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# 20-month-olds can use negative evidence while learning word meanings

Alex de Carvalho, Isabelle Dautriche

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## To cite this version:

Alex de Carvalho, Isabelle Dautriche. 20-month-olds can use negative evidence while learning word meanings. Cognition, 2025, 262, pp.106171. 10.1016/j.cognition.2025.106171. hal-05114105

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Full Length Article

# 20-month-olds can use negative evidence while learning word meanings

Alex de Carvalho<sup>a,*</sup>, Isabelle Dautriche<sup>b</sup>

## ARTICLE INFO

**Keywords:**

Language acquisition

Word learning

Lexical development

Negation

Open data

Open materials

Preregistered

## ABSTRACT

Decades of research in psychology have built models and theoretical assumptions about language development evaluating how children extract information from positive evidence to learn the meanings of novel words. In the present set of studies, we evaluated whether children can also consider negative evidence, information about what a word cannot refer to. Across two experiments (n = 73), we show that English-learning 20-month-olds can use negative evidence in the form of negative sentences (e.g., “This is not a danu”) to constrain their interpretation of a novel word meaning (“danu”). These findings raise the possibility that learning word meanings through positive evidence alone, while possible, may not be the most accurate characterization of the word learning process and invite further developments of current word learning theories and models that incorporate negative evidence.

## 1. Introduction

Negative evidence, or corrective feedback, has an important function in any type of skill learning (Hattie & Timperley, 2007; Newell, 1991). In language acquisition research, however, the availability and the effectiveness of negative evidence—information about which linguistic constructions or forms are incorrect—are subject of intense debates (Brown & Hanlon, 1970; Chouinard & Clark, 2003; Marcus, 1993, 1999; Moerk, 1991). This has led many to argue that learners can acquire the lexicon and syntax of their language solely by relying on positive evidence - information about the attested constructions and forms of the language (Angluin, 1980; Christiansen & Chater, 1999; Elman, 1993; Gold, 1967; McMurray, Horst, & Samuelson, 2012; Vong, Wang, Orhan, & Lake, 2024; Xu & Tenenbaum, 2007; Yang & Piantadosi, 2022), leaving aside the role that negative evidence might play in this process. Here we focus on word learning and provide novel evidence that 20-month-old children can use negative evidence in the form of negative sentences (e.g., “This is not a danu”) to constrain their interpretation of a novel word (“danu”), suggesting that negative evidence can be used by infants while acquiring their lexicon.

Learning the meaning of a word, even the simplest labels, is a hard problem (Quine, 1960). Consider, for instance, a child learning the English word “Dalmatian” while observing one of these spotted pets. “Dalmatian” could refer to Dalmatians but also to this particular pet, to all and only spotted pets, to all dogs, to all animals and so on. A rich body

of work has focused on how children use positive examples – examples of what the word refers to, to infer the meaning of words (McMurray et al., 2012; Siskind, 1996; Vong et al., 2024; Xu & Tenenbaum, 2007). For instance, in the case of “Dalmatian” they may observe that this word is used only when a Dalmatian is around and not any other types of dogs to constrain their interpretation of the word.

While current theories concentrated on how learners infer the meaning of a word from positive examples, that's not the only source of information that children have at disposal. To learn the meaning of “Dalmatian”, children could benefit from negative examples: knowing what in the world cannot be called a Dalmatian. For instance, hearing “This is not a Dalmatian” in the presence of a Beagle will certainly be helpful in establishing precisely the extension of the new word (i.e., “Dalmatian” applies only to Dalmatians, not to all dogs). Although parents provide negative examples using contrasting statements (e.g., “That’s not a Dalmatian, that’s a Beagle”, see e.g., Cameron-Faulkner, Lieven, & Theakston, 2007; Chouinard & Clark, 2003; Farrar, 1992; Gomes et al., 2023; Jasbi, Annika, Davidson, & Carey, 2021; Moerk, 1991; Saxton, Backley and Gallaway, 2005) and 18 month-olds understand negative sentences (de Carvalho, Crimon, Barrault, Trueswell, & Christophe, 2021; de Carvalho, Gomes, & Trueswell, 2022; Szabó & Kovács, 2022, Szabó and Kovács, 2025), it is far less clear whether children can use negative examples during word learning.

Several studies in the literature suggest that providing children with contrasting information—specifically, explicit evidence about the

<footnote><sup>a</sup> Laboratoire de Psychologie du Développement et de l'Éducation de l'Enfant - LaPsyDÉ, La Sorbonne, Université Paris Cité, CNRS, Paris, France</footnote>

<footnote><sup>b</sup> Centre de Recherche en Psychologie et en Neurosciences, Aix-Marseille Université, CNRS - Marseille, France</footnote>

<footnote>* Corresponding author at: LaPsyDÉ - La Sorbonne, 46 rue Saint-Jacques (escalier A, 4ème étage), 75005 Paris, France.</footnote>

