Bridging Social Learning with Technology: The Use of a Social Robot in Preschool Development

1. Introduction

Childhood is a crucial period for developing the ability to adhere to social norms and values, adapt to cultural expectations, and actively navigate future societies. Social deficits during this time can lead to ongoing social challenges and have long-term impacts throughout life, making it essential to utilize various educational tools to promote social skills. Acquiring sociability requires children to engage in ample social interactions with parents, siblings, and peers. However, opportunities for direct social activities are gradually diminishing due to changes in family structures and societal environments.

The weakening of social bonds, particularly exacerbated by the COVID-19 pandemic, has further reduced face-to-face interactions, resulting in increased mental health issues among children, such as anxiety, despair, and aggression (Colizzi et al., 2020; Duan et al., 2020; Yeasmin et al., 2020). Consequently, children require timely and appropriate interventions, and in this regard, social robots have emerged as a promising tool for fostering social and emotional development, especially as children have become increasingly accustomed to digital interactions following the pandemic. Beginning in August 2021, the Seoul Metropolitan Government launched a pilot project to introduce social robots in daycare centers to support the language and emotional development of preschoolers who have experienced limited social engagement due to COVID-19. Previous studies highlight the positive impact of social robots on children’s social and emotional development (Diehl et al., 2012; Freitas et al., 2017; Rakhymbayeva et al., 2021). This study aims to evaluate the effectiveness of social robots for preschoolers with varying levels of sociability-high, middle, and low-and to assess the satisfaction of both children and their parents with these interventions.

This study includes several key phases. It begins with a comprehensive literature review on the social development of preschoolers, the role of play and conversation in fostering social skills, and previous studies on the use of social robots for children, both with and without autism spectrum disorder (ASD). The empirical component of the study involves the creation and validation of play and conversation scenarios for the social robot, Pibo, followed by a four-day experiment involving 50 families of preschoolers aged 4-6 years with different sociability levels. Two pediatric psychologists and a child development center teacher provide qualitative evaluations of the intervention’s effectiveness and recommend areas for improvement, while quantitative data on the satisfaction levels of children and their parents in each sociability group are also collected and analyzed.

2. Literature Review

3. Research Questions

Previous studies have indicated that social robots are beneficial for children’s social and emotional development. However, most of these studies have been limited to single-session experiments with small participant groups in laboratory settings, often focusing exclusively on either typically developing children or children with ASD. This study seeks to explore the potential of social robots for enhancing the social development of preschoolers by conducting a four-day experiment in the homes of 50 children with varying levels of sociability.

Given that social development is a prolonged process, direct evaluation after just four days of activities is challenging. To address this, experts will qualitatively analyze interaction data to assess the potential of social robots as a tool for fostering social development in preschoolers with varying levels of sociability.

Research Question 1

Can social robots be effectively used to support the social development of preschoolers?

Furthermore, does their effectiveness vary based on children’s sociability differences?

Additionally, for social robots to be a viable tool for social development, both children and their parents must find the activities engaging and satisfactory. If satisfaction levels are low, it would be challenging to maintain long-term engagement and achieve meaningful developmental outcomes. Previous research has shown that children with ASD often experience a strong sense of psychological comfort when interacting with social robots. This study will quantitatively examine how variations in children’s sociability influence the satisfaction levels of both children and parents with social robot activities.

Research Question 2

Do the satisfaction levels of children and parents with social robot activities differ based on the sociability of the children?

