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Running Head: EFFECTS OF LANGUAGE ON COLOUR CONSTANCY

The Effects of Colour Term Acquisition on Categorical Colour Constancy

Candidate Number: 79015

University of Sussex

Word count: 5794

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EFFECTS OF LANGUAGE ON COLOUR CONSTANCY

Acknowledgements

I would like to thank Dr Anna Franklin and Dr Christoph Witzel for their much valued

support through the project. As my project supervisor Dr Franklin provided support and

opportunity wherever needed and provided the initial inspiration that drove my enthusiasm

for colour. Dr Franklin, Dr Witzel and I collaborated on the design of the experiment and Dr

Franklin and Dr Witzel provided feedback following the pilot. Dr Witzel also assisted with

some of the data collection, suggested some initial analyses and produced the figures not

possible with the usual programs. I would particularly like to thank Dr Witzel for the

weekend he spent learning carpentry to produce the frame used in each of the nurseries to

support the window filters. For the large part of data collection Ms Chen accompanied me, as

second experimenter, freely giving her time, for which I am also truly grateful. Stimuli,

remaining analyses and figures were independently produced.

Enormous thanks to the nurseries, their patient staff, kind parents of the child participants,

and of course to all the truly wonderful children who agreed to participate.

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Abstract

Colour constancy occurs when a colour appears the same despite changes in illumination

which cause the light reaching the eye to be different. Few have studied the development of

colour constancy, in particular the impact that language has on categorical colour perception.

This study tested fourteen 36-51 month olds using a sorting task to sort 163 coloured stimuli

under four illuminant conditions. The consistency with which these were categorised was

analysed, showing that categorisation of colours was related to adult-like category maturity

and not to age. When illumination changes were considered, consistency again reflected

adult consistency, showing robust categorical colour constancy exists in children of this age

group. Results also showed that some colour categories were more stable than others, and

prototypical colours were named more consistently than those at the boundary of a colour

category. The findings from this study suggest that language may indeed influence

categorical colour constancy. It also suggests adult categories emerge from conceptual

linguistic categories which may in turn have their origins in the most perceptually stable

colours.

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The Effects of Colour Term Acquisition on Categorical Colour Constancy

Introduction

Colour constancy describes the way perception of surface colour remains the same,

despite alterations in illumination which alter the light reaching the eye. Without this, an

object that is blue outdoors in sunlight appears brown under typical indoor lighting, making

object identification rather difficult. On a day to day basis, we move from indoor

environments to outdoor environments, effortlessly maintaining a constant perception of the

colours we see, despite dramatic changes in the colour of illumination (Romero, Hernandez-

Andre, Nieves, & Garcia, 2002) which in reality alter the spectrum of light reflected from the

surface, which finally reach the eye. The ability to bridge this gap between the message our

eye receives and our visual perception of colour is colour constancy.

Remarkably high levels of colour constancy can be found in adults. Most studies

suggest the visual system needs to discount the effects of any illuminants to calculate the

reflectance properties and therefore the colour of the surface in question (Foster, 2003;

Palmer, 1999). Various models have been proposed to account for colour constancy,

employing algorithms to estimate surface reflectance (Land, 1983, 1986), spatial averaging to

estimate the illuminant (Hurlbert, 1986), or the use of relative frequencies of colours

appearing together as a predictor (Long & Purves, 2003). However, no single theory seems

able to account fully for colour constancy (Foster, 2011; Kraft & Brainard, 1999).

Understanding the mechanisms which support colour constancy is addressed as a

perceptual question on the whole. In reality, colour for humans does not exist in the physical

uniform wavelength spectrum, but as fairly well-defined categories; each given a colour

name. The origin of colour names has been the source of much research, with evidence that

colour categories are universal to all humans (Berlin & Kay, 1969). There is also evidence of

categorical perception of colour in infants as young as 4 months old, broadly reflecting

categories of adults (Franklin & Davies, 2004). This suggests languages are shaped in

response to our perceptual representations. The Universal approach sees colour categories as

being arranged around focal colours (Berlin & Kay, 1969). Philipona and O’Regan (1996)

have suggested that prototypical examples of categories are so because they are the most

stable, and that this fact has led to their similar categorisation across languages. Conversely,

evidence that language shapes the way we see colour from cross cultural studies led to a far

more conceptual explanation (Roberson, Davies & Davidoff, 2000). This view sees shared

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representations as resulting in colour categories, with colours built from boundaries

negotiated through language. Considerable research has made the arguments less

dichotomous, with an answer that lies somewhere between the two.

Categorical colour constancy was assessed using a sorting paradigm with adults

across various differently illuminated conditions (Olkkonen, Hansen & Gegenfurtner, 2009;

Olkkonen, Witzel, Hansen & Gegenfurtner, 2010). They concluded by linking colour

constancy with the ability to consistently name colours. They based their conclusions on

findings that only minor boundary changes occurred with illumination changes, and that

colour categories changed little between observers, or illuminations. This correlation

between naming consistency between individuals and illuminations in particular suggests

colour constancy and categories for colour naming are linked.

When exploring the interaction of language and colour, research has turned to

developmental studies to address this type of question (e.g. Franklin, Clifford, Williamson &

Davies, 2005; Franklin, Wright & Davies, 2009). Few studies to date (Dannemiller, 1989;

Dannemiller & Hanko, 1987) have examined the development of colour constancy in infants.

