Conference Session

Work-in-Progress Session: Understanding Issues Faced by Graduate Students and Faculty

Collection

2023 ASEE Annual Conference & Exposition

Authors

Anuli Ndubuisi, University of Toronto, Canada; Glory Ovie, The King's University Edmonton, Canada; Zian (Kelly) Zhang, University of Toronto, Canada

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Educational Research and Methods Division (ERM)

theprofessional identity development of internationally trained minority ECSW in engineering, andeducation, as they represent leaders in their fields, within and beyond academia.References:[1] L. Carlson, T. Portman, and J. Bartlett, “Self-Management of Career Development: Intentionality for Counselor Educators in Training,” Journal of Humanistic Counseling, Education and Development, vol. 45, Sep. 2006, doi: 10.1002/j.2161-1939.2006.tb00012.x.[2] C. Cheng and S. Song, “How Early-Career Researchers Are Navigating the COVID-19 Pandemic,” Mol Plant, vol. 13, no. 9, pp. 1229–1230, Sep. 2020, doi: 10.1016/j.molp.2020.07.018.[3] J. P. Martin and C. Garza, “Centering the Marginalized Student’s Voice Through Autoethnography: Implications

Conference Session

Work-in-Progress Session: Supporting Students To, Through, and Beyond Transitions

Collection

2023 ASEE Annual Conference & Exposition

Authors

Giselle Guanes Melgarejo, The Ohio State University; Victoria Bill, New York University ; Julie P Martin, The Ohio State University; Tiantian Li, Purdue University, West Lafayette; Kerrie A Douglas, Purdue University, West Lafayette; Eric Holloway, Purdue University, West Lafayette

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Educational Research and Methods Division (ERM)

, 2005, doi: 10.1002/j.2168-9830.2005.tb00832.x.[2] J. P. Martin, S. D. Garrett, S. G. Adams, and J. Hamilton, "A qualitative look at African American students’ perceptions of developing engineer of 2020 traits through non- curricular activities," presented at the 2015 ASEE Annu. Conf. Expo., Seattle, WA, USA, Jun. 14-17, 2015.[3] C. A. Smith, H. Wao, G. Kersaint, and R. Campbell-Montalvo, "Social capital from professional engineering organizations and the persistence of women and underrepresented minority undergraduates," Front. Sociol., vol. 6, p. 671856, 2021.[4] J. P. Martin, R. A. Revelo, S. K. Stefl, S. D. Garrett, and S. G. Adams, "Ethnic student organizations in engineering: Implications

Conference Session

Educational Research and Methods Division (ERM) Technical Session 4

Collection

2024 ASEE Annual Conference & Exposition

Authors

Fabiola G. Rosales Sanchez, Virginia Polytechnic Institute and State University; Nicole P. Pitterson, Virginia Polytechnic Institute and State University; Karen Dinora Martinez Soto, Virginia Tech

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Educational Research and Methods Division (ERM)

contributed to the refinement ofthe observation protocol we had created. This protocol will play a key role in the larger NSF studydedicated to exploring the role of language in introductory engineering courses.Literature ReviewIn the social and behavioral sciences, direct observations are considered to be the base or root ofall research methods [1], [2]. Their main benefit of observations as a qualitative data collectionmethod is that they allow “for the researcher to see and record firsthand the activities in whichresearch participants are engaged in the context(s) in which these activities happen” [3, p. 160].Moreover, observations allow researchers to collect data about phenomena that the participantsmight not be aware of themselves and therefore

Conference Session

Educational Research and Methods Division (ERM) Technical Session 6

Collection

2024 ASEE Annual Conference & Exposition

Authors

Lin Chase, Minnesota State University, Mankato; Rob Sleezer, Minnesota State University, Mankato

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Educational Research and Methods Division (ERM)

; levels of inclusion;and social identity Jensen and Cross deployed a validated quantitative instrument to engineeringstudents at three three large U. S. public universities. Their work indicated there wererelationships between the studied constructs – specifically, that reported feelings of stress,anxiety, and depression statistically decreased with increasing reports of inclusion [14].For this research we replicated the work of Jensen and Cross by deploying the same instrumentthey used in our project-based context. Using this instrument, we collected quantitative dataon: • Mental health: self-reported stress, anxiety, and depression • Professional identity: engineering identity and engineering career • Inclusion: department caring

