You have viewed snapshots of student performance. You use analytics to understand “why” something occurred. But… what if you could determine “what’s likely to happen next?” with a high degree of certainty? You don’t need a crystal ball to predict student performance! See how Texas K-12 data is being used in Predictive Models, which leverage the current and longitudinal data you are already collecting, to provide proactive insights for making critical instructional decisions.
During the session, specific K-12 examples will be shared. Predictive analysis will project performance for the upcoming STAAR assessments. Another model will predict the likelihood of success for potential students in 8th grade in Algebra 1. You will also see how cognitive computing using Watson Analytics is applied to K-12 longitudinal data. Districts can ask natural English language questions to quickly navigate data, prepare expert dashboards and view correlations your district never knew existed.
