Conference Session

Educational Research and Methods Division (ERM) Technical Session 18

Collection

2024 ASEE Annual Conference & Exposition

Authors

Robert Harold Lightfoot Jr., Texas A&M University; Tracy Anne Hammond, Texas A&M University

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Diversity

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Educational Research and Methods Division (ERM)

STUDENT RETENTION AND SATISFACTION IN COMPUTER SCIENCE SERVICE COURSES WHEN USING COMPETENCY-BASED GRADING AND ASSIGNMENT CHOICEAbstractEnrollment in introductory engineering courses, for non-Computer Science majors, often evokesapprehension, particularly when faced with the prospect of learning programming. The presenceof peers with prior coding experience can further compound these concerns. This study,applicable to a broad spectrum of engineering service courses, centers on student assignmentchoice within an undergraduate CS-1 curriculum. Guided by Self Determination Theory, weimplement assignment choice as a mechanism for students to chart a tailored path, selectingassignments aligned with course

Conference Session

Educational Research and Methods Division (ERM) Technical Session 10

Collection

2024 ASEE Annual Conference & Exposition

Authors

Luis Delgado Jr., Penn State; Catherine G. P. Berdanier, Pennsylvania State University

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Diversity

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Educational Research and Methods Division (ERM)

trajectories; engineering writing and communication; and methodological development. ©American Society for Engineering Education, 2024 WIP: Development of a Survey to Investigate Engineering Faculty Diversity, Equity, Inclusion, and Belonging (DEIB) Practices in Graduate Research Group EnvironmentsIntroductionDiversity, Equity, Inclusion, and Belonging (DEIB) challenges in engineering education are moreevident at the graduate level where racial and ethnic diversity remains particularly low, and PhDattrition rates are extremely high for students from marginalized backgrounds [1], [2].Comprehending how to influence the culture of engineering education to successfully educate adiverse student

Conference Session

Educational Research and Methods Division (ERM) Technical Session 9

Collection

2024 ASEE Annual Conference & Exposition

Authors

Erick Vaclav Svec, Pontificia Universidad Católica de Chile; Gabriel Astudillo, Pontificia Universidad Católica de Chile; Luis Eduardo Vargas-Vidal, Pontificia Universidad Católica de Chile; Carolina López, Pontificia Universidad Católica de Chile; Ximena Hidalgo; Isabel Hilliger, Pontificia Universidad Católica de Chile; Jorge A. Baier, Pontificia Universidad Católica de Chile

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Educational Research and Methods Division (ERM)

anonymousIntroductionOver the past few years, mental health has become very important for higher education institutionsworldwide [1]. As a consequence, various universities have incorporated practices to promoteand enhance student well-being [2]. Well-being has been defined as a multidimensional concept,encompassing physical, contextual, and psychological aspects [3, 4], all of which can influencelearning processes [5]. As an intervention to foster well-being, our school of engineering hascreated the Well-being Teaching Assistant (WTA). Within our engineering courses, this role isassumed by undergraduate or graduate students, who is in constant communication with students,striving to (1) provide emotional containment for students experiencing complex situation

Conference Session

Educational Research and Methods Division (ERM) Technical Session 14

Collection

2024 ASEE Annual Conference & Exposition

Authors

Glenn Walters, University of North Carolina at Chapel Hill; Gordon Maples, University of North Carolina at Chapel Hill; Paul Mihas, University of North Carolina at Chapel Hill; Matthew Wettergreen, Rice University

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Educational Research and Methods Division (ERM)

informed framework thatcan be used to assess the quality of individual makerspaces in terms of their contribution toprofessional skill development and meaningful student experiences with long-term careerimpacts. We anticipate being able to share the work-in-progress results of our coding effortsfrom the interviews we will have completed.IntroductionOver the past two decades, makerspaces have undergone a remarkable evolution, transitioningfrom grassroots communities of hardcore independent tinkerers to vital components ofcontemporary innovation ecosystems. Starting the early 2000s, initiatives such as TechShop [1],founded in 2006, and the Hackerspace movement played crucial roles in popularizing themakerspace concept [2]. These early spaces

