Conference Session

DSA Technical Session 6

Collection

2024 ASEE Annual Conference & Exposition

Authors

Emily Nutwell, The Ohio State University; Thomas Bihari, The Ohio State University; Thomas Metzger, The Ohio State University

Tagged Topics

Data Science & Analytics Constituent Committee (DSA), Diversity

. She holds a BS in mechanical engineering, MA in educational studies, and a PhD in Engineering Education where her research focuses on digital learning environments for the STEM workforce.Thomas Bihari, The Ohio State UniversityThomas Metzger, The Ohio State University ©American Society for Engineering Education, 2024 An Online Interdisciplinary Professional Master’s Program in Translational Data AnalyticsAbstractThis paper describes an interdisciplinary data analytics professional master’s program whichincludes courses from the disciplines of computer science, statistics, and design. The onlinecurriculum structure specifically addresses the needs of working professionals

Conference Session

DSA Technical Session 5

Collection

2024 ASEE Annual Conference & Exposition

Authors

Mehmet Ergezer, Wentworth Institute of Technology; Mark Mixer, Wentworth Institute of Technology; Weijie Pang, Wentworth Institute of Technology

Tagged Topics

Data Science & Analytics Constituent Committee (DSA), Diversity

. ©American Society for Engineering Education, 2024 Bridging Theory and Practice: Building anInclusive Undergraduate Data Science Program Mehmet Ergezer, Mark Mixer, Weijie Pang Wentworth Institute of Technology Boston MA, 02115 USA {ergezerm, mixerm, pangw}@wit.edu Abstract As the field of Data Science (DS) continues to evolve, institutions of higher education face the challenge of developing curricula that prepare students for the industry’s rapidly changing landscape. In this paper, we will present a case study of the development and

Conference Session

DSA Technical Session 2

Collection

2024 ASEE Annual Conference & Exposition

Authors

Emma Fox, Franklin W. Olin College of Engineering; Zachary del Rosario, Olin College of Engineering

Tagged Topics

Data Science & Analytics Constituent Committee (DSA)

impact on design decisions. The following sections reviewrequisite Background, Frameworks, and Methods and summarize the key Results. We concludewith a Discussion including implications for collaborators on multidisciplinary teams, and fortraining engineering students to interpret statistical ideas.Background & FrameworksIn this section we review relevant definitions of the term “error” and detail our theoretical andconceptual frameworks.Definitions of errorIn mathematics, error is often defined as the accuracy of an approximation against a well-definedtrue value [7]. However, error and other sources of uncertainty are not a strong focus inmathematics. For instance, a recent review of mathematics in engineering-related work foundonly 2 out

Conference Session

DSA Technical Session 8

Collection

2024 ASEE Annual Conference & Exposition

Authors

Amirreza Mehrabi, Purdue Engineering Education; Jason Morphew, Purdue University, West Lafayette

Tagged Topics

Data Science & Analytics Constituent Committee (DSA)

Paper ID #42426Investigating and predicting the Cognitive Fatigue Threshold as a Factor ofPerformance Reduction in AssessmentMr. Amirreza Mehrabi, Purdue Engineering Education I am Amirreza Mehrabi, a Ph.D. student in Engineering Education at Purdue University, West Lafayette. Now I am working in computer adaptive testing (CAT) enhancement with AI and analyzing big data with machine learning (ML) under Prof. J. W. Morphew at the ENE department. My master’s was in engineering education at UNESCO chair on Engineering Education at the University of Tehran. I pursue Human adaptation to technology and modeling human behavior

Conference Session

DSA Technical Session 3

Collection

2024 ASEE Annual Conference & Exposition

Authors

Tushar Ojha, University of New Mexico; Don Hush, University of New Mexico

Tagged Topics

Data Science & Analytics Constituent Committee (DSA), Diversity

minimum required by a standard undergraduate degree (generally120 credit hours), or as the superfluous credits relative to the student’s specific degree program atgraduation [8, 15]. In this paper, we provide a new definition of excess credit hours (introduced byus in [13]) that takes into consideration the applicability(usability) of credits towards the degreerequirements (refer to Section 3). The more commonly used definition of excess credits used sofar in this Section will be referred to as extra credits from here on in this paper. It is clear thatexcess credits are a subset of extra credits. With this in mind, our primary objective in this paperis to explain the extra credit accumulation pattern of undergraduate engineering students