<footnote>E-mail addresses: alex.de-carvalho@u-paris.fr (A. de Carvalho), isabelle.dautriche@cnrs.fr (I. Dautriche).</footnote>
boundaries of novel word usage—can facilitate word learning (see e.g., Au & Markman, 1987; Booth & Waxman, 2003, 2009; Childers, Hirshkowitz, & Benavides, 2014; Clark, 1988, 1997; Hall & Belanger, 2005; Klibanoff & Waxman, 2000; Namy & Gentner, 2002; Waxman & Klibanoff, 2000; Waxman & Markow, 1995). For example, when learning the meaning of a novel word like “blicket,” it may be helpful for a child to understand not only which objects can be referred to as “blickets,” but also which objects receive a different label or cannot be labeled as “blickets”. This type of contrasting information has been used in many word-learning studies (see e.g., Bernal, Lidz, Millotte, & Christophe, 2007; Booth & Waxman, 2003, 2009; Childers et al., 2014; Gelman, Wilcox, & Clark, 1989; Kalish & Lawson, 2007; Waxman & Booth, 2001, 2003; Waxman & Klibanoff, 2000; Waxman, Lidz, Braun, & Lavin, 2009). However, none of these studies have included a clear control condition to isolate the effect of negative contrastive sentences on the inferences children made about the novel words.

For instance, in *Waxman and Klibanoff (2000)*, the manipulation was whether the referents being considered for the novel adjective shared a basic property (e.g., two types of plate, one transparent and one opaque) or not (e.g., a transparent plate and an opaque toothbrush). In both conditions, children were first introduced to an object with an affirmative sentence (e.g., “This is a very blickish one”), followed by a contrastive object (e.g., opaque plate or a toothbrush) introduced with a negative sentence (e.g., “This one is not blickish”). At test, children succeeded only in the condition where the contrast shared the same basic property, suggesting they used negative evidence to constrain the novel word’s meaning. However, since this condition was not compared with a control condition in which instead of the negative sentences, they used a positive or neutral condition, conclusions about the unique role of negative evidence remain unclear. It is therefore uncertain whether negative evidence is relevant for early word-learning and/or for category learning.

More recently, de Carvalho et al., 2021, 2022) studied whether 1.5- to 4-year-old children could learn novel words from positive and negative examples. They found that while children successfully learned from positive examples (“Look! This is a dax!”), they did not learn from negative examples (“Look! This is not a dax!”), performing only at chance levels (see e.g., de Carvalho et al., 2021). In sum, the effectiveness of negative examples in teaching word meanings to infants is still in question.

In the present set of studies, we tested whether children can use negative examples introduced with negative sentences (“this is not a danu”) to constrain the interpretation of a novel word (“danu”). English-learning 20-month-olds<fnref n="1" /> were first presented with a cartoon character, e.g. a red monster, a positive example of what a “danu” is, labelled several times in different affirmative sentences (“Oh look! It’s a danu!”). Participants were then assigned to either the negative or the no-label condition before being presented with a different cartoon character, e. g., a blue monster. In the negative condition, the new cartoon character was presented as a negative example, as they heard “Oh look! It’s not a danu!”. Participants in the no-label condition did not receive additional information about whether the new character was an instance of a “danu” or not. Instead, they heard neutral sentences like “This one is really nice,” where the speaker did not label the novel object. All participants were then tested in the same preferential looking procedure, in which they saw two images side-by-side (e.g., the red versus blue monster) and were asked to find the “danu” (test trials) or the “modi”, a

label never heard during the teaching phase (mutual exclusivity trials). If toddlers use the information from the negative example, they should be more likely to interpret “danu” as referring exclusively to the attested positive example (red monster) in the negative condition, excluding the blue monster from the extension of the word. Thus, they should look more toward the red monster when asked to look at the “danu”, and less so when asked to look for “modi”, by principle of mutual exclusivity (Markman & Wachtel, 1988). In contrast, in the no-label condition, seeing a single positive example of “danu” followed by the presentation of another monster without a name could lead to various interpretations, such as “danu” might mean RED MONSTER, MONSTER, etc. (Xu & Tenenbaum, 2007). If so, they may still show some preference toward the red monster when asked to find the “danu” because that’s the only object labelled “danu” they saw. Yet, if they also consider the other object to be a good candidate referent for “danu” they may not be able to apply mutual-exclusivity as both objects would have a label and thus display chance performance on mutual-exclusivity trials.

## 2. Experiment 1

### 2.1. Method

The studies reported in this paper, including their entire methods, analysis, and criteria for exclusion of participants, were preregistered on the OSF (Open Science Framework) database before running the experiments. The formal preregistrations, the stimuli used, collected data, and data analysis scripts are freely available to readers through the following link: https://osf.io/q5d3t/

#### 2.1.1. Participants

Forty-eight English-speaking children were included in the final analysis (mean age = 19M16D; SD = 49D; min = 17M2D; max = 22M2D; 19 girls). This sample size was determined based on the recommendations of Oakes (2017) who investigated the effects of sample size and statistical power in infant looking-time research and suggested that infant studies with sample sizes smaller than 24 per cell can be underpowered and result in false-positive and false-negative results. In addition, having 24 participants in each condition is consistent with the number of participants tested in previous studies using the same paradigm (see e.g., Dautriche, Fibla, Fievet, & Christophe, 2018; Dautriche, Swingley, & Christophe, 2015; de Carvalho et al., 2021). An additional 33 children were tested but excluded from the analysis because they refused to wear the eye-tracking sticker or because of difficulty to calibrate (n = 8), they were exposed to less than 60 % of English in a week (n = 9), they did not provide sufficient trials with exploitable data (n = 12; see exclusion criteria below), because of computer failure (n = 2), their caregiver interfered (n = 1) or because they did not look at the teaching videos (n = 1). Participants were recruited in the Edinburgh area via email invitations sent to the parents who were registered in the Wee Science database hosted by the University of Edinburgh.