Conference Session

Educational Research and Methods Division (ERM) Technical Session 18

Collection

2024 ASEE Annual Conference & Exposition

Authors

Daniel Kane, Utah State University; Marlee Jacobs, Utah State University; Rosemary Yahne, Utah State University; Wade H. Goodridge, Utah State University

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Diversity

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Educational Research and Methods Division (ERM)

Cutting Test When Sampling Engineering Statics Students’ Spatial AbilityIntroductionSpatial ability is broadly defined as a cognitive ability to mentally create, manipulate, and retainspatial information [1], [2]. More specifically, spatial ability can be defined by a number ofconstructs including common constructs such as mental rotation, visuospatial memory, cross-sectional visualization, and navigation. [3], [4]. Applications of spatial ability are wide rangingand the number of constructs has not been formally agreed upon [5]. In this work, we refer tospatial ability as a quantification of performance on one or more specific constructs of spatialthinking assessed through a spatial ability test. This work specifically discusses constructs

Conference Session

Educational Research and Methods Division (ERM) Technical Session 20

Collection

2024 ASEE Annual Conference & Exposition

Authors

Dorian Bobbett, University of Michigan; Jeanne Sanders, University of Michigan; Larkin Martini, Virginia Polytechnic Institute and State University; Mark Vincent Huerta, Virginia Polytechnic Institute and State University; Karin Jensen, University of Michigan

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Educational Research and Methods Division (ERM)

graduate-level engineering students and how these doctoralstudents can be better supported.IntroductionFaculty advisors are some of the most important people doctoral students interact with duringtheir degree program [1]. They are not only responsible for helping students develop technicallyas researchers and academics, but they also serve as guiding figures for students’ personal andprofessional development [1]. However, engineering faculty often receive minimal training inproviding effective psychosocial support to their students. This can lead to poor research groupclimates, “chilly” environments for underrepresented groups, and an overall feeling of lack ofbelonging [2], [3]. These negative outcomes hinder graduate students’ ability to meet

Conference Session

Educational Research and Methods Division (ERM) Technical Session 5

Collection

2024 ASEE Annual Conference & Exposition

Authors

Trevor Franklin, Cornell University

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Diversity

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Educational Research and Methods Division (ERM)

broadening participation in engineering. ©American Society for Engineering Education, 2024 Work In Progress: Development of a Taxonomy of Undergraduate Engineering Admissions Practices and ProtocolsIntroductionUndergraduate engineering admissions has a profound influence on engineering participation asthe entry point to higher education programs but has been largely unstudied and unquestioned.This is particularly concerning because engineering has been plagued by an imbalance inparticipation across demographics at every stage from higher education to industry [1].Significant research has examined this issue in the context of engineering classrooms [2], majors[3], and other institutional policies

Conference Session

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

Collection

2023 ASEE Annual Conference & Exposition

Authors

Natasha Lagoudas Wilkerson, Texas A&M University; Karen E. Rambo-Hernandez, Texas A&M University; Rachelle Pedersen, Texas A&M University

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Diversity

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Educational Research and Methods Division (ERM)

taught high school technology and engineering education (Robotics/Engineering, AP Computer Science, and Video Production). ©American Society for Engineering Education, 2023 (Work in Progress) A Systematic Literature Review of Engineering Education in Middle School GradesIntroductionThis work-in-progress paper is a systematic literature review of engineering learning andteaching in middle school classrooms. Following the release of the Next Generation of ScienceStandards (NGSS) in 2013, most state science standards now include engineering in somecapacity [1] [2]. This has resulted in a dramatic increase in research on pre-college engineeringeducation in recent years [3]. However, the

Conference Session

Educational Research and Methods Division (ERM) Technical Session 20

Collection

2024 ASEE Annual Conference & Exposition

Authors

Lise Clara Mabour, Tufts University; Geling Xu, Tufts University; Brian Gravel, Tufts University