Conference Session

DSA Technical Session 3

Collection

2024 ASEE Annual Conference & Exposition

Authors

Aidan Kenny, Northeastern University; Andrew L Gillen, Northeastern University

Tagged Topics

Data Science & Analytics Constituent Committee (DSA), Diversity

Paper ID #41625Innovating Engineering Education Analysis through Creative Data VisualizationAidan Kenny, Northeastern UniversityDr. Andrew L Gillen, Northeastern University Andrew L. Gillen is an Assistant Teaching Professor at Northeastern University in the First Year Engineering Program and an affiliate faculty member to Civil and Environmental Engineering. He earned his Ph.D. in Engineering Education from Virginia Tech and B.S. in Civil Engineering from Northeastern University. ©American Society for Engineering Education, 2024 Innovating Engineering Education Analysis through

Conference Session

DSA Technical Session 4

Collection

2024 ASEE Annual Conference & Exposition

Authors

Duncan Davis, Northeastern University; Nicole Alexandra Batrouny, Northeastern Univeristy; Adetoun Yeaman, Northeastern University

Tagged Topics

Data Science & Analytics Constituent Committee (DSA), Diversity

engineering design, collaboration in engineering, decision making in engineering teams, and elementary engineering education.Dr. Adetoun Yeaman, Northeastern University Adetoun Yeaman is an Assistant Teaching Professor in the First Year Engineering Program at Northeastern University. Her research interests include empathy, design education, ethics education and community engagement in engineering. She currently teaches Cornerstone of Engineering, a first-year two-semester course series that integrates computer programming, computer aided design, ethics and the engineering design process within a project based learning environment. She was previously an engineering education postdoctoral fellow at Wake Forest University

Conference Session

DSA Technical Session 5

Collection

2024 ASEE Annual Conference & Exposition

Authors

Nicolas Leger, Florida International University; Maimuna Begum Kali, Florida International University; Stephanie Jill Lunn, Florida International University

Tagged Topics

Data Science & Analytics Constituent Committee (DSA)

suggestexamining perspectives on how data science fits into engineering roles and day-to-day work.Terms such as “engineer,” “field,” “industry,” “role,” “system” might imply studying views ondata science's place within the broader engineering profession. Concepts like “skill,” “software,”“automation,” and “system” might indicate attitudes related to technical abilities and computingskills needed for data science may be relevant. Keywords around education and training like“master,” “class,” “program,” and “degree” might suggest studying opinions on preparation andqualifications needed for data science. Words such as “resume,” “application,” “interview,” and“hire” might point to considerations around career development and advancement in data scienceroles

Conference Session

DSA Technical Session 8

Collection

2024 ASEE Annual Conference & Exposition

Authors

Paula Francisca Larrondo, Queen's University; Brian M Frank P.Eng., Queen's University; Julian Ortiz, Queen's University

Tagged Topics

Data Science & Analytics Constituent Committee (DSA)

an M.Sc. in Mining Engineering (Geostatistics) from the University of Alberta (Canada).Prof. Brian M Frank P.Eng., Queen’s University Brian Frank is the DuPont Canada Chair in Engineering Education Research and Development, and the Director of Program Development in the Faculty of Engineering and Applied Science at Queen’s University where he works on engineering curriculum development,Julian Ortiz, Queen’s University Dr. Ortiz is a Mining Engineer from Universidad de Chile and Ph.D. from University of Alberta. Currently, he is Professor and Mark Cutifani / Anglo American Chair in Mining Innovation at University of Exeter - Camborne School of Mines, in the United Kingdom, where he conducts research related to

Conference Session

DSA Technical Session 1

Collection

2024 ASEE Annual Conference & Exposition

Authors

Betul Bilgin, The University of Illinois at Chicago; Naomi Groza, The University of Illinois at Chicago

Tagged Topics

Data Science & Analytics Constituent Committee (DSA), Diversity

indicate a substantial level of exposure to data handling, which hascontributed to a generally high degree of self-efficacy regarding their data-related skills. Thisexposure spans across their academic experiences in chemical engineering (CHE) and otherdisciplines, as well as in their personal and professional lives. The students' confidence inworking with data is reflected in the quotations and can be organized into two categories:"Working with Data in CHE and Non-CHE Context" and "Confident/Comfortable in Workingwith Data."Working with Data in CHE and Non-CHE ContextStudents reported working with data in various contexts, both within chemical engineeringcourses and in other scientific labs, suggesting that their educational programs provide a

Conference Session

DSA Technical Session 2

Collection

2024 ASEE Annual Conference & Exposition

Authors

Ben D Radhakrishnan, National University; James Jay Jaurez, National University; Nelson Altamirano, National University

