Second language learning at school enhances Theory of Mind skills

doi:10.21203/rs.3.rs-2068113/v1

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Second language learning at school enhances Theory of Mind skills

https://doi.org/10.21203/rs.3.rs-2068113/v1

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Early learning of a second language at home has been found to be beneficial for children’s cognitive development, including their ability to ascribe mental states to others, also called Theory of Mind. We investigated whether later second language learning in an educational setting can accelerate children’s Theory of Mind development and whether the amount of exposure to second language education makes a difference. We tested three groups of monolingual four-five year old children with varying language exposure at the beginning of their first year at primary school and 24 weeks later. Children attending bilingual schools and children with weekly short second language lessons exhibited very similar accelerated Theory of Mind development compared to children without any second language provision. Theory of Mind advances were not related to other cognitive advances. Thus, limited foreign language teaching can boost young children’s social cognitive development, providing an enhanced basis for their social competence development.

Learning more than one language from a very young age has been found to be beneficial to both individuals and society, including higher academic achievements, greater communicative and intercultural competence, higher salaries, as well as raised employability (see overview in Murphy et al., 2020). Some of these benefits might be driven by advantages in cognitive and social abilities, which have been found for children growing up with an additional language spoken at home (referred to herein as native bilingualism). Most studies in this field have focused on bilingual children’s accelerated development of executive functions (EFs) such as inhibition, working memory and cognitive flexibility skills (review in Barac, Bialystok, Castro, & Sanchez, 2014). However, a bilingual advantage in EF has not always been found (e.g., Abutalebi, Canini, Della Rosa, Green, & Weekes, 2015; Dunabeitia et al., 2014; Lowe, Cho, Goldsmith, & Morton, 2021), and if it does exist, it is questionable whether it leads to real-world advantages (Poarch & Krott, 2019). A second potential source of the bilingual advantage is in the ability to ascribe mental states such as knowledge, beliefs and intentions to other people and to distinguish other people’s mental states from one’s own. There is evidence that these “theory of mind” abilities are advanced in bilinguals (reviews in Barac et al., 2014; Díaz, 2022; Schroeder, 2018). Native bilingual children have been found to show a precocious ToM development from infancy into early school years and therefore during the most important years of ToM development. They outperform their monolingual peers in various types of ToM tasks such as false belief tests, visual perspective taking tasks, and socio-communicative perspective taking tasks (reviews in Barac et al., 2014; Díaz, 2022; Schroeder, 2018). Importantly, ToM is a foundational component of social competence (Devine, White, Ensor, & Hughes, 2016), that is the skill of building and maintaining relationships with others. Support for the development of ToM skills therefore provides a mechanism by which bilingualism could be beneficial for social development.

The present study focuses on advantages in socio-communicative perspective taking. Native bilingual children have been shown to be more sensitive than monolingual children to the needs and wishes of communication partners. They adjust their helping behaviour (Gampe, Wermelinger, & Daum, 2019), they are better at using referential cues of a speaker during word learning (Yow & Markman, 2011) and are superior at integrating multiple cues in order to understand a speaker’s referential intent (Yow & Markman, 2014). Furthermore, they are more sensitive to the knowledge of a communication partner when following the partner’s instructions and requests (Fan, Liberman, Keysar, & Kinzler, 2015; Liberman, Woodward, Keysar, & Kinzler, 2017). The latter has been shown with the means of the director task (Keysar, Barr, Balin, & Brauner, 2000). In this task, a participant and a director are seated at opposite sides of a grid in which various objects are placed. The director asks the participant to move some of the objects. Because some of the grid’s compartments are blocked off from the director’s view, the participant must take the director’s view into account to identify the correct referent objects. Native bilingual children have been found to be more successful in doing so than their monolingual counterparts (Fan et al., 2015; for adults see Navarro & Conway, 2021). Even children who grow up being exposed to a multilingual environment from early on, but without speaking a second language (L2), exhibit advanced performance.

What is not known is whether learning an L2 in an education setting can accelerate ToM development. This is important both practically and scientifically. Practically, any beneficial effects of L2 exposure in an educational setting are potentially deliverable to all, irrespective of family background. Scientifically, variation in educational systems provides unique opportunities to test the effects of different levels of exposure to L2, which is also informative for the viability of any practical change in educational practices. The present study asked whether L2 learning in an educational setting can accelerate children’s ToM development and whether the amount of exposure to L2 education in two different schooling systems makes a difference.

