

Authors

Azadeh Bolhari, University of Colorado Boulder; Angela R Bielefeldt P.E., University of Colorado Boulder

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Diversity, NSF Grantees Poster Session

, “Measuring entrepreneurial self-efficacy to understand the impact of creative activities for learning innovation,” Intl J Mgmt Educ, 12, pp. 456-468, 2014.[9] J.H. Dyer, H. B. Gregersen, and C.M. Christensen, “Entrepreneur Behaviors, Opportunity Recognition, and the Origins of Innovative Ventures,” Strateg. Entrepreneurship J, 2 (4): pp. 317–38, 2008.[10] G. Balau, D. Faems, J. van der Bij, “Individual characteristics and their influence on innovation: A literature review,” Proceedings of the 9th International Conference on Innovation and Management, Nov. 14-16, Eindhoven, The Netherlands. Eds. G. Duysters, A. de Hoyos, K. Kaminishi, Wuhan University Press, pp. 887-901, 2012.[11] A. Bolhari, & S. Tillema

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

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Diversity

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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

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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

Design in Engineering Education Division (DEED) - Research Investigations in the Context of Design Education

Collection

2024 ASEE Annual Conference & Exposition

Authors

Samantha Butt, University of Toronto; Elizabeth DaMaren, University of Toronto; Alison Olechowski, University of Toronto

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Diversity

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Design in Engineering Education Division (DEED)

in their capabilities of using CAD software. Therefore, there iscurrently a lack of research investigating how students develop self-efficacy in relation to CADprior to their undergraduate degree.As there currently does not exist a validated scale to measure CAD self-efficacy, in this paper,we explore the related concepts of undergraduate engineering students’ initial 3D Modeling andEngineering Design self-efficacy before formal CAD instruction at the university level.Bandura’s Theory of Self-Efficacy suggests there are four main sources of self-efficacy: masteryexperiences, social persuasion, vicarious experiences and physiological states [1]. Therefore, weaim to answer the question: “What prior CAD learning experiences influence

Conference Session

Civil Engineering Division (CIVIL) Poster Session

Collection

2024 ASEE Annual Conference & Exposition

Authors

Adebayo Iyanuoluwa Olude, Morgan State University; Pelumi Olaitan Abiodun, Morgan State University; Oludare Adegbola Owolabi P.E., Morgan State University

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Civil Engineering Division (CIVIL)

extrapolating these subgroup results. Greatersample sizes would yield more solid proof of the effects on a diverse learner’s body.According to [22], there is a high practical significance and potential for real-world impact dueto the very large effect size (d=1.03). However, depending solely on self-report measures has itslimitations due to its potential for bias. The conclusion that effects are meaningful would bestrengthened by the inclusion of objective competence measures. Long-term monitoring is alsorequired to ascertain whether effects endure over time [21]. All things considered, thispreliminary study offers a promising foundation for future research on self-efficacy andexperiment-centric pedagogy.ConclusionThis study demonstrates that

Conference Session

Lisa's Legacy: Guiding Students Toward Engineering Careers, Excellent!

Collection

2024 ASEE Annual Conference & Exposition

Authors

Britta Solheim, Wartburg College; Jack Saylor Priske, Wartburg College; Murad Musa Mahmoud, Wartburg College; Cristian Gerardo Allen, Wartburg College; Kurt Henry Becker, Utah State University

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Diversity

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Pre-College Engineering Education Division (PCEE)

students’ self-efficacy and interest in aSTEM field, we analyzed student responses to the following questions/statements (stronglydisagree/disagree/neither agree or disagree/agree/strongly agree): 1. I am able to get a good grade in my science class. 2. I am able to do well in activities that involve technology. 3. I am able to do well in activities that involve engineering. 4. I am able to get a good grade in my mathematics class.These four questions served as an indicator of self-efficacy among the student participants. Eachquestion measures the self-reported self-efficacy in each of the four major fields in the acronymSTEM (each question respectively). We then tabulated the responses to another set of statements: 1. I like