Tagged Topics

Data Science & Analytics Constituent Committee (DSA), Diversity

charged with the responsibility of taking the panels back on their EOL and re-introduce them in their new manufacturing. This practice is already being enforced in Europe (Europe’s WEEE Directive, 2021). - Recovering the rare minerals will help reduce unnecessary mining for these metals in poor countries in Africa and other countries including China. - Provide incentives for recycling.Solar Generation and its related Sustainability Benefits in EngineeringEducation with Data Analysis and Visualization toolsStudents’ perception of sustainability within the engineering management program relies largelyon personal experience and more educational background (Aginako & Guraya, 2021). In a

Conference Session

DSA Technical Session 7

Collection

2024 ASEE Annual Conference & Exposition

Authors

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

Tagged Topics

Data Science & Analytics Constituent Committee (DSA)

Virginia Tech approved ourprotocol under the IRB 21-639 number). The larger study leverages multiple sources of data, andin this analysis, we use two of those sources: 1) an initial survey that gathered demographic dataas well as data relative to mental models of assessment and 2) the first question from our eventsurveys which asked specifically about GAI and assessment.3.1 Data CollectionOur target population of participants included engineering faculty members who work for USinstitutions. We created an initial pool of faculty members from various resources: departmentfaculty lists for the top 50 engineering programs by size, engineering education journal authorlists, and the list of PIs on NSF projects related to STEM education. People who

Conference Session

DSA Technical Session 6

Collection

2024 ASEE Annual Conference & Exposition

Authors

Kristina A Manasil, The University of Arizona; Gregory L. Heileman, The University of Arizona; Bhavya Sharma, The University of Arizona; Ahmad Slim, The University of Arizona; Aryan Ajay Pathare, The University of Arizona; Husain Al Yusuf, The University of Arizona; Roxana Sharifi, The University of Arizona; Rohit Hemaraja, The University of Arizona; Melika Akbarsharifi, The University of Arizona

Tagged Topics

Data Science & Analytics Constituent Committee (DSA)

, learning analytics, and educational data mining.Prof. Gregory L. Heileman, The University of Arizona Gregory (Greg) L. Heileman currently serves as the Vice Provost for Undergraduate Education and Professor of Electrical and Computer Engineering at the University of Arizona, where he is responsible for facilitating collaboration across campus to strategically enhance quality and institutional capacity related to undergraduate programs and academic administration. He has served in various administrative capacities in higher education since 2004. Professor Heileman currently serves on the Executive Committee of AZTransfer, an organization that works across the system of higher education in the State of Arizona to

Conference Session

DSA Technical Session 5

Collection

2024 ASEE Annual Conference & Exposition

Authors

Duo Li, Shenyang Institute of Technology; Elizabeth Milonas, New York City College of Technology; Qiping Zhang, Long Island University

Tagged Topics

Data Science & Analytics Constituent Committee (DSA)

College of Technology - City University of New York (CUNY). She currently teaches relational and non-relational databases and data science courses to undergraduate students. She holds a BA in Computer Science and English Literature from Fordham University, an MS in Information Systems from New York University, and a Ph.D. from Long Island University. Her research interests focus on three key areas: data science curriculum and ethics, retention of minority students in STEM degree programs, and organization and classification of big data.Dr. Qiping Zhang, Long Island University Dr. Qiping Zhang is an Associate Professor in the Palmer School of Library and Information Science at the C.W. Post Campus of Long Island

Conference Session

DSA Technical Session 2

Collection

2024 ASEE Annual Conference & Exposition

Authors

Xiang Zhao, Alabama A&M University; Mebougna L. Drabo, Alabama A&M University

Tagged Topics

Data Science & Analytics Constituent Committee (DSA), Diversity

. Figure 1. The Logic Model © American Society for Engineering Education, 2024 2024 ASEE Annual Conference and Exposition Figure 2. Components of Summer Enrichment ProgramsTable 1 includes the data analytics related learning outcomes for the summer programs. Usingthe summer high school program as an example, lectures are given by full-time faculty membersand experienced guest speakers at national labs for instructional quality, focusing on concepts,theory, emerging topics and technical challenges in data science, physics, nuclear energy, nuclearsecurity, microelectronics, etc. Handson labs are added to reinforce the learning. Then studentsare given the opportunity to form

Conference Session

DSA Technical Session 1

Collection

2024 ASEE Annual Conference & Exposition

Authors

Gregory L. Heileman, The University of Arizona; Yiming Zhang, The University of Arizona

Tagged Topics

Data Science & Analytics Constituent Committee (DSA)

