Classroom Instructional Strategies

When teachers choose the data that are gathered during coaching, they are more motivated and consequently learn more. This doesn’t mean a coach can’t suggest types of data to gather. In fact, in some cases, teachers won’t know what data could be gathered and, therefore, will want and need suggestions from their coach. Effective coaches master the art of suggesting types of data while still positioning the teacher as the decision maker in the conversation.

You can see the difference between objective and subjective data if you watch the Winter Olympics. During speed skating, where the data are objective, whoever makes it to the finish line in the shortest amount of time goes home with the gold medal. Because the data are objective, assuming everyone has raced fairly, there are very few controversies about who wins. This is how objective data work. There is very little opinion involved; data just are what they are.

But during figure skating, where the data are subjective, the experience is often quite different. Figure skaters, or at least figure skating commentators, often criticize the subjective way in which skaters are scored. Since subjective data, by definition, involve the observer’s opinion, conversations about them can turn away from what happened and toward whether or not an opinion is accurate.

Objective data are not personal—they’re factual. When coaches gather and share reliable, objective data, their opinion shouldn’t guide the conversation. They are just reporting the facts regarding the efficacy of classroom instructional strategies. Objective data keeps the focus where it should be—on students and teaching.

A GPS that only tells us when we have arrived at our destination wouldn’t be of much help. The same is true for data gathered in the classroom. Data won’t help teachers and coaches monitor progress if they are collected only once or twice a year. Instead, data needs to be gathered at least weekly. Teachers and coaches need the feedback provided by frequently gathered data because teachers usually need to adjust how strategies are used until those strategies help students move closer to their goals. Data only helps us see what is working and what needs to change when they are gathered frequently.

Valid data measure what they are intended to measure. For example, a valid measurement of whether someone can ride a bicycle would be the act of either riding or failing to ride one; asking the person to complete a multiple-choice test on bicycle riding would be less valid. So, too, in the classroom: teachers and coaches need to make sure that the data they gather actually measures what students are supposed to be learning.

When several coaches gather the same type of data and get the same results, we say that their results are reliable. As a general rule, researchers strive for a reliability score of higher than 95 percent.

In coaching, reliability can have a slightly different meaning. During coaching, it is most important that the coach and teacher agree on (1) what data to gather, (2) how the data is gathered, and (3) why the data is gathered. There should be no surprises when it comes to data gathering.

One way to increase mutual understanding is for the coach and teacher to create a T-chart that depicts examples and non-examples of whatever data is being gathered, such as the one shown in Figure 5.1.

Coaches have told us that when teachers gather and analyze their own data, they are much more likely to accept the data and change their classroom instructional strategies as needed. The easiest way for teachers to do this is by video-recording their lessons, which also lets observers watch segments of a lesson multiple times to clarify what happened. When the observer is also the teacher, such data can especially lead to powerful learning.