Conference Session

Cooperative and Experiential Education Division (CEED) Technical Session 2

Collection

2024 ASEE Annual Conference & Exposition

Authors

Karina Ivette Vielma, University of Texas at San Antonio; Robin Lynn Nelson, University of Texas at San Antonio; JoAnn Browning P.E., The University of Texas at San Antonio

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Diversity

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Cooperative and Experiential Education Division (CEED)

undergraduatesfrom marginalized groups in engineering and to undergraduates who may not have the resourcesduring the academic year to participate in research at their institutions. Students are selectedusing holistic measures by each of the sites. The curriculum for the summer program aims tofoster self-efficacy in research through (1) participation in authentic research work, (2) facultyand experienced graduate student researcher mentoring, and (3) community building across thenatural hazards engineering and research communities.Students meet weekly through virtual means to discuss their research progress, address anychallenges, and discuss the rhetoric of scholarly publications and other activities. REU studentsalso participate in career development

Conference Session

Women in Engineering Division (WIED) Technical Session 8: Leadership and Persistence

Collection

2024 ASEE Annual Conference & Exposition

Authors

Christine Michelle Delahanty, National Science Foundation

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Diversity

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Women in Engineering Division (WIED)

Paper ID #41572Gender-Based Comparison of Creative Self-Efficacy, Mindset, and Perceptionsof Undergraduate Engineering StudentsDr. Christine Michelle Delahanty, National Science Foundation Dr. Delahanty is a Program Director at NSF in the Division of Undergraduate Education (EDU/DUE), and has a background in physics, electrical engineering, and STEM Education, with a concentration in creativity and innovation. Her research focuses on creative self-efficacy, creative mindset, and perceptions of engineering majors, particularly women, to offer insight into why there are so few women in the major and in the profession. She

Conference Session

Applications and Computational Tools for Mechanics Education

Collection

2024 ASEE Annual Conference & Exposition

Authors

Andrew R. Sloboda, Bucknell University; Kimberly LeChasseur, Worcester Polytechnic Institute; Sarah Wodin-Schwartz P.E., Worcester Polytechnic Institute

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Diversity

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Mechanics Division (MECHS)

explored the app, but did notregularly use it, which justified combining the two into a single comparison group.3.2 Data Collection and MeasuresData were collected using the retrospective Student Assessment of their Learning Gains - anNSF-funded and validated survey [14] that asks students how much they learned for each of a setof learning objectives and the extent to which they attribute their learning to specific learningactivities. The SALG has been used to date by more than 22,000 instructors to assessapproximately half a million students.3.2.1 Student OutcomesItems were averaged to construct measures of growth in content mastery, self-efficacy related tostatics, and willingness to seek help. Each of the items included the same question stem

Conference Session

First-Year Programs Division: Best of FPD

Collection

2024 ASEE Annual Conference & Exposition

Authors

Angela R. Bielefeldt, University of Colorado Boulder

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Diversity

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First-Year Programs Division (FYP)

– extremely)Post survey items to measure engineering self-efficacy (response options strongly disagree – strongly agree): I will be able to achieve most of the engineering-related goals that I have set for myself When facing difficult tasks within engineering, I am certain that I will accomplish them I believe I can succeed at most any engineering-related endeavor to which I set my mind I am confident that I can perform effectively on many engineering-related tasksPost survey items to measure commitment to engineering (response options): I have no doubt that I will graduate with a degree in engineering (strongly disagree – strongly agree) It is my intention to pursue a career in engineering (strongly disagree – strongly agree

Conference Session

Cooperative and Experiential Education Division (CEED) Technical Session 2

Collection

2024 ASEE Annual Conference & Exposition

Authors

Kamryn G. Zachek, University of New Mexico; Anjali Mulchandani, University of New Mexico; Sydney Donohue Jobe, University of New Mexico

