Data Driven Decision Making
Data-Driven Decision Making in Education[edit]
Data-Driven Decision Making is an effective strategy by which teachers can improve they way they teach to better help their students learn. It incorporates using student-based data to adjust curriculum and teaching methods to increase student achievement. It gets the teacher look at the students individually and as a whole and know how to teach students according to their needs. This method of adjusting teaching methods, classroom environment, and curriculum was introduced it 2001 when the No Child Left Behind Act was established[1].
There are 5 major steps to Data-Driven Decision Making:
Step 1: Know the Context and Standards[edit]
What is the context and standards of your data? Will you be basing your data off of a test or an assignment? Decide on what you will be measuring and how you will measure it. Determine what you will be basing your data off of and set rues and standards that the data must meet. Example: What must the data have to count as data? How will you measure the data? Time period that the data took place during.
Step 2: Identify Data Sources[edit]
Once you know the standards that your students need to master, you need to look at the different sources to which you have access that can tell you how your students are doing with those standards. Discuss with your administration and fellow teachers what sources of data you can use to measure your students' mastery such as standardized tests. You can also collect your data through assessments (formal or informal) and through student surveys, writing samples, and other assignments that they do in or for class[2]. It could be beneficial to organize these sources of data into categories based on which standard they relate to. It will not be uncommon that a single data source relates to multiple standards.
Step 3: Clean and Organize Data[edit]
Once the correct data sources have been identified and collected, it is important to have a system in place to make sure the data is clean and organized. Keeping data to a system will make it easier to find and analyze before using it in the classroom or anywhere else. When cleaning and organizing data, it is important to stick to a system that can be easily applied to any data. This makes certain that the most important data is prioritized and that it is equal and fair across the board. Whatever the data is being used for, whether it be to measure the success of students in a classroom or in determining funds for different school programs, the organization and cleanliness of the data is imperative before moving onto analysis and using the data.
Step 4: Analyze Data[edit]
The next step in utilizing data is analyzing it. Before data can be used to adjust school programs or classroom structure, the teacher and anyone else who collects the data need to analyze the data and draw conclusions. Oftentimes, flaws in data can lead to discovery of flaws in a program or curriculum, or it can help a teacher to notice a student who is struggling. The teacher must be careful when they analyze the data that they don't jump to conclusions too quickly, thus potentially undermining other potential causes for discrepancies in data. Analyzing data is a careful process that requires deep thinking and evidence to back up the conclusions the teacher comes to.
Step 5: Create Plans to Address Shortcomings and Follow Up on Them[edit]
After you have determined and received the answers you want from your data make a plan. Fix your lessons or assessments to better help your students with their shortcomings, which will be shown in the data. Follow up on these changes with more data driven decision making to see if any further changes need made to your class. Script error: No such module "AfC submission catcheck".
References[edit]
- ↑ "Data-driven decision making can improve student learning - DreamBox Learning". web.archive.org. 2016-04-16. Retrieved 2021-06-07.
- ↑ "Data-Driven Decision Making in Education: 11 Tips for Teachers & Administration". soeonline.american.edu. Retrieved 2021-06-07.
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