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Diversity

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Educational Research and Methods Division (ERM)

many knowledge sources, practices, andmethodologies that inform how they design and conduct research and their future orientations inthe discipline. Both graduate student researchers co-designed with the end user to developprojects or products [1]. Graduate student researchers in engineering education constantly designresearch studies, tools, and environments with their advisors, peers, and other researchers.However, opportunities to co-design engineering projects with learners and educators are lesscommon for engineering education graduate students. Yet the work that graduate studentresearchers develop can influence K-12 educators and students and vice versa. Thus, graduatestudent researchers must have experience working with learners and

Conference Session

Educational Research and Methods Division (ERM) Technical Session 13

Collection

2024 ASEE Annual Conference & Exposition

Authors

Greses Perez, Tufts University; Lise Clara Mabour, Tufts University; G. R. Marvez, Tufts University; Ymbar Isaias Polanco Pino, Tufts University

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Diversity

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Educational Research and Methods Division (ERM)

that can furtheralienate these students from a career in engineering [1]. The issue transcends the mere inclusionof Black and Latine communities in the discussion of what equitable and socially justengineering entails. It demands a shift towards Black and Latine communities leadingengineering ways of doing and the processes of developing technologies and solutions.Moreover, these transformations demand that the discipline sees community resources in theirown right, as legitimate forms of knowledge and practices in engineering, without expecting theacculturation of Black and Latine/x/a/o students.Another dimension of equity and justice efforts in engineering education focuses on disciplinarycontext and content, particularly what epistemologies

Conference Session

Advancing Diversity, Equity, and Inclusion

Collection

2023 ASEE Annual Conference & Exposition

Authors

Raian Islam, The University of Arizona; Gregory L. Heileman, The University of Arizona; Kian G. Alavy, University of Arizona; David Ruiter, University of California, San Diego

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Diversity

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Educational Research and Methods Division (ERM)

factors that may contribute to delays in student progressionthrough engineering degree programs. The universities engaged in this work are the University ofArizona, the University of California, San Diego, and the Georgia Institute of Technology. Thestudy was designed around three principles: (1) collaboration through task forces across multipleinstitutions, (2) disciplinary focus using an asset-based approach, and (3) a student-centered ap-proach to improving engineering student success through curriculum and instruction, leading toreforms in service of equitable outcomes. The primary analyses revealed the large variability incurricular structure and student success outcomes within each of these disciplines. Faculty andadministrators formed

Conference Session

Educational Research and Methods Division (ERM) Technical Session 6

Collection

2024 ASEE Annual Conference & Exposition

Authors

Bryce E. Hughes, Montana State University; Emmanuel Tetteh Teye, Montana State University

Tagged Topics

Diversity

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Educational Research and Methods Division (ERM)

) fields compared tostatistical expectations [1]. They are also less likely than their heterosexual, cisgender peers topersist in STEM majors and obtain STEM degrees [2, 3]. Bias, harassment, and unsupportiveenvironments in STEM departments contribute to these challenges, as LGBTQ studentsencounter more systemic hetero- and cisnormative learning and career climates than their peers[4, 5]. These climates have the potential to diminish students' identification with science andengineering, which would then inhibit their motivation, sense of belonging, and persistence inthese fields [6, 7]. Even though diversity initiatives in STEM fields have been slower to tend tothe inclusion of LGBTQ people [1], there are continued efforts to broaden participation

Conference Session

Educational Research and Methods Division (ERM) Technical Session 12

Collection

2024 ASEE Annual Conference & Exposition

Authors

Alexis Gillmore, University of Tennessee, Knoxville; Courtney June Faber, University at Buffalo, The State University of New York

Tagged Divisions

Educational Research and Methods Division (ERM)

some shared agency withresearchers to direct conversation [1]. The result can be data which provide a rich description of acomplex social topic. Interview data are typically analyzed by researchers who synthesize andinterpret findings from a large amount of data to share with research stakeholders [2].Thematic analysis or thematic coding is a common methodology for analyzing interview dataacross different approaches to qualitative research. In thematic analysis, researchers reviewinterview data for recurring words, ideas, topics, or perspectives which are categorized intothemes [3]. The results of the research are researcher-generated themes, which are oftendiscussed with supporting examples from participant quotes. When using this method