These suggest colour constancy is present in early life, with evidence of colour constancy in

infants at around 4-5 months of age. The development of categorical colour constancy poses

a number of important questions which, if answered, could add considerable understanding to

current theory. If categorical colour constancy patterns are unchanged through the lifespan,

this suggests perceptual origins, supporting universal theories. If however, these patterns

change through the acquisition of language, this would suggest categories are conceptual, and

formed by shared representations in language. This raises the question of what impact

learning the names of colours has on colour constancy.

Early studies suggested children cannot name colours consistently and reliably until

about 4-7 years old (Bornstein, 1985). In fact, more recent work shows children can

consistently comprehend and name the first nine main colours at around the age of three

(yellow, blue, green, purple, red, orange, black, pink and white), with brown and grey

following over the course of the next nine months (Pitchford & Mullen, 2002 & 2005). The

acquisition of colour terms is thought to be more difficult than acquiring other words such as

object words (Pitchford, 2006) due to its abstract nature (Kowalski and Zimiles, 2006) or an

attentional bias (Soja, 1994) toward shape. Interestingly though, this late mastery of colour

names stands in stark contrast to the early evidence of colour constancy in infants. This

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timing difference between early perceptual colour representations, with those emerging later

from language, provides an opportunity to explore how they interact.

Bonnardel and Pitchford (2006) compared children aged 26-57 months with adults in

a colour sorting study. Stimuli were 100 Munsell1 chip samples which participants were

asked to sort into eight colour categories (red, pink, orange, brown, yellow, green, blue, and

purple). Children placed the chips into boxes decorated with a picture of a teddy bear and a

Munsell chip as an example of each colour category. Children were grouped according to

colour naming ability.

This study enabled comparison of the colour categories and boundaries from adults

and children with ‘beginning’, ‘developing’ or ‘accurate’ colour naming abilities. Bonnardel

and Pitchford concluded that there was little evidence for language influencing categorization

of colours, except with brown, which appeared to require some conceptual understanding

before consistent boundaries were found.

The current study aims to determine if adult categories are the result of concepts

learned as children, or have their basis in perception. The relationship between categorical

colour constancy and acquisition of colour terms will be examined. Perceptual origins will

be supported by little change during language acquisition; conceptual origins will be

supported by the emergence of adult like patterns. Children with partial colour naming

abilities will be asked to sort colours under different illuminations. Five key questions will

be used to guide the research.

How Consistently Can Children Categorise Colour?

Children’s categories would be expected to be less consistent than adults and with

more variability between illuminant changes, as categories are forming. As children are still

learning some of the key terms some colours may be incorrectly named and categorised.

Does Children’s Consistency Change During Language Acquisition?1 Munsell Color system is a colour order system which divides colour into three dimensions; hue, value (lightness), and chroma (colour purity). Hues are divided into 5 categories; red, yellow, green, blue and purple, then with combination colours between each (for example the category between blue and purple is PB) with ten increments between each of these resulting in a possible 100 hues. Munsell produce colour swatch books with individual removable colour swatches/chips across the full range. These individual Munsell chips have maximum dimensions of 2cm x 4 cm. Further information can also be found here http://munsell.com/

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http://munsell.com/


Theoretically, if categorical colour constancy is conceptually driven and shaped by

linguistic colour categories, then this similarity to adult categories would be expected to

emerge over time as acquisition of colour terms becomes more stable. If categorical colour

constancy has a perceptual basis then it would be logical to expect learning colour words to

have little impact on these categories. The distribution of consistencies and the mapping of

the categories should be similar, even though categorization is likely to be ‘noisier’ than with

adults, resulting in lower consistency.

How Consistent Are Children When Illuminations Change?

The available research suggests children do have colour constancy, but no literature to

date suggests how well developed this is. It may not be as robust as that in adults which will

be demonstrated by the level of consistency between illumination conditions. High

consistency despite changing illuminations will suggest good colour constancy. If

consistency between illuminations and between individuals is high this would suggest that

colour constancy mechanisms are related to category formation.

Are Some Categories More Stable Than Others?

Individual colour categories may be more or less consistent than others; perhaps some

will be more stable under changing light conditions for children. Certainly there is evidence

this is the case in adults (Olkkonen et al., 2009; Olkkonen et al., 2010) after controlling for

category size. Larger categories would be expected to be more consistent as they have a

smaller proportion of hues as borders than as central (or focal) hues.

Are Boundaries Less Consistent Than Prototypes?

The Universalist view would predict that categories are built around some key focal

points (Berlin & Kay, 1969; Collier et al., 1976) most likely due to higher saturation. The

opposing view would suggest that boundaries are the critical decider, linguistically

determined, with prototype locations being influenced by where boundaries are set. Either

way, if prototypical chips represent the best example of each category, then it seems likely

that they will be located fairly centrally within categories. Categorisation consistency may

differ between children and between illuminants.

Method

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Participants

Fourteen children (seven boys) aged 36-51 (M = 41) months, with English as their

first language and with no known visual deficiencies were tested. Seven completed all four

conditions, two completed three and five completed two or less.

