There is a disconnect between traditional learning and current testing methods for professional exams, such as the Bar Exam. Without the necessary data and analytics, educators and administrators continue to employ traditional methods of learning and review to help their students prepare for the Bar.
Big data and predictive analytics can be the bridge to a law school's successful transition from the old to the new. By identifying weaknesses in any given student, class, or area of content, law schools can adjust their curriculum quickly to ensure the highest level of success for the bar.
These adjustments may be made within any given semester or may dictate changes in the curriculum for subsequent academic years. It allows law schools to be flexible in their preparation of their graduating law students for the ever-evolving bar exam.
Bar prep should ideally be the antithesis to the method of teaching employed at any law school. Within traditional law school curriculum, students are taught materials through various passive learning conduits, such as lectures, reading materials, etc., for which they are subsequently tested and assessed a grade.
Bar prep should flip the paradigm and begin with assessments that would start to generate data. But instead of just an assessment score for selecting the correct answer, the goal is to capture a great deal more data by assessing competency.
What does this mean? It means reducing the margin of error associated with guessing, even if it's an educated guess. Adding a variable to track guesses, is vitally important. Moreover, it's important to test the same concept more than once in order to see if students truly understand a concept or if they are just guessing really well that day. Predictive analytics will allow us to constantly adjust to changing factors that will ultimately determine sucess rates.
Generating big data for each individual student or class is important but how it is achieved is equally important. Students have an enormous incentive to do well on their bar exam, particularly when their career is at stake, but often times, it's not enough of an impetus for them to take that extra step to help improve their chances on the bar exam.
Much of the failure in bar prep materials and bar prep courses has to do with lack of motivation. Perhaps it's a generational thing. Perhaps the methods of review are antiquated, particularly for this generation of law students. For that reason, a push for the gamification of education has already begun.
Gamification helps to solve many issues. It increases the motivation of students to review by encouraging competition between students within a group, a class, or nationally. It also acclimates them to the testing environment by utilizing the same format and testing model of the bar exam.
While students are "playing," they are generating necessary data to identify issues with their individual knowledge base to identify for themselves their areas of weakness. As a group or class, the data generated would be invaluable to a law school in understanding any deficiencies that might exist in the curriculum.
In this session, we will cover the use of big data and predictive analytics to help law schools better prepare their students for the bar exam and to adjust their curriculum to accommodate changing standards, identify positive and negative trends in their students or classes in regards to competency within each specific subject or topic.
Finally, we will address the use of gamification to help motivate students to prepare for their bar exam and thereby generating the necessary analytical data to determine their readiness for the bar as well as contribute to the data for their law school.
Attendees should have an understanding of analytics, although much of this will be self-explanatory. A basic understanding of this subject area is required.