Conference Session

Educational Research and Methods Division (ERM) Technical Session 13

Collection

2024 ASEE Annual Conference & Exposition

Authors

Marjan Naghshbandi, University of Toronto; Sharon Ferguson, University of Toronto; Alison Olechowski, University of Toronto

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Diversity

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Educational Research and Methods Division (ERM)

features of the programthat influenced students’ build-up of social capital, and that the resulting persistence was realizedthrough students’ progress towards internships in CS and goals for paying-it-forward in CS.These findings inform our recommendations that future CS support programs and educationalsettings consider mentorship centered on socioemotional support, opportunities for collaboration,and time for fun social activities. Additional suggestions center on engaging socially-orientedindividuals with CS support programs. These insights inform facilitators and educators in CS ondesign choices that can encourage the persistence of underrepresented students in CS.IntroductionThe growing digital economy [1] and the widening gap in organizations

Conference Session

Educational Research and Methods Division (ERM) Technical Session 25

Collection

2024 ASEE Annual Conference & Exposition

Authors

Jordan Nickel, University of Waterloo; Gregory Litster, University of Toronto; Christopher Rennick, University of Waterloo; Ada Hurst, University of Waterloo; Carol Hulls P.Eng., University of Waterloo

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Educational Research and Methods Division (ERM)

Student Perceptions and Attitudes Towards Engineering Design in Work-Integrated Learning Contexts1 IntroductionTo continue enhancing student learning, many institutions are implementing work-integratedlearning programs (WIL) to aid in the development of work-ready graduates [1]. WIL integratesacademic studies with experiences within a workplace or practice setting [2]. These experiencescan take many forms including collaborative research projects, apprenticeships, co-operativeeducation, entrepreneurship, field placements, internships, professional placements, servicelearning, or work experiences. WIL programs are very common in undergraduate engineeringprograms and have more recently expanded to graduate programs

Conference Session

Educational Research and Methods Division (ERM) Technical Session 17

Collection

2024 ASEE Annual Conference & Exposition

Authors

Zachary Miller, University of South Alabama; Sean Walker, University of South Alabama; Rachel Chai, University of South Alabama

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Educational Research and Methods Division (ERM)

used to enhance studentlearning for the retention of students [1]. This cooperative model is implemented with after classstudy sessions associated with high-risk courses. The authors define a High-Risk Course as acourse with one or more of the following characteristics: (1) a 30% or higher failure rate, (2)taken within the first two years of a traditional student study program, (3) infrequent exams, (4)large amounts of reading, (5) large class sizes, and (6) voluntary/unrecorded class attendance.These classes are commonly referred to as “gatekeeper” or “weed out” courses [2]. The SI modelwas first introduced to help the retention of a 6-year medical school program in 1973 byUniversity of Missouri-Kansas City (UMKC) as Peer Assisted Learning

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)

Teams‬‭Introduction‬‭ he undergraduate engineering curriculum is made up of mostly engineering science classes, which are‬T‭classes heavy in mathematical content with little to no application. As a result, students rarely get to‬ ‭improve their‬‭engineering judgment‬‭skills, which we define as the ability to develop and use‬ ‭mathematical models for analysis and design. Our research team’s focus has been on implementing‬ ‭open-ended modeling problems (OEMPs) into the engineering science curriculum in efforts to elicit‬ ‭engineering judgment. OEMPs bring real-world engineering examples into courses and leverage the use‬ ‭of active learning that has shown to be so beneficial to students in STEM [1]. McNeill et. al found that‬ ‭undergraduate

Conference Session

Educational Research and Methods Division (ERM) Technical Session 22

Collection

2024 ASEE Annual Conference & Exposition

Authors

Amanda Ross, Virginia Polytechnic Institute and State University; Andrew Katz, Virginia Polytechnic Institute and State University; Kai Jun Chew, Embry-Riddle Aeronautical University, Daytona Beach; Holly M. Matusovich, Virginia Polytechnic Institute and State University

