The use of data is critical in determining areas where school improvement is needed. Data-driven decision making involves the school community in a needs assessment of student achievement in the school. However, data about student achievement is only valuable if interpreted appropriately, enabling educators to make decisions about improving teaching and learning and to provide a quality education for all students. Used effectively, it allows school stakeholders to assess current status and areas for growth, plan for improvement, and make decisions based on facts rather than impressions or intuitions.
This workbook is intended to assist educators to do the following:
- understand the basics about data.
- review the various types and sources of student achievement data.
- review types of standardized tests and the language of standardized test results.
- collect student achievement data.
- understand disaggregated data and use tables, graphs, and charts.
Data is ‘quantitative’ if it is in numerical form and ‘qualitative’ if it is not. Quantitative data is measurable and can take the form of various scores on tests, assignments, or report cards. Qualitative data can be much more than just words or text. Photographs, videos, sound recordings and so on can be considered qualitative data (Trochim, 2002).
Data can be derived from a variety of sources. Classroom data may take the form of unit tests, portfolios, quizzes, projects, and overall course grades. School or district data may include course grades, scores on standardized tests, attendance information, grade-to-grade transition records, graduation rates, etc.
￼Effective educators will use data to answer important questions like:
- How many students are successful in the subject(s) I teach?
- Within those subjects, what are the areas of strength and weakness?
Answers to questions like these will unlock the door to improving student achievement outcomes.