4. Method

4. 2. Verification of scenarios

4. 2. 1. Expert verification of scenarios

In-depth interviews were conducted with two pediatric psychiatrists and a pediatrician experienced in clinical trials involving social robots, from December 22, 2020, to January 7, 2021. The experts were asked to review a video showcasing a total of eight scenarios, with one scenario from each of the four play categories and one from each of the four conversation categories. The play scenarios included “putting animals into the hula hoop” for communication and verbal expression, “I am the king” for sociability and emotion, “the toilet paper road” for cognition and perception/thinking, and “dancing ghost” for motor skills. The conversation scenarios included “a magical being” for role-playing, “the mosquito and the lion” for fairy tales, “I end up using bad words” for problem-solving, and “taking turns in order” for social skills. After viewing the video, the experts participated in an in-depth interview that focused on two main aspects: the appropriateness of the scenarios for supporting the social development of preschoolers and the communication suitability of the social robot. The expert profiles are provided in Table 1, while the in-depth interview questionnaire is presented in Table 2. The video used for scenario verification is shown in Figure 1.

Table 1

Expert profiles

Table 2

In-depth interview questionnaire

Figure 1

Simulation video of play and conversation scenarios

The experts concluded that the play and conversation scenarios were suitable for preschoolers and would contribute positively to their social development. They emphasized that as social development relies on interaction, it is essential for the robot to recognize children’s emotions and encourage them to understand the emotions of others by asking about the robot’s feelings. Regarding play scenarios, they suggested incorporating high-tone praise to boost children’s concentration and maintain their interest, while also ensuring that the robot’s voice tone varies according to the content of the conversation. For conversation scenarios, the experts recommended creating situations where children could express their emotions, advising the use of simple questions like “who?”, “what?”, and “how?” rather than more complex questions such as “why?”. Additionally, since preschoolers often respond with “I don’t know,” they suggested ensuring that appropriate feedback is given in these cases. To enhance the engagement of children with ASD, the experts recommended incorporating unexpected interactions to maintain their interest, such as having the robot react to specific actions or make intentional mistakes.

4. 2. 2. Verification of scenarios through observation

Five preschoolers aged 4–6 years were observed performing two play and two conversation scenarios on May 8, 2022. The observations were conducted using revised scenarios that reflected the experts’ advice. The observations aimed to verify whether the participants engaged in the play and conversation with Pibo as intended and to identify any issues that emerge during the process.The observations were based on the items outlined in Table 3, and the actual setup is depicted in Figure 2.

Table 3

Observation items

Figure 2

Observation setup

The observational study revealed that most of the children understood Pibo’s explanations and completed the activities as intended. However, younger children sometimes struggled with understanding the explanations due to the speed or unnatural tone of Pibo’s speech. They required additional support and encouragement when performing challenging activities. The children provided appropriate responses during the conversation scenarios. Active children were particularly eager to initiate conversations with Pibo and expressed their feelings in detail. They interacted with Pibo while maintaining eye contact, and, with few exceptions, avoided touching the robot. The children were fascinated by the changing colors of Pibo’s eyes and the images displayed on its screen. However, some children noticed that Pibo did not always appear to be looking directly at them during interactions.

4. 3. Examples of play and conversation scenarios

All 50 play scenarios and 70 conversation scenarios were revised by incorporating expert advice and observational findings to develop the final versions. The final versions of the play scenario example “dancing ghost” and the conversation scenario example “a magical being” are shown in Tables 4 and 5, respectively.

Table 4

Play scenario example “dancing ghost”

Table 5

Conversation scenario example “a magical being”

4. 4. Experiment

The experiment was conducted from July 20 to October 24, 2023, involving 50 households with preschoolers aged 4–6 years and their parents. This study received approval from the Institutional Review Board (IRB). Prior to the experiment, parents completed the Social Communication Questionnaire (SCQ) to assess their children’s sociability. The SCQ is a tool in which parents respond to 40 items to evaluate the communication skills and social functioning of children who may have ASD. According to the SCQ, a score of less than 10 points corresponds to typically developing children. A score between 10 and less than 15 points indicates a child who may require observation for potential ASD, while a score of 15 points or higher suggests a high likelihood of ASD. Based on their responses, the children were categorized into three groups: high sociability (0 to less than 10 points), middle sociability (10 to less than 15 points), and low sociability (15 points or more) (Berument et al., 1999).

