When Word Learning Heuristics Meet Cross-situational Word Learning: A Comparison Between Monolingual and

Bilingual Toddlers

by

Priscilla Pui Yee Fung

A thesis submitted in conformity with the requirements for the degree of Master of Arts

Graduate Department of Psychology University of Toronto

© Copyright by Priscilla P.Y. Fung (2019)

ii

When Word Learning Heuristics Meet Cross-situational Word

Learning: A Comparison Between Monolingual and Bilingual

Toddlers

Priscilla P.Y. Fung

Master of Arts

Graduate Department of Psychology

University of Toronto

2019

Abstract

Monolingual children reportedly rely more heavily on the Mutual Exclusivity Principle (MEP)

than bilinguals in word learning. However, past work has only examined toddlers’ use of MEP

after a single labelling. Here, we examine monolingual and bilingual 2-year-olds’ reliance on the

MEP to learn novel colour labels. Importantly, cross-situational statistics linked a particular label

to a particular colour – but not to a particular object. As a secondary question, we asked whether

the fact that past studies have presented children with atypically-coloured objects (e.g., turquoise

dogs) may have influenced how readily children attached novel labels to colour terms rather than

objects. Preliminary results suggest that monolinguals and bilinguals were equally successful in

learning novel colour labels, but learning only occurred when the objects were atypically-

coloured. We conclude that researchers need to carefully consider the richness of children’s

home learning environments to better understand development in diverse language settings.

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Acknowledgments

I would like to thank my advisor, Elizabeth Johnson, for her continuous support and guidance.

Thank you for letting me to explore my ideas. This project will not be possible without your

insights and expertise. I would also like to thank Craig Chambers for his constructive feedback

and helpful comments on the manuscript. A special thanks to Thomas St. Pierre for your help

with data analysis and technical assistance (i.e. with lab equipment).

I would like to extend my gratitude to the Social Sciences and Humanities Research Council of

Canada for their financial contribution to my Master’s thesis. It is challenging to complete this

project within a year. To all the research assistants and our lab manager Lisa Hotson, thank you

for making this happen!

I am grateful to have met such amazing friends in graduate school, Madeleine Yu, Raheleh

Saryazdi, Kay Otsubo, Emma Galarneau, and Prateek Dhamija. Thank you so much for all the

moral support along the way and helping me survive this challenging year. Last, but not least, I

would like to thank my family especially my grandparents. I would not be where I am now

without your love and care!

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Table of Contents

Acknowledgments………………………………………………………………………………..iii

Table of Contents ........................................................................................................................... iv

List of Tables ................................................................................................................................. vi

List of Figures ............................................................................................................................... vii

Literature Review ........................................................................................................................1

1.1 Introduction ..........................................................................................................................1

1.2 Word Learning Heuristics in Monolingual Children ...........................................................1

1.3 Word Learning Heuristics in Bilingual Children .................................................................2

1.4 Cross-Situational Word Learning ........................................................................................3

1.5 Present Study .......................................................................................................................5

Experiment 1 ...............................................................................................................................6

2.1 Introduction ..........................................................................................................................6

2.2 Method .................................................................................................................................7

2.2.1 Participants ...............................................................................................................7

2.2.2 Stimuli and Design ...................................................................................................7

2.2.3 Procedure ...............................................................................................................10

2.2.4 Coding ....................................................................................................................12

2.3 Results and Discussion ......................................................................................................12

Experiment 2 .............................................................................................................................14

3.1 Introduction ........................................................................................................................14

3.2 Method ...............................................................................................................................15

3.2.1 Participants .............................................................................................................15

3.2.2 Stimuli and Design .................................................................................................15

3.2.3 Procedure ...............................................................................................................15

3.2.4 Coding ....................................................................................................................15

v

3.3 Preliminary Results and Discussion...................................................................................17

General Discussion ...................................................................................................................20

References ......................................................................................................................................25

vi

List of Tables

Table 1. Animate and inanimate objects used in Experiment 1 and 2 ……………………............9

Table 2. Percentage of English exposure and other language(s) as reported by caregivers of

bilingual children ……………………..........……………………..........…………..………........16

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List of Figures

Figure 1. Sample stimuli used in the training trials for Animate Block …………………….......11

Figure 2. Sample stimuli used in the training trials for Inanimate Block ………………….........11

Figure 3. Sample stimuli used in test trials for Animate Block ……………………....................12

Figure 4. Sample stimuli used in test trials for Inanimate Block ……………………..................12

Figure 5. Windows of analysis used in calculating difference scores …………………..............13

Figure 6. Mean difference scores in Animate Block and Inanimate Block after 6 and 12 training

trials in monolingual children ……………..........……………………..........…………..……….14

Figure 7. Mean difference scores in Animate Block and Inanimate Block after 6 and 12 training

trials in bilingual children ……………..........……………………..........…………..…………...18

Figure 8. Comparison of performance after 12 training trials in monolingual and bilingual

children ……………..........……………………..........…………..…………...............................19