Conference Session

Educational Research and Methods Division (ERM) Technical Session 2

Collection

2024 ASEE Annual Conference & Exposition

Authors

Jack Boomer Perry, University of Michigan; Emily Buten, University of Michigan; Aaron W. Johnson, University of Michigan

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Educational Research and Methods Division (ERM)

needed to learn‬ ‭it – giving great potential for engineering education and curriculum impact.‬‭References‬‭[1] S. Freeman‬‭et al.‬‭, “Active learning increases student performance in science, engineering,‬ ‭and mathematics,”‬‭Proc. Natl. Acad. Sci. U.S.A.‬‭, vol. 111, no. 23, pp. 8410–8415, Jun. 2014,‬ ‭doi:‬‭10.1073/pnas.1319030111‬‭.‬ ‭[2] N. J. McNeill, E. P. Douglas, M. Koro‐Ljungberg, D. J. Therriault, and I. Krause,‬ ‭“Undergraduate Students’ Beliefs about Engineering Problem Solving,”‬‭J. Eng. Educ.‬‭, vol.‬ ‭105, no. 4, pp. 560–584, Oct. 2016, doi:‬‭10.1002/jee.20150‬‭.‬ ‭[3]‬ ‭Miskioğlu, E. E., Aaron, C., Bolton, C., Martin, K. M., Roth, M

Conference Session

Educational Research and Methods Division (ERM) Technical Session 6

Collection

2024 ASEE Annual Conference & Exposition

Authors

Lin Chase, Minnesota State University, Mankato; Rob Sleezer, Minnesota State University, Mankato

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Educational Research and Methods Division (ERM)

engineeringprograms. To achieve their goals, Jensen and Cross examined stress, anxiety, and depression;engineering identity; and perceptions of inclusion in undergraduate engineering programs. Theycollected data from student populations at three large U. S. public universities. They hypothesizedthat levels of stress, anxiety, and depression would vary by social identities and that levels ofinclusion and engineering identity would vary by social identities and across socialidentities.To gather data Jensen and Cross relied upon a validated, quantitative survey that had oneopen-ended item. Their findings indicated that perceptions of inclusion and engineering identityare directly related to student mental health – measures of inclusion such as ”Department

Conference Session

Educational Research and Methods Division (ERM) Poster Session

Collection

2024 ASEE Annual Conference & Exposition

Authors

Chia-Lin Tsai, University of Northern Colorado; Lisa Y Flores, University of Missouri, Columbia; Rachel L Navarro, University of North Dakota; Pat Garriott; Han Na Suh, Georgia State University - Perimeter College; Sarah Lynn Orton P.E., University of Missouri, Columbia

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Educational Research and Methods Division (ERM)

itemquality indices to inform item selection, as these indices can identify unstable items to some extent. To conclude, our findings suggested retaining items that strongly connect to the specifieddimensions and items that are not too easy for individuals to endorse the high rating scale categories (e.g.,like and strongly like”). Future studies may further explore the relationship between item stability andother item characteristics under different data conditions. ReferencesAbdi, H. (2010). Holm’s sequential Bonferroni procedure. Encyclopedia of research design, 1(8), 1-8.Boateng, G. O., Neilands, T. B., Frongillo, E. A., Melgar-Quiñonez, H. R., & Young, S. L. (2018). Best practices for

Conference Session

Educational Research and Methods Division (ERM) Technical Session 21

Collection

2024 ASEE Annual Conference & Exposition

Authors

Kelsey Scalaro, University of Nevada, Reno; Indira Chatterjee, University of Nevada, Reno; Ann-Marie Vollstedt, University of Nevada, Reno; Adam Kirn, University of Nevada, Reno

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Educational Research and Methods Division (ERM)

, outcome expectations, physics identity, and physics career choice: A gender study,” J. Res. Sci. Teach., p. n/a-n/a, 2010, doi: 10.1002/tea.20363.[8] R. Friedensen, E. Doran, and S. Rodriguez, “Documenting engineering identity: Electrical and computer engineering departmental documents and student identity,” in 2018 ASEE Annual Conference & Exposition Proceedings, Salt Lake City, Utah: ASEE Conferences, Jun. 2018, p. 30343. doi: 10.18260/1-2--30343.[9] A. Godwin and G. Potvin, “Fostering female belongingness in engineering through the lens of critical engineering agency

Conference Session

Research Methodologies – Session 1

Collection

2023 ASEE Annual Conference & Exposition

Authors

Matthew Bahnson, Pennsylvania State University; Catherine G. P. Berdanier, Pennsylvania State University