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Diversity

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Cooperative and Experiential Education Division (CEED)

in academia at a R1 Hispanic servingUniversity in the American Southwest. The research was guided by the following question: Towhat extent does participation in undergraduate level research affect student’s self-efficacy andconfidence to succeed in undergraduate level academia/research? Students’ confidence and self-efficacy was measured using a Likert-scale survey. Responses were compared before and afterparticipating in the program to determine whether students’ confidence improved. We used SPSSfor statistical analysis of data which focused primarily on changes to mean response values.Following the conclusion of the Fellowship, interviews of the students were conducted via emailto gain further qualitative data on the impacts of the

Conference Session

Community Building and Student Engagement

Collection

2024 ASEE Annual Conference & Exposition

Authors

Tridib Kumar Saha, Purdue University ; Jason Morphew, Purdue University

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Diversity

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Electrical and Computer Engineering Division (ECE)

composition of teams (considering factors like gender, ethnicity, major, GPA, prior circuit experience, and year in school) influence student perceptions of the CLE and, consequently, student outcomes?To address these questions, we investigate the relationships in our survey data set throughquantitative analysis, focusing on two dependent variables: student performance, in terms of theirexam scores (Exam), and Collaborative Learning Experience (CLE), a measured variable from asurvey questionnaire at the end of the semester about the student’s perception of thecollaborative learning experience. We in turn examine how these dependent variables may beaffected by other collected measures, such as task and general self-efficacy, test anxiety

Conference Session

Entrepreneurship & Engineering Innovation Division (ENT) Technical Session 6

Collection

2024 ASEE Annual Conference & Exposition

Authors

Nada Elfiki, Stanford University; Helen L. Chen, Stanford University; George Toye; Micah Lande, South Dakota School of Mines and Technology; Felix Kempf, King's College London; Lauren Marie Aquino Shluzas, Stanford University; Sheri Sheppard, Stanford University

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Entrepreneurship & Engineering Innovation Division (ENT)

-Efficacy Measure and Social Cognitive Career TheoryIn the realm of human behavior, self-efficacy holds profound importance, particularly ininnovation and entrepreneurship. Several self-efficacy measures have been developed in theinnovation and entrepreneurship research fields and tailored to the specific tasks that areassessed in this context (e.g., [20]–[24]). Innovation Self-Efficacy (ISE) refers to theindividuals’ confidence in their ability to innovate and engage in specific behaviors thatcharacterize innovative people [23], [25], whereas Entrepreneurial Self-Efficacy (ESE) is thebelief and confidence individuals have in their own capabilities to execute tasks aimed atentrepreneurial outcomes and pursuing new venture opportunities [20], [21

Conference Session

MECH - Technical Session 13: Technological Advancements and Applications

Collection

2024 ASEE Annual Conference & Exposition

Authors

Golnaz Mirfenderesgi, The Ohio State University; Syedah Zahra Atiq, The Ohio State University

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Diversity

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Mechanical Engineering Division (MECH)

,” Applied Thermal Engineering, vol. 112, pp. 841–854, Feb. 2017, doi: 10.1016/j.applthermaleng.2016.10.134.[4] B. A. Al-Sheeb, A. M. Hamouda, and G. M. Abdella, “Modeling of student academic achievement in engineering education using cognitive and non-cognitive factors,” JARHE, vol. 11, no. 2, pp. 178–198, Apr. 2019, doi: 10.1108/JARHE-10-2017-0120.[5] M. Khan, M. Ibrahim, and N. Wu, “Measuring Self-Efficacy in Engineering Courses – Impact of Learning Style Preferences,” in 2019 ASEE Annual Conference & Exposition Proceedings, Tampa, Florida: ASEE Conferences, Jun. 2019, p. 33092. doi: 10.18260/1-2-- 33092.[6] M. Khan and M. Ibrahim, “Women in Engineering – Focus on Self-Efficacy in Modeling and Design through

