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I Miss My Pet Capability: Critique evidence NoS achievement aims: Investigating in science Contextual strands: Living world Level : 2,3,4

Author: Ken Benn.  Connected 2, 2006, pages 2–9

This resource illustrates how a mathematics statistical investigation can be used to provide opportunities for students to strengthen their capability to critique evidence in the context of science.

Curriculum Aims and AOs

The Nature of Science Strand

Aims

Achievement objectives relevant to this resource

Investigating in science

Carry out scientific investigations using a variety of approaches: classifying and identifying, pattern seeking, exploring, investigating models, fair testing, making things or developing systems.

L1 & 2:

Extend their experiences and personal explanations of the natural world through exploration, play, asking questions, and discussing simple models.

 L3 & 4:

Build on prior experiences, working together to share and examine their own and others’ knowledge.

Living World

Aims

Achievement objectives relevant to this resource

Life processes

Understand the processes of life and appreciate the diversity of living things.

L1 & 2:

Recognise that all living things have certain requirements so they can stay alive.

L3 & 4:

Recognise that there are life processes common to all living things and that these occur in different ways.

Learning focus

Students critique their data.

Learning activity

This story is about the data collected by a class about the lifespan of their pets, and the ensuing discussion about what the data could tell them and what it couldn't, and how it can be reorganised to tell a different story.

The story itself gives plenty of pointers for the sorts of questions to ask students. The Notes for Teachers that accompany this Connected booklet clarify some of the key statistical ideas.

Adapting the resource

After reading and discussing the story, complete an additional activity to check students' capability to critique data.

Provide some statements related to the data in the story (see table below). Ask students:

  • Do the data provide sufficient information to support the statement?
  • Why do you think that?
  • What else might you need to know?

The table below provides:

  • some examples of statements that could be given to students
  • the sort of response you might be looking for
  • an example of a justification that supports that response
  • where applicable, the sort of question you would need to ask to find out the answer.

Statement

Response

Possible justification

What else do we need to know?

Cats are most likely to die from being run over on the road. Can’t tell Although one child said her cats kept getting run over, there was no data collected about how the pets died. How did the pets die?
Goldfish live for 12 years. Some do and some don’t The data showed that some lived for a shorter time, others longer. 12 years was the number in the middle of the range.  
More people own cockatiels than rats. Can’t tell There were more cockatiel deaths than rats, but there are also likely to be pets that are still living. How many of each type of pet, both still living and dead, have been owned by class members?
Rabbits live longer than rats. Can’t tell For the class’s pets this statement is true, but this is not enough evidence to apply to rabbits in general. 

We would need to ask many more people about their pets to get a bigger sample.

We would also have to find out about those animals living in the wild.

Of the pets owned by the class, the median life expectancy for rabbits is 5 years. Yes Both the median life expectancy table and graph confirm this is true for this class.  
Cockatiels last the longest because they are the easiest to look after. Can’t tell No data was collected about how easy it is to look after cockatiels.  What does it take to look after all the types of pets?
More students in the class would prefer a pet cat than a pet rabbit. Can’t tell More cats died than rabbits. That could be because more people have cats, but we can’t be sure. No information was collected about what sorts of pets the class would most like to have. What is each student’s preferred pet if they had a choice?
Rats don't make very good pets. Can’t tell Rats had the lowest median life expectancy, which means they might die more quickly. However, they could make very good pets during that time. How does each animal score against criteria of what makes an animal a good pet?
Big dogs don't live as long as small dogs. Can’t tell No data was collected on the size of the dogs that died. What sizes were the dogs that died?

Students could also come up with their own statements that others critique in a similar way.

  1. To explore the idea of effect of sample size, ask:
    • If another class did this exercise for their pets would the data collected be similar? Why or why not?
    • To be able to say the evidence is true in general what would have to happen next? [Have a much bigger sample size.]
    • What size sample do you think would be big enough?
  2. To explore the idea of generalising from data (making an inference from a sample to apply to a population), ask:
    • Is there any pattern that you can see that might answer the question, "What sorts of pets might have a longer life span? [They might need prompting to think about classification, size, what they eat, etc.]
    • Is there enough data to be able to say that birds live longer than mammals? Explain why you think that.

What’s important here?

In order to able to evaluate the trustworthiness of data, students need statistical knowledge to know what sorts of questions to ask.

Knowing something about interpreting data, and the limits of what you can infer from the data you have, supports students to become scientifically literate, i.e., to participate as critical, informed, and responsible citizens in a society in which science plays a significant role. (This is the purpose of science in NZC.)

What are we looking for?

Can students see patterns over a whole data set rather than just being able to read particular points?

Can they recognise the limits of the conclusions that can be drawn from a particular data set?

Can they recognise which questions can be answered by a data set and which can't? Do they understand the key statistical ideas that will help them see the strengths and limits of a particular data set?

Opportunities to learn at different curriculum levels

For suggestions about adapting tasks in ways that allow students to show progress in critiquing evidence see Progressions .

Exploring further

As it stands this activity has little science content. To develop understandings about the Living World, this statistical inquiry could however be embedded in a “science unit” (see, for example, Animal Life Histories: Reproduction, Growth and Change, Building Science Concepts, Booklet 4).

There are three activities in Figure It Out: Statistics, Level 3-4 (2001) that could be extended to strengthen students’ capabilities to critique data:

  • Fish Figures (page 8)
  • Stretching Out (page 9)
  • Bean Climbing (pages 10-11)

In Healthy Tomato plants  (Assessment Resource Banks), students are asked to draw conclusions from data.

Other resources for this capability

Fibres and Fabrics (L2, 3 & 4) Making Better Sense of the Material World

Magnet investigation (PW3662) (L2, 3 & 4) Assessment Resource Banks

Which of these materials make the light go on? (L2, 3 & 4) Science Online

Types of Rubbish (L2, 3 & 4) Figure It Out: Sustainability, Level 2-3, 2010

Zoom, Zoom! (L3 & 4) Figure It Out: Forces, Level 2-3, 2010

Butterfly transects (L3 & 4) Monarch Butterfly New Zealand Trust webpage

Marine Metre Squared (L3, 4 & 5) Mm2.net.nz webpage

Where will the wood float? (L4) Assessment Resource Banks

Disinfecting wastewater interactive (L5) Science Learning Hub

Factors affecting ball bounce (L5) Science Online

Measuring the temperature of the ocean (L5) multiple webpages

NCEA Level 1 Investigations (L5) NCEA on TKI

Key words

Connected, pets


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