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Educational Research and Methods Division (ERM)

] used content analysis of gender research in the Journal ofEngineering Education to identify categories of gender-related research in engineering education.This example demonstrates the utility of content analysis to identify trends and gaps in the waysin which topics are investigated across a large body of research.Useful methods texts and resources for content analysis methods:[10] H.-F. Hsieh and S. E. Shannon, “Three Approaches to Qualitative Content Analysis,” Qual.Health Res., vol. 15, no. 9, pp. 1277–1288, 2005. Thematic Analysis[13] L. L. Kaid, “Content Analysis,” in Measurement of Communication Behavior, P. Emmert andL. L. Barker, Eds. New York: Longman, 1989, pp. 197–217.Thematic AnalysisBasic Definitions: First, thematic analysis is

Conference Session

Supporting Students with Disabilities and Understanding Spatial Ability and Accessibility

Collection

2023 ASEE Annual Conference & Exposition

Authors

Rachel Figard, Arizona State University; Samantha Ruth Brunhaver, Arizona State University; Jennifer M. Bekki, Arizona State University

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Diversity

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Educational Research and Methods Division (ERM)

identified as male and four as female. The representation of the sample’s race and ethnicity makeup include: Black (n=1), Hispanic or Latino (n=1), Middle Eastern (n=2), and white (n=6). Table 1 provides additional co-researcher demographic information, as reported in the screening survey. Table 1 Co-researcher Demographic InformationPseudonym Race Gender Disability(s) Engineering Year-in-School International Major Student (Y/N)Joe Middle Male Learning Civil First-year Y EasternSammy Middle Male Cognitive

Conference Session

Investigating Student Pathways to and through Undergraduate and Graduate Programs

Collection

2023 ASEE Annual Conference & Exposition

Authors

Samantha Splendido, Pennsylvania State University, University Park; Catherine G. P. Berdanier, Pennsylvania State University

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Educational Research and Methods Division (ERM)

phenomena and continue learning about interactions and situations betweenindividuals in a system. The growth of computation and simulations began in the 1950’s and 60’s in technicalsectors of natural science research like physics and chemistry intending to perform large-scalepredictive computations [13]–[15]. Beyond the natural sciences, computational techniques movedinto economics to perform large scale calculations and provide large new data storage options[16].Many of these computational techniques are the precursors to how we use ABM today to approachproblems. ABM has, more recently, found success and been proven reliable in simulations fortransmission and event prediction in medicine [11] and immunology [10]. These studies haveproduced

Conference Session

Student Teams and Teamwork

Collection

2023 ASEE Annual Conference & Exposition

Authors

Siqing Wei, Purdue University at West Lafayette (COE); Amirreza Mehrabi, Purdue University; Li Tan, Arizona State University; Matthew W. Ohland, Purdue University at West Lafayette (COE)

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Educational Research and Methods Division (ERM)

South AsiaData CollectionData was collected via semi-structured, one-to-one interviews in the middle of October 2022.The interview protocol was developed to guide participant to reflect on their team experienceschronologically and capture their reactions to the team interaction and dynamics. We focused onsoliciting significant milestones and key events from the participants and attempting tounderstand the roles of everyone in the team and how the person(s) influenced the dynamics.Therefore, we drafted the protocol based on the framework of Tuckman’s team developmentalsequence model [11-12] discussed in the literature review section above. Our research teamcarefully examined and revised the interview protocol to ensure the quality, relevance

Conference Session

Educational Research and Methods Division (ERM) Technical Session 26

Collection

2024 ASEE Annual Conference & Exposition

Authors

Sushant Makarand Padhye, University of Cincinnati; David Reeping, University of Cincinnati; Nahal Rashedi , University of Cincinnati

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Educational Research and Methods Division (ERM)

engineeringstudents, this paper focuses on understanding the sequencing and overall arrangement of coursesin a program. We adopt the terminology from Heileman et al. [7] to formally call these constructscurricular design patterns, which they describe as, “collection[s] of curricular and co-curricularlearning activities intentionally structured so as to allow students to attain a set of learningoutcomes within a given educational context” [p. 5]. Although the term co-curricular is used inthis definition, there is much greater emphasis on the structure of prerequisite and corequisiterelationships. Still, by examining these roadmaps for how students are expected to progressthrough their discipline’s plan of study, we can understand how different curricular

