Schedule at a Glance

An over of the K-12 Data Analytics Research Consortium
8:00 AM - 9:00 AM:
Room: Superior B
Format: Concurrent Session - 60 Minutes
Primary Essential Skill: Data Management
Secondary Essential Skill: Information Technology Management
Audience: School System Administrators
Brief Session Description: Can big data and data-intensive modeling support a school district in successfully increasing achievement and efficiency, as well as reducing academic failure, dropout, or catastrophes in the lives of K12 learners?

One promising aspect of educational technology is the application of data mining tools and methods to solve difficult problems inherent in complex systems such as school districts. Data modeling is being used daily in business and industry. How can these approaches be critically applied to improve the campus educational experience of K-12 school students?
The University of Texas at Arlington has formed a K-12 Data Analytics Research Consortium to better understand how data can be mined to provide insight into students' instructional and emotional needs, but also to predict disruptive behaviors, events, and catastrophes.

Dr. Andrew Berning will present an overview of the consortium and the infrastructure needed to collect and model the data.
Skill Level: Beginner