School-Wide Data Analysis Sample Form - ed gov nl 2025

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Tips and Considerations Use both qualitative and quantitative methods to analyze and describe assessment results. Compare data to provide greater meaning. Analyze data with an equity mindset. Analyze data in the context of stated SLOs and benchmarks. Note and describe observations and trends.
Example: A company analyzes sales data to determine the monthly average sales over the past year. They calculate the mean sales figures and use charts to visualize the sales trends.
Administrators may also use discipline records, attendance records, and dropout and graduation data to better understand student performance. Teachers also use student achievement data to improve curricula and instruction, inform student course placement, and provide differentiated student supports.
Data analysis helps teachers understand their students learning abilities and challenges, and facilitates an ingrained cultural process that uses detailed inputs (information) to ensure optimal outputs (results for students).
Some of the most powerful and versatile tools for data analysis in Higher Education research are R, Python, Stata, and SAS. These tools allow you to run various kinds of analysis, from simple to complex, create graphs and charts, and generate reports and summaries.
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Analysis consists of breaking something down and taking a close look at each of its parts while looking for themes, patterns, and assumptions. Critical thinking skill analysis is the process of methodically breaking something down to gain a better understanding of it.
A whole school approach includes: An overarching supportive, safe and inclusive school culture. School-based programs in and out of the classroom that focus on social emotional learning and respect for differences.

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