Figure 9. Correlation between CDI scores and performance in Animate Block after 12 training

trials in both monolingual and bilingual children ……………………..........…………………...20

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Literature Review

1.1 Introduction

During the second year of life, toddlers can learn new words at a remarkable rate. They do this

despite the fact that there are an infinite number of possible referents in the environment for

every label. There are two well-studied word learning heuristics that children use to reduce

referential ambiguity, namely the Mutual Exclusivity Principle (MEP) and Whole-Object

Assumption. However, our understanding of these word learning strategies has been based

almost entirely on work with monolingual children (e.g., Hall, Waxman, & Hurwitz, 1993;

Liittschwager & Markman, 1994; Markman, 1990). Given that half of the world’s population is

multilingual (e.g., U. S. Census Bureau, 2010), basing our theories of early word learning on

work solely with monolinguals is risky because those theories may not generalize to multilingual

children. Indeed, recent work has suggested that bilingual children may rely much less on the

MEP than monolingual children (e.g. Davidson & Tell, 2005; Houston-Price, Caloghiris &

Raviglione, 2010). And since strong reliance on the MEP has played a major part in classic

approaches to explain how children learn second-order attributes such as colour, this begs the

question of how bilinguals learn adjectives like colour names. Moreover, other well-established

word learning strategies, such as the tracking of cross-situational statistics (e.g., Smith & Yu,

2008; Suanda, Mugwanya, & Namy, 2014; Yu & Smith, 2007), have never been explored in

bilingual toddlers. In this thesis, we examine monolingual and bilingual two-year-olds’ use of the

MEP and cross-situational statistics to learn that a novel label refers to a colour (but not to the

object displaying the colour). As a secondary question, we look at the attachment of colour

attributes to animate versus inanimate objects. We aim to not only compare colour label learning

in monolingual versus bilingual children, but also to begin to better understand how in general,

the design of laboratory experiments can impact children’s reliance on different types of word

learning strategies.

1.2 Word Learning Heuristics in Monolingual Children

Although monolingual and bilingual infants experience a different language environment, they

both face the same challenge of having to determine word meanings from the continuous speech

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stream that they are hearing. It has been suggested that children rely on word learning heuristics

to narrow the search space for possible word-referent mappings (Clark, 1988; Markman and

Wachtel, 1988; Markman, 1994; Landau et al., 1998). Children use the Whole-Object

Assumption to predict a novel label refers to an object as a whole but not to its parts, colour, or

other properties (e.g., Markman & Wachtel, 1988; Soja, Carey, & Spelke, 1991). For example,

upon hearing the word “rabbit”, children will assume the word refers to the whole rabbit that

they are seeing, rather than its ears or the colour white. In a monolingual environment, words and

objects largely follow a one-to-one mapping, with most object kinds only have one label.

Therefore, it has been argued that it is adaptive for monolingual children to follow the MEP to

assume one object has only one basic-level label. This helps them to override the Whole-Object

Assumption and consider the possibility that the novel label refers to properties of the object, for

example “white” refers to the colour of the rabbit instead of the whole rabbit.

1.3 Word Learning Heuristics in Bilingual Children

More recent studies have started to extend the study of word learning biases to multilingual

children. These children differ from monolinguals because they routinely encounter situations

that violate the MEP (e.g. dog in English and chien in French). Therefore, compared to

monolinguals, bilingual children might be less likely to use MEP in acquiring word meanings

because they might perceive it as less useful. Indeed, studies have consistently shown that

bilingual children rely less MEP than monolinguals (e.g. Davidson & Tell, 2005; Houston-Price,

Caloghiris & Raviglione, 2010). Particularly, Byers-Heinlein and Werker (2009) found that, at

18 months, monolinguals showed the strongest use, bilinguals showed marginal use, and

trilinguals showed no use at all. Kandhadai, Hall, and Werker (2017) further asked whether

bilinguals were simply confused in these novel word learning situations or in fact they were able

to interpret the novel word systematically as a second object category label for the familiar

object. In their experiment, 18-month-old monolinguals and bilinguals heard a novel label for a

familiar object that had a salient colour (e.g. an aqua-coloured dog). They were then tested

whether they interpreted the novel label as a second category label for the object (e.g. another

label for dog) or as a label for its salient property (e.g. aqua). They found that bilinguals did not

rely on MEP; instead, they systematically interpreted the novel word as a second label for the

familiar object. Monolinguals, on the contrary, rejected the novel word as a second label and

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showed a tendency to interpret it as a property term for the familiar object (i.e. colour label).