Materials

For the initial colour naming and comprehension task rabbit flashcards were produced

(Pitchford & Mullen, 2002) on grey backgrounds and laminated. For colour naming,

individual rabbits wearing coloured clothes (focal colours from each of the eight selected

colours; red, green, blue, purple, yellow, orange, pink and brown) were used (Appendix A)

and for colour comprehension a central rabbit was pictured with eight coloured jumpers in a

circle around it (Appendix B) were used.

One hundred and sixty three glossy chromatic Munsell sample chips were used as

stimuli. These were always the highest chroma available, across 40 hues covering all hue

groups every 2.5 steps with lightness values of 3, 5, 6 and 8. These are shown in Figure 1.

Card shapes (jumper, shorts, or hats) with dimensions of approximately 4cm² were painted

grey (N5 Munsell colour) and the glossy Munsell (1966) colour chips attached. The reverses

of stimuli were coded for identification. A wooden board was painted in the same grey paint

and used to display all stimuli, including eight toy animals.

Figure 1. shows the Munsell chip collection. A further 3 were added to provide some prototypical reds at value 4.

For the filtered light conditions, red and green Lee filters (http://www.leefilters.com)

were used to cover windows, either using a frame, or stapled directly over the window frame

and natural light was used for the daylight conditions.

Ishihara and Tritan plates were used to test for colour deficiency.

Illumination levels were measured using a specular reflectance standard using a

Minolta colour meter. These were averaged to provide CIE xyY values shown in table 1.

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http://www.leefilters.com/

Figure 2. Example of experimental set up


Table 1. Lee filter specifications with the corresponding average CIE xyY values. Means and standard deviations are taken from across all testing sessions for each illumination

Illuminant Filter x mean (SD) y mean (SD)Y (cd/m²) mean

(SD)

Daylight - 0.307 (0.021) 0.327 (0.02) 125 (89)

Red 35 Light pink 0.345 (0.009) 0.301 (0.005) 78 (39)

Green 138 Pale green 0.257 (0.123) 0.353 (0.016) 65 (28)

All data were recorded using templates (Appendices C,D,E & F)

Design

A pilot was conducted with two children, which highlighted the need for three

additional colour chips for ‘red’. Subsequently 163 were used.

Naming and comprehension. The comprehension task was completed by showing

children the rabbit flashcards surrounded by different colour clothes, asking them to ‘point to

the colour red’ (yellow, green, etc.) and recording their responses. The naming task was

completed by showing children flashcard single rabbits and asking them to name the colour

of each of the eight rabbits. Their responses were again recorded.

Main task. A repeated measures design was used across a maximum of 4 different

illuminant conditions; daylight, red, green and a second daylight. The dependent variable

was the consistency with which each chip is re-categorised across varying illuminations and

participants. Illumination conditions were separated in most cases by one week and no child

completed more than one condition in a day. The first condition was always daylight, but

subsequent conditions were

counterbalanced across participants.

Each room was cleared to remove

as many distractions as possible. The

board was positioned to take advantage of

the best natural light; ensuring stimuli

would be well lit for the child. Animals

were placed in plastic boxes along the back of the board (Figure 2.). The arrangement of the

animals and ‘favourite colour’ allocated for each condition and participants were

counterbalanced. Colour name labels were positioned at the rear for the use of experimenters

during testing. Stimuli were laid out with the hue circle running from one side to the other,

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darkest chips closest to the child. The hue circle was either centred with pink or green, and

this was alternated across conditions for each child.

Children were asked to sort the colour chips into categories and then identify a

prototype from each category. Once children had completed the task and left, stimuli from

each category were turned over and photographed as a category, so that recording and coding

of data could take place later.

Colour deficiency tests were administered before the first condition by asking children

to trace the coloured line on Ishihara plates and to point to the different corner on Tritan

plates. Participant information and data was collected using forms (Appendices 3-6).

Procedure

Materials were arranged as described above and light measurements taken and

recorded. Children for whom consent had been obtained were approached and asked if they

would like to come and play. Assenting children were first presented with the

comprehension task, followed by the naming task and colour deficiency tests.

Main colour task. Children were asked if they would like to play a game with the

animals. The experimenter explained that each animal would like to collect a particular

colour and children were asked to sort the stimuli into colour categories. On completion, the

experimenter asked the child to select the best example from each category for the animal.

Children were thanked and given a picture to colour in. Light levels were retested and

recorded once the child had left. All testing sessions were conducted between the hours of

9.30 and 3.30 to ensure that lighting conditions were as consistent and light as possible.

The procedure for the main task was repeated for the four illuminations where

children agreed. On the final session, the naming and comprehension test was repeated.

Ethical considerations. Each nursery was visited to provide details of the study

(Appendix G), and show the stimuli, flashcards and toys. Parents were provided with an

information (Appendix H) and consent letter (Appendix I) regarding the experiment and

requesting consent for their children’s participation. Children whose parents’ had consented

to their participation were approached in the nursery setting and asked if they would like to

participate in some games. Children’s assent was sought separately for each of the

conditions. Children were thanked after each session and informed that they would be asked

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again next week. All participant data was anonymised. Ethical approval was obtained from

the University of Sussex Ethics board and British Psychological Society guidelines were

complied with at all times. A satisfactory CRB check was obtained for experimenters.

