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Working with data

Information for educators who want to be able to load or download data onto a spreadsheet and use it for their own analysis.

You may want to go beyond the data reports from the digital assessment tools available, or from your student management system, or analyse data from assessments which produce only raw data.

The topics in the section have advice on manipulating data on a spreadsheet to prepare it for analysis. There are basic instructions on how to clean, sort and move data, and how to make and read simple graphs.

Working with data topics

Creating a datasheet of assessment data

Quantitative data in the form of scores can be entered into a spreadsheet in several ways. Data can be downloaded from a digital assessment tool or student management system.

Cleaning, sorting and merging data

It is important that data with which you are working to analyse results and draw conclusions is consistent, accurate and complete.

Creating your own simple graphs

Graphs (also called charts) play an important role in data analysis. A graphic representation can make the relationship between sets of data much easier to understand.

Disaggregating data

Disaggregating data means looking at achievement results or teacher judgments by specific subgroups of students. Disaggregated data can reveal patterns, trends and other important information.

Working with data concepts

Standards-based assessment

Standards-based assessment relies on teachers making qualitative judgments about student’s learning.

Reliability and validity

The reliability of an assessment tool is the extent to which it consistently and accurately measures learning. The validity of an assessment tool is the extent by which it measures what it was designed to measure.

Types of data

It is important to be aware of the types of data that are available so that the appropriate analytic techniques are used, and inappropriate ones are avoided.

Mean, median, and standard deviation

Mean, median, and standard deviation

The mean and the median are both measures of central tendency. Standard deviation (SD) is a widely used measurement of variability used in statistics.

Percentages, percentiles, and stanines

In order to understand and analyse data from an assessment tool, you need to know the differences between the ways that different tools measure student achievement, and what that might mean for your analysis.

Norms

Norms are statistical representations of a population, for example PAT maths scores for year 6 males, or e-asTTle reading scores for year 9 Māori females.

Effect size

Effect sizes allow us to compare things happening in different classes, schools or subjects regardless of how they are measured.