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Diversity

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Educational Research and Methods Division (ERM)

identified by the other model. The GPT-4 model tended to identifymore basic relationships, while manual analysis identified more nuanced relationships.Our results do not currently support using GPT-4 to automatically generate graphicalrepresentations of faculty’s mental models of assessments. However, using a human-in-the-loopprocess could help offset GPT-4’s limitations. In this paper, we will discuss plans for our futurework to improve upon GPT-4’s current performance.IntroductionAssessments are found in every engineering classroom and are an important part of our educationsystem [1]-[3]. Assessments play many different roles, including understanding studentimprovements in learning [4], acting as a tool to assist students with learning [5], [6

Conference Session

Educational Research and Methods Division (ERM) Technical Session 4

Collection

2024 ASEE Annual Conference & Exposition

Authors

Robin Jephthah Rajarathinam, University of Illinois at Urbana - Champaign; Joshua E. Katz, University of Illinois at Urbana - Champaign; Saadeddine Shehab, University of Illinois at Urbana - Champaign; Blake Everett Johnson, University of Illinois at Urbana - Champaign; Yuting W. Chen, University of Illinois at Urbana - Champaign; Marcia Pool, University of Illinois at Urbana - Champaign; Kristin M. Chochola, University of Illinois at Urbana - Champaign

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Educational Research and Methods Division (ERM)

, instructors, and researchers in that it shows the importance of establishing asystem that supports PD of GTAs (administrator relevance), describes the implementation ofservice learning in a course (instructor relevance), and connects the work and findings toliterature (researcher relevance).BackgroundGTA in engineeringGraduate Teaching Assistants are pivotal to the teaching infrastructure in higher education,particularly within the STEM disciplines, such as engineering. These individuals, who arethemselves pursuing graduate degrees, undertake a variety of teaching roles, from assistingfaculty in large lectures to leading small laboratory or recitation sessions [1]. Their contributionsare especially significant in introductory STEM courses, where the

Conference Session

Educational Research and Methods Division (ERM) Technical Session 10

Collection

2024 ASEE Annual Conference & Exposition

Authors

Serena Mao, Harvey Mudd College; David Chen, Harvey Mudd College; Magdalena Jones, Harvey Mudd College; Aye Mon Htut-Rosales, Harvey Mudd College; Laura Palucki Blake; Leah Mendelson, Harvey Mudd College; Steven Santana, Harvey Mudd College

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Diversity

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Educational Research and Methods Division (ERM)

identity, with data sourcedfrom pre- and post-term surveys, with a phased deployment of the diary and reflection activitiesacross multiple semesters. Given our centering of equity-mindedness, we analyze demographicdata to identify and attend to any equity gaps in student learning and experience. In this work-in-progress paper, we include a subset of Student Learning Outcomes (SLOs) focused on the designprocess and teamwork and a single measure for students’ identity as engineers. Data are analyzedusing a two-factor Analysis of Variance (ANOVA). The factors include (1) the phaseddeployment of data-collection, diary, and reflection activities (PHASE), and (2) whether thestudent identifies as a member of a racial or ethnic group that is historically

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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Diversity

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Educational Research and Methods Division (ERM)

scienceand engineering education? Through our analysis, we present four themes that characterize theexperiences of our study participants: (1) Experiencing painful isolation from faculty and peers,(2) Facing increased pressure to succeed, (3) Seeking and finding connection with faculty andpeers when faced with isolation, (4) Understanding themselves inside their respective programs.By comprehending the pervasive and hidden storylines influencing the interactions betweenfaculty and Black students in computer science and engineering, faculty members can gaininsights into how their actions can contribute to the success of these students. Introduction and BackgroundPrior literature underscores the vital role that students

Conference Session

Educational Research and Methods Division (ERM) Technical Session 14

Collection

2024 ASEE Annual Conference & Exposition

Authors

Hillary E. Merzdorf, Texas A&M University; Anna Stepanova, Texas A&M University; Saira Anwar, Texas A&M University; Pouneh Abbasian, Texas A&M University; Tracy Anne Hammond, Texas A&M University