Results

Of the eight colours tested there was no significant difference between children’s

initial (M = 8, SD = 0) and final comprehension scores (M = 8, SD = 0) or initial (M = 7.9, SD

= .32) and final naming scores (M = 7.8, SD = .42), t(9) = .56, p = .59, ns. Many children

performed at ceiling for this task.

Main Task

Guide to analysis. Frequencies with which each colour chip was re-categorised as

the same colour across illuminations or by other children were calculated to provide

‘consistency’ scores. A score of 1 reflects perfect consistency, 0.5 reflects 50% consistency

and 0 reflects no consistency. High consistency between illumination changes is evidence of

colour constancy. This was calculated for the two daylight conditions first to determine the

degree of variability due to retesting, then for all other pairs of illuminant conditions and

between individuals. Consistency of categorisation between participants is referred to as

consensus. Where adult data is referred to, this was obtained from Olkonnen and colleagues

(2010) and is based on a matched sample of Munsell chips, unless stated otherwise. Where

‘maturity index’ is referred to this was calculated in the same way, but with adult daylight

data compared to child daylight data to provide a consistency score.

A

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B

Figure 3. Average colour categories over all illuminations and all participants. Black lines show boundaries of categories. Hue varies from left to right and value (lightness) increases from bottom to top. Circles represent the prototypical loci, larger disks were selected more frequently than smaller disks. In adult data (A) consistency of less than 90% is reported as % consistency and values above 90% are omitted. Child data (B) is from the current study. Consistency of below 60% is represented by a lighter shade and above 60% in the darker shade. At lightness level 4, only three chips were used.

How consistently can children categorise colour? Individually, children varied

somewhat in their consistency between illuminants, certainly more than adults (see Figure 3);

with mean consistencies across all illuminants ranging from 0.53 to 0.81 (M = 0.69, SD =

0.11). Similar adult data found a higher mean consistency of 0.89 (although this included

four filtered conditions rather than two, and a larger chip selection). Figure 4 shows the

variation across conditions for each participant and also that between illuminations variations

were not confined to any particular illumination colour. Interestingly some of the children

with lower consistencies were also those who completed fewer conditions.

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P1 P2 P3 P4 P5 P6 P7 P8 P9 P10 P11 P120

0.10.20.30.40.50.60.70.80.9

1 Daylight1-2Daylight1-RedDaylight1-GreenDaylight2-RedDaylight2-GreenMaturity index

Participant

Mea

n co

nsis

tenc

y (+

/-1 S

EM

)

Figure 4. Mean consistency scores for each participant for each illumination pair and maturity index. The maturity index is a measure of the consistency between adult and children daylight categorisation for each chip. (Missing participants completed insufficient conditions for comparison.)

Does children’s consistency change during language acquisition? The consistency

between children and adults in the daylight conditions were calculated to provide a maturity

index. This reflects how similar the children’s categories are to that of the adults. Average

age in days at testing was also calculated for each child and is shown in Table 2. There was

no significant relationship between age and the maturity index, r = -.24, p = .16, ns or age and

categorisation consistency in the daylight condition which was used as a baseline condition, r

= -.14, p = .4, ns, but this consistency was positively and significantly related to the maturity

index, r = .68, p < .01, meaning that classification becomes more consistent as children’s

categories begin to resemble those of adults.

Table 2. Mean age in days at testing across total number of conditions completed where available.Participant number Mean age at testing in

days (SD)Gender Number of

Conditions1 1297 (8.66) M 42 1113 (7) M 33 1198 (8.66) F 45 1211 (18.41) M 46 1268 F 17 1110 (16.15) F 48 1125 (17.62) M 39 1392 (7.21) M 310 1226 (9.04) F 411 1468 (9.04) F 412 1180 (5.91) F 413 1553 F 114 1256 (4.95) M 2

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How consistent are children when illuminations change? Children’s categorisation

for daylight, red and green illumination conditions are shown in Figure 5. Consistency across

illuminants was derived by calculating individual consistencies for each illumination then

averaging each illuminant change across children. This was significantly related to

consistency across illuminants for adults, r = .63, p < .01 suggesting similar patterns of

constancy occurred between illuminations for both adult and child samples.

A

B

C

Figure 5. Average colour categories for all children for aggregated neutrals (A), red (B) and green (C) filtered conditions. Black lines show category boundaries. Hue varies from left to right and value (lightness) increases from bottom to top. Circles represent the prototypes; larger disks were selected more frequently than smaller disks. Consistency < 60% is represented by a lighter shade and > 60% the darker shade.

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The effect of the illumination changes was calculated for each of the illuminations by

comparing the consistency between one pair of conditions with that of another pair. If a child

is colour constant, similar consistency would be expected between both daylight conditions

and filtered conditions. A lack of colour constancy would be represented by higher

consistency between the two daylight conditions and lower consistency between daylight and

a filtered condition as it would be expected that some colours would appear to be different

under the altered illumination. Ratios were calculated between the various illuminations for

each participant by dividing the consistency from coloured conditions with those of the

repeated measures of daylight (see Table 3). Some ratios were 1 or greater, so some children

performed better between illumination changes than between the daylight repeated measures.

