I once worked with a school that was great at collecting data. When I asked to see the data they had, they brought out reams of paper with tiny numbers on it. They also were able to share social and emotional screening data that had been sitting in a desk drawer for a while. I certainly understand how mounds of seemingly unusable data can be collected. However, I once heard Rob Horner (a leading education researcher) say to never collect data unless you are going to us them.
Image from Flickr Creative Commons
Data are useful! There are great webinars on the topic of early warning systems that I think would be helpful to review. As I work with schools, conduct research, and read through best practices, there appear to be a few reoccurring themes related to data. Interestingly these data are not necessarily the things that appear on standardized tests, and are sometimes referred to as non-cognitive skills. Before you begin to collect information, you need to be clear on the types of data that can help you make decisions for your school.
Be clear on your purpose. First, you need to clear on why you need the data. From a professional learning community (PLC) standpoint, you should know, “what do you want all students to know and be able to do, how are you going to know if they can do it, and what are going to do if they cannot?” The answers to these questions should be clear to you before you collect data. The PLC approach is one way to look at this, but whatever approach you use (e.g., multi-tiered systems of support), prepare before your collect data.
Start with the core. There appear to be a few data types of data that show up on many early warning systems. They seem to reliably predict important students’ outcomes (e.g., graduation). These include attendance and grade point average (see this article), suspensions, and on time grade progression (see this article). Particularly in high school, GPA in English I and Algebra seem to be indicators commonly used.
Think beyond academics. At some point adding behavior outcomes such as office discipline referrals and screening data that addresses internalized and externalize behaviors can help predict future problems before they occur. One of the best resources on systematic screening is this website CiET. Kathleen Lanes provides a free webinar here as an introduction to these ideas.
Get visual. Pictures and effective tables sometimes speak louder than words when it comes to data. This link includes wonderful resources on creating teacher, school, and district dashboards for sharing your data graphically which I have written about before.
Finally, if you want to know more about what works for making decisions with data, I would highly recommend you read this paper.
Remember, prepare for what you need by knowing why you need the data and what you will do with them before you collect them. Get clear on a few core reliable indicators and eventually think outside of what you already have. I wonder what successes or challenges you have had with your own data-decision making. Please leave a comment on my blog about your thoughts, I would really like to learn from you.