Most studies on cognitive and socio-cognitive advantages in bilingual children have focused on children who have acquired both languages at home or who have been immersed into an L2 at preschool or school. Both full immersion into an L2 and partial immersion into a bilingual school has been found to lead to improved EF performance in terms of working memory (Gillet, Barbu, & Poncelet, 2020; Hansen et al., 2016; Purić, Vuksanović, & Chondrogianni, 2017), cognitive flexibility (Carlson & Meltzoff, 2008; Christoffels, de Haan, Steenbergen, van den Wildenberg, & Colzato, 2015; Kalia, Daneri, & Wilbourn, 2019) as well as inhibitory and attentional control (Neveu, Crespo, Ellis Weismer, & Kaushanskaya, 2021; Nicolay & Poncelet, 2015; Yang, Yang, & Lust, 2011). Similarly, growing up with a minority language and the subsequent full immersion into the majority language at school has been found to accelerate ToM development in relation to monolingual control groups, with advanced understanding of mental representations (Berguno & Bowler, 2004) and advanced ToM (Goetz, 2003).

Studies on the effects of L2 learning in an educational setting are scarce, with very few on EF and no study on ToM development. The former are mainly intervention studies that reported improved EF skills after short-term L2 learning (Bak, Long, Vega-Mendoza, & Sorace, 2016; Janus, Lee, Moreno, & Bialystok, 2016; Rafeekh, Krishna, Kapiley, & Mishra; Sullivan, Janus, Moreno, Astheimer, & Bialystok, 2014). For instance, Bak and colleagues (2016) found that a one-week Scottish Gaelic course improved attention switching in adults compared to a passive control group. Similarly, Janus and colleagues (2016) reported that a 20-day French conversation training program increased children’s performance on a challenging condition (i.e. conjunction search condition) of a visual search task compared to a 20-day music training program. In contrast, Puric and colleagues (2017) found that low exposure to an L2 at school did not significantly improve EF skills. They compared high L2 exposure (5 hours a day) with low exposure (1.5 hours a day) at school and no exposure. After 1 year, high exposure led to a working memory advantage (but not an inhibition or cognitive flexibility advantage) compared to no exposure. The performance of the low exposure group did not significantly differ from either group.

The present study investigated whether L2 learning in an educational setting accelerates the development of ToM, more specifically, socio-communicative perspective taking of monolingual children. Furthermore, it asked whether the amount of exposure is important, that is whether the effect of minimal exposure through a weekly lesson would be comparable to high exposure through the immersion into a bilingual school. We tested children on the director task as a socio-communicative perspective taking task. In contrast to previous bilingual ToM studies, we employed a longitudinal design that assessed children at the beginning of their L2 exposure (beginning of first year of primary school) and 24 weeks later. All children were monolingual when entering school. We compared the performance of three groups: children who attended bilingual schools that taught about half the time in an L2, those who attended schools with a weekly L2 lesson (L2 learners) and those who attended schools without any L2 provision (control group). If L2 learning in an educational setting accelerates ToM, then both the bilingual school children and the L2 learners should improve their performance in the director task more strongly than the control group without an L2 provision. A comparison between the two L2 learning groups shows whether the amount of L2 educational exposure affects ToM development.

Individual differences in ToM are broadly related to variations in EF skills (see meta-analysis in Devine & Hughes, 2014) and language abilities (see meta-analysis in Milligan, Astington, & Dack, 2007). It is therefore important to examine whether learning an L2 in an educational setting might accelerate the development of ToM through the development of domain-general cognitive control or language skills. We thus measured children’s EF skills (conflict processing and cognitive flexibility) and language skills (English vocabulary) at both testing points and investigated the relationships between ToM improvement and EF / language improvement.

Participants

One-hundred-and-nine 4- to 5-year-old monolingual children in their first year at an English primary school took part in the experiment. Of those, children who were exposed to an L2 at home (n = 6), were reluctant to complete more than one task (n = 2) or had moved school after first testing point (n = 2) were excluded from the analysis. The final sample therefore included data from ninety-nine 4 to 5-year-olds, all monolingual before entering school. Thirty-two children attended bilingual schools (BilS), 29 received weekly L2 classes in mainstream schools (L2 learners) and 38 did not have any L2 instruction (NoL2). Children in bilingual education were recruited from two schools, one located in Oxfordshire and the other in South East London in the United Kingdom, that taught in an L2 for approximately half of the school time, but with different structures of L2 immersion. In one school, English was used as a medium of instruction for the core subjects (maths, English, and science) in the morning, while L2 (French) was used for remaining subjects (e.g., sports, arts) in the afternoon. In the other school, all subjects were taught in L2 (either French, German or Spanish) for half of the week and in English for the other half. L2 learners were recruited from 4 mainstream schools and received 30 to 60-minute L2 classes once a week (either French, German or Spanish), led by an L2 specialist teacher. The NoL2 control group was recruited from two mainstream schools with no L2 provision.