There were no significant relationships between these and age at testing or category maturity,

so this analysis shows categorical colour constancy does not appear to improve with age or

maturity of categories.

Table 3. Ratios between illumination change pairs. In each column the average consistency between the top two conditions is divided by the average consistency of the bottom two conditions. Ratios over 1 are highlighted.

allilluminations/

daylight &red/

daylight &green/

daylight2 &red/

daylight2 &green/

Participantrepeated daylightmeasures

repeated daylightmeasures

repeated daylight measures



1 0.94 0.96 0.95 0.95 0.923 1.09 1.20 1.05 1.18 0.945 0.95 0.97 0.95 0.86 1.017 0.92 0.92 1.01 0.87 0.888 0.74 0.67 - 0.81 -9 1.17 1.17 - 1.18 -10 0.98 1.00 0.99 0.99 0.9511 0.96 1.01 0.92 1.03 0.8912 0.98 1.04 1.01 0.94 0.95

Are some categories more stable than others? The consistency of each colour

category is shown both across illumination and across participant and illustrated by Figure 6.

Both follow a similar pattern with an almost perfect correlation, r = .98, p < .01. There was a

significant difference between the consistency of the various colour categories, F(7, 67.16) =

3.37, p = .004, (the assumption of homogeneity of variance was violated so the Welch F ratio

is reported). Although the greatest consistency occurred for green, blue also appears to be

highly consistent, as with purple, but post hoc tests revealed no significant differences for

individual comparisons. Consistency appears lower at some category boundaries, but the

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lowest consistency appears to coincide with the points at which different lightness levels

account for the variation in hue, such as with yellow and brown.

R2.5 R7.5YR2.5

YR7.5 Y2.5 Y7.5GY2.5

GY7.5 G2.5 G7.5BG2.5

BG7.5 B2.5 B7.5PB

2.5PB

7.5 P2.5

P7.5

RP2.5

RP7.5

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

Across Illum

Across Partic

Munsell hue

Con

sist

ency

inde

x

Figure 6. Across illumination and across participant classification consistencies for each of the Munsell hues (+/- 1 SEM). Value has been condensed across hues and chroma is the highest available at all times. Category centres for all illuminations have been added for clarity, and are based on aggregated classifications for all children across all illuminations.

Ora

nge

Brow

n

Yel

-lo

w

Gre

en

Blue

Purp

le

Pink

Red

Are boundaries less consistent than prototypes? To compare boundaries, the most

frequently chosen category for each chip in the two neutral conditions for all children was

used (figure 1.). Prototypes were those selected by the children as most representative of

each colour category. Unlike in adult data, some prototypes were also boundary colours (e.g.

Figure 3 B and Figure 5 A, B & C), these were excluded from analysis, leaving 36 boundary

chips and 41 prototype chips. A two way 2 (consistency type: illumination or participant) x 2

(category status: boundary or prototype) mixed ANOVA was completed to address this

question. There was a significant main effect of consistency type, F(1, 75) = 38.12, p < .001,

so consistency was different between participants and between illuminants. There was also a

significant main effect of category status, F(1, 75) = 55.25, p < .001, but a non-significant

interaction between consistency type and category status F(1, 75) = .33, p = .57, ns. Figure 7

shows these results.

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Participant Illuminant0

0.10.20.30.40.50.60.70.80.9

1

BoundaryPrototype

Consistency type and category status of chip

Mea

n co

nsist

ency

scor

e (+

/- 1

SEM

)

Figure 7. Mean consistency scores for participants and illuminants for chips categorised as prototypical colour chips or boundary colour chips.

Discussion

Results showed children display a high level of categorical colour constancy and that

despite increased variability due to incomplete colour knowledge, their categories closely

resemble those of adults. Consistency between children and for individual children over

varying illuminations, were both very similar and reflected previous findings in adults

(Olkkonen et al., 2010). Individual colour categories reflected those of adults too, both

between participants and between illuminations, but prototypes were widely dispersed and

lacking consensus between participants, unlike in adults.

Naming and Comprehension

There was no evidence of a significant change in naming or comprehension of colours

over the experimental period but many children achieved ceiling performance which limited

the findings. Sadly, the ceiling level performance demonstrated by the majority of the

children may have obscured any interesting results. Ideally, this could have been used to

divide participants into two groups for comparison, but the task was too easy. This may also

have been evidence of an improvement in colour naming and comprehension over the

experimental time frame.

How Consistently Can Children Categorise Colour?

On the whole children appeared reasonably consistent with their categories, but over

repeated testing sessions children varied in the consistency with which they categorised the

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chips. It seemed that those who were the least confident with their colours were also those

least likely to complete the conditions. Children appeared to categorise colours in a way that

is remarkably similar to adults, although the additional variability children displayed resulted

in considerably lower consistency than with adults.

Pitchford and Mullen (2002) found that children reliably learn 9 basic colours

(yellow, blue, green, purple, red, orange, black, pink and white) during age 35.6 to 39.5

months, with brown and grey following about 9 months later. The children tested in the

current study were consistent with these claims on the whole. During testing it appeared that

colour labels which children were less certain with, such as brown, grey or black were

frequently used to categorise colours they were unsure of. This is consistent with the idea

that children eliminate possible meanings for words by assuming they are mutually exclusive,

(e.g. Markman & Wachtel, 1988). In this example if a child is unsure exactly what

constitutes ‘brown’, then is presented with an unusual colour, but is already confident about

red and blue, then they will assume this unusual colour must belong to the unknown category;

brown.

