Data informed practice

This section contains information about how school leaders and teachers can use a whole school approach to data collection and analysis to support high-ability students.

Collecting data

A whole school approach to data collection for high-ability needs to recognise the different purposes of data. Data can be used to identify high-ability students. They can also be used across the teaching and learning cycle. Data can be:

  • Diagnostic
  • Formative
  • Summative

Each of these types of data should be included when planning a whole school approach to high-ability. The following questions can be asked when considering how to collect data to support high-ability students.

  • How can diagnostic assessments be used to know what a high-ability student can do? How can they be used to identify a student's point of need?
  • How can formative assessments be used to track the learning of a high-ability student through a teaching sequence? How can they be used to make in the moment teaching decisions?
  • How can summative assessments be used to identify what a high-ability student has achieved? How can they be used to inform future planning for high-ability?

When planning for data collection, it is important to remember that all data collection tools must allow high-ability students to show the extent of what they can do. This means that the way data are collected matters. Some strategies to use for high-ability students include:

  • use above level tests
  • use tasks that have more than one solution
  • use tasks that require higher order thinking skills
  • take observational notes of student questions and responses
  • use tasks that require high-ability students to work together.

Data can be collected from different sources. It is important to use different forms of data when seeking to understand what a student can do. Some examples of data sources include:

  • teacher observations
  • student conferences
  • rubrics
  • learning journals
  • learning portfolios
  • peer feedback
  • standardised tests
  • school developed tests.

It is important to remember that if data are being used to identify high-ability students, it should be part of a multiple measures approach. This means that data should be sought from other sources such as parents, which should be considered alongside what has been collected by the school.

Analysing data

Once the data have been collected, they need to be analysed. It is important that school leaders and teachers understand what information can be taken from different types of data. This is known as data literacy. A whole school approach to data analysis for high-ability should, if necessary, provide professional learning for school leaders and teachers on data literacy.

A process for how data are to be analysed can also be part of a whole school approach. This process may answer questions such as:

  • At what points in time will data be analysed?
  • For what purpose is the data being analysed?
  • Who will be involved in the data analysis?
  • What will be the results of this data analysis?
  • How will the analysis of the data be recorded and reported?

When analysing data, using more than one type of data on the same topic helps to triangulate the data. This increases the validity of the data analysis and will result in a better understanding of the high-ability student.

For example, a student may perform poorly on a test due to anxiety. However, when formative assessment tasks and teacher observations are considered, it is evident the student does understand the content and requires extension. Another example could be a student who is performing well in one subject area, English, but not in another, Mathematics. If the data sets are considered separately, the Mathematics teacher may not be aware of the student's potential. This teacher may miss the opportunity to draw on the student's high-ability in English, to develop their understanding in Mathematics.

Teachers will also be informally analysing data throughout their lessons. This can be used to make in-the-moment decisions about the direction of a lesson for the high-ability student. For example, a teacher checks in with a high-ability student after a short introduction to the content for the lesson. The teacher finds the high-ability student understands the content and what they need to do with it. The high-ability student can move off to begin working independently, while their peers continue to engage in explicit teaching.

Data in practice

Watch this video to see how data is considered and used at a secondary college in Melbourne. While watching, consider the following questions. Does our whole school approach to data collection and analysis for high-ability:

  • value numerical data more than qualitative data?
  • promote an understanding of the whole student?
  • inform the teaching of high-ability students?
  • include a process for ongoing data collection?
  • include a process for ongoing and collaborative data analysis?