The test was conducted in the children’s playroom or living room, both familiar and comfortable spaces for them. The parents participated in and observed all the activities alongside their children and the social robot. Parents were provided with instructions on how to install and operate Pibo, as well as guidelines for the activities, and monitored the daily progress of the experiment. To enhance the children’s engagement with the social robot, a video introducing Pibo’s appearance and functions was shown to the children before the experiment, in line with previous research suggesting that such exposure fosters a stronger personal connection (Chung, 2023). After watching the introduction video shown in Figure 3, the children engaged in 30-minute daily play and conversation sessions with Pibo over a four-day period, with all conversations between the children and Pibo recorded as text data. To support the child in interacting naturally with Pibo, no cameras were installed for video recording. Instead, Pibo recognized all conversations through voice and converted them into text. The text data were later used for analyzing the interactions between the child and the robot.

Figure 3

Introduction video of Pibo

Following each session, Pibo solicited feedback from the children regarding their satisfaction with the activities, which was quantified on a 5-point scale (5 for positive responses, 3 for neutral, and 1 for negative). After the completion of all four days, parents were asked to rate their satisfaction with the activities using a 5-point Likert scale and were encouraged to provide open-ended feedback on their child’s activities with Pibo. The experimental setup is depicted in Figure 4.

Figure 4

Experimental setup

4. 5. Data analysis

4. 5. 1. Expert evaluation

An expert evaluation of the text data between the children and Pibo was conducted from November 24 to December 3, 2023. Data preprocessing, including disfluency removal, was performed on the recorded conversation data in Pibo. The preprocessed text data from all the conversations over a four-day period between the 50 children and Pibo were delivered to the experts, and their responses to the evaluation questions were collected in writing, with additional inquiries clarified through oral communication. The experts who participated in this evaluation included the same pediatric psychiatrists who had been involved in the scenario validation, as well as a teacher specializing in children with low sociability at a psychomotricity-based child development center. The expert profiles are provided in Table 6, and the expert evaluation survey, which focused on developmental support and differences among groups, is outlined in Table 7.

Table 6

Expert profiles

Table 7

Questionnaire for expert evaluation

4. 5. 2. Quantitative and qualitative analysis

The satisfaction levels of both the children and parents with the robot activities were analyzed using an ANOVA test with SPSS Statistics 27. The interview data on the parents’ satisfaction with the experiment were analyzed using thematic analysis. First, the interview transcripts were created, and recurring concepts were open-coded through repeated examination. Subsequently, similar codes were grouped to derive key themes. After that, patterns were analyzed by including quantitative information on how frequently specific themes appeared.

5. Results

50 preschoolers who participated in the experiment were classified into three groups based on their sociability: high sociability, middle sociability, and low sociability, according to the results of their responses. Out of a maximum score of 40, the lowest score among the children who participated in the experiment was 0, and the highest score was 23. The profiles of the participants are listed in Table 8.

Table 8

Participant profiles

5. 2. Research Question 2

The difference in children’s satisfaction based on variations in sociability was analyzed. No significant differences were found in satisfaction levels among children with high sociability (M = 4.10, SD = 0.66), children with middle sociability (M = 3.85, SD = 0.52), and children with low sociability (M = 3.93, SD = 0.78). Similarly, no significant differences were observed in the satisfaction levels of parents of children with high sociability (M = 3.33, SD = 0.81), parents of children with middle sociability (M = 3.46, SD = 0.50), and parents of children with low sociability (M = 3.79, SD = 1.50). The results of the ANOVA analyses are presented in Tables 8, 9, and 10.

Table 8

Average and standard deviation of groups of children

Table 9

Test of homogeneity of variances of children’s satisfaction and parents’ satisfaction

Table 10

Anova of children’s satisfaction and parents’ satisfaction

Figure 5

Satisfaction of children with high, middle and low sociability and their parents

Parents’ opinions on the four-day activity exhibited both commonalities and differences based on the sociability level of their children. Common opinions among parents included the following:

First, 19 parents (38%) out of 50 appreciated the diversity of the play activities, noting that the level of play was appropriate for their child’s age.

