Data-driven learning to meet educator and student challenges

Sharnell S. Jackson, President, Data-Driven Innovations Consulting, Inc. explains how DreamBox models the data-driven decision making process for educators for more efficient, more effective teaching and learning.

Hello.  My name is Sharnell Jackson.  I’m the President of Data-Driven Innovations Consulting.  The work that I do is around helping schools to develop a process under which to use data to inform the teaching and learning process.  I’ve just recently published a book called Transforming Teaching and Learning Through Data-Driven Decision Making.  I’ve worked across the country with school districts, state departments, and individual schools.  DreamBox learning is one of those rare adaptive learning systems that I’ve seen across the country that really helps to inform that teaching and learning process but it makes it more effective and more efficient.  The Data-Driven Decision Making process is about lining standards and goals.  Then it goes on to collecting actually identifying the curriculum under which you’re using and then identifying where the problem was in student learning.

So, the diagnostic, diagnostics formative assessments that teacher’s administer in classroom every day.  Then it’s about identifying, analyzing the data to identify a student learning problem, and then verifying that cause, getting down the really the root cause the analysis of that problem that exist in student learning.  And then giving teachers identifying instructional interventions, that’s what teachers do in classrooms.  And then monitoring the progress of that student and then starting that whole process all over again.  Well, DreamBox Learning actually makes it more effective and more efficient and it models the Data-Driven Decision Making process for teachers in classrooms.