Friday, December 21, 2012

Coaching needs to reduce blame

This post is a commentary on the shifts that are needed in schools in order to make the role of a data coach more effective.

The shift that I will comment on is this:
  • Placing blame needs to shift to inquiries in examining potential solutions
I feel that a lot of this feeling of blame and accusation when looking at data comes from the issues of when we look at the data. Most times, we look at autopsy data. Autopsy data is the information that comes out and is available after time to affect any change on the issue has passed. Ex. Parent-Teacher conferences after the grading quarter has ended. If we examine data when there is no chance for change the questions the arise are all about "why did this happen" and "what didn't you do".

Another issue is that while we are bombarded with numbers and data, we don't know where to being. This causes us to suffer from the DRIPs (Data Rich, Information Poor). Teachers can look no further than their own grade books to begin finding a lot of valuable information.

When I was in the classroom, I know that I would fall into the grading trap of either doing a mad rush of grading at the progress report and report card times or, when I was on top of it, just entering the grades in the grade book without examining what the data is telling us. Think of a time when you were entering grades into your grade often do you look at the aggregate? Most times, teachers get so caught up in the individual cell at the intersection of the assignment and the student, that they do not look at the entire row (to see if any patterns are developing for that student) or the entire column (to determine if there are patterns developing for the class on that assignment).

(Looking for some alternatives to traditional grades? You can look at this article on Motivating $tudent$ or De-grading your classroom)

Simple measures of central tendency can illustrate volumes about a particular assignment. If you are asking "measures of central tendency" that is the fancy way of saying average. There are multiple ways to measure this though. We can take a look at the mean, median, and mode.

The arithmetic mean is commonly known as just the mean and what we think of when we discuss average. Simply put, add up all of the numbers and divide the sum by the number of terms. This can give you an idea of how most students performed.

The mode is simply the most repeated term in a set. The mode can help explain a low or high mean and also provide another insight into how students performed.

The median is simply the middle number of a set when the terms are arranged from lowest to highest. If you have a data set that is skewed, this can help provide more insight that simply the mean.

Even if you hated sadistics (or statistics), these are simple things that can be calculated and provide insight into student achievement. Importantly, these measures can get you or your curricular team asking questions about the assignments and level of understanding of the students. More importantly, these calculations can be done quickly, help provide immediate feedback to students and the class, and allow for change before the autopsy of the report card.

By examining the data as it is entered, blame is reduced because it is live information and the information from the data can help raise questions about how to improve the practices within the classroom.

Avoid the blame game by doing these calculations in your own class. Get comfortable with your own information and then begin working with colleagues. When we can move to a space that is safe and supportive, we can then seek out the help of a teacher who has better or improving student achievement to determine how to improve one's own practices.

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