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Educational Research and Methods Division (ERM)

survey results and summarizes suggestions for goingforward. This paper aims to provide a public and archival history of FIE 2023 to ensuretransparency and public engagement The conference was co-sponsored by two IEEE societies(i.e., Education Society and Computing Society) and the Educational Research and MethodsDivision (ERM) division of ASEE. We hope this paper starts a trend for future conferences.1 IntroductionThe IEEE ASEE Frontiers in Education (FIE) Conference is a major international conferencefocusing on educational innovations and engineering and computing education research. Theleading-edge science projects in educational approaches and technologies are generated at the FIEannual conference. The 53rd IEEE ASEE Frontiers in Education

Conference Session

Educational Research and Methods Division (ERM) Technical Session 7

Collection

2024 ASEE Annual Conference & Exposition

Authors

Mohammad Faraz Sajawal, University of Oklahoma; Javeed Kittur, University of Oklahoma

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Educational Research and Methods Division (ERM)

shown in Table 1. As a part of this project, one other studyhas been conducted using the collected data to examining students’ beliefs on the use of ChatGPTin engineering (Sajawal & Kittur, 2024). Table 1. Overview of Scales within the Instrument (Sajawal & Kittur, 2024) Scale (# of items) Definition Example Items Learning Tool (10) Students’ perceptions on the use of - ChatGPT can be used to write ChatGPT as a learning tool in doing essays homework, completing assignments, - ChatGPT can be used to expand projects, etc. general knowledge Trustworthiness (5

Conference Session

Educational Research and Methods Division (ERM) Technical Session 19

Collection

2024 ASEE Annual Conference & Exposition

Authors

Hudson James Harris, University of Oklahoma; Javeed Kittur, University of Oklahoma

Tagged Divisions

Educational Research and Methods Division (ERM)

+ Engineering, AI, or Artificial Intelligence + Engineering,Chat GPT + engineering + education, and Undergraduate artificial intelligence. (II) Screening theabstracts and full text of the articles to eliminate papers beyond the research topic's scope.Exclusion criteria such as EC 1: Articles written before 2013, EC 2: Articles not written in English,EC3: Articles not pertaining to engineering, EC 4: Articles not pertaining to generative AIexcluding Chat GPT (Deep learning, text generation, vast data input), were used. EC 5: Articlesnot pertaining to undergraduate engineering EC 6: Articles not pertaining to higher education EC7:Articles not pertaining to traditional Artificial intelligence / machine learning EC 8: Article is awork in progress. EC 9

Conference Session

Educational Research and Methods Division (ERM) Technical Session 23

Collection

2024 ASEE Annual Conference & Exposition

Authors

Godwyll Aikins, Florida Institute of Technology; Catherine G. P. Berdanier, Pennsylvania State University; Kim-Doang Nguyen, Florida Institute of Technology

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Educational Research and Methods Division (ERM)

acrossscience, technology, and industry. This revolution calls for data-savvy engineers who can extractinsights from information and apply them strategically. Data skills range from fundamentalmanipulation to advanced machine learning and AI [1]. Proficient engineers, able to contextualizeand interpret data, will be indispensable in the landscape of data-driven technologies. While datahas always been important in engineering, today's unprecedented volume and quality represent aparadigm shift [2]. Data itself now dictates hypotheses, making nearly every engineeringdiscipline data-intensive [3].This study investigates Mechanical and Aerospace Engineering (MAE) students' experiencesnavigating this data-centric field. Understanding their development of

Conference Session

Educational Research and Methods Division (ERM) Technical Session 28

Collection

2024 ASEE Annual Conference & Exposition

Authors

Mitchell Gerhardt, Virginia Polytechnic Institute and State University; Nicole P. Pitterson, Virginia Polytechnic Institute and State University; Emily Dringenberg, The Ohio State University; Benjamin Ahn, The Ohio State University

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Diversity

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Educational Research and Methods Division (ERM)

in their own ways.Dr. Benjamin Ahn, The Ohio State University Dr. Benjamin Ahn is an Associate Professor at The Ohio State University in the Department of Engineering Education. ©American Society for Engineering Education, 2024 Re-imagining Behavioral Analysis in Engineering Education: A Theoretical Exploration of Reasoned Action ApproachIntroductionAs a discipline, Engineering Education continues to expand its reach, and subsequently, itsmethods of analysis. Integrating research from the behavioral sciences and psychology hasenhanced researchers’ capacities to explore the intricate and multifaceted behaviors inherent toengineering practice and education [1], [2], [3]. These

