Success Factor 5: Data

February 23, 2022
Written by
Jim Knight

Success Factor 5: Data

June 14, 2024
February 23, 2022
Written by
Jim Knight


My friend John Campbell, one of the leading coaching pioneers in Australia, is responsible for one of my favorite comments about coaching: “If there’s no goal, it is just a nice conversation,” a quotation that John attributes to Tony Grant. If John is correct, and I believe he is, then data, which I describe in Chapter 5, are essential. They help us to paint a clear picture of our destination and reveal whether we are on or off track. I suggest that data be gathered for two main foci for coaching—engagement and achievement:

  1. Engagement: Data can be gathered on at least three kinds of engagement: behavioral, cognitive, and emotional. Behavioral engagement measures whether students are doing what they are supposed to be doing; that is, whether they are on task. Cognitive engagement measures whether students are experiencing the learning their teacher intends for them to experience from an activity. Finally, emotional engagement measures the extent to which students feel they belong in their school, are physically and psychologically safe, engage in positive and meaningful experiences at school, have friends, and have hope.
  2. Achievement: To measure achievement, teachers must first identify what students need to learn during a unit or a lesson and then use different kinds of assessments (e.g., selected response or short-answer tests, checks for understanding, rubrics). Sometimes an informal conversation is enough to identify achievement goals, but teachers usually need more precise methods of gathering data to make the adaptations necessary for students to meet those goals.

Below is an excerpt regarding emotional engagement from The Definitive Guide to Instructional Coaching: Seven Factors for Success, with rules to guide how we use data within coaching: 

Six Data Rules

Teachers and coaches need data to establish goals, monitor progress, make adaptations, and increase efficacy. However, data are only helpful when used well. I have identified six rules that will help you use data more effectively.

Data Should Be Chosen by the Teacher

Teachers will be most motivated, and consequently will learn the most, when they choose the data that are gathered during coaching. 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.

Data Should Be Objective

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 is judged to have 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 a given 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. Objective data keep the focus where it should be—on students and teaching.

Data Should Be Gathered Frequently

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 only collected once or twice a year. Instead, data need 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 help us see what is working and what needs to change when they are gathered frequently.

Data Should Be Valid

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 measure what students are supposed to be learning.

Data Should Be Reliable and Mutually Understood

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 are gathered, and (3) why the data are 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 nonexamples of whatever data are being gathered, such as the one shown in Figure 5.1.

Data Should Be Gathered by Teachers When Possible

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 behavior 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.

The six data rules should inform how coaches and teachers gather data of all types. What those types actually are constitutes much of the rest of this chapter.

Engagement Data

Students who stay in school do so because they feel they belong, they have hope, they feel safe, and they feel engaged by school. In fact, engagement is the main reason students who stay in school do so (Knight, 2019). If we want students to experience happiness, have healthy relationships, be productive, and graduate, we must do what we can to ensure they are engaged. To do this, we need to first know what we mean by engagement. For that reason, I have broken this discussion down into three categories: behavioral, cognitive, and emotional engagement.

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