They concluded that bilinguals have clear expectations that guide their mappings even though

they do not adhere to MEP. A recent study by Byers-Heinlein (2017) explored the question of

whether monolingual and bilingual children initially follow similar word learning heuristics and

then diverge later in development after they have acquired more knowledge of word-object

relations, or, in fact, whether bilingual language experience changes their expectations about

how words refer to object kinds early in life. She examined the use of MEP in 9- to 10-month-

old monolingual and bilingual infants and found that they did not share the same expectation

even before they had acquired a sizable vocabulary. Taken together, these studies show that

language experience affects how strictly children follow the MEP from early lexical

development. While these findings are interesting, they raise more questions than they answer –

if bilingual children are less reliant on MEP, then how do they overcome the Whole-object

Assumption and learn labels for object properties?

1.4 Cross-Situational Word Learning

Both monolingual and bilingual children can clearly learn labels for object properties such as

colour names. Note that this does not conflict with the claim that bilinguals are less reliant on

MEP than monolinguals because MEP is not the only way for them to learn adjectives. In the

real world, there is much more information available in the environment to help children

determine word meanings than in a typical lab setting. For example, in the studies outlined

above, children’s tendency to use MEP to resolve ambiguity in word-referent mappings was only

tested once after a single object was labelled. However, there are typically many words and

many potential referents present in the same environment, where word-to-object pairing is not

always as apparent as the experimental settings. For example, when a mother asks her child

during dinner, “Do you want more water?” On the table there are food, water, plates, forks, and

napkins. How can the child identify the correct referent for water among all the irrelevant ones?

One way for children to learn this is by keeping track the statistical evidence of which particular

words and objects co-occurred across multiple situations. For example, on the first night, the

child may have used word learning heuristics to identify three potential referents for “water” –

plates, water, napkins. On the second night, when the mother asks the same question again, the

child may identify another three potential referents – water, apple, forks. Because water is the

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only object common in these two instances, the child will then be able to identify it as the correct

referent even when the word-object pairing is ambiguous in each individual instance. Indeed, a

growing body of literature suggests that both infants and adults are able to learn word-to-object

mappings over multiple instances by tracking statistical evidence (e.g., Smith & Yu, 2008;

Suanda, Mugwanya, & Namy, 2014; Yu & Smith, 2007), which is known as cross-situational

word learning. In a classic cross-situational word learning paradigm (e.g., Smith & Yu, 2008),

participants have to learn novel words through a series of individually ambiguous trials. Within

each trial, they will hear two or more novel words and see their potential referents in a random

order so that they will not know which word refers to which object. However, since the novel

words and their referents consistently co-occurred across trials, they would be able to figure out

the word-object pairings by accumulating and evaluating the statistical information over multiple

trials. It has been shown that both 12- and 14-month-olds are sensitive to these cross-situational

co-occurrence patterns and are capable to use this knowledge to acquire new word-to-object

mappings (Smith & Yu, 2008). This finding indicates that, even under referential uncertainty,

children can attach some information about potential referents to the novel words that they heard.

They can then retrieve and update this information across trials to identify the correct word-

object pairings.

Apart from object labels, it has also been found that toddlers can use cross-situational

consistency to learn verbs and adjectives. In Scott and Fisher (2012), the authors showed 2.5-

year-olds two novel action events simultaneously along with two novel verbs (e.g., Look, she is

pimming. And she is nading.). Each action had multiple tokens performed by different actors.

The only source of information about the intended referent of each verb is the consistency

between the verb and its accompanied action. The authors found that children were able to

abstract across actions performed by multiple actors and learn the verb through statistical

consistency.

Compared to nouns and verbs, the acquisition of adjectives emerges later in development

(Fenson et al., 1991). One proposed reason is that adjectives refer to selected properties and

children need to selectively attend to those properties and segregate them from the whole object

(Smith, Gasser, & Sandhofer, 1997; Gasser & Smith, 1998). Akathar and Montague (1999)

examined whether 2-, 3-, and 4-year-olds could use cross-situational statistical consistency to

learn labels for shape and texture. In particular, they showed children novel objects that differed

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systematically in shape and texture. Then they labelled one set of shape with the same novel

adjective in the shape condition but one set of texture in the texture condition (e.g., This is a

modi one). They found that all three groups of children were able to learn the novel adjective by

attending to the consistent element across naming contexts and extend the novel adjectives to

new exemplars.

To date, no study has examined cross-situational word learning in bilingual children. However,

recent studies from monolingual and bilingual adults have provided some initial evidence that

bilinguals might be better than monolinguals at this task (Chen, Gershkoff-Stowe, Wu, Cheung,

& Yu, 2017; Escudero, Mulak, Fu, & Singh, 2016). It has been argued that the advantage for

bilinguals stems from their constant need to extract patterns from complex dual language input

and, as a result, that bilinguals are more capable in tracking multiple regularities and structures

simultaneously. This is evidenced in Antovich and Graf Estes (2017), where the authors

presented 14-month-old monolinguals and bilinguals with two interleaved speech streams in

artificial languages, which mimics code-switching in bilingual speech. They found that

bilinguals, but not monolinguals, were able to learn the structure of the two interleaved

languages and segment words from the speech stream using transitional probabilities alone.