Conference Session

MECH - Technical Session 9: Advanced Mechanical Engineering Topics

Collection

2024 ASEE Annual Conference & Exposition

Authors

Samuel James Murphy, The University of Iowa; Martell Cartiaire Bell, The University of Iowa; Rachel Vitali, The University of Iowa; Jae-eun Russell

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Diversity

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Mechanical Engineering Division (MECH)

] E. Fast and E. Horvitz, "Long-Term Trends in the Public Perception of Articial Intelligence," AAAI, vol. 31, no. 1, 2017.[2] M. Borrego, "Conceptual difficulties experienced by trained engineers learning educational research methods," Journal of Engineering Education, vol. 96, no. 2, pp. 91-102, 2007.[3] N. A. Mamaril, E. L. Usher, C. R. Li, D. R. Economy and M. S. Kennedy, "Measuring Undergraduate Students' Engineering Self-Efficacy: A Validation Study," Journal of Engineering Education, vol. 105, no. 2, pp. 366-395, 4 2016.[4] R. M. Marra and B. Bogue, "Women Engineering Students' Self Efficacy-A Longitudinal Multi- Institution Study," 2006.[5] J. S. Weedon, "Judging for Themselves: How Students Practice Engineering

Conference Session

Continuing Professional Development Division (CPD) Technical Session 1

Collection

2024 ASEE Annual Conference & Exposition

Authors

Mary Grace Golden, Purdue University ; Emeline Anne Ojeda-Hecht, Purdue University ; Savannah Meier, Purdue University ; Eric Holloway, Purdue University; Jennifer S. Linvill, Purdue University

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Continuing, Professional, and Online Education Division (CPOED)

careerdevelopment, was founded by Robert Lent, Steven Brown, and Gail Hackett [21]. The theory isbased on Bandura’s general social cognitive theory and self-efficacy theory [22], [23]. Bandura[24] describes self-efficacy as dependent on four main factors: personal performanceaccomplishments, vicarious learning, social persuasion, and physiological and affective states.SCCT draws on Bandura’s theories to argue that interests develop from outcomes expectationsand self-efficacy and acknowledges the dynamic nature of interests and expectations asindividuals have new experiences [25]. SCCT is often utilized to understand “why people chooseand persist in their career paths” [26, p. 4]. Additionally, SCCT considers both environmentaland individual factors that

Conference Session

The Best of Computers in Education Division (COED)

Collection

2024 ASEE Annual Conference & Exposition

Authors

Phyllis J. Beck, Mississippi State University; Mahnas Jean Mohammadi-Aragh, Mississippi State University

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Diversity

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Computers in Education Division (COED)

formative times in their computing education [6, 8]. There have been many attempts at developing novel approaches to support various aspects of programming metacognition, improve self-efficacy, and provide automated feedback and assessment for students in introductory programming courses [5, 6, 8]. Programming metacognition can be broadly defined as how students think about programming and the problem-solving strategies they employ to achieve a goal when given a programming task [9]. However, most of these methods have yet to be successfully scaled and applied in the classroom. Previous studies suffer from issues such as being too small, difficult to validate or replicate, and software that is not shared or is abandoned

Conference Session

First-Year Programs Division Technical Session 7: Retention & Success

Collection

2024 ASEE Annual Conference & Exposition

Authors

Navid Yaghoubisharif, Oregon State University; Shane A. Brown P.E., Oregon State University; Natasha Mallette P.E., Oregon State University