Information on family language background, parents’ education and employment, annual family income, children’s age and extracurricular activities was collected through a parental questionnaire (for details see Table 1 and description below). All parents reported that both they and their children were born and brought up in the United Kingdom or in an English-speaking country, that English was the only language spoken at home and that the children had no exposure to any other language than English at home. All children had resided in the United Kingdom since birth except for twins in the BilS group who had lived in Singapore between the ages of 5 weeks and 15 months. At the beginning of the study, the three participant groups were matched on SES, F(2,95) = 1.0, p = 0.389, number of hours of extra-curricular activities per week, Kruskal-Wallis χ2(2) = 4.0, p = .135, number of hours of computer usage per week, Kruskal-Wallis χ2(2) = 1.3, p = .511, total number of siblings, Kruskal-Wallis χ2(2) = 1.0, p = .600, number of older siblings, Kruskal-Wallis χ2(2) = 2.1, p = .354, and non-verbal general IQ (Raven’s Coloured Progressive Matrices; Raven et al., 1998), F(2,96) = .2, p = .790. However, the groups differed in age, F(2,96) = 7.2, p = .001, ηp2 = .131 (see participant characteristics in Table 1). NoL2 children were significantly older than BilS children (p =.001) and tended to be older than L2 learners (p = .063). Given the group differences in age, we checked whether any of our measures of interest correlated with age. This was only the case for the performance improvement of cognitive flexibility, measured by the Dimensional Change Card Sort test (DCCS) (Pearson r(99) = -.252, p = .012; all other ps > 0.05). Thus, while no group differences could be explained by age differences, we took age into account when investigating improvements on the DCCS.

Design and Procedures

Parents provided consent for the participation of their children in the study. They also filled in a background information questionnaire before the start of the study. Children took part in a battery of tests: a child-adapted version of the director Task (Keysar et al., 2000) as a measure of socio-communicative perspective taking, the Coloured Progressive Matrices (Raven et al., 1998) as measure of general IQ, the British Pictures Vocabulary Scale III (BPVS; Dunn et al., 2009) as a measure of schools’ teaching effectiveness, and the Attention Network Test for children (ANT; Rueda et al., 2004) and the Dimensional Change Card Sort test (DCCS; Zelazo, 2006) as measures of EF. We chose the ANT and the DCCS as two very common tasks measuring inhibition/attention and cognitive flexibility respectively. Both have been found to be related to ToM in general and in bilingual children in particular (Buac & Kaushanskaya, 2020; Devine & Hughes, 2014). Tests were administered in the first months of the school year, when all children had minimal or no exposure to an L2. The tests were repeated after 24 weeks. Both times, children were tested over three testing sessions, taking place on different days over the course of 2 weeks. In the first session (30 minutes) participants completed Raven’s Matrices, followed by a divergent thinking task (results for this task are unrelated to the present research question and are not reported) and the DCCS. In the second testing session (30 minutes), they completed the ANT and the BPVS. In the final session, they took part in the director Task (15 minutes).

Measures

Background Information Questionnaire (Luk & Bialystok's, 2013). A modified version of Luk and Bialystok's (2013) Language and Social Background Questionnaire provided information on participants’ characteristics such as gender, date of birth, extra-school activities (type and amount of hours per week), computer and video game usage (amount of hours per week), number of older and younger siblings, maternal and paternal country of birth and upbringing, maternal and paternal level of education, maternal and paternal employment status and occupation, annual family income, participant’s place of birth and previous residence in non-English speaking countries, languages spoken by participant and daily exposure to other languages besides English at home. Parents were also asked to describe their child’s language status by choosing from four options: monolingual, exposed to different languages, bilingual or multilingual. Only children who were described as monolingual and had no exposure to other languages besides English at home were accepted in the study.

We obtained a socio-economic status (SES) index for each child by averaging indices of parental education, occupational status and annual income. The latter were calculated as follows. Level of education for each parent was measured on a 6-point scale, with 1 being ‘no formal educational qualification’ and 6 ‘masters/Doctoral degree, National Vocational Qualification level 5, or equivalent’. Occupational status for each parent was classified according to the Standard Occupational Classification Hierarchy redacted by the Office for National Statistic. Indices for education and occupational status were obtained by averaging the scores of both parents (if applicable). Finally, annual family income was measured on a 7-point scale, with 1 being ‘less than £15,000’ and 7 ‘£65,000 or more’. All three indices were converted onto a 0-1 scale before being averaged for the SES index.