#### 2.1.2. Procedure and experimental design

During the experiment, children sat on their caregiver’s lap in front of a monitor. Caregivers wore opaque glasses, and were asked to not interact with the child during the procedure. The experiment was composed of 3 phases as depicted in Fig. 1.

**Introduction phase:** All participants saw an introductory video where a native English female speaker greeted the child, before telling them that she was going to turn on the television behind her and that they were going to watch a cartoon together.<fnref n="2" />

**Teaching phase.** Participants saw two videos. In the first video

<footnote n="1">¹ We chose this age range as it represents the youngest age most commonly tested in earlier experiments on infants’ ability to use syntactic information to learn novel word meanings (see e.g., Dautriche et al., 2015, 2018; de Carvalho et al., 2019, 2021). This is also the youngest age range in which infants were shown to be able to understand negative sentences in English (see e.g., de Carvalho et al., 2022; but see also de Carvalho et al., 2021; Szabó & Kovács, 2025, for similar results in other languages).</footnote>

<footnote n="2">² The female speaker who introduced the monsters to the children during the introduction and teaching phase was presented in a video on the screen. Participants never saw that female speaker in person.</footnote>
<figure><img src="image_4.png" /><figcaption>**Fig. 1.** Design of Experiment 1 – In the teaching phase, all infants watched a video of a speaker labeling a cartoon character (a red monster) with a novel word (“danu”) (1). Then, depending on the condition they were assigned in, they watched a video where a second cartoon character (a blue monster) was presented as a negative example of the novel word (2a) or was presented without a label (2b). Finally, all infants went through the same test phase (3), a preferential looking procedure, where the two cartoon characters were presented on the screen and infants were asked to find the “danu” (test trials) or the “modi” (mutual-exclusivity trials).</figcaption></figure>

(common to all participants), participants were introduced to a positive example of a novel word's referents. The speaker turned on the television and participants saw a cartoon character on the screen (e.g., a red monster). The speaker labelled the cartoon character 5 times using the novel word “danu” (e.g., “Oh look! It’s a danu! This is a really nice danu!”) pointing toward the character and looking back and forth toward the character on screen and the camera (as if she was talking with a child in front of her).

In the second video, a different cartoon character appeared on the television (e.g., a blue monster). For half of the participants, the novel character was presented as a negative example of the novel word “danu” (the *negative condition*). They heard the speaker using 5 negative sentences describing the novel character as “not a danu” (“That is clearly not a danu. It is really nice! But it is not a danu,”). For the other half of the participants, the novel character was not labelled (the *no-label condition*). They heard the speaker using 5 neutral sentences to refer to the novel character (“This one is really nice. Have you ever seen something so nice?”). Which character, the blue or the red monster, was designated as the “danu” in the first teaching video, was counterbalanced within each condition.

Test phase. The test phase assessed children's interpretation of the novel word “danu”. Participants were tested using a preferential looking procedure, in which they saw two objects on the screen and heard the speaker from the teaching phase naming one of the objects. Participants were administrated a total of 16 trials: 8 familiar word trials and 8 novel word trials, 4 for the word “danu” heard during the teaching phase (test trials) and 4 for an unknown novel word, “modi”, not heard during the teaching phase (mutual exclusivity trials). Each trial started with the simultaneous presentation of two pictures on the right and left sides of the screen (the baseline period). Two seconds later, the test sentences started, e.g., “Look at the [target]! Do you see the [target]?”. Infant’s eye movements and gaze patterns were continuously monitored and

recorded during the entire experiment by an eye-tracking device (eyelink1000, SR Research Ltd., Ottawa, ON, Canada).

We added familiar word trials to our task to make the task more engaging for children with several trials in which they would have no difficulty identifying the right referent for the target word and also to make the task less pragmatically confusing for children. Since there were only two potential referents for the novel words—the blue and red monsters—repeating test trials consecutively would likely reduce infants’ engagement, as they would see the same images on the screen repeatedly. Intervening the presentations of these trials with familiar words made the task more natural as at each trial children were asked to find a different referent.

### 2.1.3. Material

Familiar word trials. Each familiar word trial featured two familiar objects (butterfly, orange, dog, banana, car, ball, boat, cat, hat, fish, duck, spoon, apple, bird, book, star). Pictures were yoked in pairs (i.e., the butterfly appeared always with the orange), each pair appeared one time in the experiment in order to avoid repetition and increase children’s attention. Children were tested for only one label of each pair (counterbalanced across children).

Novel word trials. All novel words trials featured the two cartoon characters introduced during the teaching phase: the red monster and the blue monster. The novel words were both bisyllabic and did not have any phonological neighbours in children’s lexicon (“danu” and “modi”).

The number of items we used (familiar and novel words) were based on previous studies who used a similar paradigm with children from the same age (Bion, Borovsky, & Fernald, 2013; Dautriche et al., 2015; Ferguson, Graf, & Waxman, 2014, 2018; Fernald, Zangl, Portillo, & Marchman, 2008; Schmale, Cristia, & Seidl, 2012; Swingley & Aslin, 2000).

