Creating a personal learning journey
We know that children learn better—and faster—when teachers have a clear picture of what each student knows and what they are ready to learn next.
That’s why our assessments react to each student’s answers. In the testing world, this makes our tests “adaptive,” or personalized to measure the needs of every student.
In the simplest terms, growth is change over time. To study growth, we measure a thing repeatedly on successive occasions and draw conclusions about how it has changed.
Most people are familiar with physical growth and some of the ways in which it is measured. For example, one of the things doctors do with new babies is to weigh them and measure their length. Height and weight measurements are continued as the child matures. The change in these measurements over time tells us about the growth in height and weight of the individual, which in turn gives us clues about the child’s general health and well-being.
Measuring reading ability is more like measuring temperature. Although we can see a person’s height or weight, we cannot directly observe the temperature of an object. We can see evidence of temperature by observing the height of a column of mercury in a thermometer. Similarly, we cannot see a person’s reading ability. However, we can see evidence of a person’s reading ability by asking them to respond to questions about textual matter they have read.
What is “typical” growth?
When we ask, “What is typical?” whether it pertains to performance, height, reading ability, or growth in these attributes, we generally assume that we can make a judgment about what occurs most frequently in the general population of individuals. Usually this is accomplished by gathering information about the general population so that we have a frame of reference (data) against which to make comparisons. This data is gathered at a particular time in the school year and represents an approximation of what the student performed on that day. When using data it is important to look at those numbers over time. We may look at them over one year, but this type of data shows a much clearer picture when looked at over the course of several years.
Adapted from: What is Expected Growth? A white paper from MetaMetrics® , Inc. by Gary L. Williamson, Ph.D.