Director Task (Keysar et al., 2000). The ability of taking the interlocutor’s perspective during a conversation was assessed through the director task, a widely-used test of perspective-taking during communication. Our procedure was adopted from Fan, Liberman, Keysar, and Kinzler (2015). Children followed the instructions given by a director and moved objects around a 4 x 4 array of boxes (see example configuration in Figure 1). An adult assistant played the part of the director, while the experimenter took note of the child’s behaviour. Assistant and child were seated on opposite sides of the array, facing each other, and the experimenter sat beside the child. On the director’s side, 4 boxes were blocked by slats, thus creating a limited view of the objects on the grid. Eight objects were placed on the grid, 3 of which in the slatted boxes. To familiarise the children with the task and the differences in visibility of the objects depending on the view, children first played the part of the director, while the assistant responded to their instructions. The experimenter said: “We are playing a game with this grid. I put some objects on the grid, but from this side we cannot see all the objects that are on the grid. She/He [the assistant] can see everything that is on the grid, but we cannot see everything because some objects are hidden behind these slats [pointing to the blocked boxes]”. First, you tell her/him [the assistant] to move something on the grid, then, if she/he moves the right object, we will swap places and she/he will tell you what to move”. Then, the experimenter suggested the first instruction to the child: “Can you see two cups? One big and one small? Tell her/him to put the big cup next to the green frog”. After the child had repeated the instruction, the assistant moved a bigger cup which was in a blocked box, deliberately making a mistake. At this point, the experimenter, with a tone of confused surprised, would ask the child: “Oh! Did she move the right cup?” If the child did not acknowledge the mistake, then the experimenter said “Yes, that’s a big cup but we could not see that big cup from our side!” and explained the error. Afterwards the experimenter said to the assistant: “Let’s try again! Remember that from this side we cannot see everything that you can see”. A second critical instruction was presented, and this time the assistant selected the target object. The child was then shown the grid from the assistant’s privileged point of view and made aware that the correct object had been selected despite the presence of a referential alternative (the same object in a different size) in one of the blocked boxes.

The two familiarisation trials were followed by 12 experimental trials, with the adult assistant taking over the role of the director and the child responding to the instructions. Thus, for the experimental trials, the child participant and the adult assistant swapped places so that the child had the full view of all objects, while the assistant had a limited view (see Figure 1). The trials were presented in 4 different displays. For each display, three instructions were given, one of which was critical due to the presence of a distractor object in the privileged ground. To reduce learning effects, the grid was rotated 90° anti-clockwise after each set of instructions so that the covered slots changed their position in the grid. During the instructions, the director kept his/her gaze towards the centre of the grid, in order to not give away which object needs to be moved. One point was awarded for each correct selection in critical trials, with a maximum score of 4 points. Scores were calculated on children’s first responses, ignoring any repairs. At the second testing point of the study, all objects were replaced with new ones, but the presentation order of critical instructions was kept the same as at the first testing point.

Coloured Progressive Matrices (Raven et al., 1998). This is a commonly used measure of non-verbal reasoning. Children were presented with 36 incomplete figural patterns (sets A, B and AB) and were asked to select the missing part of each pattern from a choice of six options. For each correct answer one point was awarded, with a maximum score of 36. Stimuli were presented on a laptop via E-prime (E-Studio 2.0). Children pointed to the chosen option. The experimenter entered the choice by pressing corresponding buttons on the keyboard.

The British Pictures Vocabulary Scale III (BPVS; Dunn et al., 2009). This is a standardised measure of receptive vocabulary. Children are shown tables of 4 pictures and asked to point to the picture that match a word produced by the experimenter. Tables are grouped in 14 sets of 12 items. Following the guidelines of the test, children worked through the tables until they made 8 or more incorrect selections within a set. A score was calculated by subtracting the total number of errors from the number of tables presented.

Attention Network Test for children (Rueda et al., 2004). We measured inhibition ability with a widely-used child-friendly flanker task, the Attention Network Test for children (ANT), implementing the version by Rueda et al. (2004). Participants “fed” a hungry fish by pressing a left or right button according to the orientation of the fish. In neutral trials, a single yellow fish faced left or right, while in congruent and incongruent trials the target fish appeared in the middle of a row of five identical fish. The four flanking fish either faced the same direction as the target fish (congruent trials) or the opposite direction (incongruent trials). All trials started with a fixation cross for 400 ms in the middle of a laptop screen, followed by a warning cue (an asterisk) for 150 ms and a stimulus for 450 ms. Attentional cues appeared in the centre, above or below the position of the fixation cross. Stimuli appeared above or below the position of the fixation cross. Stimuli were displayed till the child responded, with a maximum duration period of 1700 ms. Correct responses received a visual and auditory feedback as the target fish moved its mouth making bubbles and a “wohoo” sound was played. Incorrect or late responses were followed by auditory feedback only, namely a ‘wrong buzzer’ sound. Stimuli were presented on a laptop via E-prime (E-Studio 2.0). Responses were recorded using a Cedrus RB-844 response pad with a right button showing a picture of the target fish oriented to the right and a left button showing the target fish oriented to the left.

