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 4

Collection

2024 ASEE Annual Conference & Exposition

Authors

Galen I. Papkov, Florida Gulf Coast University; Jiehong Liao, Florida Gulf Coast University

Tagged Topics

Data Science & Analytics Constituent Committee (DSA), Diversity

Paper ID #42267Effectiveness of a Semi-Mastery-Based Learning Course DesignDr. Galen I. Papkov, Florida Gulf Coast University Dr. Galen Papkov is a Professor of Statistics at Florida Gulf Coast University where he founded the minor in statistics and currently serves as the Graduate Program Coordinator for the M.S. Program in Applied Mathematics. His collaborations have resulted in publications in engineering education, agriculture, and health sciences. Originally from New York, he earned his Ph.D. in Statistics from Rice University. Galen’s research interests include experimental design, survey design and data analysis

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

Paper ID #42406Extra Credit Analysis of Undergraduate Engineering StudentsTushar Ojha, University of New Mexico Tushar Ojha is a graduate (PhD) student in the Department of Electrical and Computer Engineering at the University of New Mexico (UNM). His work is focused on researching and developing data-driven methods for analyzing and predicting outcomes in the higher education space. He works as a Data Scientist for the Institute of Design & Innovation (IDI), UNM.Don Hush, University of New Mexico Dr. Hush has worked as a technical staff member at Sandia National Laboratories, a tenure-track professor in the ECE

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)

could also explore Battery management systems, which controls the operating conditions on the pack level.The second topic is more focused on continuous education and career upskilling and containsthese specific keywords: course, work, career, industry, field, design, experience, master,analysis, role, software, engineer, project, time, company, machine, management, code, class,area, math, interest, process, python, system, research, matlab, simulation, thing, mech. Thekeywords overall seem to capture themes around perceptions of data science's place in theengineering profession, its relationship to technical skills, and considerations around training andcareer development in data science. The attitudes and viewpoints around these areas

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

and faculty.The insights presented in this study offer valuable guidance for educators and industryprofessionals seeking to seamlessly embed data science into the chemical engineering curriculumand better prepare students for a data-centric industry.This paper provides a comprehensive overview of interview development, data distribution, andkey findings. It underscores the urgency of further research to enhance the integration of datascience in the CHE curriculum and the essential role of preparing students for an industry thatincreasingly relies on data analytics and computational techniques.IntroductionThe integration of data science in chemical engineering is a rapidly evolving field, with a focuson data management, statistical and machine

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

Paper ID #42783Application of Data Analysis and Visualization Tools for U.S. Renewable SolarEnergy Generation, Its Sustainability Benefits, and Teaching In EngineeringCurriculumMr. Ben D Radhakrishnan, National University Ben D Radhakrishnan is a Professor of Practice, currently a full time Faculty in the Department of Engineering, School of Technology and Engineering, National University, San Diego, California, USA. He is the Academic Program Director for MS Engineering Management program. He develops and teaches Engineering courses in different programs including engineering and business management schools. His research

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)

Computing SQL Programming, Introduction to Programming, Algorithms, Data Fundamentals Structures, Object Oriented Programming, Software Engineering, Systems Analysis and Design, Human-Computer Interaction 2 Data Management, Data Warehousing, SQL, Databases, Security, Fraud Detection, Network Governance, Privacy Security, Ethics 3 Data Visualization Data Visualization 4 Machine Learning Machine Learning, Data Modeling, Artificial Intelligence, Deep Learning 5 Data Mining, Big Data Data mining, Data modeling, systems analysis, Big Data, Data munging 6 Data

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

Paper ID #41074Integrating Data Science into the Pipeline Building Toward a Diversified Workforcein Nuclear Energy and SecurityDr. Xiang Zhao, Alabama A&M University Dr. Xiang (Susie) Zhao, Professor in the Department of Electrical Engineering and Computer Science at the Alabama A&M University, has over 20 years of teaching experience in traditional on-campus settings or online format at several universities in US and aboard. Her teaching and research interests include programming languages, high performance algorithm design, data science, and evidence-based STEM teaching pedagogies. Her recent research work has been

