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A major purpose of the monitoring plan is to put in place a system for the ongoing collection of data aligned with the content standard indicators/objectives you are responsible for teaching. You can't analyze data you don't have. And it is not useful to analyze data that is not aligned with your learning outcomes. Once you have the data, you are ready to analyze it.

A Breeze Presentation created by CTAP4 and RSDSS to help users understand how to use the free CST Analyzer tool with student test data.

A Louisiana district scours a year's worth of discipline reports for patterns. It occurred to Bowman that analyzing the reports could provide insight into the root causes of disciplinary problems--tardiness, dress code violations, fighting, vandalism, and more--as well as the effectiveness of how the schools deal with them, and how fairly discipline is enforced. The reports generally contain structured data, including demographic information such as the student's grade and age, and a written narrative that describes the infraction.

Continuous Improvement: It takes more than test scores. Analyzing state assessment results is only the beginning of effective data-driven decision making. There is no question that the passage of No Child Left Behind in 2001 has impacted schools in at least two ways: First and foremost, NCLB has made the use of data to improve student achievement imperative; and second, NCLB has increased the need for continuous improvement processes within schools. Summative data just the beginning

Flagship product, Remark Office OMR®, is the leading scanning software for collecting and analyzing data from plain-paper OMR (optical mark recognition) forms, using any common image scanner. You have the flexibility to create and print your own OMR (or "bubble") forms, and scan them with your TWAIN compatible image scanner.

CTAP Region IV and Regional System of District and School Support (RSDSS) developed these Microsoft Excel® templates to assist you in analyzing CST and benchmark assessments.

Like never before, today's classroom teachers routinely are being asked to collaboratively analyze student data, develop or implement new mandated curricula, and assess the effectiveness of these innovations. Ironically, few preservice preparatory or in-service professional development programs actively train classroom instructors in the use of team-based inquiry or collaborative data- driven problem solving. Framed within the context of the literature and governmental efforts to achieve school reform, this article describes one such in-service program, in practice at public and charter schools in high-need communities in New York City. The Inquiry Based School Improvement Program (IBSIP) was created and designed to help schools serving high-need communities in New York City engage in the types of team-based inquiry and data-driven problem solving needed to meet the everchanging institutional demands on these schools to improve.

Analyzing your data is a process in which you will want to involve your entire staff. Good data-driven dialogue keads to data-driven decisions. If you engage staff in an ongoing data dialogue, it is much more likely that you will feel ownership for the data-based decisions you collectively make.

Analyzing your data is a process you will want to involve your entire staff. There are a number of variables that will help you determine the best strategy for your school including the size of staff, organization of teams, availability of computers with Internet, and the amount of staff meeting time. The critical piece is that you model the importance of data analysis and that you involve (mandate) all staff in the process. The odds of teachers making the instructional changes needed for improved student achievement are much greater when the data and what it tells them about current achievement.

The momentum behind building high-quality data systems to harvest better information about student, school, and district performance has never been stronger. Although collecting data is essential, knowing how to analyze and apply this information is just as important for meeting the end goal of improving student achievement. The purpose of this study is to identify, quantify, and report on district-level processes that enable effective utilization of data to increase academic achievement at the classroom level.

The Pivot tables and chartsfeature in Excel lets educators begin disaggregating and analyzing data within seconds (literally) of receiving original data files from state departments, testing companies, and/or school districts. These ten tutorials show how to use what is perhaps the most powerful data analysis tool within Excel