“I think the content and structure of the play were very rich.”

“The level of play was appropriate for the child’s age, and the play method was interesting and easy for the child to participate in.”

Second, 13 parents (26%) out of 50 appreciated responding to the child’s answers, empathizing, or offering praise as effective ways to encourage participation.

“I was impressed by the part where the robot listened to the child’s thoughts, responded, and empathized with him. It was like a conversation between friends.”

“I liked that the robot said it was okay when the child answered that he didn’t know.”

Third, 5 parents (10%) out of 50 found that calling the child’s name helped foster a sense of intimacy between the child and the robot.

“Calling the name was the best. The child said it felt like a real friend was calling him.”

“It was good that the child’s name was continuously called during the activities.”

Fourth, 30 parents (60%) out of 50 evaluated the interaction between the child and the robot negatively, citing that it was not always smooth. Among them, 20 parents (67%) expressed dissatisfaction with the robot’s interaction due to technical issues, such as voice recognition and response speed, while 13 parents (43%) were dissatisfied with the robot’s inability to provide more natural and flexible responses to the children’s reactions.

“It is not satisfying that the interaction was not smooth. The child’s voice is not recognized properly, or the response is too slow.”

“The conversation was not smooth because only fixed answers were given.”

15 parents of children with high sociability (58%) out of 26 expressed the opinion that the playtime should have been longer and that more specific, detailed responses to the child’s answers should have been provided.

“The play activities were more diverse than expected, which was good, but the time was too short.”

“It was unfortunate that there were no detailed responses to the child’s answers, but rather stereotyped responses.”

8 parents of children with middle sociability (57%) out of 14 suggested that a more tailored, flexible approach would have been beneficial, rather than a standardized one-size-fits-all structure.

“The child became more familiar after adjusting, so the child participated in the activity better on the last day than the first day.”

“It feels like one-sided progress, which is disappointing.”

Lastly, 3 parents of children with low sociability (30%) out of 10 observed that children felt more comfortable interacting with the robot than with humans and suggested that the robot program should be adapted to the child’s developmental level.

“My child seemed interested in answering the robot and responded more actively than he did to me.”

“I was satisfied because it provided the situation and conversation that the child needed.”

“I was surprised that the child told the robot a detailed story about school that he had never told me.”

“It was difficult for my child, who could not answer right away, to follow along. It seems that a program suitable for the child’s level needs to be developed.”

6. Discussion

This study explored the interactions between preschoolers aged 4–6 years and a social robot, focusing on evaluating its effectiveness in supporting children’s social and emotional development, as well as the satisfaction of both children and their parents with social robot activities. The experiment involved a diverse sample of children with varying levels of sociability, and expert evaluations provided insights into the effectiveness and limitations of using social robots for social and emotional development in early childhood contexts.

The findings from the expert feedback revealed several key insights. First, while children generally perceived the social robot as a friendly and engaging entity, as observed in previous studies (Melson et al., 2009; Kim et al., 2018), the robot’s current limitations in two-way communication hindered the full potential of human-like interactions. Experts noted that while the children felt comfortable interacting with the robot and expressed their feelings in a seemingly appropriate manner, the robot’s inability to recognize and co-regulate emotions limited its support for deeper social and emotional development. Children benefit from feedback that is reciprocal and nuanced, as it encourages emotional co-regulation, which is a crucial component of social learning.