Similarly, Kovács and Mehler (2009) found that 12-month-old bilinguals were able to learn and

generalize the mutually inconsistent regularities of two structures that were presented

simultaneously, whereas their monolingual peers learned only one of them. These results reveal

that the cognitive systems of bilingual infants are adapted to track multiple regularities in their

environment, and thus they are more flexible at learning speech structures.

1.5 Present Study

The present study sought to examine monolingual (Experiment 1) and bilingual children’s

(Experiment 2) use of the MEP in learning labels for object properties over the course of

multiple labelling instances. In Experiment 1, we aim to replicate earlier work demonstrating that

monolingual children can learn object property labels such as colour names with the help of

MEP. As a secondary question, we examine whether the learnability of colour names through the

MEP might be conditioned by factors such as colour typicality effects. We include this question

because past studies examining the use of the MEP to learn colour labels have used colour

pairings not typically seen in nature (e.g., turquoise dogs and purple elephants). These unusual

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pairings may have drawn children’s attention to colour information in a way that facilitated the

learning of a novel label as referring to the colour. As a result, children’s reliance on the MEP

might have been overestimated if the relationship between the colour and the coloured object is

less salient (e.g., turquoise mittens). We therefore compare the ease of learning if the colour is

typical for the object or not. In Experiment 2, we use the same materials and methodology to

examine how bilingual children use cross-situational statistics to overcome the Whole-Object

Assumption and learn colour labels.

In both of these experiments, the word-referent pairing in each individual trial was ambiguous

such that the novel word could either be interpreted as a colour label or as an object label.

However, the pairings were consistent over the trials so that a child could in principle deduce

that the novel word referred to a colour label. We asked whether monolingual and bilingual

children could learn the intended referent of the novel label by tracking consistently co-occurring

pairings across trials, and whether there would be a difference if the relationship between the

colour and coloured object is salient or not. All of the objects were in a colour that does not map

onto any primary colour (i.e., non-focal colour) because children tend to learn primary colours

first. We manipulated the saliency by dividing our stimuli into animate and inanimate objects.

Although both types of objects have the same colours, it would be more salient in animate than

in inanimate objects because these colours are atypical in animate objects (e.g., a turquoise dog)

but possible in inanimate objects (e.g., turquoise mittens). We test 22- to 26-month-olds in the

current study because at this age, most toddlers (1) have acquired productive vocabularies of at

least 50 words, (2) have begun to map words to object properties, and (3) are more likely to

know the noun labels for all the objects used in the experiment.

Experiment 1

2.1 Introduction

In Experiment 1, we examine whether monolingual children can learn a novel word as a colour

label by tracking cross-situational statistics. Specifically, 2-year-olds heard a novel word (e.g.,

wug) and saw a familiar object in a non-focal colour in each trial, such that the novel word could

either be interpreted as a second label for the object or as a colour label. In one block of trials,

children saw pairings that were atypical in nature (e.g., an animate object such as a dog paired

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with an unlikely color such as turquoise). In the other block of trials, children saw pairings that

were less atypical (e.g., an inanimate object such as a mitten paired with a possible color such as

turquoise). Children were presented with four novel words over the trials: two for animate

objects (the Animate Block, always with atypical colors) and two for inanimate objects (the

Inanimate Block, always with possible colors). In each block, the two novel words (e.g., wug;

teek) were paired with different familiar objects but of the same colour (e.g., magenta-coloured

cat, magenta-coloured turtle; coral-coloured bed, coral-coloured shirt). Note that although the

word-referent pairing was ambiguous in each of these individual trials, the consistency of the

pairing across trials would in principle allow the novel word to be reliably paired with one of the

two colours. To test children’s understanding on the trained novel words, we pitted the two

colours against each other as children heard the label (e.g. magenta-coloured elephant, coral-

coloured elephant). If they successfully learned the novel word (e.g. wug) as a colour label, they

should look longer at the object that was matched in colour (e.g. magenta-coloured elephant).

We predicted 2-year-olds would learn colour labels for both animate and inanimate objects, but

more readily for animate objects because the atypical colours in animate objects are more likely

to draw their attention.

2.2 Method

2.2.1 Participants

Thirty-two 22- months to 26-month-olds (MAge = 701 days, range = 663−804 days; 14 females)

monolingual English-learning children from middle- to upper middle-class families in the

Greater Toronto Area were tested. All monolinguals received at least 90% English language

input (M = 97% English) and English vocabulary size was measured by parental report (CDI

percentile score: M = 47.8%). Fifteen additional children were tested but were excluded from the

study prior to coding due to fussiness (12), parental influence (1), or reportedly not being

familiar with the names of all the objects used in the study (2).