Conference Session

Educational Research and Methods Division (ERM) Technical Session 22

Collection

2024 ASEE Annual Conference & Exposition

Authors

Xiaorong Zhang, San Francisco State University; Stephanie Claussen, San Francisco State University; Fatemeh Khalkhal, San Francisco State University; Yiyi Wang, San Francisco State University

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Educational Research and Methods Division (ERM)

quotes below are in response to the criterion "Connectionbetween Identity and Team Experiences" (T1S1's rating was 1, whereas T1A1's ratingwas 4): This was a clear weakness in the GPT-generated ARM. To me, GPT seemed to fabricate the stated connection between Omar’s experience in [Engineering Course ST] and his engineering identity (I don’t think Omar indicated that this experience made him feel more – or less – like an engineer). … As another example of where I think GPT may be giving an interpretation that the data does not support, it said, “Omar's teamwork experience in [Engineering Course ST] made him feel more like an engineer.” I don’t see Omar actually saying this. In short, GPT’s

Conference Session

Educational Research and Methods Division (ERM) Technical Session 21

Collection

2024 ASEE Annual Conference & Exposition

Authors

Kaden Holt, University of Oklahoma; Javeed Kittur, University of Oklahoma

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Diversity

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Educational Research and Methods Division (ERM)

Statistics. Retrieved July 8, 2023, from https://nces.ed.gov/programs/digest/d22/tables/dt22_311.15.asp 5. Heyman, E. (2010). Overcoming student retention issues in higher education online programs: A Delphi study. University of Phoenix. 6. Christensen, G., Steinmetz, A., Alcorn, B., Bennett, A., Woods, D., & Emanuel, E. (2013). The MOOC phenomenon: Who takes massive open online courses and why? Available at SSRN 2350964. 7. Bawa, P. (2016). Retention in online courses: Exploring issues and solutions—A literature review. Sage Open, 6(1), 2158244015621777. 8. Brunhaver, S., Bekki, J., Lee, E., & Kittur, J. (2019, March). Understanding the factors contributing to persistence

Conference Session

Educational Research and Methods Division (ERM) Technical Session 27

Collection

2024 ASEE Annual Conference & Exposition

Authors

Fanyi Zhang, Purdue University; Beth M. Holloway, Purdue University ; Eric Holloway, Purdue University

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Educational Research and Methods Division (ERM)

Conference Session

Computer Science Education and AI research

Collection

2023 ASEE Annual Conference & Exposition

Authors

Na Zhao, Nanyang Technological University; Ibrahim H. Yeter, Nanyang Technological University; Cristina Diordieva, Nanyang Technological University

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Educational Research and Methods Division (ERM)

this material are those of the author(s) and do notnecessarily reflect the views of the URECA program. We would like to acknowledge all theresearchers, data collectors, and students who participated in the study.References[1] L. D. Xu, E. L. Xu and L. Li, “Industry 4.0: state of the art and future trends,” InternationalJournal of Production Research 56, no. 8, pp. 2941-2962, 2018.[2] R. Jiao, L. Luo, J. Malmqvist and J. Summers, “New Design: Opportunities for EngineeringDesign in an Era of Digital Transformation,” Journal of Engineering Design 33, no. 10, pp. 685-690, 2022.[3] J. M. Wing, “Computational Thinking,” Communications of the ACM 49, no. 3, pp. 33-35,2006.[4] Y. Li, A. H. Schoenfeld, A.A. diSessa, A. C. Graesser, L. C. Benson, L. D

Conference Session

Educational Research and Methods Division (ERM) Technical Session 27

Collection

2024 ASEE Annual Conference & Exposition

Authors

Andrew Jackson, University of Georgia; Daniel Bayah, University of Georgia; Nathan Mentzer, Purdue University ; Scott R Bartholomew, Brigham Young University; Scott Thorne, Purdue University ; Wonki Lee, Purdue University

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Educational Research and Methods Division (ERM)

design and manufacturing. He is also currently serves as a board member for Indiana TSA as the Competitive Events Coordinator.Ms. Wonki Lee, Purdue University Wonki Lee is pursuing a PhD in Curriculum and Instructionˆa C™s Literacy and Language program at Purdue University. She received her B.A and M.S in Korean Language Education from Seoul National University, South Korea. She served culturally and linguistical ©American Society for Engineering Education, 2024 Assessing design thinking mindset: Using factor analysis to reexamine instrument validityAbstractThis method paper analyzes validity evidence of the Design Thinking Mindset Questionnaire andextends the

