Making the Numbers Come Alive: Basic Data Analysis

		Does the thought of analyzing data make you squirm? If so, you are like many educators who often have limited experience doing this type of work. Some educators may remember taking a course in statistics during their preservice or graduate training, but often this experience makes data analysis seem complex and aversive.

		This lesson aims to make the process of analyzing educational data "user-friendly" by organizing it into four steps. You will find that by following these steps, you will be able to respond to most of the guiding questions you have about your school and the performance of your students.

		Before starting the lesson, write down three questions you have about student performance in your school. Consider some issues that you have long wondered about or issues that align to some of your primary school improvement goals. After you record these guiding questions, use them as a reference throughout the course of the lesson. As you learn about various graphing techniques, identify which type(s) of graph(s) most appropriately respond to each of your questions. By doing this, you will have begun the process of data analysis by creating guiding questions and aligning those questions to the appropriate data analysis strategies.

		The documents that have been abstracted for this lesson relate to data quality. Two primary indicators of data quality are the concepts of reliability and validity. There is much to know about different types of reliability and validity, more than could be explained in this lesson. Therefore, these abstracts and the chapters from which they come are recommended reading.

		As you learn the four steps of data analysis and begin to link your own guiding questions to different analysis techniques, consider what your own next steps will be. Will you apply what you have learned to the data at your school? What other concepts do you need to learn to better use data at your school setting? Think forward to the second module of this course, which will go in-depth into a collaborative data analysis process that can be used for all staff. Get ready to learn about data analysis.

Introduction to Data-Driven School Improvement