A Deeper Look at Bar Success: The Relationship Between Law Student Success, Academic Performance, and Student Characteristics

Autor: Amy N. Farley, Keanen M. McKinley, Courtney Gilday, Joel Chanvisanuruk, Christopher M. Swoboda, Alicia Boards
Rok vydání: 2019
Předmět:
Zdroj: Journal of Empirical Legal Studies. 16:605-629
ISSN: 1740-1461
1740-1453
DOI: 10.1111/jels.12228
Popis: In recent years, law schools have experienced a decline in enrollment and bar passage, and legal education has been challenged to understand this new phenomenon and conduct research that can inform practices and policies regarding law student success. This article presents findings from research conducted at the University of Cincinnati College of Law, a large, midwestern public university, which aimed to investigate which factors and student characteristics contribute to bar passage within the home jurisdiction (Ohio). Results suggest bar passage can be predicted by a wide battery of variables, most notably student performance during the law school course of study. Despite some prior literature that suggests otherwise, however, LSAT and undergraduate GPA were only weakly predictive of first‐time bar passage among admitted students: the best prelaw model based on student admissions and demographic data identified just over one‐third of the students who ultimately failed the bar on the first attempt. Information from the first year of law school—even just performance in one first semester course—explained significantly more variation in bar passage. Furthermore, data from beyond the first year of legal study, including upper‐level course taking in bar‐tested subjects, enriched the predictive power of the model, enabling us to predict 78 percent of students who failed the bar compared to just 58 percent after the first year. These preliminary results provide important insights into bar passage, particularly given the increased public scrutiny around incoming student credentials, bar success, and law school performance and accreditation.
Databáze: OpenAIRE