In the current study children in fact suggested other categories of colour, such as

peach, silver and gold, sometimes with great precision, and sometimes without. Interestingly,

peach was named and categorised by several children in one nursery and no other, and silver

and gold in two nurseries and no other, all suggesting some ‘locally’ learned input. At the

setting in which peach featured highly, nursery staff identified peach as the colour paint

recently used for self-portraits as skin colour, explaining the origins of this one extra category

to these particular children.

Does Children’s Consistency Change During Language Acquisition?

Chronological age and maturity were not significantly correlated, so adult like

categories did not develop directly with age. As age was calculated as a mean of each child’s

age at each testing session, the total experimental time frame varied for individuals. It could

be that shorter experimental timeframes improved (or hampered) consistency with practice.

It is also possible that the experience of sorting the colours may have improved the children’s

attention to colour.

Age was also not related to children’s categorisation consistency so children did not

improve their consistency in line with their age. The maturity index was however related to

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children’s consistency, so the correlational data suggested that child consistency reflected

adult patterns rather than being a product of age. Categorical colour consistency then seems

to be linked to the conceptual acquisition of categories arising from language. Perhaps

children’s categories during colour term acquisition are not changing in line with age, but

rather beginning to reflect adults’ linguistic categories.

How Consistent Are Children When Illuminations Change?

Consistency between illuminant changes essentially indicate colour constancy, so this

question addresses to some degree how ‘colour constant’ children are. When illuminations

changed, children’s consistency was correlated with adult categories once again; suggesting

categorical colour constancy followed a similar pattern in children to adults. In the absence

of colour constancy, with green illuminations, colour maps of the perceptual appearance of

the chips would likely reflect a larger green area, perhaps less yellow. For the red

illumination, a larger red, more pink, and purple might be expected, but in reality the colour

maps show little obvious change, so both visually and statistically children displayed fairly

robust colour constancy.

When comparing the ‘consistencies of illumination changes’ and ‘consistencies with

no illumination changes’, there was a great deal of variability. The most illustrative of these

comparisons should have been comparing daylight-red or daylight-green (illuminant change)

with the two daylight (no illuminant change) conditions, and most participants performed

very close to ‘1’ which means no difference and therefore good colour constancy. However

the presence of several ratios of above ‘1’ shows that sometimes children actually performed

better between illumination changes. Simply put, between illumination changes some

children appeared to perform better than between the daylight repeated measures, which is

unexpected. There was no significant relationship between these results and age or maturity,

it seems most likely that these can be accounted for by the experimental timeframe providing

practice effects and helping to consolidate children’s concepts of the categories ‘on-line’.

Are Some Categories More Stable Than Others?

Consistency across illuminations and consensus among participants were both

remarkably similar, a pattern that was also found by Olkkonen and colleagues (2010). Given

the higher variability in children’s data, this seems even more surprising. The degree of

consistency across the eight categories varied significantly. It could be that larger categories

19


(like green) are more stable than small ones (like red) as a smaller proportion overall is close

to a boundary. Consistencies might be expected to dip at boundaries, and be highest in

category centres and whilst this is so in some cases it does not seem as though the troughs in

Figure 7 are all consistent with boundaries. Aggregating lightness levels may have hidden

this, in fact some of the lowest consistency was found around the brown, red and yellow hues

where categories are divided by lightness rather than simply hue. Olkkonen and colleagues

(2010) found that consistency decreased with lightness and increased as chroma increased.

The current study did not consider the impact of chroma, but by using only the highest

chroma, consistency levels should be maximised. High saturation levels have been

implicated as significant if categories are universal (Collier, 1976; Regier & Kay, 2007),

providing the external ‘peaks’ in colour space and associated with the basic focal colours.

Are Boundaries Less Consistent Than Prototypes?

If prototypes represent the typical example of a colour, then they would be expected to appear

fairly centrally within a category. In reality this was not the case, prototypes were widely

distributed. It may be that aggregation of data has caused a lack of consensus between the

participants to appear this way. The consistency of boundary chips was significantly lower

than prototypes for children, but many boundary colours were also nominated as prototypes

and were less localised than in adults. The ‘perceptual’ prediction that categories are built

around focal colours is supported with this data, but the lack of consensus between

participants may undermine this finding.

Basic colour terms were used here, which in practice was not always the case with the

children, with names like peach, gold and silver evidenced. If, for example additional

categories (turquoise, peach, lilac…) which have been found in free-choice naming

experiments were available (Boynton & Olson, 1987, Roca-Vila, 2012), then boundaries

would have been differently located. This is after all, a time when children are learning

colour terms and so as additional terms become available, some boundaries may be changing.

General Discussion

In terms of the key questions this study aimed to address, it seems that categorical

colour constancy in children is rather like that of adults in many ways. Previous research had

provided evidence that colour constancy was present from very early on in infants, possibly

developing alongside colour vision generally. The design was ambitious, with children

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sorting 163 chips on four occasions, providing far finer calibration of colour than has

previously been attempted elsewhere in colour sorting tasks (Bonnardel & Pitchford, 2006).