2.2.2 Stimuli and Design

The experiment was divided into two blocks. One block consisted of animate objects and one

block consisted of inanimate objects (see Table 1). The order of the two blocks were

8

counterbalanced across children. Children learned two novel words in each block, with a total of

four novel words − wug, teek, pog, and gaf. In the training trials, each of the novel words was

paired with different objects, but of the same colour − namely coral, magenta, turquoise, or

periwinkle. The word-colour pairings were counterbalanced across participants. Each colour was

labelled six times, with a total of 12 training trials in each block. We chose six labelling

instances for each colour because toddlers were able to learn a novel adjective after six pairings

in Scott and Fisher (2012). Trial order was pseudo-randomized, with the same colour appeared

no more than twice in a row. The visual stimulus consisted of an image in the centre presented

on a white background. This was accompanied by a recording in which the colour of the object

was labelled. Each novel word was preceded by an attention-getting speech sound (‘Look!’ or

‘Wow!’). All auditory stimuli were produced in an infant-directed manner by a female native

English speaker. To facilitate learning, all images were animated with a zoom effect that was

synchronized with the audio (Gogate, Bolzani, & Betancourt, 2006; Gogate, Maganti, & Bahrick,

2015).

In each test trial, two images were presented side-by-side on a white background along with an

audio labelling the colour (e.g., “Look, wug! Can you see it?”). The side which the object was on

was counterbalanced across children. Each word was tested twice – once after six training trials,

and once after an additional six training trials. The order of which word was tested first was

counterbalanced. We included test trials after both six and 12 training trials because we were

uncertain how quickly children would learn the labels. In this way, we could maximize the

likelihood of observing any potential differences in how the labels would be learned across

conditions.

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Table 1. Animate and inanimate objects used in Experiment 1 and 2.

Animate Objects Inanimate Objects

Horse Bed

Frog Car

Pig Ball

Duck Mittens

Chicken Table

Giraffe Chair

Lion Hat

Mouse T-shirt

Rabbit Pants

Turtle Shoes

Monkey Balloon

Elephant Box

Bear Socks

Dog Book

Sheep Cup

Cat House

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2.2.3 Procedure

The study was conducted in a sound-attenuated booth, where children watched the video on a TV

screen while sitting on their caregiver’s lap. Their caregivers wore headphones and listened to

masking music to prevent them from biasing their child’s responses. The masking music

consisted of continuous music mixed with multiple overlaid tracks of the speech stimuli used in

the study (Pinto, Fernald, McRoberts, & Cole, 1998). Caregivers were instructed not to point to

the screen unless it was to direct the children’s attention. The experiment started with the first six

training trials in Block 1. Each trial was 5 seconds long. A novel word was played twice, once at

2 s into the trial and once at 4 s into the trial. A familiar object in a non-focal colour was shown

on the screen. The novel words consistently occurred with the colour (see Figures 1 and 2). After

the first six training trials, children were presented with two test trials in which the two colours

used in the experiment were pitted against each other (see Figures 3 and 4). A 2 s flashing white

star on a black screen was inserted before each test trial to attract children’s attention to the

center of the screen. Each trial was 10 seconds long and each of the two labels was tested once.

Children were then presented with the next six training trials and two test trials in Block 1. After

that, they completed Block 2 with the same procedure. A 4-second animated clip was inserted

after each testing block in order to keep children engaged in the video. The entire procedure was

videotaped for offline coding.

At the end of the experiment, caregivers were asked to fill out a vocabulary questionnaire to

assess whether children could both understand and say the labels of all the objects used in the

experiment, either in English or in another language.

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Figure 1. Sample stimuli used in the training trials for Animate Block. In this example, wug

refers to the colour periwinkle, whereas teek refers to the colour magenta.

Figure 2. Sample stimuli used in the training trials for Inanimate Block. In this example, pog

refers to the colour coral, whereas gaf refers to the colour turquoise.

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Figure 3. Sample stimuli used in test trials for Animate Block.

Figure 4. Sample stimuli used in test trials for Inanimate Block.

2.2.4 Coding

Children’s eye movements were hand-coded frame-by-frame from silenced videos using

SuperCoder (Hollich, 2005). Each 33 ms frame was coded as a look to the left image, right

image, or away.

2.3 Results and Discussion

We first established children’s baseline looking preferences in the test trials before any labels

were provided. The baseline target proportion score was computed by dividing the time spent

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looking at the target by the total time spent looking at both object before the label onset (between

0 ms to 1500 ms; see Figure 5). The effect of labelling was then calculated using a difference

score that compares looking to the target object before and after labelling. The proportion of

fixations to the target object after labelling was computed by dividing the number of fixations to

the target by the total time spent looking at both objects in the in a time window that began 500

ms following word onset and ended 3000 ms later.

Figure 5. Difference scores were calculated by subtracting the proportion of fixations to the

target object during the pre-labelling baseline window from the proportion of fixations to target

during the post-labelling window.

We predicted that, if children could learn the novel words as a colour label, the mean difference

score would be significantly higher than zero. Following Kandhadai, Hall, and Werker (2017),

we conducted one-sample t-tests for both animate and inanimate object test trials (see Figure 6).