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Diversity

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First-Year Programs Division (FYP)

influencing the self‐efficacy beliefs of first‐year engineering students,” J. Eng. Educ., vol. 95, no. 1, pp. 39–47, 2006.[2] M. W. Ohland, S. D. Sheppard, G. Lichtenstein, O. Eris, D. Chachra, and R. A. Layton, “Persistence, engagement, and migration in engineering programs,” J. Eng. Educ., vol. 97, no. 3, pp. 259–278, 2008.[3] J. J. Appleton, S. L. Christenson, D. Kim, and A. L. Reschly, “Measuring cognitive and psychological engagement: Validation of the Student Engagement Instrument,” J. Sch. Psychol., vol. 44, no. 5, pp. 427–445, 2006.[4] J. L. Meece, P. C. Blumenfeld, and R. H. Hoyle, “Students’ goal orientations and cognitive engagement in classroom activities.,” J. Educ. Psychol., vol. 80, no. 4, p. 514, 1988.[5] R

Conference Session

Educational Research and Methods Division (ERM) Technical Session 5

Collection

2024 ASEE Annual Conference & Exposition

Authors

Kenneth West, University of Florida; Bruce Frederick Carroll, University of Florida; Jinnie Shin, University of Florida; Kent J. Crippen, University of Florida

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Diversity

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Educational Research and Methods Division (ERM)

supportprocess[2]. Outcomes include improvements in student self-efficacy and ultimately in studentpersistence to remain in the major[3]. The Mediation Model of Research Experiences (MMRE)empirically established engineering self-efficacy, teamwork self-efficacy, and identity as anengineer as mediating, person-centered motivational psychological, processes that transmit theeffect of programmatic support activities into an increased commitment to an engineeringcareer[4]–[8]. For the current work, we speculate that students with low measures of engineeringself-efficacy, teamwork self-efficacy, or engineering identity are good candidates for proactiveadvising intervention. Additional measures of non-cognitive and affective attributes may alsoprovide

Conference Session

Educational Research and Methods Division (ERM) Technical Session 14

Collection

2024 ASEE Annual Conference & Exposition

Authors

Cory Lam, University of Washington; Denise Wilson, University of Washington

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Diversity

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Educational Research and Methods Division (ERM)

following the COVID-19 pandemic) andremote (during the pandemic) learning settings in mechanical and electrical and computerengineering. Variables representing expectancy, value, and predictors of expectancy and valuewere integrated into hierarchical linear models to understand their influence on cognitiveengagement and to explore whether or not the expectancy-value model was stable over time inthe engineering education context. Consistent with expectancy-value theory, our results indicatedthat expectancy (measured by self-efficacy) and value (as measured by intrinsic and utility value)positively and significantly predicted cognitive engagement for all time periods. Previousacademic achievements as measured by overall GPA was also consistent across

Conference Session

Educational Research and Methods Division (ERM) Technical Session 12

Collection

2024 ASEE Annual Conference & Exposition

Authors

Matthew Bahnson, Purdue University; Eric Trevor McChesney, University of Pittsburgh; Carlie Laton Cooper, University of Georgia; Allison Godwin, Cornell University; Linda DeAngelo, University of Pittsburgh; Kevin R. Binning

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Diversity

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Educational Research and Methods Division (ERM)

differences in these relationships by studentrace and gender. The model includes engineering identity as directly predicted by self-efficacy,interest, and sense of belonging. Sense of belonging is likewise predicted by self-efficacy andinterest, generating additional indirect influences on engineering identity. Finally, a sense ofbelonging is further predicted by cross-racial and cross-gender belonging experiences. The strongrelationships between measures provide insight into the potential for interventions to improveengineering identity in early career engineering students. Future work to analyze the longitudinalchange in measures and identity in association with the intervention will further demonstratevariable relationships. Results provide

Conference Session

Entrepreneurship & Engineering Innovation Division Technical Session 2

Collection

2024 ASEE Annual Conference & Exposition

Authors

Azadeh Bolhari, University of Colorado Boulder; Angela R. Bielefeldt, University of Colorado Boulder; Richard W Saxton, University of Colorado Boulder; Anvie Gowrishankar, University of Colorado Boulder; Maya Leizerovich, University of Colorado Boulder; Shane Gavney, University of Colorado Boulder