The experimenter introduced the task to the children following the procedure described in Rueda et al. (2004). They placed a laminated card with a right-facing target fish above the buttons. Children were told that the fish was very hungry, and their task was to feed him by pressing one of the two buttons. Pointing first to the card and to the right button, the experimenter said: “Sometimes the fish is facing this way. In this case, you need to press this button”. Then, presenting a card with a target fish facing left and, pointing to the left button, the experimenter continued “but sometimes the fish is facing the other way. So, which button do you need to press if he is facing the other way?”. The correct answer was suggested if the child showed hesitation. Afterwards, the experimenter presented a card with a row of five fish all facing left and, pointing to the central one, said: “Sometimes the fish is not alone on the screen, he is with other fish, but you need to look at him in the middle. Which button do you press to feed him?” and, showing the right-oriented row of fish, “which button do you press if he is facing the other way?”. Finally, the experimenter presented a card showing one of the two incongruent flankers and, pointing to the target fish, said: “I told you that you always have to look at the fish in the middle and not at the others because sometimes the other fish are tricky. They want to trick you and they go in the opposite direction. But you need to feed the fish in the middle and not the others, so which button do you press for the fish in the middle?” and, showing the other flanker stimuli card, continued “and which button do you press for this other one?”. Correct responses were demonstrated, and further explanation were given in case of incorrect answers. Children were told that there would be a small cross in the middle of the screen and that they had to keep their eyes on the cross as the target fish would appear above or underneath it. The presence of different cue types trials was not mentioned. Children were encouraged to keep their right pointer finger on the right button and their left pointer finger on the left button before starting the task and told to press the relevant button as quickly as possible when the fish appeared on the screen.

There were 24 practice trials followed by two blocks of 48 trials, consisting of an equal number of trials in each condition and an equal number of trials with the target fish facing left or right, presented in random order. Accuracy and reaction times (RTs) were recorded. Omissions of response were recorded as errors. Since bilingualism has been associated with advanced inhibition skills in this task (Mezzacappa, 2004; Yang et al., 2011; Yoshida, Tran, Benitez, & Kuwabara, 2011), we focussed for the analysis on the conflict index, calculated by subtracting children’s performance in congruent trials (where no conflicting stimuli had to be resolved) from their performance in incongruent trials (where target fish and flankers were in competition). Results for orienting and altering indices can be found in the Supplementary Material. We calculated a conflict index by adding standardised accuracy scores and standardised reversed RTs, so that higher values corresponded to better performance.

Dimensional Change Card Sort (DCCS; Zelazo, 2006). As a second EF measure, we administered both the standard and the advanced versions of a widely-used measure of children’s cognitive flexibility, the DCCS (Zelazo, 2006), summing the scores of the two versions for a composite score. In both versions, children were asked to sort cards according to colour or shape of the depicted objects. At both testing points, the same procedure was followed, but the objects and colours differed (first testing point: red rabbit and blue boat; second testing point: yellow flower and blue car).

In the standard version, children were first asked to sort cards by one dimension (colour) and halfway through by another dimension (shape). Two practice and 12 testing cards (7 x 11 cm) were used. At the first testing point, half of the cards showed a red rabbit and the other half a blue boat. Cards needed to be sorted into two open transparent containers (16.8 x 11.6 x 4.5 cm). A target card was attached at the back of each container, clearly visible to the child. Target cards showed a blue rabbit and a red boat so that cards to sort were never identical to the target cards. The experimenter told children that they were going to play some games with the cards. The experimenter said: “The first game is called the colour game. In the colour game, you need to sort the cards by colour, so all the red cards go here [pointing to the container featuring the red target card] and all the blue cards go here [pointing to the container featuring the blue target card]”. Then, the experimenter showed the red rabbit practice card and said: “Here’s a red card. Where does it go?” Children were asked first to point to the correct container and then to place the card face down into it. The same was repeated with the blue boat practice card. Correct responses were demonstrated if the child made mistakes. After the two practice trials, there were six pre-switch trials presenting three red rabbit cards and three blue boat cards in pseudorandom order. No feedback was given. After the child completed the 6 pre-switch trials, the experimenter said: “Now we are changing game, we are playing another game called picture game. In the picture game, you need to sort cards by picture, so all the rabbits go here [pointing to the container with the target rabbit card] and all the boats go here [pointing to the container with the boat target card]. Here’s a rabbit, where does it go?”. The card was handed to the child who put it face down in one of the containers, no feedback was given. There were 6 post-switch trials with 3 red rabbit cards and 3 blue boat cards in pseudorandom order. Both in pre- and post-switch trials the card was presented mentioning the relevant feature (“Here’s a red/blue card” for pre-switch, “Here’s a rabbit/boat card” for post-switch) and handed to the child who put the card face down into one of the containers. One point was given for each card sorted correctly, with a maximum score of 12 points.

Immediately after the child completed the standard version, the advanced version was administered. In this version, the sorting rule was indicated on the cards, with a rainbow for sorting by colour and black outlines of a rabbit and a boat for sorting by shape. A new set of 2 practice cards and 12 testing cards was used: 8 red rabbit cards and 6 blue boat cards. Half of the rabbit cards and half of the boat cards were colour-sorting cards, the other half were shape-sorting cards. Cards were presented in a pseudorandomised order so that in 50% the rule needed to be switched, while in the other 50% the rule stayed the same. The first two cards were used for practice.

