Alexander, Charlotte and Iannarone, Nicole G., Coding and Collaboration: Data Analytics in the Law School Classroom (June 2021). Forthcoming, Transactions: Tennessee Journal of Business Law, Available at SSRN: https://ssrn.com/abstract=3965047 or http://dx.doi.org/10.2139/ssrn.3965047

“Technological advances provide opportunities for lawyers to deliver sophisticated – and cost effective – legal advice. A basic understanding of the emerging field of legal analytics, which employs computational and statistical modeling, analysis, and visualization of legal data to accomplish both descriptive and predictive goals, helps lawyers better serve their clients while meeting their ethical responsibility to understand the benefits and risks of technology in law practice. Lawyers and technologists have much to learn from each other and their respective fields. They must also learn to collaborate. In this session at the 2021 Emory Transactional Law & Skills Conference, we provided an overview of a co-taught Legal Analytics course that brought together law and master’s level computational analytics students to teach and learn from each other as they approached a real-world analytics problem. For analytics students, the course provided an introduction to the U.S. legal system and legal reasoning, the types of legal materials that analytics projects might analyze, and the problems and questions present in the law. For law students, the course offered an introduction to basic computer coding, as well as to the theory and applications of text mining, natural language processing, machine learning and other methods for managing and analyzing unstructured data such as that found in legal documents. Working in teams, students learned and deployed analytics skills to extract information from large numbers of legal documents, identify patterns, and attempt to predict future outcomes. Our remarks describe the collaborative, experiential approach taken in delivering the course material and student learning outcomes as student teams worked together to apply data analytics tools to derive insight from FINRA securities arbitration awards. “