All sentences used in the experiment were recorded in child-friendly speech. For the videos used in the teaching phase, the same intonation was used to utter the negative sentences and the no-label sentences. The speaker was always very positive, so that any difference in performance can only be attributed to the differences in the lexical materials and gestures used and not the prosody of the sentences.

### 2.1.4. Criteria for trial and participant exclusion

Trials for which we had more than 35 % of trackloss were rejected. Participants that provided fewer than 6 valid trials (with a minimum of 2 familiar trials, 2 test trials and 2 mutual-exclusivity trials; *n* = 12) were also excluded from the final analysis. Note that we first pre-registered a more stringent criterion of 4 valid familiar trials, yet given the difficulty in recruiting during and post COVID, we decided to keep infants with 2 valid familiar trials instead of 4.

### 2.1.5. Measurement and analysis

We measured the time course of children’s eye gaze toward the attested positive example of “danu” introduced during the first video of the teaching phase (e.g., the red monster in Fig. 1). Gaze position on each trial was recorded via an eye-tracker (eyelink1000) mounted on the bottom of the screen, with a 2 ms sample rate. For all analyses and plots, we coded the proportion of looks toward the positive example relative to the total number of looks to both characters (excluding looks away) for each 50 ms time bin. We inspected the time course of eye movements from the onset of the first occurrence of the target word (“Look at the [target]”) until the end of the trial (5 s).

First, we conducted a cluster-based permutation analysis (Maris & Oostenveld, 2007) to find a time window where we observed a significant difference in fixation proportion toward the positive example between test trials and mutual exclusivity trials in each condition. For each time bin, we conducted a two-tailed *t*-test on fixations to the positive example between test trials and mutual-exclusivity trials. All fixation proportions were transformed via the arcsin square function to fit better the assumptions of the *t*-test. Adjacent time points with a significant
effect ($t > 2$; $p < 0.05$) were grouped together into a cluster. The size of each cluster was computed as the sum of all t-values within this cluster. To obtain the probability of observing a cluster of the same size by chance, we conducted 1000 simulations where trial types (test vs. mutual-exclusivity) were randomly assigned for each trial. For each simulation, we computed the size of the biggest cluster identified with the same procedure that was used for the real data. A cluster from the original data was considered significant if the probability of observing a cluster of the same size or bigger in the randomized data was smaller than 5%, corresponding to a $p$-value of 0.05.

Note that this analysis follows the pre-registration of Experiment 2. In Experiment 1's preregistration, we planned to compare fixation proportions to the target referent against chance (0.5). However, while pre-registering Experiment 2, and after we saw Experiment 1's results, we identified key issues: (1) both conditions may show a bias toward the positive example simply because it was the only labelled object; (2) assuming a 0.5 chance level may not hold, as biases (e.g., toward the 'not a danu' object or any labelled item) can vary across conditions (see e.g., de Carvalho et al., 2021). Thus, we opted to compare differences between test and mutual exclusivity trials to control for baseline effects. The original chance-level analysis is still reported in the results.

Second, we compared the overall proportion of looking times toward the attested positive example, averaged across the whole trial duration (5 s), between trial types and conditions. We modelled the proportion of attested positive example looks in a mixed model analysis (Bates et al., 2015) in R using the following model: PropPositiveExample ~ Condition $x$ Trial_type + (1 | Participant).<fnref n="3" /> We added this more standard analysis to our pre-registered cluster-based analysis as recommended by previous research (Delle Luche, Durrant, Poltrock, & Floccia, 2015). This allowed us to compare the interaction of trial type and condition within the same statistical model (which was impossible with the cluster-based analysis without doing 2-by-2 comparisons). $P$ values for main fixed effects are based on likelihood ratio tests, simple effects are reported from the summary table of the model. Fixed effects were dummy coded.

Additionally, a reviewer suggested we analysed the proportion of looks toward the positive example in the negative condition vs. the no-label condition for mutual exclusivity trials and test trials separately. The reasoning is the following: if negative evidence is helpful in narrowing the novel word meaning, then we should observe a stronger performance on test trials in the negative condition compared to the no-label condition, as children in the negative condition would be able to more conclusively reject the second monster as not being a danu. Although we share the same intuitions, we believe such analysis does not constitute a satisfactory test due to the concerns outlined in point 2 above: there is no certainty that the chance level and the proportion of looks to the positive evidence is comparable across conditions. This is because the object presented without a label in the no-label condition could be less salient, causing toddlers in this condition to prefer to look at the labelled object (positive example) more often than toddlers in the

negative condition who may actually be more likely to look at the “not a danu” object (see e.g., de Carvalho et al., 2021). For this reason, we decided not to include this analysis in the paper, even though it supports the hypothesis by showing better performance in test trials in the negative condition compared to the no-label condition. We have added this additional and exploratory analysis to our OSF folder (see “analysis”: https://osf.io/q5d3t/).

## 2.2. Results

Fig. 2-A-B (left side) presents the proportion of looks toward the attested positive example of the word “danu”, from the onset of the target word for test trials in red (“where is the danu?”) and mutual-exclusivity trials in light grey (“where is the modi?”) for participants assigned to the negative condition (A) and the no-label condition (B).

The nonparametric cluster-based permutation test found a significant time-window where the proportion of looks toward the attested positive example was significantly different in the test trials compared to the mutual exclusivity trials for participants in the negative condition (Fig. 2A, from 1750 ms until 2350 ms; $p = 0.021$): children looked significantly more toward the attested positive example of “danu” during test trials than during mutual exclusivity trials. In the no-label condition (Fig. 2B) no difference was found between test trials and mutual exclusivity trials.

