Data based decision making

Data driven decision making refers to educator’ ongoing process of collecting and analyzing different types of data, including demographic, student achievement test, satisfaction, process data to guide decisions towards improvement of educational process. DDDM becomes more important in education since federal and state test-based accountability policies. No Child Left Behind Act opens broader opportunities and incentives in using data by educational organizations by requiring schools and districts to analyze additional components of data, as well as pressing them to increase student test scores. Information makes schools accountable for year by year improvement various student groups. DDDM helps to recognize the problem and who is affected by the problem; therefore, DDDM can find a solution of the problem

Purposes of using DDDM

The purpose of DDDM is to help educators, schools, districts, and states to use information they have to actionable knowledge to improve student outcomes. DDDM requires high-quality data and possibly technical assistance; otherwise, data can misinform and lead to unreliable inferences. Data-management techniques can improve teaching and learning in schools. Test scores are used by many principals to identify “bubble kids”, students whose results are just below proficiency level in reading and mathematics.^[1]

Using DDDM in educational organizations

The U.S. Department of Education and the Institute of Education Sciences require to use data and DDDM in past decades to run educational organizations. Using gut feelings, anecdotes, and opinions are no longer acceptable to base decisions. Hard evidence and and the use of data are emphasised to inform decisions.

For example, in a rural area educators tried to understand why a particular subset of students were struggling academically. Data analysts collected students performance data, medical records, behavioral data, attendance, and other data less qualitative information. After not finding direct correlation between collected data and student outcomes they decided to include transportation data into the research. As result, educators found that students who had longer way from houses to the school were struggling the most. According to the finding administrators modified transportation arrangements to make the way shorter for students as well as installing Internet access in buses so students could concentrate on doing homework. DDDM in this particular case helped to improve student results.^[1]

Effects of DDDM in schools

Effective schools showing outstanding gains in academic measures report that the wide and wise use of data has a positive effect on student achievement and progress. DDDM is suggested to be a main tool to move educational organizations towards school improvement and school effectiveness. Data can be used to measure growth over time, program evaluation along with identifying root causes of problems connected to education. Involving school teachers in data inquiry causes more collaborative work from staff. Data provides increasing communication and knowledge which has a positive effect on altering educator attitudes towards groups inside schools which are underperforming ^[2]

History of using DDDM

Using DDDM is not completely new to education. Data was used by policymakers and educators in cases of analyzing student test scores; however, the process was not systematic or automated. Scanning classes for the signs of understanding or misconceptions, observations of students, examining student student work products is counted as DDDM. By the time when IES was created as a new research branch of U.S. Department of Education, its leaders decided that education needs to be more reliable and resource rich area.^[1]

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