Conference Session

DSAI Technical Session 10: Research Infrastructure and Institutional Insights

Collection

2025 ASEE Annual Conference & Exposition

Authors

Jordan Esiason, SageFox Consulting Group; Talia Goldwasser, SageFox Consulting Group; Rebecca Zarch, SageFox Consulting Group; Alan Peterfreund, SAGE

Tagged Topics

Diversity

Tagged Divisions

Data Science and Artificial Intelligence (DSAI) Constituent Committee

national or PEER’s home institution.state-level tables and reports, many researchers require more The data wing of Engineering PLUS (Continuous Improve-granular data at the institutional and/or discipline level in ment through Data, Evaluation, and Research, or CIDER)order to fully contextualize their work. This can introduce a was established to support project leadership, researchersprohibitive amount of labor into the act of retrieving data, such as PEERs, and Hub member stakeholders. The CIDERand complicates the process of joining datasets that exist at team brings together a multidisciplinary effort to supportdifferent levels of granularity

Conference Session

DSAI Technical Session 1: K–12 and Early Exposure to Data Science and AI

Collection

2025 ASEE Annual Conference & Exposition

Authors

Faiza Zafar, Rice University; Carolyn Nichol, Rice University; Matthew Cushing, Rice University

Tagged Divisions

Data Science and Artificial Intelligence (DSAI) Constituent Committee

services to boost productivity and streamline tasks. Google Scholar,for instance, provides a free database that helps students find scholarly articles, research papers,and other academic resources for their projects [15]. Notion serves as an all-in-one productivityplatform, combining note-taking, project management, and collaboration features, making itespecially useful for group work and managing busy schedules [15]. Grammarly, an AI-poweredwriting assistant, helps students refine their writing by checking for grammar, spelling,punctuation, and style while also offering suggestions for improving clarity and organization[14]. ChatGPT stands out as a powerful tool for homework assistance, test preparation,language learning, and other

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

self-directed learning opportunities. In this course, students learn how togather and analyze data as part of the engineering design process, apply systems thinking to anengineering or societal phenomenon, collaborate with peers to find solutions, and effectivelypresent solutions to an audience. Moreover, students are exposed to the introduction of theapplication of machine learning techniques to environmental datasets and Google Earth enginefor remote sensing datasets.This work will aim at reporting four main issues, namely (1) the unique components of thecurrent integrated data science course, (2) an account of selected environmental engineeringprojects using Python, (3) a survey result collecting data on students’ perception about the

Conference Session

DSAI Technical Session 10: Research Infrastructure and Institutional Insights

Collection

2025 ASEE Annual Conference & Exposition

Authors

Iqbal Hossain, The University of Arizona; Thomas Harman, University of Arizona; Wesley Nguyen, University of Arizona; Ravneet Chadha, The University of Arizona

Tagged Topics

Diversity

Tagged Divisions

Data Science and Artificial Intelligence (DSAI) Constituent Committee

Generation (RAG) system for research-related inquiries at the University of Arizona. Dr. Hossain has published over two dozen peer-reviewed articles in areas including data science, computer algorithms, graph theory, network visualization, information retrieval, information visualization, machine learning, natural language processing, and database systems. He actively collaborates with external groups, students, and researchers at the University of Arizona on a wide range of research projects. With over 20 years of professional experience in research, IT systems development, team management, and innovation, Dr. Hossain is passionate about designing data science systems and leading efforts to solve the university’s

Conference Session

DSAI Technical Session 7: Natural Language Processing and LLM Applications

Collection

2025 ASEE Annual Conference & Exposition

Authors

Alexis Frias, University of California Merced; Shrivaikunth Krishnakumar, San Jose State University; Ayush Pandey, University of California Merced

Tagged Divisions

Data Science and Artificial Intelligence (DSAI) Constituent Committee

’ interests and can lead to an increase in student engagementand agency.Recent innovations aim to address these limitations by integrating ML and NLP technologies intoautograding systems. These advancements enable tools to assess nuanced aspects of code, suchas design patterns, code readability, and logical structure [4]. For instance, ML models can ana-lyze code comments and programming styles to provide more personalized and detailed feedback.These systems balance the efficiency of automation with the depth of personalized evaluation,particularly for open-ended and creative assignments [5]. Furthermore, peer grading systems andML-based similarity detection are being explored to handle diverse outputs in open-ended projects.These innovations hold

Conference Session

DSAI Technical Session 1: K–12 and Early Exposure to Data Science and AI

Collection

2025 ASEE Annual Conference & Exposition

Authors

Carrie Grace Aponte, Kansas State University; Safia Malallah, Kansas State University; Lior Shamir, Kansas State University

Tagged Divisions

Data Science and Artificial Intelligence (DSAI) Constituent Committee

science courses bring them together and show the connections betweenthe concepts. Many new practices are also introduced in these data science courses, includingdata scraping, data cleaning, unsupervised machine learning, writing functions, and chainingfunctions. This shows that data science holds value as a standalone subject, separate fromstatistics, mathematics, or other subjects.Integration into Existing Courses The nature of K-12 curriculum and schooling does not easilyallow for the creation of an entirely new course focused on data science, largely due to timelimitations. The integration of data science into existing courses can be an efficient way to botheducate students about data science and show practical applications for the concepts