For animate objects, there was no effect of labeling after six training trials (M = 0.01, SE = 0.05,

t(31) = 0.24, p = .41), but we found a positive difference score after 12 training trials, indicating

a significant increase in the proportion of looking to the colour-matched object (M = 0.11, SE =

0.04 , t(31) = 2.86, p = .004). For inanimate objects, however, the difference scores were not

significantly different from zero after either six (M = -0.11, SE = 0.06 , t(31) = - 1.83, p = .96) or

12 training trials (M = 0.01, SE = 0.05 , t(31) = 0.10, p = .46). Next, we conducted a two-sample

t-test to compare the performance in Animate Block and Inanimate Block. Overall, colour labels

in Animate Block (M = 0.06, SE = 0.03) were easier to learn than in Inanimate Block (M = -0.05,

SE = 0.04, t(117) = 2.18, p = .015).

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These results only provide evidence for the learning of colour labels in the Animate Block; and

even then, evidence for learning was only apparent after 12 training trials. Thus, colour label

learning appeared to be a difficult task for monolinguals in our study.

Figure 6. Mean difference scores in Animate Block and Inanimate Block after 6 and 12 training

trials in monolingual children. Error bars indicate the standard error.

Experiment 2

3.1 Introduction

In Experiment 1, we showed that monolinguals can use learn colour labels in this paradigm, but

only when colour terms were used with animate objects and only after 12 (rather than just six)

training trials. Presumably, the animacy effect was driven by colour typicality. We return to this

issue of animacy and colour typicality in the General Discussion. In Experiment 2, we repeat

Experiment 1 with only one modification: we test bilingual children instead of monolingual

children. We anticipate two likely possible outcomes: (1) Bilingual children will be less

successful than monolinguals tested in Experiment 1 because bilinguals rely less on the MEP to

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learn labels for object properties, or (2) Bilingual children will outperform monolinguals in view

of the evidence that adult bilinguals are better than monolinguals at cross-situational learning. Of

course, it is also possible that these two opposing effects will cancel each other out, leading to no

differences between the performance of monolinguals in Experiment 1 and bilinguals in

Experiment 2.

3.2 Method

3.2.1 Participants

Sixteen 22- months to 26-month-olds (MAge = 722 days, range = 670−765 days; 9 females)

bilingual children from middle- to upper middle-class families in the Greater Toronto Area were

tested. All bilinguals received a range of 30% to 70% exposure to English, and the rest from at

least one other language (M = 56% English; see Table 2). English vocabulary size was measured

by parental report (CDI percentile score: M = 32%). The differences between the vocabulary size

in bilingual and monolingual in Experiment 1 was marginally significant (Monolingual: M =

303, SE = 0.88; Bilingual: M = 190, SE = 1.12, t(28) = 1.82, p = .08), with bilingual had a lower

vocabulary score than monolingual. Five additional children were tested but were excluded from

the study prior to coding because of fussiness (4) or reportedly not being familiar with the names

of all the objects used in the study in (1).

3.2.2 Stimuli and Design

The stimuli were the same as in Experiment 1.

3.2.3 Procedure

The procedure was the same as in Experiment 1.

3.2.4 Coding

We used the same coding procedure as in Experiment 1.

16

Table 2. Percentage of English exposure and other language(s) as reported by caregivers of

bilingual children.

Children English Exposure Exposure to other language(s)

1 50 50% Urdu

2 60 30% Vietnamese, 10% Tagalog

3 40 50% Hindi, 10% Punjabi

4 70 15% Italian, 10% Polish, 5% Portuguese

5 70 30% Romanian

6 70 30% Cantonese

7 60 40% Cantonese

8 60 20% Portuguese, 20% Italian

9 40 60% Cantonese

10 40 40% Albanian, 20% French

11 60 40% Portuguese

12 60 20% Spanish, 20% Italian

13 60 40% Portuguese

14 60 40% Mandarin

15 50 50% Polish

16 35 45% Cantonese, 15% Mandarin, 5% Taiwanese

17

3.3 Preliminary Results and Discussion

The effect of labeling was again measured using difference scores, calculated in the same

manner as in Experiment 1. As in Experiment 1, we conducted one-sample t-tests for both

animate and inanimate object test trials (see Figure 7). For animate objects, learning did not

occur after six training trials (M = -0.06, SE = 0.07 , t(15) = - 0.77, p = .77) but only after 12

training trials, with a difference score significantly higher than zero (M = 0.19, SE = 0.05 , t(15)

= 1.90, p = .03). For inanimate objects, bilingual children did not learn the novel words as a

colour label after either six (M = -0.002, SE = 0.08 , t(15) = -0.04, p = .52) or 12 training trials

(M = 0.08, SE = 0.10 , t(15) = 0.80, p = .22). Next, we conducted a two-sample t-test to compare

the overall performance in Animate Block (M = 0.11, SE = 0.05) and Inanimate Block (M = 0.03,

SE = 0.04; t(58) = 1.20, p = .05). The results show that colour labels in Animate Block were

easier to learn than in Inanimate Block.