Conference Session

Educational Research and Methods Division (ERM) Technical Session 20

Collection

2024 ASEE Annual Conference & Exposition

Authors

Terkuma Stanley Asongo, University of Massachusetts, Lowell; Hsien-Yuan Hsu, University of Massachusetts, Lowell

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Educational Research and Methods Division (ERM)

validity, some lack detailed psychometric properties, emphasizing the need for further validation studies to enhance the quality of measurement tools in doctoral education. Conclusions: This scoping review not only identifies validated instruments but also underscores the importance of rigorous validation protocols and transparent reporting of psychometric properties for ensuring the credibility and replicability of research findings in this critical area. Future research should prioritize the development of instruments tailored to the unique dynamics of doctoral mentoring relationships. 1. INTRODUCTION 1.1 Importance of Effective Mentorship in Doctoral

Conference Session

Educational Research and Methods Division (ERM) Technical Session 10

Collection

2024 ASEE Annual Conference & Exposition

Authors

Xiaoye Yang, University of Massachusetts, Lowell; Hsien-Yuan Hsu, University of Massachusetts, Lowell; Yanfen Li, University of Massachusetts, Lowell

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Educational Research and Methods Division (ERM)

learning andstudents’ outcomes, encompassing participation in STEM, academic and socialaccomplishments, as well as persistence and retention. In our previous work centered oninstruments measuring SB [1], we discerned that within the college context, SB’s nature —whether singular or multifaceted — hinges on the underlying theoretical framework. This naturemight intersect with other concepts such as “university connectedness” [2], “sense of inclusion”[3], “sense of social fit” [4], “sense of community” [5], and “perceived cohesion” [6]. However,without comprehensive research to determine if these concepts are synonymous with SB ordistinct yet related, our previous study refrained from using these terms as search keywords.Hence, the instruments

Conference Session

Educational Research and Methods Division (ERM) Technical Session 12

Collection

2024 ASEE Annual Conference & Exposition

Authors

Hank Boone, University of Nevada, Las Vegas; Danxu Wang, University of Nevada, Las Vegas; Emma Regentova, University of Nevada, Las Vegas; Venkatesan Muthukumar, University of Nevada, Las Vegas; SJ Kim, University of Nevada, Las Vegas; Jonathan Hilpert, University of Nevada, Las Vegas

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Diversity

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Educational Research and Methods Division (ERM)

schools, thecommunity, and the workplace [1]. Studies show that students who have an increased interest inscience, mathematics, and engineering in the early years (elementary and middle schools) oftheir education are more likely to pursue a STEM-related career [2]. Informal STEM educationexperiences are considered critical to developing the future STEM workforce [3]. InformalSTEM education can also help to address equity and access issues in STEM education. Studentsfrom underrepresented groups, including women and minorities, may face barriers to STEMeducation in traditional classroom settings, but informal STEM education can provide alternativeavenues for learning and engagement that are more inclusive and accessible [4]. Informal STEMeducation

Conference Session

Educational Research and Methods Division (ERM) Technical Session 28

Collection

2024 ASEE Annual Conference & Exposition

Authors

Elisa Koolman, University of Texas at Austin; Audrey Boklage, University of Texas at Austin

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Educational Research and Methods Division (ERM)

makerspaces can result inincreased collaboration, creativity, leadership, and problem solving [1], so understanding theaspects that can affect student experience is important. To understand the student staff’sstrengths in makerspaces, this work seeks to answer the research questions: • What are the assets student staff articulate through their experiences with others in the makerspace?Researchers interviewed eight student staff members at a university makerspace in theengineering building at a large university. These semi-structured interviews were analyzed usinggrounded theory techniques and qualitative methods including inductive coding to develop atheoretical framework for interactions among student staff in university maker spaces