The experimenter showed the new set of cards to the child and said: “Now we are going to play another game with this special set of cards. In this set, some cards have a rainbow and some cards have two small pictures. If the card has got a rainbow [showing a rainbow-labelled rabbit card], it’s a colour-game card and you have to play the colour game, but if the card has got two small pictures [showing an outlines-labelled rabbit card], it’s a picture-game card and you need to play the picture game”. Then, the experimenter handed the rainbow card to the child and said: “This has got a rainbow, so it’s a colour game card. Can you remember the rule for the colour game?” If the child failed to remember the rule, the experimenter said: “In the colour game, red cards go here and blue cards go here [pointing to the corresponding target cards]. This is a colour game card, where does it go?” If the child placed the card in the wrong container, the mistake was corrected, and the rule reminded again. The same procedure was repeated with a picture-game rabbit card. The two practice trials were followed by 12 trials presenting 3 picture-game rabbit cards, 3 colour-game rabbit cards, 3 picture-game boat cards and 3 colour-game boat cards in a pseudo-random order. In all trials the card was presented hinting at the relevant rule (“Here’s a colour-game/picture-game card”). For each card sorted correctly 1 point was rewarded, with a maximum score of 12 points. The maximum total score for both standard and advanced version was 24 points. Scores were calculated on children’s first sorting responses, ignoring any corrections.

Figure 2 shows the results of the director task. An ANOVA with the factors Time (T1 vs T2) and Group (BilS, L2, No-L2) revealed no effect of Group, F(2, 96) = 2.1, p = .126, , ηp2 = .042, but an effect of Time, F(1, 96) = 67.2, p < .001, ηp2 = .412, and a Time x Group interaction, F(2, 96) = 14.9, p < .001; ηp2 = .237. There were no differences between groups at T1, F(2, 96) = 1.3, p = .293, but at T2, Welch F (2, 62.92) = 7.1, p = .002. Games-Howell post-hoc tests for T2 showed higher perspective taking scores for BilS children (p = .001) and L2 learners (p = .013) than NoL2 children, while scores for BilS children and L2 learners did not differ (p = .741).

To check whether children’s ToM development was related to that of their cognitive control skills or their language skills, we correlated the improvement of performance (scores at T2 – scores at T1) in the director task with that in the two EF tasks (conflict index and DCCS scores) and the BPVS (for group differences on these measures across testing points see the Supplementary Material). We removed the data from one participant in the NoL2 group who had a much lower improvement score (< 3 SD) in the director task than any other participant.

With respect to the ANT task and thus the conflict index, we noticed that some children had very high error rates. Therefore, we calculated how many correct trials were needed for a participant to score statistically above chance in the ANT (i.e., 50% correct responses). Making 57 correct responses out of 96 total responses has a one-tailed probability of 0.041 by binomial test. Thus, we included in the analysis only children who made at least 57 correct responses (60% accuracy) at T1. This led to a final sample for the ANT of 76 children (26 BilSs, 24 WL2s and 26 NoL2s). Before analysing Response Times (RT), we removed RTs faster than 200 ms (anticipatory responses) and slower than 2.5 standard deviations (SD) above the mean of each participant, which amounted to 19.5% of trials being excluded. RTs of incorrect responses were not considered in the analyses. Response omissions were recorded as errors.

Taking all groups together, there was no significant relationship for performance improvement in the director task and the conflict index, Pearson r(76) = .04, p = .719. Similarly, a partial correlation between performance improvement in the director task and the DCCS, controlling for age, showed no relationship either, Pearson r(95) = .16, p = .116. Separate analyses for the three participant groups confirmed these results. There were no correlations between performance improvement in the director task and the conflict index, BiLS: Pearson r(26) = .12, p = .574, L2: Pearson r(24) = .09, p = .681, NoL2: Pearson r(26) = -.02, p = .920. Also, partial correlations between performance improvement in the director task and the DCCS, controlling for age, showed no relationships either, BilS: Pearson r(29) = -.10, p = .601, L2: Pearson r(26) = .17, p = .402, NoL2: Pearson r(34) = .068, p = .694. Finally, we found no significant relationship between performance improvement in the director task and in the BPVS, Pearson r(98) = .06, p = .585. Separate analyses for the three participant groups again confirmed this finding, BiLS: Pearson r(32) = -.06, p = .764, L2: Pearson r(29) = .22, p = .260, NoL2: Pearson r(37) = -.20, p = .243.

We found that L2 learning in an educational setting accelerated development of socio-communicative perspective taking in monolingual children. While at the beginning of the first year at primary school, all groups of children performed similarly on the director task, after 24 weeks in their school environments L2 learners and children attending bilingual schools showed significantly greater improvement than children without L2 provision. L2 learners were exposed to weekly lessons of 30 minutes to 1 hour, while children attending bilingual schools were immersed in an L2 for half of their school time. Our findings of similar improvement on the director task in these two groups therefore suggest that socio-communicative perspective taking can be boosted effectively through moderate levels of L2 education and high exposure to an L2 is not necessary to reach the same effect.