Conference Session

Educational Research and Methods Division (ERM) Technical Session 11

Collection

2024 ASEE Annual Conference & Exposition

Authors

Denise M. Driscoll, Purdue University ; Kristin M. Everett, Everett Evaluation; Alycia J. Sterenberg Mahon, Everett Evaluation

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Educational Research and Methods Division (ERM)

or 2-factor solution. Both solutions were explored using a CFA.Model-data fit, item factor loadings, and interfactor correlations were evaluated to determine thebest factor solution.Results of COI ItemsA 2-factor solution was first explored (see Table 1 below that also includes the data in 2021 whenthe items were in a set order). Six items significantly loaded onto Factor 1 (Inclusion) with fiveitems significantly loading onto Factor 2 (Culture) using the threshold of 0.45. “I feel that I fit inwith ’s workplace culture” had the highest loading on Factor 1 with a loadingof 0.966. The interpretation for this item on Factor 1 is – when all other items are held constant, if“I understand ’s workplace culture” increased by one unit, we expect

Conference Session

Educational Research and Methods Division (ERM) Technical Session 13

Collection

2024 ASEE Annual Conference & Exposition

Authors

Kyle Shanachilubwa, Harding University; James L. Huff, Harding University; Amy L. Brooks, University of Pittsburgh

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Educational Research and Methods Division (ERM)

. AcknowledgmentsThis work was supported through funding by the National Science Foundation (NSF CAREER#2045392). Any opinions, findings, and conclusions or recommendations expressed in thismaterial are those of the author(s) and do not necessarily reflect the views of the NationalScience Foundation. Additionally, the authors gratefully acknowledge the anonymous reviewersfor their constructive feedback, which helped us to sharpen the paper. References[1] S. A. Bjorklund, J. M. Parente, and D. Sathianathan, “Effects of faculty interaction and feedback on gains in student skills,” J of Engineering Edu, vol. 93, no. 2, pp. 153-160, 2004.[2] E. K. Briody, E. Wirtz, A. Goldenstein, and E. J. Berger, “Breaking

Conference Session

Educational Research and Methods Division (ERM) Technical Session 15

Collection

2024 ASEE Annual Conference & Exposition

Authors

Olanrewaju Paul Olaogun, University of Georgia; Nathaniel Hunsu, University of Georgia

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Educational Research and Methods Division (ERM)

Education, vol. 35, no. 4, pp. 601-635, 2013.[7] J. P. Smith III, A. A. DiSessa, and J. Roschelle, "Misconceptions reconceived: A constructivist analysis of knowledge in transition," The journal of the learning sciences, vol. 3, no. 2, pp. 115- 163, 1994.[8] J. H. Wandersee, J. J. Mintzes, and J. D. Novak, "Research on alternative conceptions in science," Handbook of research on science teaching and learning, vol. 177, p. 210, 1994.[9] S. Vosniadou, "Conceptual change research: An introduction," in International Handbook of Research on Conceptual Change: Routlege, Taylor and Francis, 2013, pp. 1-8.[10] C. A. Chinn and W. F. Brewer, "The role of anomalous data in knowledge acquisition: A theoretical

Conference Session

Educational Research and Methods Division (ERM) Technical Session 4

Collection

2024 ASEE Annual Conference & Exposition

Authors

Gabriella M. Sallai, Pennsylvania State University; Catherine G. P. Berdanier, Pennsylvania State University

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Educational Research and Methods Division (ERM)

Grant #DGE1255832.Any opinions, findings, conclusions, or recommendations expressed in this material are those ofthe author(s) and do not necessarily reflect the views of the National Science Foundation.REFERENCES[1] Council of Graduate Schools, “Ph.D. completion and attrition: Analysis of baseline program data from the Ph.D. completion project,” Washington D.C, 2008.[2] R. Sowell, J. Allum, and H. Okahana, “Doctoral initiative on minority attrition and completion,” Council of Graduate Schools, Washington D. C, 2015.[3] M. Bahnson and C. G. P. Berdanier, “Current trends in attrition considerations of engineering Master’s and Ph.D. students at research-intensive universities in the United States,” Int. J. Eng. Educ., vol. 39, no. 1