Our results revealed that bilingual children were only able to learn colour labels for animate

objects – and the task appeared to be difficult for bilinguals since they only learned the colour

label mappings after 12 training trials. Thus, based on this preliminary analysis, we fail to find

reliable evidence that monolinguals and bilinguals differ in this task, but we do find additional

support for our prediction that colour labels are easier to learn in animate than in inanimate

objects.

18

Figure 7. Mean difference scores in Animate Block and Inanimate Block after 6 and 12 training

trials in bilingual children. Error bars indicate the standard error.

Since learning only occurred after 12 training trials for both monolingual and bilingual children,

we compared performance in the monolinguals and bilinguals after 12 training trials (see Figure

8). Two-sample t-tests were conducted to compare their performance in animate object and

inanimate object test trials. Based on this preliminary data set with only 16 bilinguals tested,

bilingual and monolingual children’s performance was not significantly different for either

animate (t(19) = 0.71, p = .48) or inanimate objects (t(23) = 0.87, p = .39). However, the mean

difference scores of bilinguals are consistently higher than monolinguals, which suggests that

bilinguals might be better than monolinguals in learning colour labels using this paradigm. We

will be able to draw a firmer conclusion after collecting additional bilingual data.

19

Figure 8. Comparison of performance after 12 training trials in monolingual and bilingual

children.

In an exploratory analysis, we examined if the potential difference in monolingual and bilingual

children’s performance is due to their differences in language experience or vocabulary size. We

conducted a correlation analysis between their vocabulary size and performances in Animate

Block after 12 training trials by collapsing monolingual and bilingual children (see Figure 9).

Results of the Pearson correlation indicated that there was no significant association between

CDI scores and performance (r(45) = -0.03, p = .97). This suggests that the vocabulary size

differences between monolinguals and bilinguals do not seem to affect performance on this task.

However, one reason could be our final sample only include those who could both understand

and say all the object labels that we used in the experiment and so there was no difference in

their word knowledge on our stimuli.

20

Figure 9. Correlation between CDI scores and performance in Animate Block after 12 training

trials in both monolingual and bilingual children.

General Discussion

Children learn words remarkably fast, regardless of whether they are learning one language or

more than one language. But recent work has reported that monolingual and bilingual toddlers

differ in how heavily they rely on well-established word learning heuristics, like the MEP (e.g.

Davidson & Tell, 2005; Houston-Price, Caloghiris & Raviglione, 2010). In one study,

monolingual toddlers tended to interpret a novel word for a familiar object as a second order

label (e.g., colour names; Kandhadai, Hall, & Werker, 2017). Unlike monolinguals, bilinguals

appeared to more readily accept multiple labels for individual referents, leading them to fail to

map novel labels onto second order properties like an object’s colour. In the real world, however,

bilinguals can clearly learn labels for second order properties. In the current study, we examined

the acquisition of novel colour labels by monolingual and bilingual 2-year-olds. Our results

suggest that when provided with appropriate contextual information (i.e., cross-situational

21

statistics), all children were able to acquire novel colour labels. However, the task was not easy.

Evidence for learning was only observed after 12 (but not six) training trials, and only highly

salient atypical colour-object pairings (e.g. turquoise dogs and magenta turtles) triggered the

mapping of novel labels to colour properties in either group.

In line with our predictions, labels for colours were easier to learn in atypical colour-object

pairings (i.e., in animate objects) than in typical colour-object pairings (i.e., in inanimate objects)

for both monolingual and bilingual children. In fact, contrary to our prediction, neither

monolinguals nor bilinguals showed any evidence of learning colour labels in inanimate objects.

This suggests that colour typicality might play a role in how easily children could learn a colour

label. The atypical colours in animate objects might have drawn their attention more, and thus

facilitating a mapping between the adjective and the perceptual property. In contrast, the more

probable colour-object pairings in inanimate objects are less salient, it is possible that children at

this age might adhere to the Whole-Object Assumption if the perceptual property is not as

apparent. Another possibility is that children tend to pay more attention to objects with faces than

those without (Fantz, Fagan, & Miranda, 1975). Children might simply pay more attention

during the animate object block than the inanimate object block, leading to the higher

performance with animate objects. To tease apart whether the pattern is due to the colour

typicality or an attentional bias, we plan to run a follow-up study with colours that are probable

in both animate and inanimate objects, such as yellow or grey. If the advantage of animate

objects disappears, this would mean colour typicality influences how easy children can map a

novel adjective to a colour. An alternative explanation is that all animate objects we used in the

experiment belong to the same superordinate category – animal, whereas the inanimate objects

we used do not share a same superordinate category. A familiar inclusive label for the animate

objects might have facilitated the mapping between the novel adjective and the colour, and

subsequently allowed them to extend the adjective to another member within the same

superordinate category. However, we found this explanation to be unlikely because another line

of research has shown that toddlers and young children were only able to extend novel adjectives

to the test objects when all objects were drawn from the same basic level category, but failed to

do so if the objects were drawn from different basic level categories (e.g., Klibanoff & Waxman,

2000; Waxman & Markow, 1998), even when superordinate labels were explicitly provided to

22

them (Graham, Cameron & Welder, 2005). This suggests that having all objects in the same

superordinate category does not fully explain the learning advantage in animate objects.