The lack of ToM performance difference between the two language learning groups is congruent with the finding by Fan et al. (2015) that children merely growing up in a multilingual environment from very early on without speaking the L2 themselves performed comparably to children growing up as native bilinguals in the director task. But our results stand somewhat in contrast to Cheung et al.’s (2010) finding that a full immersion into an L2 preschool led to higher ToM performance (on false belief tasks; Wimmer & Perner, 1983) compared to teaching 5 hours of L2 lessons per week. Cheung et al’s study differed from the present study in its use of a different ToM task, higher L2 exposure, and a younger age group. We think it is unlikely that the choice of ToM task (false belief tasks in Cheung et al; director task in the present study) accounts for our different findings, since both are age-appropriate ways of assessing ToM. The L2 children in Cheung et al. (2010) had twice as much L2 time per day (full vs half day) for twice as long (12 vs 6 months) compared with our BiL group. While this might account for differences in our results, the present finding that the benefit to ToM did not vary depending on level of L2 exposure suggests that this might not be the critical factor. However, since ToM abilities change rapidly in early childhood (e.g., Apperly, 2011; Wellman 2014), it is possible that the amount of L2 exposure has different effects at different ages, and so the younger sample in Cheung et al. (~48 months) benefited in a different way from the older sample in the present study (~58 months). These questions require further research.

The acceleration of ToM development in children attending bilingual schools compared to the monolingual control group contrasts with a finding by Buac and Kauschkanskaya (2020) who reported no difference in false-belief reasoning between monolingual children and children immersed into a bilingual school (they use the term ‘dual-immersion’ school). The children in their study were markedly older (90 months) than the children in the present study (~58 months). Thus, again, the studies differ in terms of both task and age group and further research is needed to investigate the reasons for the different findings.

It has been argued that bilingual children’s enhanced ToM is caused by them growing up in and navigating sociolinguistic environments with speakers who differ in linguistic knowledge and mental states (see review in Díaz, 2022). It needs to be considered that bilingual environments are generally confounded with multicultural environments. This is important as ToM development is not only affected by differences in linguistic experiences, but also by differences in cultural experiences, which can influence the timing and order of ToM development (Wellman, Cross, & Watson, 2001; Wellman, Fang, Liu, Zhu, & Liu, 2006). Furthermore, growing up in environments with two systems of cultural traditions and beliefs, including sociocultural behaviour, provides not only experience with different languages, but also with two systems of non-verbal behaviour, knowledge and mental states. Furthermore, in many cases, growing up in a bilingual environment also means growing up in a societal minority group. In such cases, there is a social pressure to integrate into the majority society and children need to be particularly sensitive to the beliefs and behaviours of the majority culture. This situation might particularly train their ToM skills. In our study, children with weekly L2 lessons did not live in a multicultural environment and did not train their ToM due to their minority background. They thus learned an L2 without navigating complex sociolinguistic environments. Our results therefore support the stance that it is the L2 learning that improves ToM, including the experience that the L2 teacher had different knowledge (e.g., L2 names for objects) and therefore different mental states than they themselves. This resonances with the suggestion that bilingual superior ToM is related to heightened sociolinguistic awareness, which is likely caused by experiences with environments of individuals with differing linguistic knowledge (Díaz, 2022). Alternatively, the advantage might not be grounded in sociolinguistic experiences, but might stem from the experience of linking two different verbal labels to the same objects and therefore linking two representations (or ‘mental files’) of the same objects (Doherty & Perner, 2020). These representations capture different perspectives and therefore provide children with the experience of differing mental representations for the same referents.

The results in perspective taking in our study could in principle be due to differences in the effectiveness of teaching by the different types of schools. This is, however, unlikely the case for two reasons. First, children in each group were recruited from at least two schools, meaning that teaching will have varied among schools of each type. Second, if we allow that vocabulary development of the children’s native language can serve as an indication of teaching effectiveness, it is notable that it showed a different pattern of results than that for perspective taking (see Supplementary material). All groups started off with comparable English vocabulary scores at the beginning of the school year. After 24 weeks, bilingual school children showed an accelerated vocabulary development compared to the other two groups, who did not differ from each other. If anything, the teaching methods of bilingual schools, but not of schools with weekly L2 provisions, were more effective in promoting native vocabulary development. Thus, it is unlikely that the acceleration of ToM development in both bilingual and weekly L2 schools was due to higher teaching effectiveness. The results are line with our conclusion that it is the L2 education that boosted ToM development.