Conference Session

Educational Research and Methods Division (ERM) Technical Session 23

Collection

2024 ASEE Annual Conference & Exposition

Authors

Zain ul Abideen, Utah State University; Oenardi Lawanto, Utah State University; Talha Naqash, Utah State University; Angela Minichiello, Utah State University

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Educational Research and Methods Division (ERM)

the growing needs ofthe industry.References[1] J. Krajcik, “Three-Dimensional Instruction: Using a New Type of Teaching in the Science Classroom,” Science Scope, vol. 039, no. 03, 2015, doi: https://doi.org/10.2505/4/ss15_039_03_16.[2] İ. Topsakal, S. A. Yalçın, and Z. Çakır, “The Effect of Problem-based STEM Education on the Students’ Critical Thinking Tendencies and Their Perceptions for Problem Solving Skills,” Science Education International, vol. 33, no. 2, pp. 136–145, May 2022, Available: https://icaseonline.net/journal/index.php/sei/article/view/400[3] C. Sen, Z. Ay, A. Seyit, and Kiray, “STEM Skills in the 21 st Century Education.” Available: https://www.isres.org/books/chapters/STEM

Conference Session

Educational Research and Methods Division (ERM) Technical Session 28

Collection

2024 ASEE Annual Conference & Exposition

Authors

Berenice A. Cabrera, University of Michigan; Shannon M. Clancy, University of Michigan; Vibhavari Vempala, University of Michigan; Jingfeng Wu, University of Michigan; Erika Mosyjowski, University of Michigan; Lisa R. Lattuca, University of Michigan; Joi-lynn Mondisa, University of Michigan; Shanna R. Daly, University of Michigan

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Educational Research and Methods Division (ERM)

Chemical Engineering from the University of Dayton and a Ph.D. in Engineering Education from Purdue University. ©American Society for Engineering Education, 2024 Understanding the Skills and Knowledge Emphasized in Undergraduate Industrial Engineering CoursesAbstractIn an effort to characterize how, if at all, required courses in industrial engineering (IE) facilitatestudents’ development of sociotechnical engineering skills, this research examined the generalcontent of required IE courses at a large, predominantly white institution in the Midwest. Thispaper drew on data generated for a larger research study that leverages Holland et al.'s figuredworlds framework to explore the messaging that

Conference Session

Virtual Training, Online and Open Education; Instructional Technology

Collection

2023 ASEE Annual Conference & Exposition

Authors

Olivia Ryan, Virginia Tech Department of Engineering Education; Marin Jayne Fisher, Department of Engineering Education at Virginia Tech; Lisa Schibelius, Virginia Tech Department of Engineering Education; Mark Vincent Huerta, Virginia Polytechnic Institute and State University; Susan Sajadi, Virginia Tech

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Educational Research and Methods Division (ERM)

conflict management skills from the workshop on their studentteams. References[1] “Criteria for Accrediting Engineering Programs, 2022 – 2023 | ABET.” https://www.abet.org/accreditation/accreditation-criteria/criteria-for-accrediting-engineering -programs-2022-2023/ (accessed Jan. 23, 2023).[2] K. J. Behfar, R. S. Peterson, E. A. Mannix, and W. M. K. Trochim, “The critical role of conflict resolution in teams: a close look at the links between conflict type, conflict management strategies, and team outcomes,” J. Appl. Psychol., vol. 93, no. 1, pp. 170–188, Jan. 2008, doi: 10.1037/0021-9010.93.1.170.[3] T. A. O’Neill and M. J. W. McLarnon, “Optimizing team conflict

Conference Session

Educational Research and Methods Division (ERM) Technical Session 27

Collection

2024 ASEE Annual Conference & Exposition

Authors

Mayar Madboly, Virginia Polytechnic Institute and State University; Nicole P. Pitterson, Virginia Polytechnic Institute and State University

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Educational Research and Methods Division (ERM)

. Mehra, D. A. (Denny) Gioia, and S. Borgatti, “Brokering Trust toEnhance Leadership: A Self-Monitoring Approach to Leadership Emergence,” in Knowledgeand Networks, vol. 11, J. Glückler, E. Lazega, and I. Hammer, Eds., in Knowledge and Space,vol. 11. , Cham: Springer International Publishing, 2017, pp. 221–240. doi: 10.1007/978-3-319-45023-0_11.[4] A. Speer, “Quantifying with words An investigation of the validity of narrative‐derivedperformance scores.” Personnel psychology, 2018.[5] X. M. Wang, K. F. E. Wong, and J. Y. Y. Kwong, “The roles of rater goals and rateeperformance levels in the distortion of performance ratings.,” Journal of Applied Psychology,vol. 95, no. 3, pp. 546–561, 2010, doi: 10.1037/a0018866.[6] S. B. Hunter, “The

