Open Number sense Siegler and Opfer, 2003

Number line.

You see a number and a line: 0 at one end, 100 or 1000 at the other. You press where the number belongs and let go. After twenty numbers your estimates are plotted: do they look more like a straight line, or like a logarithmic curve that inflates the small numbers?

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EXP. 048

Where does 150 sit on a line from 0 to 1000? How accurately do you place numbers on the ruler in your head?

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Science box

Placing numbers on a line gives a picture of how magnitudes are represented in our minds. Young children give small numbers too much room on a 0–1000 line and squeeze the large ones; their estimates look like a logarithmic curve. With school and experience the estimates straighten out and become linear.

What we measure

We measure how accurately you place numbers on a number line and which shape your estimates follow. In each of five rounds four numbers appear one at a time. In rounds 1 and 4 the ends of the line read 0 and 100; in rounds 2, 3 and 5 they read 0 and 1000; there are no other marks on the line. You press where the number belongs; you can slide your finger or mouse to move the mark, and your answer is recorded when you let go. On a keyboard you can also use the arrow keys and Enter. The numbers are chosen to come from every region: on the 0–1000 line one number from each of twelve ranges (2–9, 10–24, 25–49, 50–99, 100–149, 150–249, 250–349, 350–499, 500–649, 650–799, 800–899, 900–998), and on the 0–100 line one from each of eight ranges; multiples of 50 on the 0–1000 line and of 25 on the 0–100 line are not used, because they fall on obvious points of the line. The error is the distance between where you put the number and where it really belongs, as a share of the line's length. Each number scores 10 / (1 + (error / 5%)^1.6); an error of 2 per cent of the line earns about 8 points, 5 per cent earns 5, and 10 per cent about 2.5. A round's score is the average of its four numbers; the five rounds add up to at most 50 points. At the end, for each line, we calculate the straight line (linear model) and the logarithmic curve (estimate = a + b · ln(number)) that best fit your estimates and compare which fits better using R².

What the research says

In 2003 Robert Siegler and John Opfer asked second, fourth and sixth graders and university students (32 in each group) to place numbers on 0–100 and 0–1000 lines. On the 0–1000 line a logarithmic curve fitted second graders' median estimates very well (95 per cent of the variance explained), a linear model much worse (63 per cent); for sixth graders and adults the linear model explained almost all of the variance. The same second graders were much more linear on the 0–100 line: the numerical context determined which representation was used. Booth and Siegler (2006) found the same development across different estimation tasks in children from kindergarten to fourth grade, and showed that all estimation skills were positively related to math achievement test scores. Opfer and Siegler (2007) found that giving second graders who made logarithmic estimates feedback about a single number could straighten their estimates across the whole 0–1000 range at once, often after a single trial. Dehaene and colleagues (2008) reported that the Mundurucu, an Amazonian indigenous group with very little schooling, placed numbers on a logarithmic scale at every age.

Why it happens

One interpretation is that people's innate number sense is logarithmic: the difference between 1 and 2 feels much bigger than the difference between 101 and 102. School, measuring and counting build an evenly spaced, linear number line on top of this intuition; children move between the two representations depending on the context (Siegler and Opfer, 2003). This interpretation is debated. Barth and Paladino (2011) argued that the number-line task is really a proportion judgment, that curves that look logarithmic can also be explained by models of proportion estimation that use the end points and the midpoint as references, and so there may be no need to assume a 'representational shift'. Anobile, Cicchini and Burr (2012) showed that even schooled adults, when their attention was taken up by another demanding task at the same time, placed clouds of dots on a line in a compressed, logarithmic-like way: linear placement seems to require attention. In this experiment the numbers are written as digits and there is no time pressure; we expect largely linear estimates from adults. What is really interesting is whether there is a systematic rightward shift for small numbers.

Limitations

Four or eight numbers are too few to reliably tell the linear and logarithmic models apart for a single person; if the two R² values are close, don't read too much into the difference. The logarithmic model cannot include 0, so it is fitted only to numbers of 1 and above; and because the numbers are chosen from every region of the line, the two models can produce similar estimates. On a touchscreen the width of your finger can cause errors of a few pixels, which on the 0–1000 line correspond to a few units. This experiment is not a test of mathematical ability; the result shows a personal tendency, and the general picture comes from the crowd's data.

95% (linear 63%)Second graders, 0–1000 line: variance explained by the logarithmic modelSiegler and Opfer, 2003
~100%Adults, 0–1000 line: variance explained by the linear modelSiegler and Opfer, 2003
often a single trialFeedback needed to straighten logarithmic estimatesOpfer and Siegler, 2007
logarithmic at every ageThe Mundurucu, with little schoolingDehaene et al., 2008
logarithmic-like compressionAdults with their attention taken up by another taskAnobile et al., 2012
  1. Siegler, R. S., & Opfer, J. E. (2003). The development of numerical estimation: Evidence for multiple representations of numerical quantity. Psychological Science, 14(3), 237–243. View source ↗
  2. Booth, J. L., & Siegler, R. S. (2006). Developmental and individual differences in pure numerical estimation. Developmental Psychology, 42(1), 189–201. View source ↗
  3. Opfer, J. E., & Siegler, R. S. (2007). Representational change and children's numerical estimation. Cognitive Psychology, 55(3), 169–195. View source ↗
  4. Dehaene, S., Izard, V., Spelke, E., & Pica, P. (2008). Log or linear? Distinct intuitions of the number scale in Western and Amazonian indigene cultures. Science, 320(5880), 1217–1220. View source ↗
  5. Barth, H. C., & Paladino, A. M. (2011). The development of numerical estimation: Evidence against a representational shift. Developmental Science, 14(1), 125–135. View source ↗
  6. Anobile, G., Cicchini, G. M., & Burr, D. C. (2012). Linear mapping of numbers onto space requires attention. Cognition, 122(3), 454–459. View source ↗

Where is 150 on the ruler?