Paper ID #41711Minimizing Curricular Complexity through Backwards DesignProf. Gregory L. Heileman, The University of Arizona Gregory (Greg) L. Heileman currently serves as the Vice Provost for Undergraduate Education and Professor of Electrical and Computer Engineering at the University of Arizona, where he is responsible for facilitating collaboration across campus to strategically enhance quality and institutional capacity related to undergraduate programs and academic administration. He has served in various administrative capacities in higher education since 2004. Professor Heileman currently serves on the

Conference Session

DSA Technical Session 1

Collection

2024 ASEE Annual Conference & Exposition

Authors

Ahmad Slim, The University of Arizona; Gregory L. Heileman, The University of Arizona; Melika Akbarsharifi, The University of Arizona; Kristina A Manasil, The University of Arizona; Ameer Slim, University of New Mexico

Tagged Topics

Data Science & Analytics Constituent Committee (DSA), Diversity

, ensuring that themodel considers the multifaceted influences on graduation rates. The causal network diagram alsosuggests potential mediation effects, such as how the influence of Gender on graduation rates maybe mediated through variables like Pell Award or Program Complexity. Integrating this causalnetwork diagram into the study’s findings provides a powerful illustration of the causal relation-ships suggested by the PC algorithm. It offers a concrete foundation for further analysis, such asapplying statistical techniques such as logistic regression or gradient-boosting classifier (GBC) toestimate the causal effects quantitatively. These methods can validate the suggested pathways andassess the strength and significance of the relationships

Conference Session

DSA Technical Session 5

Collection

2024 ASEE Annual Conference & Exposition

Authors

Karl D. Schubert FIET, University of Arkansas; Shantel Romer, University of Arkansas; Stephen R. Addison, IEEE Educational Activities; Tina D Moore; Laura J Berry, North Arkansas College; Jennifer Marie Fowler, Arkansas State University; Lee Shoultz, University of Arkansas; Christine C Davis

Tagged Topics

Data Science & Analytics Constituent Committee (DSA)

Paper ID #42697Envisioning and Realizing a Statewide Data Science EcosystemDr. Karl D. Schubert FIET, University of Arkansas Dr. Karl D. Schubert is a Professor of Practice and serves as the Associate Director for the Data Science Program at the University of Arkansas College of Engineering, the Sam M. Walton College of Business, and the Fulbright College of Arts & Sciences.Shantel Romer, University of ArkansasStephen R. Addison, IEEE Educational ActivitiesTina D MooreLaura J Berry, North Arkansas CollegeJennifer Marie Fowler, Arkansas State UniversityLee Shoultz, University of ArkansasChristine C Davis

Conference Session

DSA Technical Session 8

Collection

2024 ASEE Annual Conference & Exposition

Authors

Neha Kardam, University of Washington; Denise Wilson, University of Washington; Sep Makhsous, University of Washington

Tagged Topics

Data Science & Analytics Constituent Committee (DSA)

during pre-pandemic semesters (2017,2018) or in a post-pandemic return to in-person learning (2022). Others experienced coursesduring the COVID-19 pandemic (2020 and 2021) when traditional teaching transitioned toemergency remote instruction [20]. 38.7% of students responding to the survey completed itwhile enrolled in traditional learning settings while 61.3% completed it during remoting learning(Emergency Remote Teaching or ERT) during the peak of the COVID-19 pandemic.The gender composition of the student population in this study was representative ofundergraduates enrolled in engineering programs in the U.S. The majority of students (n = 1376,74.1%) in this study were male, compared to national representation where 74.1% of students

Conference Session

DSA Technical Session 3

Collection

2024 ASEE Annual Conference & Exposition

Authors

Yiming Zhang, The University of Arizona; Gregory L. Heileman, The University of Arizona; Ahmad Slim, The University of Arizona; Husain Al Yusuf, The University of Arizona

Tagged Topics

Data Science & Analytics Constituent Committee (DSA)

collaboration across campus to strategically enhance quality and institutional capacity related to undergraduate programs and academic administration. He has served in various administrative capacities in higher education since 2004. Professor Heileman currently serves on the Executive Committee of AZTransfer, an organization that works across the system of higher education in the State of Arizona to ensure students have access to efficient, seamless, and simple ways to transfer from a community college to a university in Arizona. He serves on the board of the Association for Undergraduate Education at Research Universities, a consortium that brings together research university leaders with expertise in the theory and

