skip to main content
US FlagAn official website of the United States government
dot gov icon
Official websites use .gov
A .gov website belongs to an official government organization in the United States.
https lock icon
Secure .gov websites use HTTPS
A lock ( lock ) or https:// means you've safely connected to the .gov website. Share sensitive information only on official, secure websites.


Title: A Home Study of Parent-Child Co-Reading with a Bilingual Conversational Agent
Conversational agents (CAs) are increasingly prevalent in children’s lives, serving as educational companions, particularly in shared reading activities. While effective for monolingual children’s learning, there exists a gap in meeting the unique needs of the rapidly expanding bilingual child population, who face dual challenges of school readiness and heritage language maintenance. Moreover, most current CAs, designed for one-to-one interactions with children, neglect the importance of parents’ active participation in shared reading. Our study introduces the development and home deployment of a bilingual CA, integrated within e-books, designed to foster parent-child joint engagement in shared reading, thereby promoting children’s bilingual language development. Results of the study indicated high levels of family engagement in co-reading activities over an extended period, with observable language learning gains in children. This study provides valuable design implications for designing effective and engaging CAs for bilingual families.  more » « less
Award ID(s):
2115382
PAR ID:
10526783
Author(s) / Creator(s):
; ; ; ; ;
Publisher / Repository:
ACM
Date Published:
ISBN:
9798400703317
Page Range / eLocation ID:
1 to 8
Format(s):
Medium: X
Location:
Honolulu HI USA
Sponsoring Org:
National Science Foundation
More Like this
  1. Recognizing the challenges bilingual children face in school readiness and the potential of bilingual dialogic shared reading in improving language and literacy, this study investigates the use of a bilingual conversational agent (CA) to enhance shared reading experiences in home environments. While current CAs hold promise in fostering young children's learning, they do not typically consider the linguistic and cultural needs of bilingual children and rarely involve parents intentionally. To this end, we developed a bilingual CA, embedded within ebooks, to support children's language learning and parent engagement for Latine Spanish-English bilingual families. A week-long home-based study with 15 families indicated that the bilingual CA elicited a high level of bilingual verbal engagement from children, thereby promoting their vocabulary acquisition. It also stimulated meaningful conversations among parents and children. This study provides design implications for developing CAs for bilingual children and parents. 
    more » « less
  2. Early literacy skills are crucial predictors of children’s academic success. Dialogic reading—an interactive approach where adults and children engage in discussions about stories—has proven highly effective in developing these skills. However, many families face barriers implementing this practice due to time constraints, limited resources, or linguistic challenges. We present StoryPal, an LLM-powered conversational agent that facilitates dialogic reading through contextual questioning, adaptive scaffolding, and personalized feedback. In a study with 23 children ages 4-7 from diverse socioeconomic and linguistic backgrounds, we found high levels of verbal engagement with distinct patterns between English-dominant and bilingual children. The system’s dynamic scaffolding effectively supported struggling readers while challenging proficient ones. Parents valued StoryPal as a supplementary tool that maintained children’s reading engagement when they were unavailable, but emphasized that it should not replace parent-child interactions. Our findings demonstrate the potential of LLM-powered agents to support dialogic reading by adhering to established educational practices. 
    more » « less
  3. Bilingual children at a young age can benefit from exposure to dual language, impacting their language and literacy development. Speech technology can aid in developing tools to accurately quantify children’s exposure to multiple languages, thereby helping parents, teachers, and early-childhood practitioners to better support bilingual children. This study lays the foundation towards this goal using the Hoff corpus containing naturalistic adult-child bilingual interactions collected at child ages 2½, 3, and 3½ years. Exploiting self-supervised learning features from XLSR-53 and HuBERT, we jointly predict the language (English/Spanish) and speaker (adult/child) in each utterance using a multi-task learning approach. Our experiments indicate that a trainable linear combination of embeddings across all Transformer layers of the SSL models is a stronger indicator for both tasks with more benefit to speaker classification. However, language classification for children remains challenging. 
    more » « less
  4. Understanding and assessing child verbal communication patterns is critical in facilitating effective language development. Typically speaker diarization is performed to explore children’s verbal engagement. Understanding which activity areas stimulate verbal communication can help promote more efficient language development. In this study, we present a two stage children vocal engagement prediction system that consists of (1) a near to real-time, noise robust system that measures the duration of child-to-adult and child-to-child conversations, and tracks the number of conversational turn-takings, (2) a novel child location tracking strategy, that determines in which activity areas a child spends most/least of their time. A proposed child–adult turn-taking solution relies exclusively on vocal cues observed during the interaction between a child and other children, and/or classroom teachers. By employing a threshold optimized speech activity detection using a linear combination of voicing measures, it is possible to achieve effective speech/non-speech segment detection prior to conversion assessment. This TO-COMBO-SAD reduces classification error rates for adult-child audio by 21.34% and 27.3% compared to a baseline i-Vector and standard Bayesian Information Criterion diarization systems, respectively. In addition, this study presents a unique location tracking system adult-child that helps determine the quantity of child–adult communication in specific activity areas, and which activities stimulate voice communication engagement in a child–adult education space. We observe that our proposed location tracking solution offers unique opportunities to assess speech and language interaction for children, and quantify the location context which would contribute to improve verbal communication. 
    more » « less
  5. Learning companion robots for young children are increasingly adopted in informal learning environments. Although parents play a pivotal role in their children’s learning, very little is known about how parents prefer to incorporate robots into their children’s learning activities. We developed prototype capabilities for a learning companion robot to deliver educational prompts and responses to parent-child pairs during reading sessions and conducted in-home user studies involving 10 families with children aged 3–5. Our data indicates that parents want to work with robots as collaborators to augment parental activities to foster children’s learning, introducing the notion of parent-robot collaboration. Our findings offer an empirical understanding of the needs and challenges of parent-child interaction in informal learning scenarios and design opportunities for integrating a companion robot into these interactions. We offer insights into how robots might be designed to facilitate parent-robot collaboration, including parenting policies, collaboration patterns, and interaction paradigms. 
    more » « less