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Diversity

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Entrepreneurship & Engineering Innovation Division (ENT)

conducted in a single junior-level course for environmentalengineering students. The innovation self-efficacy of participants was measured using a surveythat included items from the Very Brief Innovation Self-Efficacy scale (ISE.6), the InnovationInterests scale (INI), and the Career Goals: Innovative Work scale (IW). The drawings wereanalyzed for Artistic Effort (AE) and Creative Work (CW) by engineering and art evaluators,respectively. The ISE survey results were compared with the AE and CW scores and thecorrelations with travel, gender, and multilingualism on creativity attributes were explored. Astrong correlation between CW scores and AE scores was observed. A negative correlationbetween CW and ISE.6 was found. The CW scores were significantly

Conference Session

Educational Research and Methods Division (ERM) Technical Session 13

Collection

2024 ASEE Annual Conference & Exposition

Authors

Rachel E. Durham, Notre Dame of Maryland University; Michael L. Falk, The Johns Hopkins University; Alexis Daniels, The Johns Hopkins University; Allison Reigel, The Johns Hopkins University; Alisha Nicole Sparks, The Johns Hopkins University; Margo K. Williams, The Johns Hopkins University; Emily J Yanisko, American University

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Diversity

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Educational Research and Methods Division (ERM)

design was used where schools were assignedto either treatment or control conditions. Students in treatment schools accessed algebra-for-engineering modules, STEM-professional role model videos, and field trips, while students incontrol schools accessed role model videos and field trips only. Surveys measuring math self-efficacy, and STEM interest, outcome expectations, and choice goals were completed byparticipants in both conditions at the beginning and end of two separate program years, 2021-22and 2022-23. Across both years, quantitative results suggest some positive effects of BOASTparticipation, particularly for STEM choice goals, but benefits depend upon student participationlevels. Qualitative data offer student voice around prior

Conference Session

Educational Research and Methods Division (ERM) Technical Session 18

Collection

2024 ASEE Annual Conference & Exposition

Authors

Navarun Gupta, University of Bridgeport; Junling Hu, University of Bridgeport; Ioana A. Badara, Post University; Buket D. Barkana, The University of Akron; Deana A. DiLuggo, University of Bridgeport

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Diversity

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Educational Research and Methods Division (ERM)

specific questions and aspects of the engineering design process,brainstorming ideas, and actively engaging in research as a team. Observations have revealedstrong student engagement in course activities and evidence of faculty following the ARG model.4.3 EDSE InstrumentThe EDSE instrument is a 36-item questionnaire designed to measure students' self-conceptstoward engineering design tasks. It assesses four areas related to engineering identity developmentusing a scale of 0 to 100 (0 = low level; 50 = moderate level; 100 = high level). The areas assessedinclude: self-efficacy, motivation, expectancy, and anxiety. In each area the following engineeringdesign tasks were assessed: conducting engineering design, identifying a design need, researchinga

Conference Session

NSF Grantees Poster Session

Collection

2024 ASEE Annual Conference & Exposition

Authors

Andrea Ramirez-Salgado, University of Florida; Tanvir Hossain, The University of Kansas; Swarup Bhunia; Pavlo Antonenko

Tagged Topics

Diversity, NSF Grantees Poster Session

: Measures: Self-efficacy, Self-efficacy, interest, interest, outcome expectations, identity outcome expectations, identity Datasources: Data sources: Intrapersonal Intrapersonal factors factors survey, interviews, and focus groups survey, interviews, and focus

Conference Session

Principal Skinner's Secrets: Cultivating STEM in Remote Locations, Steamed Hams!