Conference Session

DSA Technical Session 1

Collection

2024 ASEE Annual Conference & Exposition

Authors

Ahmad Slim, The University of Arizona; Gregory L. Heileman, The University of Arizona; Husain Al Yusuf, The University of Arizona; Yiming Zhang, The University of Arizona; Asma Wasfi; Mohammad Hayajneh; Bisni Fahad Mon, United Arab Emirates University; Ameer Slim, University of New Mexico

Tagged Topics

Data Science & Analytics Constituent Committee (DSA)

Framework for Curriculum AssessmentExpanding upon our previous discussions on curricular analytics, we examine the nuanced chal-lenge of analyzing the impact of curricula on student progression. This analysis is particularlycomplex due to the multifaceted nature of curriculum-related components influencing studentprogress. Our methodology focuses on decomposing the overall complexity of a curriculum into (a) (b)Figure 1: Undergraduate Electrical Engineering program structures at two major public univer-sities with the same ABET accreditation standards.two primary elements: instructional complexity, which refers to the pedagogical methods andsupport mechanisms

Conference Session

DSA Technical Session 3

Collection

2024 ASEE Annual Conference & Exposition

Authors

Tushar Ojha, University of New Mexico; Don Hush, University of New Mexico

Tagged Topics

Data Science & Analytics Constituent Committee (DSA)

propose a novelfeature engineering method as a way to study cooperation between a student feature sequence(e.g., financial aid, program change, etc.) and an outcome feature sequence (e.g., excess credits).As a result, each relevant student feature sequence is mapped into a feature value that attempts tocapture information that is relevant to the outcome. This enables a data-driven way to analyze theeffect of a large number of student features on excess credit accumulation.1 IntroductionThe credit hour was born out of the need to standardize learning for all students, to improveefficiency of institutions, to facilitate cross-institutional transfer, and to keep tabs on curriculumquality [20]. Recently, it has additionally grown into an instrument

Conference Session

DSA Technical Session 6

Collection

2024 ASEE Annual Conference & Exposition

Authors

Smitesh Bakrania, Rowan University

Tagged Topics

Data Science & Analytics Constituent Committee (DSA)

LA. The combinationof the insights gained by addressing the two questions above are captured in this work. Theoutcomes have the potential to inform future implementation of LA in regular courses andimprove teaching effectiveness.MethodologyTo address the two research questions, this work was split into two stages. The first stage,Course Learning Analytics, involved applying LA to two existing courses and recognizing thepotential insights. For the second stage, Instructor Perspective Survey, the LA results were thenused to gather faculty perceptions on the value of LA to their courses. It was important to useexisting courses at Rowan University’s Mechanical Engineering program for LA to demonstrateits utility in making educational decisions

Conference Session

DSA Technical Session 5

Collection

2024 ASEE Annual Conference & Exposition

Authors

Safia Malallah, Kansas State University; Ejiro U Osiobe, Baker University; Zahraa Marafie, Kuwait University; Patricia Henriquez-Coronel; Lior Shamir, Kansas State University; Ella Lucille Carlson, Kansas State University; Joshua Levi Weese, Kansas State University

Tagged Topics

Data Science & Analytics Constituent Committee (DSA)

, Baker University .Zahraa Marafie, Kuwait UniversityPatricia Henriquez-CoronelLior Shamir, Kansas State University Associate professor of computer science at Kansas State University.Ella Lucille Carlson, Kansas State UniversityJoshua Levi Weese, Kansas State University Dr. Josh Weese is a Teaching Assistant Professor at Kansas State University in the department of Computer Science. Dr. Weese joined K-State as faculty in the Fall of 2017. He has expertise in data science, software engineering, web technologies, computer science education research, and primary and secondary outreach programs. Dr. Weese has been a highly active member in advocating for computer science education in Kansas including PK-12 model standards

Conference Session

DSA Technical Session 6

Collection

2024 ASEE Annual Conference & Exposition

Authors

tonghui xu, University of Massachusetts, Lowell; Hsien-Yuan Hsu, University of Massachusetts, Lowell

Tagged Topics

Data Science & Analytics Constituent Committee (DSA)

Paper ID #41785Integrating Data-Driven and Career Development Theory-Driven Approachesto Study High School Student Persistence in STEM Career Aspirationstonghui xu, University of Massachusetts, Lowell PhD studentDr. Hsien-Yuan Hsu, University of Massachusetts, Lowell Dr. Hsien-Yuan Hsu is an Assistant Professor in Research and Evaluation in the College of Education at the University of Massachusetts Lowell. Dr. Hsu received his PhD in Educational Psychology from Texas A&M University and has a background of statistics ©American Society for Engineering Education, 2024 Integrating Features Selection