Furthermore, we investigated whether any ToM development would be related to broader developments in EF or language. But performance improvement in the director task across the two testing points did not correlate with children’s improvement in conflict/attentional control, measured by the conflict index of the ANT, improvement in cognitive flexibility, measured by the DCCS, or language development, measured by the BPVS. This was the case both when taking all participants groups together and when examining the groups separately. Previous research provides somewhat mixed evidence on the existence of relations between ToM, language and EF in bilingual children (Buac & Kaushanskaya, 2020; Dahlgren, Almén, & Dahlgren Sandberg, 2017; Diaz & Farrar, 2018a, 2018b; Fan et al., 2015; Liberman et al., 2017; Nguyen & Astington, 2014). The present findings suggest that accelerated development of ToM through L2 learning was independent of EF or language development and was not caused by accelerated progression of EF or language abilities. These results partly dovetail with previous findings that EF skills are not related with ToM skills for native bilingual children (Buac & Kaushanskaya, 2020; Dahlgren et al., 2017; Diaz & Farrar, 2018a, 2018b; Fan et al., 2015; Liberman et al., 2017). Taking current evidence together, neither native bilingualism nor formal L2 education seems to accelerate children’s ToM development through EF advancement. Our result that language ability development was not related for ToM development is in line with the report that language ability did not correlate with false-belief reasoning in children enrolled in a dual-language immersion programme (Buac & Kaushanskaya, 2020). In contrast, language ability has been found to correlate with false-belief reasoning in native bilingual children (Buac & Kaushanskaya, 2020; Diaz & Farrar, 2018a), even though it does not seem to predict false-believe reasoning in native bilingual children longitudinally (Diaz & Farrar, 2018b). Together with our finding that the amount of L2 learning did not make a difference in ToM performance, it therefore appears that language ability is not important for the acceleration of ToM development in children learning an additional language.

The results of the present study have potential societal implications. As indicated, ToM is a foundation for social competence. For instance, ToM of six-year-olds predicts teacher ratings of social skills at age ten (Devine et al., 2016). In relation to this, it is interesting that children from a minority language background (thus native bilinguals) are rated higher by teachers and observers on measures of interpersonal skills, compared with monolingual children who speak the majority language (Halle et al., 2014). This might be due to their superior ToM skills. If language learning in an education setting indeed fosters social competence, then language learning could have long-lasting effects on children’s lives. For example, for school-aged children, good social competence predicts future mental health, academic outcomes, and success in the workplace (Bornstein, Hahn, & Haynes, 2010; Burt, Obradović, Long, & Masten, 2008). On a societal level, language learning might even lead to a society with less xenophobia and aggression against minorities. It has been found that individuals with superior perspective taking skills more easily suppress automatic expressions of racial bias (Todd, Bodenhausen, Richeson, & Galinsky, 2011) and perspective taking is related to civic identity (Johnson, 2015). Developing social skills through L2 learning is therefore a potential tool to cultivate a civic identity in children and to build a functioning diverse society. Furthermore, L2 learning at school was effective even at a low dose, meaning that benefits are achievable without major modifications to the standard school curriculum.

To conclude, our study showed that learning a second language in early childhood in a formal educational setting enhances ToM in terms of social-communicative perspective taking. A high amount of L2 exposure does not seem to be necessary for such a boost to occur because short weekly lessons led to the same acceleration as attendance at a bilingual school. While it is not yet clear how exactly L2 learning accelerates ToM in children, the present results present an argument for early language teaching in schools. Future studies will need to explore any long-term effects of early second language provisions, especially on social competence development and general academic achievements.

Data deposition

All data and materials for the experiment are available at the open science framework at https://osf.io/s9ghz/?view_only=d3d0bdf8a5a443a581d78b4ff51e746b

Ethics

The study was conducted in accordance with the British Psychological Society ethical guidelines and approved by the University of Birmingham’s STEM Ethics committee ERN_17-0324

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Table 1. Participant characteristics by group.

	BilS (n=32)	L2 learners (n=29)	NoL2 (n=38)
M age in months¹(range)	56.0 (50-62)	57.2 (51-64)	59.5 (53-65)
Gender (f/m)	11/21	15/14	21/17
Maternal background UK²	96.9%	96.5%	100%
Paternal background UK³	93.8%	100%	100%
M SES (0-1) (SD)	.78 (.19)	.71 (.21)	.76 (.16)
M hours of extra-curricular activities/week (SD)	1.2 (.3)	1.6 (.2)	1.4 (.2)
M hours of computer usage/week (SD)	2.2 (.5)	2.4 (.4)	2.6 (.6)
Mdn number of siblings (IQR)	1.0 (1 - 2)	1.0 (1 - 2)	1.0 (1-1.25)
Mdn number of older siblings (IQR)	.5 (0 -.5)	1.0 (1 -1.5)	1.0 (0-1)
M IQ (Raven’s)	15.4 (3.3)	14.8 (3.7)	15.1 (3.6)

Note.

1. Children only differed in age, with NoL2 children being significantly older than BilS children and marginally older than L2 learners (for statistics, see text).

2. Non-U.K. places of birth for mothers were USA (n=1) in the BilS group and Ireland (n =1) in the WL2 group.

3.Non-U.K. places of birth for fathers were New Zealand (n=1) and South Africa (n=1) in the BilS group.

There is NO Competing Interest.

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Second language learning at school enhances Theory of Mind skills

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