With regards to our original pre-registered analysis, the cluster-based analysis revealed that when tested on the word “danu”, children in the negative condition fixated the attested positive example above chance (red curve in Fig. 2A, from 1600 ms until 2300 ms, $p = 0.007$), while their fixations were significantly below chance when tested on “modi” (light grey curve in Fig. 2A; from 2650 ms until 3700 ms, $p < 0.001$). In the no-label condition, children's fixations in both trial types were not different from the chance level (i.e., no time window found while comparing each trial type fixations to the chance level).

The mixed-effect analysis conducted on the overall looking times toward the positive example (bar plots on right side of Fig. 2) showed a significant interaction between trial type (test vs. mutual exclusivity) and condition (negative vs. no-label) ($\chi^2(1) = 9.087$; $p = 0.002$) with children showing increased looks toward the attested positive example of “danu” in test trials compared to mutual-exclusivity trials in the negative condition ($\beta = 0.121$, $t = 3.673$, $p < 0.001$) but not in the no-label condition ($\beta = 0.019$, $t = 0.595$, $p = 0.557$). There was also a main effect of trial type with children looking significantly more toward the attested positive example in test trials than in mutual-exclusivity trials ($\chi^2(2) = 4.891$; $p = 0.027$). There was no main effect of Condition.

## 2.3. Discussion

Our results suggest that 20-month-old children can use negative examples to constrain their interpretation of a novel word's meaning. When presented with a positive example of a “danu”, e.g., a blue monster, and an unlabelled object, e.g., a red monster, children looked equally at the two cartoon characters at test, consistent with the hypothesis that this learning situation may not be sufficient for them to be certain about the interpretation of the word (MONSTER VS. RED MONSTER) or that they interpreted “danu” as referring to MONSTER, a concept that would include both objects seen during the teaching phase. In contrast, when children were presented with a negative example (the blue monster was explicitly described as being “not a danu”), children appropriately restricted “danu” to the red monster only, suggesting that the negative evidence provided by the negative sentences helped children to refine their hypothesis about the novel word.

An alternative possibility is that negative evidence does not constrain the meaning of a word but rather enhances children's ability to map a novel label onto an unlabelled referent (i.e. boosting their ability to apply mutual exclusivity). However, we consider this unlikely. As mentioned above, we find a stronger preference for the positive example

<footnote n="3">³ Adding a random slope for Trial_type did not change the model's result and our interpretation as the random slope coefficient had a near-zero variance due to the small number of data points per individual (2 to 4 time points). We fully acknowledge the limitations posed by the small number of trials per participant, which restrict the complexity of the statistical models that can be reasonably estimated. This is a common challenge in infant research, where practical constraints such as infant's limited attention spans and participant availability often make it difficult to collect larger datasets. To address this concern, we compared our preregistered model (with random intercept only) with a model including a random slope for Trial Type by participant. This comparison revealed no significant difference between the models ($\chi^2(2) = 0.0002$, $p > 0.9$), consistent with the minimal variance attributable to the slope. While collecting more data with infants, even over two or more sessions would undoubtedly strengthen statistical inferences, our approach reflects a balance between methodological rigor and the practical realities of working with infant populations.</footnote>
<figure><img src="image_5.png" /><figcaption>**Fig. 2.** Results for the negative condition (A) and the no-label condition (B) of Experiment 1 and the no-label condition of Experiment 2 (C). The spaghetti plots on the left represents the proportion of looks toward the attested positive example of the word “danu”, time locked from the onset of the target word for test trials in red (“where is the danu?”) and mutual-exclusivity trials in light grey (“where is the modi?”). The ribbon surrounding each curve represents the standard error of the mean obtained at each time bin for each trial type. The dark grey shaded areas indicate the time region where children’s looking behaviour was significantly different (*p* < 0.05) between the test and the mutual exclusivity trials following our cluster-based permutation analysis. The bar plots on the right side of the Figure represent the overall proportion of looks toward the attested positive example of the word “danu” averaged across the entire trial duration (5 s) for each type of trial: test trials in red and mutual-exclusivity trials in light grey. The dots represent individual data points and the error bars standard error of the mean. The lines connect the dots representing each participant across trial types. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)</figcaption></figure>

in the negative condition compared to the no-label condition only for test trials but not for mutual exclusivity trials (see supplemental analysis in the OSF folder).

However, Experiment 1 alone leaves open the possibility that children's behaviour in the no-label condition does not reflect their

interpretation of the novel word. Instead, it may be due to confusion with the unlabelled object or forgetting of the word “danu,” as they only heard it during the first teaching video, unlike children in the negative condition. In other words, one could think that infants better performance in the negation condition compared to the no-label condition is
attributed to the fact that they heard more examples of the target word (10 times in total, 5 in each video of the teaching phase), while infants in the no-label condition only heard the target word 5 times (in the first video of the teaching phase). While this does not undermine the finding that children in the negative condition excluded the negative example from the word's extension, it raises questions about whether the negative example actually constrained children's interpretation of the word if participants' behaviour in the no-label condition is not the reflection of their interpretation after seeing one positive example. To address this issue, and investigate whether other types of negative evidence can guide word learning, we designed a second experiment.

