School leaders are often drowning in data but are unsure which forms of data will help them create a portrait of student achievement that will motivate staff to look beyond simple trends and delve deeper into root causes. Teachers often wish for more guidance on the kinds of data analysis and teaching strategies that will help them move the needle…

The key practices that improve struggling schools, writes Chenoweth--a researcher who's studied successful high-poverty schools and their leaders--aren't a mystery. From both decades of research and the craft knowledge of educators who've jumped in and turned around schools, we know these practices generally yield improvement: (1) a…

Despite repeated calls for educators to get more instructional mileage out of the assessment data they have at hand, two deterrents typically stand in the way of most educators' effective use of test data. First, there's a missing "realization", and second, there's a missing "skill". Educators who possess both this realization and this skill will…

Discusses how connecting instruction, professional development, and student learning can make the difference between successful and unsuccessful data use. Uses a case-study approach to show that by acknowledging that implementation occurs over time, schools can safeguard against discarding new instructional practices prematurely. (Contains one…

Calls for simplicity when presenting data on student achievement. Data should help teachers improve teaching and learning, and focus on specific goals such as determining how many students are succeeding in a subject and, within that subject, what are the areas of strength or weakness. (Contains 22 references.) (WFA)

A primer for schools attempting to analyze the data they collect. Describes ways schools can get a better picture of how to improve learning by gathering, intersecting, and organizing four categories of data more efficiently: (1) demographic data; (2) student-learning data; (3) perceptions data; and (4) school-processes data. (WFA)

Discusses how schools can avoid mistakes in building their school-improvement plans. The two most common mistakes are (1) using measures of student learning that are not sensitive to the actual learning occurring, and (2) having no system for interpreting and using the data. (Contains 1 figure and 11 references.) (WFA)

Discusses data warehousing, which provides information more fully responsive to local, state, and federal data needs. Such a system allows educators to generate reports and analyses that supply information, provide accountability, explore relationships among different kinds of data, and inform decision-makers. (Contains one figure and eight…

Discusses which kinds of data educators should respect and which they should reject. Asserts that most state accountability tests fail to produce the kinds of data that will improve teaching and learning. Teachers can get the data they need from their own instructionally useful classroom assessments. (WFA)