The "Every Student Succeeds Act" requires that student's test scores be disaggregated by racial characteristics. Nevertheless, the author's recent study suggests that K-12 school principals may not intentionally think about race when they collect, interpret, analyze, and make decisions about data. By not disaggregating data by race,…

Schools are awash in data, and teachers are being asked to gather data in a myriad of high-tech and low-tech ways. But gathering is not analyzing, and without analysis there is little reason to gather the data in the first place. Teachers need data-collection systems that lend themselves to rapid analysis and action. This article presents several…

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…

Schools and districts rarely have a fair distribution of teacher talent. Poor children and black children are less likely to be taught by the strongest teachers and more likely to be taught by the weakest. Several districts have implemented programs to reduce the teacher quality gap. Hamilton County, Tennessee, launched an initiative that included…

The purpose of this paper is to attempt to operationalize a number of Gall's criteria in order to measure whether there is any empirical relationship between these criteria and the level of teacher questions. (Author)

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)