Conference Session

Formation and Development of Engineers

Collection

2023 ASEE Annual Conference & Exposition

Authors

Corin L. Bowen, California State University, Los Angeles; Michael W. Ibrahim; Gustavo B. Menezes, California State University, Los Angeles

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Diversity

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Educational Research and Methods Division (ERM)

provide the average duration of their commute, and those wholive off-campus are asked whether they live with the individuals who raised them as children andwhether they have responsibilities to care for children themselves. This demographic informationTable 1: Dependent Variables Variable Construct and Source Survey Items (Adapted) Classroom “Perceived Classroom Please rate your agreement with the following statements, which Comfort Comfort” from Hoffman et relate to your comfort levels about having discussions, academic, al.’s “Sense of Belonging personal, or otherwise, with members of the Cal State LA Scale” [12] community

Conference Session

Educational Research and Methods Division (ERM) Technical Session 21

Collection

2024 ASEE Annual Conference & Exposition

Authors

Jack Elliott, Iron Range Engineering, Minnesota State University, Mankato; Angela Minichiello, Utah State University

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Educational Research and Methods Division (ERM)

,” Int J Technol Des Educ, vol. 26, no. 3, pp. 413–437, 2016, doi: 10.1007/s10798-015-9318-z.[2] C. N. Gunawardena, N. V Flor, D. Gomez, and D. Sanchez, “Analyzing social construction of knowledge online by employing interaction analysis, learning analytics, and social network analysis,” Q Rev Distance Educ, no. 3, p. 35, 2016.[3] S. Hall, C. T. Amelink, and S. S. Conn, “A case study of a thermodynamics course: Informing online course design,” Journal of Online Engineering Education, vol. 1, no. 2, 2010.[4] B. K. Jesiek, L. K. Newswander, and M. Borrego, “Engineering education research: Discipline, community, or field?,” Journal of Engineering Education, vol. 98, no. 1, pp. 39–52, Jan. 2009, doi

Conference Session

Educational Research and Methods Division (ERM) Technical Session 29

Collection

2024 ASEE Annual Conference & Exposition

Authors

Matthew M. Grondin, University of Wisconsin, Madison; Michael I. Swart, University of Wisconsin, Milwaukee

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Educational Research and Methods Division (ERM)

generated for each dyad using ENA [25]. Panel A of Figure 7 shows the ENA graph of the baseline strength of interconnectionsamong codes representative of students’ argumentation and negotiation in the classroom.Observations of epistemic relationships during argumentation and negotiation (red connections)show a weak CD-M correlation (r=0.16) and moderate CC-M correlation (r=0.49). This suggeststhat during argumentation and negotiation, students produced less gestures that were misalignedwith course-specific speech compared to gestures conceptually aligned with course-specificspeech. This differs from H1’s prediction that there would be a stronger correlation betweenstudents conceptually misaligned gestures and course-specific speech

Conference Session

Educational Research and Methods Division (ERM) Poster Session

Collection

2024 ASEE Annual Conference & Exposition

Authors

Amirreza Mehrabi, Purdue University; Jason Morphew, Purdue University

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Educational Research and Methods Division (ERM)

transition from colleges of engineering to employment,” European Journal of Engineering Education, vol. 37, no. 1, pp. 3–14, Mar. 2012, doi: 10.1080/03043797.2011.644761.[4] T. R. Guskey, “Closing Achievement Gaps: Revisiting Benjamin S. Bloom’s ‘Learning for Mastery,’” http://dx.doi.org/10.4219/jaa-2007-704, vol. 19, no. 1, pp. 8–31, Nov. 2007, doi: 10.4219/JAA-2007-704.[5] M. Hansen, L. Cai, S. Monroe, and Z. Li, “Limited‐information goodness‐of‐fit testing of diagnostic classification item response models,” British Journal of Mathematical and Statistical Psychology, vol. 69, no. 3, pp. 225–252, Nov. 2016, doi: 10.1111/BMSP.12074.[6] M. Winget and A. M. Persky, “A Practical Review of Mastery Learning,” Am J Pharm Educ, vol. 86