## 3. Experiment 2

While Experiment 1 demonstrated that 20-month-olds can use negative examples to constraint their interpretation of novel word meanings, Experiment 2 tested whether children's behaviour in the no-label condition reflects their interpretation of the novel word (i.e., they believed both monsters were danus), rather than confusion with the unlabelled object.

Experiment 2 tested another group of children in the no-label condition of Experiment 1 at the difference that we introduced a clear conceptual contrast between the positive example shown during the first teaching video (e.g., monster), and the second, non-labelled object (e.g., a spinning toy). If children's behaviour in the no-label condition reflected confusion with the unlabelled object, or lack of memory for the first teaching video, then we expect the same to happen in Experiment 2 with children showing a chance-level performance in both test and mutual-exclusivity trials. However, if children in the no-label condition of Experiment 1, as we hypothesized, generalized the word "danu" to both novel objects (therefore understanding "danu" as "monster") then we expected that children's behaviour in Experiment 2 should also reflect their interpretation of the novel word. In contrast to Experiment 1, we expected that the clear conceptual contrast between the two novel objects (an animate vs. an artifact), should help children to refine their interpretation of the novel word "danu" and to block the possibility that "danu" could refer to the second object (Dautriche et al., 2015, Dautriche et al., 2018). Thus, we expected that children in Experiment 2 would behave similarly to children in the negative condition of Experiment 1.

### 3.1. Method

#### 3.1.1. Participants

Twenty-five English-learning toddlers were included in the final analysis (mean age = 19M10D; SD = 47D; min = 17M5D; max = 22M6D; 13 girls). As in Experiment 1, we planned on testing 24 children. An additional 10 children were tested but excluded from the analysis because they refused to wear the eyetracking sticker (n = 3), they were exposed to less than 60 % of English in a week (n = 3), they did not provide sufficient trials (n = 3), their caregiver interfered (n = 1). Participants were recruited in the Edinburgh area via the Wee Science database hosted by the University of Edinburgh.

#### 3.1.2. Procedure and experimental design

The procedure was the same as in Experiment 1. Participants were presented with the same videos as participants in the no-label condition of Experiment 1, except that instead of using a red and a blue monster respectively as exemplars of the novel word "danu" and as a no-label character, we used a monster and an inanimate object (e.g., a spinning toy; see Fig. 3). Which object, the animate character or the inanimate object was designated as the "danu" in the first teaching video, was counterbalanced between participants.

#### 3.1.3. Material

The material was the same as in Experiment 1 except for the set of

<figure><img src="image_6.png" /><figcaption>Fig. 3. Design of Experiment 2 – The design of Experiment 2 is identical to the no-label condition of Experiment 1, except that this time the conceptual contrast between the two objects seen during the teaching phase was greater. While the first object described as a “danu” was the same cartoon character as in Experiment 1, a red monster (1), the second object that was described by the speaker and left unlabelled was a spinning toy (2) and not another monster as in Experiment 1.</figcaption></figure>

novel objects introduced during the teaching phase. One was the red monster of Experiment 1 and the other, an inanimate object, a spinning colourful toy (see Fig. 3).

### 3.1.4. Criteria for trial and participant exclusion

Same as in Experiment 1.

### 3.1.5. Measurement and analysis

Same as in Experiment 1. Additionally, the mixed model analysis was conducted on both experiments' data to allow group comparisons.

### 3.2. Results

As illustrated in Fig. 2-C, children looked significantly more toward the attested positive example of "danu" during test trials (red curve in Fig. 2C) than during mutual exclusivity trials (light grey curve in Fig. 2C, from 2300 ms until 3250 ms; *p* = 0.001). In the test trials, when asked to find "a danu", children fixated the positive example of "danu" significantly above chance (from 2300 ms until 3450 ms; *p* = 0.007). However, in the mutual-exclusivity trials their fixations were at chance when they were asked to find "a modi" (light grey curve in Fig. 2C; no significant cluster identified, *p* = 0.247).

The mixed-effect analysis conducted on the overall looking time toward the positive example of the word across the two experiments (see bar plots of the right side of Fig. 2) showed a significant interaction between trial type (test vs mutual exclusivity) and condition (negative vs. no-label (Exp1) vs. no-label (Exp2); $\chi^2(2) = 11.350; p = 0.003$). The interaction between trial type and condition was significant between the no-label condition of Experiment 2 and the no-label condition of Experiment 1 ($\beta = 0.119, t = -2.720, p = 0.007$) but not between the no-label condition of Experiment 2 and the negative condition of Experiment 1 ($\beta = 0.02, t = 0.541, p = 0.589$). As in the cluster-based analysis, children showed increased looks toward the positive example of "danu" in test trials compared to mutual-exclusivity trials in the no-
label condition of Experiment 2 ($\beta$ = 0.098, *t* = 3.271, *p* = 0.001). There was also a main effect of trial type with children looking significantly more toward the positive example in test trials compared to mutual-exclusivity trials ($\chi^2(1) = 12.978; *p* < 0.001). There was no main effect of Condition ($\chi^2(2) = 1.045; *p* = 0.593).