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

curriculum.A key finding from our causal analysis indicates that an increase in program complexity by 20points is correlated with a decrease of 3. 74% in the likelihood of graduating within four years.Moreover, our counterfactual scenarios demonstrate that for students with specific demographicprofiles, such as males with a certain HSGPA not receiving Pell Grants, an increase in complexitycould inversely affect their graduation prospects. These nuanced discoveries underscore the impor-tance of curriculum design in alignment with student demographics and preparation, challengingeducators to balance academic rigor with the facilitation of student success. The breadth and scaleof our dataset significantly enrich the quality of our conclusions, providing

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)

. Python 127. MATLAB93. Statistics 105. Mathematical 116. R 128. Scala94. Algorithms Optimization 117. Apache Hadoop 129. NoSQL95. Data Engineering 106. Data Architecture 118. Java 130. Power BI96. Agile Methodology 107. Automation 119. Tableau 131. Object-Oriented97. Extract Transform 108. Artificial Intelligence 120. Apache Spark Programming Load 109. Data Management

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)

) (b) (c)Figure 7: Engineering program curricular patterns, showing course structural complexities withineach vertex. (a) Standard design for calculus-ready students, with a complexity of 22. (b) Alter-native design for non-calculus-ready students, with a complexity of 35. (c) Revised design fornon-calculus-ready students, reducing complexity to 25.administrators, and students. This case study explores the impact of curricular modifications ongraduation rates. We utilize the original and revised curricular patterns depicted in Figure 7, mod-eling them through MDP as demonstrated in Figure 8. The structural differences between thesetwo patterns are distinct, with the complexity of the original

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 6

Collection

2024 ASEE Annual Conference & Exposition

Authors

Smitesh Bakrania, Rowan University

Tagged Topics

Data Science & Analytics Constituent Committee (DSA)

interacting with somecontent online. However, the outcomes of LA can be mixed depending on its use andimplementation.In some ways, educating the educators about the LA outcomes is important for its effectiveimplementation. There is a need to overcome the negative sentiments towards LA and recognizethe value-added to both online and in-person learning. We must also investigate the cause for thenegative sentiments. Secondly, the majority of the studies focused on courses with largeenrollments. Would the benefits also translate to smaller classes designed for more traditionalon-campus students? Furthermore, many of these studies involved established online educationprograms. Students enrolled in these online programs are already familiar with online

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)

Paper ID #43321Optimizing Transfer Pathways in Higher EducationDr. Yiming Zhang, The University of Arizona Yiming Zhang completed his doctoral degree in Electrical and Computer Engineering from the University of Arizona in 2023. His research focuses on machine learning, data analytics, and optimization in the application of higher education.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

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)

Paper ID #42410Credit-Hour Analysis of Undergraduate Students Using Sequence DataTushar Ojha, University of New Mexico Tushar Ojha is a graduate (PhD) student in the Department of Electrical and Computer Engineering at the University of New Mexico (UNM). His work is focused on researching and developing data driven methods that are tailored to analyzing/predicting outcomes in the higher education space. He works as a Data Scientist for the Institute of Design & Innovation (IDI), UNM.Don Hush, University of New Mexico Dr. Hush has worked as a technical staff member at Sandia National Laboratories, a tenure-track

Conference Session

DSA Technical Session 4

Collection

2024 ASEE Annual Conference & Exposition

Authors

Fengbo Ma, Northeastern University; Xuemin Jin, Northeastern University

Tagged Topics

Data Science & Analytics Constituent Committee (DSA)

. Xuemin Jin is a teaching professor at the Department of Mechanical and Industrial Engineering at Northeastern University. He teaches two core courses for the Data Analytics Engineering Graduate Program, Data Management for Analytics and Data Mining in Engineering. His current research interests include emotion detection, remote sensing and atmospheric compensation. Before joining Northeastern University, Dr. Jin was a data scientist at State Street Corporation, a principal scientist at Spectral Sciences, Inc., a software engineer at eXcelon Corp, and a scientist at SerOptics, Inc. Dr. Jin received his Ph.D. in physics from University of Maryland at College Park. He was a postdoctoral at MIT and at TRIUMF Canada