Collection

2024 ASEE Annual Conference & Exposition

Authors

Frank Bowman, University of North Dakota; Bethany Jean Klemetsrud P.E., University of North Dakota; Emine Ozturk, North Carolina State University; Julie Robinson, University of North Dakota; Erin Lacina

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Diversity

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Pre-College Engineering Education Division (PCEE)

to students and Experiences local community Iteration – opportunity to review, revise, improve lessons based on measurable outcomes Focusing pedagogical shifts/PD within one content area creates relevance but allows for impact across all content areas Affective Success/student engagement begets positive affective state leads to States increased self-efficacy Verbal Support and collaboration from administration persuasion On-going touchpoints, check-ins for continuous learning, reflection, collaborationSummer institutesTeacher participants began the [Anonymous

Conference Session

Mathematics Division (MATH) Technical Session 3

Collection

2024 ASEE Annual Conference & Exposition

Authors

Zenaida Aguirre Munoz Ph.D., University of California, Merced; Melissa Almeida, University of California, Merced; Comlan de Souza, California State University, Fresno; Keith Collins Thompson, University of California Merced; Khang Tran, California State University, Fresno; Yue Lei, University of California, Merced; Erica M Rutter, University of California, Merced; Lalita G Oka, California State University, Fresno; Maribel Viveros, University of California Merced; Bianca Estella Salazar, University of California, Merced; Changho Kim, University of California, Merced

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Diversity

Tagged Divisions

Mathematics Division (MATH)

area involvesuniversities with small proportions of URMs. Thus, continued study of the impact of thesefactors on more diverse student populations is also necessary to better capture the calculusexperience of URM engineering majors. The purpose of the study was to examine student andclassroom-level factors that influence course performance measured by course grade. This studyfocused on two engineering-related psychosocial factors: (1) engineering self-efficacy and (2)engineering sense of belonging, and three mathematics-specific psychological factors which werefer to as math motivators, (1) math interest, (2) self-concept, and (3) anxiety. Classroom levelfactors included active engagement practices, proportion of females, proportion of

Conference Session

Experiential Learning in ET Programs II

Collection

2024 ASEE Annual Conference & Exposition

Authors

Paul Davidson, University of Illinois at Urbana - Champaign; Travis Johnson, University of Illinois at Urbana - Champaign; Molly H. Goldstein, University of Illinois at Urbana - Champaign; Brandon Hollenback, University of Illinois at Urbana - Champaign

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Diversity

Tagged Divisions

Engineering Technology Division (ETD)

overall planning, organizing,and time management. With that desire, we have reason to research if these project managementskills and concepts are being taught effectively enough to prepare students for senior-levelcapstone courses and future careers. Degree programs that do not heavily focus on managementprinciples may impact students' abilities to obtain manager-style roles. Outside the classroom,there are opportunities to obtain this experience, such as through internships and studyingabroad. Data collected stem from a self-efficacy questionnaire administered to 811 students andvoluntarily completed by 361. The survey was issued at the beginning of the semester for ninefall courses through 15 different majors and intended to take approximately

Conference Session

Graduate Studies Division (GSD) Technical Session 6: Programs in Graduate Education

Collection

2024 ASEE Annual Conference & Exposition

Authors

Jamie R. Gurganus, University of Maryland, Baltimore County; Michael M. Malschützky, Hochschule Bonn-Rhein-Sieg, Germany; Neha B. Raikar, University of Maryland, Baltimore County; Yarazeth Medina, University of Maryland, Baltimore County

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Diversity

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Graduate Studies Division (GSD)

item-difficulty. SD P(i) = standard deviation of item-difficulty. Md P(i) = median of item-difficulty.In result, only one item (V13), with item-difficulty P(13) = .79, is in the desired value-range todifferentiate between participants. The other items are agreed to unilaterally throughout, meaningthat all participants show very high ratings in teaching self-efficacy.4.2.2. Corrected item-total correlationsThe part-whole-corrected item-total correlation r(i,total-i) of an item i indicates how much theitem i measures the same psychological construct as the other items combined (total-i). Valuesbetween 0.4 and 0.7 are preferred [15]. Table 4 gives an overview of item-total correlations ofthe 18 items taking the sub-scales and the aggregate scale