2026 ASEE Annual Conference & Exposition

From Curiosity to Capability: Expanding Pathways into Data and AI through ExLENT

Presented at NSF Grantees Poster Session I

Funded by NSF ExLENT program, "Data Crossings - Bridging to AI and Data Science Careers" initiative reimagines how adult learners and non-STEM professionals can access, engage with, and apply data and artificial intelligence (AI) tools in their careers. Rooted in the belief that data literacy is the new foundation of civic and economic participation, Data Crossings bridges the persistent gap between aspiration and opportunity by creating inclusive pathways into the data workforce. The program integrates experiential learning, design thinking, and industry mentorship to transform participants’ understanding of data from abstract concepts into lived, applicable skills. Through project-based modules and interdisciplinary collaborations, learners develop proficiency in data analysis, visualization, and ethical reasoning while addressing real-world challenges in their own professional and community contexts.

The Data Crossings model combines academic rigor with flexible, learner-centered design. Participants, many of whom are mid-career adults or from non-traditional educational backgrounds, gain not only technical skills but also confidence and agency to navigate AI-driven change. Evaluation of early cohorts demonstrates measurable gains in data self-efficacy, professional readiness, and cross-disciplinary collaboration, underscoring the program’s potential as a scalable framework for workforce transformation. By linking data skills to human purpose, Data Crossings embodies a new model of inclusive innovation - one that expands who gets to participate in the data revolution and how data can serve the common good.

Authors

Valentina Kuskova University of Notre Dame [biography]

Dr. Valentina (Valya) Kuskova is a Professor and Associate Director at the Lucy Family Institute for Data & Society at the University of Notre Dame. She holds a Ph.D. in Decision Sciences, an MBA, and master’s degrees in Applied Statistics and Business, along with a B.S. in Psychology. Professor Kuskova is dedicated to exploring how artificial intelligence can be leveraged to address complex societal challenges, including systemic inequities in access to healthcare education and careers in underserved communities, the socioeconomic impact of large corporations and the measurement of corporate social responsibility, and the systemic network factors driving poverty in disadvantaged regions. Her innovative work bridges advanced analytics, network analysis, and social sciences, driving impactful solutions across diverse domains such as social systems, corporate strategy, and public policy. Kuskova employs advanced AI techniques, including graph neural networks (GNNs), large language models (LLMs), natural language processing (NLP), neural network modeling, and AI-driven forecasting, to analyze and enhance complex problems, enabling diverse applications across various fields. She was the founding director of a network analytics institute and established and supervised two master’s programs in Advanced Analytics and Network Analysis. Dr. Kuskova has extensive experience collaborating with corporate clients, including Coca-Cola, McDonald’s, Volkswagen, the Association of European Businesses, and many others, serving as principal investigator, co-principal investigator, or advanced analytics methodologist. She is passionate about applying scientific research to create meaningful impact across industry and society.
At the Lucy Family Institute for Data & Society, Professor Kuskova serves as a Co-Principal Investigator (Co-PI) of several educational initiatives. She plays a key role in shaping a holistic educational experience that bridges theoretical rigor with practical, real-world engagement. Professor Kuskova co-supervises interdisciplinary programs such as the Lucy Internship Program, and is the faculty of the new Responsible and Ethical AI Course developed in partnership with the National Education Opportunity Network, as well as a range of targeted workshops. Dr. Kuskova serves as the lead Principal Investigator (PI) of the NSF ExLENT Explorations Track project, Bridging to AI and Data Science Careers through Experiential Learning and Training. This project advances the national interest by designing and implementing a transformative experiential learning program in data science and artificial intelligence for undergraduate students and adult learners. In addition, Professor Kuskova is a Co-Principal Investigator (Co-PI) of the Ascension Foundation–funded #GOALS Evaluation Study project, which aims to evaluate how #GOALS (Go Out and Love Science) events, organized by Ascension Foundation, inspire middle-school students from underserved communities to pursue careers in healthcare. Collectively, these initiatives advance the Institute’s mission to prepare students to address complex societal challenges through data-driven inquiry and innovation.
Dmitry Zaytsev University of Notre Dame
Richard P. Johnson University of Notre Dame [biography]

Rick Johnson serves as an associate professor of the practice and managing director of the Applied Analytics and Emerging Technology Lab (AETL) as part of the Lucy Family Institute for Data & Society at the University of Notre Dame. AETL collaborates with iNDustry Labs to help accelerate economic and innovation impact in the South-Bend Elkhart region, achieving the goals of the LIFT Network. He co-leads a data and AI focused internship program for undergraduate students at the University of Notre Dame. His research interests include data and AI platforms and systems, human computer interaction, and informatics.

Previously within the Hesburgh Libraries at Notre Dame, Johnson has combined his research, industry, and technology experience as the Director of the Strategic Innovation Lab which analyzed, prototyped, and vetted mid-to-long-term strategic opportunities for the Hesburgh Libraries. Rick also spearheaded the implementation of the University of Notre Dame’s institutional repository, CurateND, contributed to several data preservation research grants, and served as a Visiting Program Officer for the Association of Research Libraries for the SHARE project.

Prior to joining the university in 2008, Rick worked as a software developer in the banking industry in Seattle for seven years, and spent two years in software sales and consulting in Chicago and Tokyo. He holds two bachelor’s degrees from the University of Notre Dame in Computer Science and Japanese, and a Masters of Library and Information Science from the University of Wisconsin-Milwaukee.
Prof. Nitesh Chawla
Sugana Chawla http://orcid.org/https://0009-0001-7530-5189 University of Notre Dame [biography]

Sugana Chawla is an Associate Professor of the Practice at the Lucy Family Institute for Data & Society at the University of Notre Dame and serves as the Data Science Education Program Director for iTREDS. Her work focuses on designing and leading innovative educational programs that integrate data science, artificial intelligence, and real-world applications. She is the Principal Investigator of the #GOALS project, where she leads research on using AI-driven platforms to explore student engagement and career pathways in STEM and healthcare. Her research has been presented at leading venues such as AIED and centers on advancing responsible AI in education. Sugana actively contributes to interdisciplinary curriculum development and collaborates with university and external partners to expand access to AI and data science education. She also serves as Education Chair for the RISE AI Conference, supporting broader engagement in AI-focused learning initiatives. She holds a an MA in Education and a BS in Environmental Science and Policy, and her work reflects a strong commitment to student learning, innovation, and impact.

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