Write 0 at one end of a line and 1000 at the other, and ask a seven-year-old 'where is 150?', and the mark often lands much further right than it should; young children's estimates give small numbers a large part of the line. An adult puts the mark at about the 15 per cent point. The difference opens an interesting window onto how numbers are arranged in our minds.

In this experiment you place twenty numbers on two different lines: eight on the 0–100 line and twelve on the 0–1000 line. At the end we plot your estimates against the numbers' true values and compare them with two models: a straight line, like an evenly spaced ruler, or a logarithmic curve that gives small numbers too much room?

Siegler and Opfer's experiment

In a study published in Psychological Science in 2003, Robert Siegler and John Opfer gave the same task to second, fourth and sixth graders and to university students. On the 0–1000 line, second graders' median estimates fitted a logarithmic curve very well: the curve explained 95 per cent of the variance, while a straight line explained only 63 per cent. Fourth graders were in between; for sixth graders and adults the linear model explained almost all of the variance.

The study's most interesting finding was about context. The same second graders made much more linear estimates on the 0–100 line. According to Siegler and Opfer, children did not have a single representation of number; they chose between several representations depending on the context, and with age they chose the right one more often.

One piece of feedback may be enough

How does this change happen? In 2007 Opfer and Siegler showed second graders who made logarithmic estimates the correct positions of some numbers. Feedback on numbers where the linear and logarithmic representations differ most had the biggest effect. The change was strikingly abrupt and broad: often after a single piece of feedback, all estimates between 0 and 1000 straightened out at once.

In 2006 Booth and Siegler found the same development across four different estimation tasks, including the number line, in children from kindergarten to fourth grade: increasing reliance on linear representations and decreasing reliance on logarithmic ones. All estimation skills were positively related to scores on math achievement tests.

A number line without school

Is logarithmic intuition found only in children? In 2008 Dehaene, Izard, Spelke and Pica worked in Science with the Mundurucu, an Amazonian indigenous group with very little schooling and a limited vocabulary of number words. At every age the Mundurucu placed both sets of dots and numbers on a logarithmic scale. Western adults placed small or written numbers linearly, and clouds of dots that discouraged counting logarithmically.

According to the authors, the intuition of mapping numbers onto space is universal and this initial intuition is logarithmic; the evenly spaced linear number line is a cultural invention that does not develop without formal education. This strong interpretation was debated in the following years.

Representation, or proportion?

In 2011 Barth and Paladino proposed a different explanation: the number-line task is really a proportion judgment. When answering 'how much of 1000 is 150?', people use the end points and the middle of the line as references; models of perceptual proportion judgment can also explain curves that look logarithmic. On this view there may be no need to assume a 'shift from logarithmic to linear'; what changes is the precision of proportion estimation.

In 2012 Anobile, Cicchini and Burr asked adults to place clouds of dots on a line. Under normal conditions the adults placed them linearly; but when they were given another attention-demanding task at the same time, their placements turned into a compressed, logarithmic-like curve. The linear number line seems to be not a spontaneous intuition but a tool that requires attention.

Your score and your chart

Each number's score is calculated from the distance between where you put it and where it belongs, as a share of the line's length: 10 / (1 + (error / 5%)^1.6). An error of 2 per cent of the line earns about 8 points, 5 per cent earns 5 points and 10 per cent about 2.5 points. A round's score is the average of its four numbers; the five rounds add up to at most 50 points.

In the chart on the results screen each dot is a number: horizontally the number itself, vertically where you placed it. The dashed line is the perfect answer. The orange line is the straight line that best fits your dots, and the blue curve the best-fitting logarithmic curve; the closer R² is to 1, the better the model fits. With just a few numbers the two models can easily come close to each other; if the R² values are close, don't make too much of the difference.

FAQ

What is a logarithmic number line?

A line on which equal ratios take up equal lengths: the stretches from 1 to 10, from 10 to 100 and from 100 to 1000 each take a third of the line. On such a line, 100 falls about two-thirds of the way along a 0–1000 line, and 150 at about 73 per cent. Young children's estimates look like this.

How is my score calculated?

For each number, the distance between where you put it and where it belongs is divided by the line's length, and the score is 10 / (1 + (error / 5%)^1.6). A round's score is the average of its four numbers, rounded to two decimals. The total for five rounds is at most 50.

What is R²?

It is a number that shows how much of the variability in your dots a model explains: 1 means a perfect fit, 0 means no fit at all. By comparing the R² values of the linear and logarithmic models we see which shape your estimates resemble more.

If I came out logarithmic, am I bad at maths?

No. This comparison with a few numbers is not an ability test; the two models can give close results and a single hasty estimate can tip the balance. Some researchers also argue that curves that look logarithmic actually come from proportion-estimation strategies (Barth and Paladino, 2011).

How do I place a number?

Press where the number belongs on the line. You can slide your finger or mouse to move the mark; your answer is recorded when you let go. On a keyboard you can move the mark with the arrow keys and confirm with Enter. Be quick: your first impression matters.

What are the daily series and the challenge?

In free play you get new numbers every time. In the daily series everyone sees the same numbers in the same order that day; the day changes according to Istanbul time. In a challenge you play exactly your friend's numbers via their link; in a race room 2–6 people play the same numbers at the same time. Only your first game is kept in the scientific data.

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