# data[].attributes.headline
Data can be very useful when used with other information to create a whole picture of a student.

# data[].attributes.subject
Data can be very useful when used with other information to create a whole picture of a student.

# data[].attributes.body
Data should be made available to all staff when assessing a students welfare.
Make sure that staff do not make judgement based on data alone . they need to asses all areas of the student.

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*I understand the importance of the collation of education data and that a simple assessment is not enough for a complete picture of a student - it's just a snapshot.

# data[].attributes.subject
*I understand the importance of the collation of education data and that a simple assessment is not enough for a complete picture of a student - it's just a snapshot.

# data[].attributes.body
* Start comparisons and look for trends more and not simply use the figures from that point in time.
*if the data is collected and analysed correctly it can be a powerful tool.
*I need to ensure that the data is triangulated.
* I need to ensure that I use the data effectively at the time it is collacted.
* A challenge will be to ensure that staff understand the data in the way it is presented otherwise it will be useless.Monica P.

# data[].attributes.body
* It is important to understand the difference between correlation and causation.
* Being able to effectively collect and collate data is essential to professional learning.
* Data needs to be complete and not used in isolation.

* Make data visible and accessible.
* Use background information together with the collected data.

* To ensure the data has a clear purpose.

# data[].attributes.headline
 2. The importance of data triangulation

# data[].attributes.subject
 2. The importance of data triangulation

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3. Importance of using data to inform practice
1. Variance in data and the use of averages.

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3.
* Educational data provides a starting point for further discussion. Behind the number is a student, and it is important to explore the narrative to understand the number and determine the significance of that number.
* Data can be used for many purposes. We need to be very clear about this and ensure the data we collect is valid.
* Triangulation is key to ensuring the data is valid.
* There are many forms of relevant data - all have value depending on context.
2.
* Visually represent data to assist with identifying trends.
* Lead staff in the use of data to support teaching and learning more effectively.
1.
* Drawing conclusions from correlations.

# data[].attributes.headline
3. Educational data is more than just numbers - there is a range of collection techniques that are useful in creating a more complete picture of a student.

# data[].attributes.subject
3. Educational data is more than just numbers - there is a range of collection techniques that are useful in creating a more complete picture of a student.

# data[].attributes.body
2. data will be very useful to assist in planning engaging lessons and allowing for support students.

1. Remember that there is always more to the data than numbers - be sure to check any background or well being issues if you are only presented with numerical data.

# data[].attributes.body
3 important aspects from Dr. Sarra's interview.
1- It is fundamental to get to know your ATSI students and invest time in that student.
2. If a student knows someone believes in them they are likely to pursue whatever it is you are motivating them to do (in this case education) can be very empowering for aboriginal students.
3. Family is of upmost importance. A support network, again people who believe in the aboriginal students will make the work of difference.

# data[].attributes.body
*Averaged data. Apart from possible manipulation of the final score, what is an 'average student'?

# data[].attributes.body
*Use more variety in data types
*Not get bogged down in the numbers - look for the trend

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*Data should pose is about questions as much as answers
*Data comes in many forms - look beyond the grade
*You need a 'complete' data set as one set could lead to false conclusions

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* Following up surprises where the impact is important to the overall picture.
* Making sure that data being considered are worthy of collection.
* Being aware of the limitations of the data being collected. RW

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* Ensuring that I have a clear purpose and formulate questions to be answered prior to collection of data.
* Using evidence from different types of data sources to add insight to and strengthen data collected. RW

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Ensuring that visual representations are easily read and portray a realistic view of data collected.
Take away: Choose the right visual for the right purpose. RW

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2. There are different types of data to consider.

# data[].attributes.subject
2. There are different types of data to consider.

# data[].attributes.body
Looking at multiple sources of data is handy to improve your understanding of data collected. Including student well-being data, contextual student characteristic data & Perception data to supplement student achievement data will support and validate evidence.
Take away: Build the bigger picture! RW

# data[].attributes.headline
1. There are many ways to collect and represent educational data. 

# data[].attributes.subject
1. There are many ways to collect and represent educational data. 

# data[].attributes.body
As educators, we need to be discerning that we are collecting usable data.
Take away: Garbage in = Garbage out! RW