Colour constancy is thought to rely on perceptual mechanisms (Amano & Foster,

2011; Hurlbert, 1999), which provide us with consistency of colours across illumination

changes that are near perfect. Categorical perception on the other hand is shown to be subject

to at least some degree of moulding from the cultures we are immersed in. So if when

categorical colour constancy is considered, the effect of learning the colour names and what

they refer to results in changes, then this could provide evidence that categorical colour

constancy is conceptually driven.

Recent claims have been made that perceptually stable areas of colour space

correspond with the focal areas of red, yellow, green and blue (Philipona & O’Regan, 2006).

The findings here support other work (Olkkonen et al., 2009; Olkkonen et al., 2010) which

has found that consistency between individuals and across repeated measurements with the

same individual are strongly related. This provides additional evidence to support the idea

that this perceptual stability provides some ‘anchoring’ for colour categories. The evidence

here also points to a change taking place over the course of colour term acquisition which

sees adult-like categories emerge, rather as a result of learning than as a product of age.

Ideally, if it had been possible to divide the children based on their colour naming and

comprehension skills, some comparison may have provided evidence of ‘before’ and ‘after’

group differences, in addition to correlational analysis. Ceiling performance ruled this out,

leaving correlational analysis as the main tool in answering this question. If children’s

consistency improves as categories take on adult form and neither of these things are

significantly related to age, then children’s newly acquired concepts of colour categories are

reflected in the improvements in categorisation consistency. This suggests a trajectory

toward conceptual categories. This could be taken to show adult categories emerge from

those learned during language acquisition. This adds significantly to the still widely debated

influence of language on how we see colour.

Whilst in the current study gender was not analysed, this could certainly be explored

in further analyses. Substantial gender differences (Bimler, Kirkland & Jameson, 2004;

Roca-Vila, 2012) in use of colour terms have been found and although varying reasons have

been offered , both physiological and cultural, this could be another indicator of cultural

influence (Moore, Romney & Hsai, 2002). If gender differences emerge during colour term

21


acquisition this would provide additional support for the influence of language and culture on

how we see colour.

This study is the first of its kind, considering categorical colour constancy origins

from a developmental perspective. It provides, not only a very valuable and detailed picture

of the state of toddlers categorical colour constancy which is currently not accounted for

elsewhere in developmental or vision literature, but most significantly provides insight into

the origins of adult categorical colour constancy. This study heralds exciting new evidence

suggesting a story of early category formation reliant on perceptual factors, such as the

enhanced stability of some focal colours, but moulded during language acquisition by what

they learn from others. So despite a perceptual beginning, it seems adult colour categories

and categorical colour constancy are shaped by what we learn at the tender young age of

three and a bit.

22


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Franklin, A., Clifford, A., Williamson, E., & Davies, I. (2005). Color term knowledge does

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Appendix A

Colour comprehension test. Available in Pitchford & Mullen 2002.

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Appendix B

Example flashcard for colour naming. From Pitchford & Mullen 2002.

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Appendix C

Overview template for each participant

ID Nursery Start date

IniID Ishihara Comprehension Naming

N1Pre Post Centred Set-up Photo Order: Main (sat) Unsat

pink green Session: Session:

RPre Post Centred Set-up Photo Order: Main (sat) Unsat


GPre Post Centred Set-up Photo Order: Main (sat) Unsat


N2Pre Post Centred Set-up Photo Order: Main (sat) Unsat


FinID Comprehension

(post)Naming (post) (Ishihara)

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Appendix D

IDNursery: Nursery ID:

ID:

Birthday (age): Gender:

Nationality: Mother Tongue: (mono- / bilingual)

Start date:(first session)

Start time:(first session)

Experimenter:

(Defic. & Lang.)Assistant:(Defic. & Lang.)

Ishihara

a.) Daltonism

Let child choose one of two plates of each type; mark chosen one.

Type Practice Green-Orange Orange-Green Black-Red

Plate Nr. 38 37 36 35 34 26 27

Correct

If indications of daltonism: Test the other one in each pair; if successful, test one of the difficult ones 32 or 33:

Type Green-Orange Orange-Green Black-Red Difficult

Plate Nr. 37 36 35 34 26 27 33 32

Correct

b.) Tritan

Plate Nr. 0 (practice)

Nr. 3 (medium)

Nr. 2 (easy)

Nr. 4 (difficult)

Nr. 5 (very diff)

Correct

If no success with Nr. 3: show correct answer with plate Nr. 1; then proceed with the easy Nr.2, and test with Nr. 4.

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Language (pre)

Random order of colours; 2 for each plate.

a.) ComprehensionCat. Pink red orange yellow Green blue

Answer

Cat. Purple brown grey black white

Answer

b.) NamingCat. Pink red orange yellow Green blue

Answer


Answer

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Appendix E

Template to record each sessions data

ID:

Date:

Condition:

Start-Time: End-Time

Experimenter: Assistant

Measurement of illuminationWhite-Standard: Munsell N9,5 ----- Reflectance standard

Measurements:

Pre/Post Y X y Comments

CategorisationSpatial Arrangement: Green-centred ----- Pink-centred

Teddy-Colour-Order: Template Row

Hue-Full

Animals

Colours

Prototypes

Neutral

Animals

Colours GREY BLACK WHITE

Prototypes

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Appendix F

Template to record final session including language test.

