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Data analysis, whether at lower primary, upper primary, or even at a more specialised level of statistics, is essentially the same process:
- It starts with a question, that doesn’t have an obvious and/or immediate answer. Information is then collected relevant to the question.
- This collected information or data is represented in a structured way that makes it easier to read.
- This represented data is then examined and compared (interpreted) in such a way as to be able to make statements about what it reveals and, in turn, to possibly answer the initial question (if the question remains unanswered it may be necessary to re-start the process again, perhaps using different methods).
Thus, every data activity should start with a question, for example:
- What is the most common eye/hair colour in our class?
- Which fruit/colour do we prefer?
- How did we come to school today?
- What pets do we have?
- What age are most people in this room?
- What weather did we have in the past week/month?
- Where did we go on holidays?
- Where do our grandparents live?
- Which picture book should we read next?
- How can we sort out our shoes?
- Who is in school today?
When choosing a question it is worth appreciating that some questions might not lend themselves to rich answers. Take, for example, the first question above; once the data is collected, and represented, there is not that much scope for interpretation of results other than identifying the most common eye/hair colour and comparing the number of children with one colour as being more/less than another colour. However, other questions might lead to richer answers, with more possibilities to collect further information, to make predictions and to create connections with learning in other areas. Take, for example, the question above about travel; the children could be asked to suggest reasons for the results e.g. can they suggest why they think most children walked/came by car on the day in question, whether weather/season/distance from school was a factor and to suggest how the results might be different on another day/time of year. Even in a very simple way, the children are beginning to appreciate that data analysis has a purpose i.e. to collect, represent and interpret information, so as to answer a question.
Sets and Data
Data is very closely related to sorting and classifying sets:
- The initial question may focus on a particular set in the classroom e.g. identifying the most common/frequent occurring item in the set of farm animals, the set of buttons in our button box, the shoes that the children are wearing, the nature items collected on the walk etc
- Information is then collected by sorting and classifying the items in the original set according to the target attribute.
- This collections of items are represented in a structured way that makes it easier to compare e.g. items put in lines of same type, use cubes or drawings to represent the actual items.
- This represented data is interpreted to answer the question and to make other statements about relationships e.g. which group has more, less etc
Thus sorting and classify activities should be viewed as potential springboards into data activities and it is important that the children realise that they can represent and compare the size of the sets within each sort by graphing them.
Even as the children move into first and second classes, it is important that their data activities continue to follow a CPA approach:
Concrete: Continuing to use real objects initially to sort and classify ) e.g. the number of different colour crayons in a box, the different type of PE equipment in the hall , the different fruit we brought for lunch etc), progressing towards using unifix cubes, blocks, cuisinere rods etc to represent the same data. Indeed, the children themselves could be used at this stage; sort the children into groups according to eye colour, hair colour, age etc and get them to organise themselves into lines that represent the same criterion. This is turn can be very useful for the children to realise that how they are lined up is crucial to being able to interpret the data easily and correctly. If you have visible tiles/markings as flooring on the classroom/hall/corridor, these can be used to organise the “data” accurately!
Pictorial: using multiple copies of identical images to make pictograms and/or using identical cut out squares/rectangles of paper on which the children draw an image that represents the data as it relates to them (e.g. how I traveled to school today). These can then be collected and organised into lines, so that it is easier to read the data. As a development, identical cut out squares/rectangles of paper of different colours can be used with the children taking the correct colour as it relates to them (e.g. choosing the colour for their eyes/hair colour etc.) while also progressing towards using a specific colour for a specific criterion (“Take a blue square if you walked to school today”). Thus, the children should begin to appreciate the need to label the graph, axes etc so that the meaning of the represented data can be correctly interpreted.
Abstract: the final stage, where the focus is primarily on numbers and/or digits e.g. identifying how many, how many more prefer this than that etc.
- The Operation Maths Digital Resources have specific resources designed to support this strand, and have suggestions of online games in the Weblinks section. Full details of these can be found in your TRB. Click here for the Quick Start Guide to the Digital Resources
- Download the PDST Data and Chance Handbook for Teachers
- Early Math Collaborative: Check out the data analysis suggestions in their ideas library
- Use the graph quiz on That Quiz to provide extra practice reading and interpreting graphs. Choose the option to show only pictograms, and easier content.