The study found no significant differences in satisfaction levels among children with high, medium, or low sociability, though parents noted various challenges and benefits. Children with low sociability, who often struggle with human interactions, appeared to benefit more from engaging with the robot. They were observed to express themselves more confidently and actively when interacting with the robot compared to their interactions with people. These parental responses aligned with experts’ opinions that the social robot was more effective for children with lower sociability. Conversely, children with high sociability seemed to expect more complex and meaningful exchanges, which the robot could not fully provide, leading to some dissatisfaction among these children and their parents. This suggests that, as observed in previous studies, social robots may be particularly effective in engaging children who are shy or socially avoidant but may require more advanced features to sustain the interest of highly sociable children (Dautenhahn & Billard, 2002; Scassellati, Admoni, & Mataric, 2012). Parental feedback further highlighted both the strengths and limitations of the activities. Parents appreciated features such as personalized interactions, age-appropriate play content, and the robot’s ability to listen, empathize, and offer encouragement. However, they also pointed out the need for smoother and more spontaneous interactions.

This study provides essential insights that must be considered when developing social robots for social and emotional development in early childhood contexts. These include the need for scenario differentiation based on a child’s level of sociability, child-led interaction models, the integration of social robots as tools to enhance interactions between children and others, active empathy toward children’s speech and behavior, and personalized interactions. These insights underscore the importance of tailoring social robot interventions to meet individual developmental needs and fostering connections beyond the robot itself.

7. Conclusion

This study highlights both the promise and the limitations of using social robots to support the social and emotional development of preschoolers. While the robot’s design and functionality facilitate engagement and emotional expression, particularly for children with lower sociability, the absence of sophisticated emotional recognition and adaptive communication features limits the depth of these interactions. The study underscores the need for continuous improvement in robot capabilities, such as emotion recognition and contextually appropriate responses, to better support children’s developmental needs.

This study holds both academic and practical significance in the fields of early childhood development and human-robot interaction. Academically, it contributes to the growing body of research exploring how social robots can serve as tools for children’s social and emotional learning. It provides empirical evidence on how preschoolers interact with robots differently based on their sociability levels and highlights the complexities involved in creating engaging, human-like experiences. Practically, this study has important implications for early childhood education and therapy. Social robots could serve as valuable tools for educators and therapists, helping to create engaging and inclusive learning environments. For children with developmental challenges or social anxiety, social robots can provide non-judgmental and consistent interaction experiences. The study also underscores the importance of personalized interactions, such as tone of speech, terms of address, and voice, to enhance engagement between social robots and children. Additionally, it highlights the need for responses that foster encouragement and empathy, which may sometimes be lacking in human interactions. These findings offer practical insights for social robot designers and developers working on robots for children.

Despite its contributions, this study has several limitations that must be acknowledged. First, the study’s sample size, consisting of 50 preschoolers, while meaningful, may not be sufficient to generalize the findings broadly. Future studies with larger samples could offer deeper insights into the effectiveness and adaptability of social robots. Second, the relatively short duration of the experiment may limit the ability to observe long-term effects and changes in children’s social and emotional development. A longer-term study would be necessary to better understand how sustained interaction with a social robot influences children’s developmental outcomes over time. Third, the reliance on expert and parental feedback, while valuable, introduces a level of subjectivity in evaluating the effectiveness of the robotmediated activities. Objective measures of children’s social and emotional development, such as behavioral observations or standardized assessments, were limited in this study. Future research could incorporate more comprehensive assessment tools to provide a more objective evaluation of the robot’s impact.

Future research should explore ways to enhance the robot’s interactive features, create more tailored content based on individual sociability profiles, and investigate the long-term impact of robot-mediated activities on social and emotional development. Additionally, integrating social robots as mediators to promote human interaction, rather than as standalone engagement tools, could maximize their developmental benefits. Overall, while social robots hold significant potential in early childhood education, thoughtful design and continuous refinement are essential to optimize their role in fostering social and emotional growth.

Acknowledgments

This work was supported by the Industrial Fundamental Technology Development Program (20023495, Development of behaviororiented HRI AI technology for long-term interaction between service robots and users) funded By the Ministry of Trade, Industry and Energy (MOTIE, Korea).

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