Another important finding is that monolinguals did not perform better than bilinguals in this task;

they were only able to learn the colour labels in animate objects, and were only successful after

12 training trials. This implies monolingual children do not, as previous studies suggested,

reliably use MEP in learning labels for second order properties. Instead, the tendency to use

MEP might depend on the specific paradigm and specific properties being tested. Akathar and

Montague (1999) found that children could use cross-situational consistency to learn labels for

shape and texture, so why did children in our experiment not reliably learn colour labels? A

possible explanation comes from another body of literature that has repeatedly demonstrated

toddlers and young children attend to shape when classifying inanimate objects but instead

attend to both shape and texture when classifying animate objects because these dimensions are

critical to lexical category membership (e.g., Booth & Waxman, 2002; Jones & Smith, 2002;

Jones, Smith, and Landau, 1999) . Particularly, Graham and Poulin-Dubois (1999) found that 16-

to 20-month-olds generalized novel labels to same shape referents but not to the same colour

referents in both animate and inanimate objects. This means that children might bias their

attention more towards shape and texture than colour when searching for commonalities between

the objects used in the task, which helps them to more easily identify the potential referent as

shape or texture as opposed to colour.

Our results also demonstrate that both monolingual and bilingual children are able to use cross-

situational consistencies to learn second order property labels, but perhaps to a different degree.

Virtually all studies in the past used syntactic cues (e.g., This is a blick-ish one) to indicate the

adjectival status of the novel word in order to facilitate learning because infants as young as 14

months were found to be sensitive to these grammatical categories and are able to make relevant

inferences about meanings (Hall, Waxman, and Hurwitz, 1993). Therefore, since the

grammatical category of our novel words is ambiguous, and could either be interpreted as a noun

or an adjective, children, especially bilinguals, would need to rely on cross-situational

consistency in order to accurately map them to the object property. Based on our preliminary

results in Experiment 2, although it did not reach a significant level, bilinguals showed some

evidence that they might be outperforming monolinguals because of their consistently higher

mean scores. If their difference is indeed significant, this would provide the first evidence that

23

bilingual children are better than monolingual children in tracking cross-situational statistics. To

be successful in this task, children would need to track the two word-to-referent pairings

simultaneously. Bilinguals might have benefited in this task due to their constant need to track

multiple regularities and structures in their environment. Another possible explanation is that,

counterintuitively, the smaller vocabulary size in bilinguals might be beneficial to adjective

learning without a strong syntactic cue indicating the adjectival status. Sandhofer and Smith

(2007) compared 24-month-olds who had high CDI scores to those who had low CDI scores.

They found that those who had a smaller noun inventory learned adjectives better without strong

syntactic cues; In contrast, those who had a larger noun inventory learned adjectives better with

strong syntactic cues. This is because children with a larger vocabulary size are more sensitive to

the distinction between nouns and adjectives, and are therefore more likely to use word class

information in learning new adjectives. However, this type of explanation seems to be unlikely

given our sample because there is no significant correlation between performance and CDI

scores, in either monolinguals or bilinguals.

This study provides three important contributions. First, we found that bilinguals do not, as

previously suggested, always suspend the MEP or systematically infer a novel word as a second

label for a familiar object. Instead, when given more contextual information, they are able to take

other cues in the environment into account in resolving referential ambiguity. Therefore, future

studies should focus more on how children utilize or weigh the different cues in the environment,

instead of focusing on whether they adhere to or suspend a single type of cue. Second, neither

monolinguals nor bilinguals made use of the MEP equally well in all conditions. In particular,

based on our findings, children appeared to successfully use the MEP only when the colour-

object pairings were atypical, which suggests that colour typicality affects the ease of learning

novel colour labels. Third, this study also adds to the growing literature that young children can

make use of cross-situational statistics in word learning. Thus far, there is only a handful of

studies of cross-situational word learning in children and no study has been done on bilingual

children. In fact, word-to-object pairings are often learned across multiple situations in everyday

contexts due to the many potential referents in the environment. Future studies can directly

compare monolingual and bilingual children’s abilities in tracking cross-situational statistics.

This strategy could help tease apart possible explanations for the results in current study, such as

whether children are using both the MEP and statistical information, or only statistical

24

information in learning colour names, if indeed any difference between monolinguals and

bilinguals emerges.

To conclude, this study highlights the importance of considering the ecological validity as well

as the richness of the word learner’s home environment. It also highlights the importance of

linguistic background in shaping children’s word learning strategies, which, in turn, shape lexical

development.

25

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