## 4. Discussion

In Experiment 2, the presence of a clear conceptual distinction between the two possible referents (an animate object vs an inanimate object) helped children to refine their interpretation of the word “danu” and blocked the possibility that “danu” referred to both objects. This suggests that the no-label condition was not confusing for children, but rather that their behaviour in that condition reflected their interpretation of the novel word given the information they had at disposal. Thus, in Experiment 1, children’s behaviour in the no-label condition may indicate that they understood both objects to be possible referents for the word “danu.”

## 5. General discussion

Across two experiments we demonstrated that by 20 months, English-learning infants can use negative examples to constrain the meaning of a novel word. When toddlers were presented with two objects—one being a positive example of a novel word and the other an unlabeled object, conceptually similar (another monster)—they showed no preference for attributing the novel label to either object. This reflected their interpretation of the novel word as a term applicable to both objects. Critically, this behaviour disappeared when the unlabeled object was presented as a negative example of the novel word via a negative sentence (e.g., “This is not a danu”), showing that children were able to take into account the information provided by this negative evidence to guide their interpretation of the novel word.

Our findings dovetail nicely with recent studies demonstrating that infants in the same age range tested here can process and understand negative sentences (de Carvalho et al., 2021, 2022; Szabó & Kovács, 2022, Szabó and Kovács, 2025). However, while these recent studies simply showed that infants can learn a novel word meaning with affirmative sentences (e.g., *Look! This is a bamoule!*!), but they do not make inferences about word meanings when hearing negative sentences (e.g., *Look! This is not a bamoule!*), here we extend these findings demonstrating that the information provided by negative sentences can be exploited by infants during word learning. This shows for the first time that English-learning 20-month-olds can use negative evidence in the form of negative sentences to constrain their interpretation of a novel word meaning.

The usefulness of negative evidence as a source of information during language acquisition has been a longstanding debate in the language acquisition literature (Gold, 1967). Historically, the debate mostly centered around the acquisition of grammar: Proponents of innateness theories argued for the necessity of a syntactic blueprint to compensate for the absence of the inefficiency of negative evidence (Marcus, 1993). In contrast, opponents of these theories built new theories and models relying solely on positive evidence to suggest that no innate structure was necessary (e.g., Christiansen & Chater, 1999; Elman, 1993; Pullum & Scholz, 2002; Reali & Christiansen, 2005). The idea that grammar acquisition must occur without negative evidence lingered into the field and influenced all domains of language acquisition including word learning, leading researchers to rarely consider negative evidence as a source of information for children while they are learning words (McMurray et al., 2012; Siskind, 1996; Vong et al., 2024; Xu & Tenenbaum, 2007). While we do not address the overall role of negative evidence in language learning, our results indicate that children can use negative evidence conveyed through explicit negative sentences (“This is not a X”) when learning word meanings. Certainly, this does not imply that negative evidence is necessary for word learning but rather that it

represents an additional source of information available in the infant’s toolkit that should be further explored and incorporated into future accounts of word learning.

When is negative evidence useful in the context of word learning? In our studies, children were first presented with a positive example of a novel word, followed by a negative example. This corresponds to a specific situation where children have already had the opportunity to form some hypothesis about the meaning of the novel word (through the positive example), which the negative example can further refine. This mirrors certain natural cases of negative evidence where a child’s erroneous word production is corrected by their caregivers (“No dear, this is not a Dalmatian, this is a bever”; see e.g., Chouinard & Clark, 2003; Gomes et al., 2023; Jasbi et al., 2021; Liu & Jasbi, 2025; Saxton, 2000; Saxton, Backley and Gallaway, 2005). Whether negative evidence can be useful in the absence of an initial representation of a word meaning remains to be tested. For instance, one could imagine that much like learners can recall one or more potential referents of a word in certain accounts of word learning (Trueswell, Medina, Hafri, & Gleitman, 2013; Yu & Smith, 2007) they may also recall and/or inhibit the ones that may not be part of the extension of the word. More generally, the role of negative evidence in constraining word meaning may vary depending on the word-learning context. In our study, negative evidence was used to contrast two objects of the same kind (e.g., two monsters), suggesting that negative evidence helps reduce ambiguity and guide children toward the correct interpretation. This highlights its value in situations with high ambiguity or when learners need to distinguish between closely related concepts (or questions under discussion, see e. g., Reuter, Feiman, & Snedeker, 2018; Tian, Breheny, & Ferguson, 2010). However, it remains unclear whether negative evidence also aids in less challenging word-learning scenarios, where the potential for ambiguity is lower. For instance, in cases with fewer overlapping referents (e.g., a novel vs. a familiar object; or the situation in Exp2), negative evidence might still reinforce correct word-referent mappings (as in e.g., Bernal et al., 2007; Booth & Waxman, 2003, 2009; Childers et al., 2014; Gelman et al., 1989; Kalish & Lawson, 2007; Waxman & Booth, 2003; Waxman et al., 2009; Waxman & Booth, 2001; Waxman & Klibanoff, 2000). Future studies should explore this more carefully by comparing the effects of negative evidence in varying levels of word-learning complexity.

