Conference Session

DSAI Technical Session 3: Integrating Data Science in Curriculum Design

Collection

2025 ASEE Annual Conference & Exposition

Authors

Md. Yunus Naseri, Virginia Polytechnic Institute and State University; Vinod K. Lohani, Virginia Polytechnic Institute and State University; Manoj K Jha P.E., North Carolina A&T State University; Gautam Biswas, Vanderbilt University; Caitlin Snyder; Steven X. Jiang, North Carolina A&T State University; Caroline Benson Sear, Virginia Polytechnic Institute and State University

Tagged Topics

Diversity

Tagged Divisions

Data Science and Artificial Intelligence (DSAI) Constituent Committee

proficient at basic to advanced data science skills, has not made acquiringthese competencies in undergraduate programs obsolete but rather more relevant, as criticalthinking abilities developed through data science literacy education are essential for analyzingLLM outputs [2]. Moreover, when properly integrated into pedagogical practices, these LLMscan facilitate the teaching of data science literacy skills through enhanced personalized learningapproaches [3]. Data science literacy education typically follows two main approaches: standalonecourses (including general and core disciplinary courses, immersive degrees, minors, certificates,and MOOCs (massive open online course)) or integration within existing disciplinary courses.While

Conference Session

DSAI Technical Session 8: Learning Analytics and Data-Driven Instruction

Collection

2025 ASEE Annual Conference & Exposition

Authors

Chuhao Wu, Pennsylvania State University; Sarah Zipf, Pennsylvania State University; Na Li, Penn State University; David Benjamin Hellar, The Pennsylvania State University

Tagged Divisions

Data Science and Artificial Intelligence (DSAI) Constituent Committee

information. The online activity data records students’frequency of interacting with LMS and other related digital learning applications on a dailybasis.The selected class is an advanced-standing undergraduate course in psychology, designed andtaught by the same instructor during Fall 2021, 2022, and 2023. The instructor confirmed nomajor revisions were made to the course during these semesters, which provides a level ofconsistency for us to review and compare data points. Three undergraduate teaching and researchassistants coded each class as different types of activities (i.e., quiz, assignment) based on theinformation in the syllabus, LMS, and the faculty’s reflection on in-class activities (ICAs). Boththe syllabus and ICAs are provided by the

Conference Session

DSAI Technical Session 3: Integrating Data Science in Curriculum Design

Collection

2025 ASEE Annual Conference & Exposition

Authors

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

Tagged Topics

Diversity

Tagged Divisions

Data Science and Artificial Intelligence (DSAI) Constituent Committee

. However not all programslist their course syllabus online. Only those who provide free public access to the course syllabuswere chosen for the study.Table V lists all 14 data science programs chosen for this study. Six U.S. institutions analyzedincluding three private institutions: Columbia University, Duke University, University ofRochester, and three public institutions: University of Georgia, University of San Diego, andUniversity of Wisconsin-Madison. Eight Chinese institutions analyzed were Beijing Institute ofTechnology, Central University of Finance and Economics, Harbin Institute of Technology,Hefei University of Technology, Peking University, Shandong University of Finance andEconomics, Southwestern University of Finance and Economics

Conference Session

DSAI Technical Session 3: Integrating Data Science in Curriculum Design

Collection

2025 ASEE Annual Conference & Exposition

Authors

Ashraf Badir, Florida Gulf Coast University; Ahmed S. Elshall, Florida Gulf Coast University

Tagged Divisions

Data Science and Artificial Intelligence (DSAI) Constituent Committee

, which is freely available online (https://aselshall.github.io/edsbook). The isrequired as generic textbooks on Data Science with Python such as “Python for Data Analysis,O’Reilly, 3rd Edition” [20], which freely available online https://wesmckinney.com/book, do notcover specific tools and core package required for environmental data science such as Xarray,CartoPy, Earth engine, and Geemap.This EDS course serves as an introduction to water and environmental data analysis usingPython, a dynamic programming language with rich libraries for data science and scientificcomputing. These libraries include Pandas for spreadsheet analysis, Matplotlib for plotting,Plotly for interactive graphs, NumPy for scientific computing, Xarray for n

Conference Session

DSAI Technical Session 3: Integrating Data Science in Curriculum Design

Collection

2025 ASEE Annual Conference & Exposition

Authors

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

Tagged Divisions

Data Science and Artificial Intelligence (DSAI) Constituent Committee

shows an example of the student project outcomes, which include the implementationcode snippets, results, and presentation summary. Classification and regression models are usedto analyze the power plant operation datasets downloaded from Keggle [20]. Student projectswere implemented on Microsoft Azure or Google Colab. Table 1 includes the student assessmentresults in CS413/520 regarding the learning outcomes and the ABC rates (only grades A,B, andC are considered as “Pass” according to the computer science curriculum in the university). Thebase line data in Fall 2023 (without ProjBL) and the new data in Fall 2024 (with ProjBL) arecompared. The same instructor taught the course using the same syllabus. And the same courselearning outcomes have