ID: Name:

End date:(All sessions)

Start time:(Last session)

Experimenter

(Lang.)

Assistant(Lang.)

Language (post)

a.) Comprehension

Cat. Pink red orange yellow Green blue

Answer


b.) Naming

Cat. Pink red orange yellow Green blue

Answer


Turn

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Ishihara (if indications for deficiency)

a.) Daltonism

Let child choose one of two plates of each type; mark chosen one.

Type Practice Green-Orange Orange-Green Black-Red

Plate Nr. 38 37 36 35 34 26 27

Correct

If indications of daltonism: Test the other one in each pair; if successful, test one of the difficult ones 32 or 33:

Type Green-Orange Orange-Green Black-Red Difficult

Plate Nr. 37 36 35 34 26 27 33 32

Correct

b.) Tritan

PlateNr. 0 (practice)

Nr. 3 (medium)

Nr. 2 (easy)

Nr. 4 (difficult)

Nr. 5 (very diff)

Correct

If no success with Nr. 3: show correct answer with plate Nr. 1; then proceed with the easy Nr.2, and test with Nr. 4.

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Appendix G

Example nursery recruitment letter which was printed on headed paper.

Sussex Colour GroupSchool of PsychologyUniversity of SussexSussex HouseBrightonBN1 9RH

Date

Dear *****,

I am a researcher of the Sussex Colour Group at the University of Sussex and am doing

research on how toddlers see colours. The research project is investigating whether learning

the names of colours influences how colours are seen.

I am looking for children aged between 36 and 42 months to take part in this research. I will

ask the children to complete two child-oriented, fun tasks, which measure children’s ability to

name and sort colours using animal characters.

These tasks would be completed with children on a one-to-one basis at the nursery over a few

days. The sessions can be at mutually convenient times and each individual session would

take no longer than half an hour. I would of course provide the nursery with a summary of

the research findings. The research project has been approved by the University of Sussex's

ethics committee.

I will ring you in the next couple of days to discuss whether it would be possible to conduct

this research in your nursery.

Yours sincerely,

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Appendix H

Information letter provided to parents and printed on headed paper.

INFORMATION SHEET

Does learning colour names influence how children see colour?

I am a researcher for The Sussex Colour Group at the University of Sussex. We are conducting a research project looking at whether learning the words for colours, influences how children see colours. To investigate this, I will ask children to complete a quick and fun colour game on up to four occasions.

One game will involve naming the colours of clothes on an animal character and will take less than five minutes. The main game (which will be repeated on different days) will involve asking children to sort colours into different groups.

Overall, the sessions will take a total of around half an hour each, and will be conducted at your child’s nursery, during their usual nursery time.

Risks/benefits and use of the study

There are no known risks of taking part - the fun tasks are similar to the kinds of pre-school games that are played in nursery. If you and your child wish to take part in the research, then I will send you a summary of the study once it is complete. In the long term, the research aims to help us understand how children see the world around them.

Right to withdraw

If at any time, and for any reason, you or your child wish for the session to stop this is fine, and you are free to withdraw your child's data from the study up until the study is submitted for publication. All information and data from the session will be stored, managed and destroyed in accordance with the Data Protection Act (1998). All data from the session will be confidential — your child will be given a participation number, but this will be kept separate from this consent form so we will not be able to link your child's name to the number.

Please note: if you have a concern about any aspect of your participation, please raise this with the investigator: ****, email: *****@sussex.ac.uk, or with the research supervisor: Dr Anna Franklin, tel: 01273 678885, email: [email protected]

This research has been approved by the School of Psychology Ethical Review Board.

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Appendix I

Consent form

I the undersigned voluntarily agree on behalf of my child to take part in the study of whether learning colour names influences how children see colour.

I have read and understood the Information Sheet provided. I have been given a full explanation by the investigators of the nature, purpose, location and likely duration of the study and of what my child will be expected to do. I have been given the opportunity to ask questions on all aspects of the study and have understood the advice and information given as a result.

I understand that all personal data relating to volunteers is held and processed in the strictest confidence, and in accordance with the Data Protection Act (1998).

I understand that I am free to withdraw my child from the study during the session, or withdraw my child's data before the study is submitted for publication without needing to justify my decision and without prejudice.

I confirm that I have read and understood the above and freely consent to my child participating in this study. I have been given adequate time to consider my child's participation and agree to the study.

Please email me if you would like to receive a summary of the study once completed. Note that we will not disclose individual data, but only group-level analysis.

Your name …………………………………………………………………………………………..……....(BLOCK CAPITALS)

Child's name ……………………………………………………………………………………………..……(BLOCK CAPITALS)

Nursery representative…………………………………………….....................................

Signed………………………………………………………………………………………

Date ………………………………………………

Name of researcher / person taking consent …………………………………………………(BLOCK CAPITALS)

Signed ………………………………………………………………………………………………

Date ……………………………………………….

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Web viewWhen illumination changes were ... an object that is blue outdoors in sunlight appears brown...

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