The current study extends existing research on the role of negative evidence in vocabulary development (see e.g., Chouinard & Clark, 2003; Clark, 2020; Clark & de Marneffe, 2012; Lustigman & Clark, 2019; Saxton, 1997, 2000; Saxton, Backley and Gallaway, 2005; Strapp, Bleakney, Helmick, & Tonkovich, 2008; see also Pullum & Scholz, 2002) by specifically investigating whether negative evidence in the form of negative sentences can influence children’s vocabulary development. While we know that negative sentences are present in the input parents address to young children (see e.g., Farrar, 1992; Gomes et al., 2023; Liu & Jasbi, 2025; Jasbi et al., 2021; Saxton, Backley and Gallaway, 2005) future studies need to more clearly look at how negative sentences are used in conversational exchanges that can allow children to learn word meanings. In the context of our study, we show that toddlers can benefit from the contrast between an affirmative and negative statement to refine their interpretation of word meanings. But it remains to be seen whether this type of information is systematically used by parents when they want to teach a child a word they don’t yet know and how this information can interact with other cues that parent tend to use when talking about novel words to their children (see e.g., Clark, 2007, 2010; Clark & Wong, 2002).

It is also important to note that negative sentences are not the only form of “negative evidence” available to guide word learning. Some researchers argue that children can also rely on contrastive corrections without negation. For example, when an adult provides the conventional form of a word in response to a child’s error, the contrast between the child’s erroneous form and the adult’s correction serves as “negative evidence” (Chouinard & Clark, 2003). In everyday interactions, parents
offer additional cues—such as using a more conventional expression, along with rising intonation, or pointing—that can also help clarify a child’s intended meaning (see Clark, 2007, 2010; Clark & Estigarribia, 2011; Clark & Wong, 2002). Negative evidence could also be conveyed through social reinforcement. For example, if a child uses the word “cat” correctly in context, their interlocutor might respond by engaging in a conversation about cats, signalling communicative success and reinforcing the child’s word choice. Conversely, when the interlocutor shows signs of misunderstanding or communicative failure—such as confusion or an inability to understand the child—this might serve as negative evidence. Such implicit social signals may prompt children to reconsider and adjust their understanding of the word’s meaning. The availability and the influence of such implicit communicative feedback remains to be fully evaluated (Nikolaus & Fourtassi, 2023).

Another factor to consider is how the benefit of negative evidence might change across different stages of development. On one hand, children's ability to process negation and effectively use negative evidence for word-learning is expected to improve with age as they acquire more linguistic knowledge and reasoning/cognitive skills (see e.g., Cheng & Kibbe, 2024; Doyle, Friesen, Reimer, & Pexman, 2019; Feiman, Mody, & Carey, 2022; Grigoroglou, Chan, & Ganea, 2019; Zhang & Zhou, 2024). Even adults benefit from negative evidence to constrain word-learning in certain contexts (e.g., de Carvalho et al., 2021, 2022; Strapp, Helmick, Tonkovich, & Bleakney, 2011), and understanding negation seems to be linked to inhibitory control and theory of mind (Beltrán, Liu, & de Vega, 2021; Cuccio, 2012; Montalti, Calbi, Umiltà, Gallese, & Cuccio, 2024; Nordmeyer, Yoon, & Frank, 2016)—domain-general skills that begin developing during the first few years of life and continue to strengthen significantly throughout adulthood (e.g., Best & Miller, 2010; Diamond, 2013; Merkley, Thompson, & Scerif, 2016; Wellman, Cross, & Watson, 2001; Wright, Waterman, Prescott, & Murdoch-Eaton, 2003). On the other hand, reliance on negative evidence for word learning may change across development, as children acquire other tools, such as mutual exclusivity, which can also help constrain word meanings (see e.g., Bion et al., 2013).

In conclusion, the present study demonstrates that by 20 months of age, children are already able to integrate explicit negative evidence, such as negative sentences, to refine their interpretation of novel words. These findings challenge the traditional view that word learning relies predominantly on positive evidence, suggesting that negative evidence – whether in the form of negation, contrastive corrections, or social feedback - may play a more integral role in shaping word meaning than previously acknowledged. In other words, our findings raise the possibility that learning word meanings through positive evidence alone, while possible, may not be the most accurate characterization of the word learning process. This work opens up new avenues for further investigation into how various forms of feedback interact to support word learning across development.

## Funding disclosures

This research was supported by the European Research Council (ThoughtOrigins: 101161107), and the Agence Nationale de la Recherche (ANR-20-CE28-0005) awarded to I. Dautriche and the Institute for Language, Communication and the Brain (ILCB) through the Agence Nationale de la Recherche (ANR-16-CONV-0002). It has also received financial support from the CNRS through the MITI interdisciplinary programs, and from Sciences Po – Université Paris Cité (Fonds Investissement d'Avenir) awarded to A. de Carvalho.

## CRediT authorship contribution statement

**Alex de Carvalho:** Conceptualization, Methodology, Validation, Resources, Data curation, Writing – original draft, Writing – review & editing, Visualization, Supervision, Funding acquisition. **Isabelle Dautriche:** Conceptualization, Methodology, Software, Validation, Formal

analysis, Investigation, Resources, Data curation, Writing – original draft, Writing – review & editing, Visualization, Supervision, Project administration, Funding acquisition.

## Declaration of Competing Interest

The authors declare that there are no conflicts of interest with resect to the authorship or the publication of this article.

## Acknowledgements

We thank Rachel Kindellan and Rebekah Oakley for data collection and the actress and voice of our stimuli, Emma Healey. We also thank all the families who participated in our studies.

## Data availability

Data from all participants of each study can be found in our OSF folder called "data", via the following link (see Files section): https://osf.io/q5d3t/

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