How much are they engaged and on task?
At the beginning of this chapter, we suggested that collecting concrete data about how time is spent in the classroom is likely to yield some interesting and useful insights, as well as surprises. All of which can serve as a produc- tive foundation for creative problem-solving around getting more currency for students to spend toward learning. Marzano (2003) refers to this as conducting time audits: gathering data that will reveal how much time in the day or a class period is devoted to actual instruction, how much time in class is generally taken up by non-instructional activities or management tasks, how much time individual students are focused and engaged, what they are doing or what is going on that distracts them, and so forth.
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PART TWO | MANAGEMENT | TIME
We once studied the time use of students in five classrooms of a K–5 school using a technique adapted from Engel (1977). The class was scanned every five minutes, and a notation was made for each student on a class roster. The no- tation recorded what the student was doing and with what level of attention or involvement. From these data, a color-bar graph was constructed for each student, color coded to study activities showing student time use over a whole morning. Coded cross marks in black were overlaid on the color bar to indicate degrees of inattention or non-involvement. Putting all the bars together on one graph for the class gave the teachers an enormous amount of information on individual students and patterns across the class.
For example, one teacher was losing a great deal of time in classroom management: passing out papers, setting up in the morning, and getting ready for transitions. Another teacher had students with low levels of involvement due to social chatter at table groups—quiet and unobtrusive but nevertheless persistent and interfering with their work. Another teacher found her students were involved with individual tasks and projects, but sometimes received only five minutes of direct teacher instruction in the course of the day. All of these teachers made changes to increase their effectiveness after they saw their class data. The changes involved more attention to momentum, rearranging space, rescheduling their own instructional time, and clarifying their expectations for student behavior. The point is that the obvious was not so obvious to them until they directly faced objective data about their own students and their own classes. When they had the data, they were able to improve their effectiveness. Academic engaged time and student time spent in interactive instruction may sound obvious enough, but teachers who get the numbers on their own classes may well find some new priorities emerging.
Although there are structured formal models to use to conduct this type of audit (Marzano, Kendall, & Gaddy, 1999), teachers could do much of this as action research in their own classrooms independently or with the support of a colleague present in the room. There are many kinds of data one might gather: noting starting and ending times of activities, transitions, and length of time spent on direction giving, for example. Comparing data gathered to what you might have predicted or anticipated the data would look like can lead to fine- tuning time estimates, problem identification, and pinpointing the means for using time more effectively. Or a colleague could collect data for you about how individuals or groups of students are spending their time: How much are they engaged and on task? When they aren’t, what is going on? How much is interac- tive instructional time versus independent work? What kind of success are they having? The resulting data can be used to make adjustments and modifications that might increase student productivity and level of performance.