Interactive Children’s Story Rewriting Through Parent-Children Interaction (2022)

Abstract: Storytelling in early childhood provides significant benefits in language and literacy development, relationship building, and entertainment. To maximize these benefits, it is important to empower children with more agency. Interactive story rewriting through parent-children interaction can boost children’s agency and help build the relationship between parent and child as they collaboratively create changes to an original story. However, for children with limited proficiency in reading and writing, parents must carry out multiple tasks to guide the rewriting process, which can incur a high cognitive load. In this work, we introduce an interface design that aims to support children and parents to rewrite stories together with the help of AI techniques. We describe three design goals determined by a review of prior literature in interactive storytelling and existing educational activities. We also propose a preliminary prompt-based pipeline that uses GPT-3 to realize the design goals and enable the interface.

## introduction storytelling in early childhood can enhance language and literacy development and contribute to improved oracy, listening, reading, and writing skills later in life @xcite . when interaction is added to the storytelling experiencefor example, a storyteller asking a child a questionthe attention of the child can be maintained. enhancing the children's engagement can increase the educational benefits of interactive storytelling @xcite . therefore, researchers have developed a number of technologies to support interactive storytelling for young children, which range from letting children record and playback stories @xcite to asking children to answer comprehension-based questions @xcite or illustrate stories @xcite . in engaging children with interactive storytelling, three aspects of agency are important: autonomy, competence, and effectance @xcite . children feel more engaged if they feel more autonomous and competent in their decision-making @xcite . also, it is important to make children feel their decisions have an immediate (local effectance) and overall (global effectance) effect on the narrative @xcite . as an example of interactive stories that support these aspects of agency, "pick-a-path" or "choose your own adventure" stories can maintain children's engagement by providing different plots that children can explore depending on their choices about the plot @xcite . like "pick-a-path" stories, story rewriting can be one of the activities to support children's agency in interactive storytelling in that a child makes @xcite and the story changes according to this decision (effectance). though it is well known that story rewriting activities are helpful for developing storytelling and reading comprehension skills @xcite , it is challenging to provide the rewriting activities to children with limited proficiency in reading and writing. as children may struggle to rewrite stories by themselves, parents could help them by participating in this activity. based on existing rewriting activities and literature on scaffolding children's story writing and constraints from younger children's lack of proficiency in reading and writing @xcite , parentchildren story rewriting can be composed of the following processes: (1) changing the setting and finding what to change in the story, (2) parents asking questions to their children about how they might want to change the story, and (3) rewriting the story based on the children's decisions. however, it is difficult for parents to carry out these processes alone, because parents have been shown to struggle in similar multitasking scenarios such as provid-ing story-relevant questions while storytelling due to the high cognitive load incurred @xcite . instead of burdening parents, a viable solution for parent-children story rewriting can be to adopt a human-ai collaborative approach. ai models can quickly and automatically perform tasks that can be tedious for humans, while allowing children and parents to focus on the tasks that increase the children's agency and build parent-child relationships. specifically, entity extraction, question generation, and text generation techniques from recent natural language-based ai technologies can reduce the load on parents in the aforementioned processes of story rewriting, allowing them to focus more on the interactions with their children. therefore, in this work, we introduce design sketches of our interface that supports children to rewrite the story through parent-children interaction with the help of ai techniques. specifically, the system can help parents using a three-step pipeline: (1) finding entities in the story that could be changed based on a set of pre-defined dimensions from literature, (2) generating questions that a parent can ask their child to decide on how to rewrite, and (3) rewriting stories based on the child's decisions while keeping coherency with prior context. ## design goals this work focuses on supporting interactive rewriting of children's stories through parent-child interaction to provide children with agency in storytelling experiences. since children's reading skills are very different from age to age and it is important to provide support that fits their age, we set the target age range of our potential users to be three to eight years old, including the pre-reading stage and early-reading stage @xcite . this work aims to allow children in these stages in reading development to make decisions on story elements by answering to their parents' questions and experience rewritten stories based on these interactions with their parents. our review of the previous literature on interactive storytelling and story writing, as well as existing educational activities for story writing, led to three high-level goals that informed our design of a human-ai system for interactive story rewriting. ## system based on the design goals, we envision an interface that supports parent-ai-child interaction for interactive story rewriting. in this section, we describe the interface and a preliminary prompt-based pipeline that uses gpt-3 @xcite ) to enable such an interface. ## evaluation plan we describe plans for evaluating our system, including the technical evaluation and human evaluation for each tasks in the pipeline, and a user study. ## future work in this work, we presented a preliminary pipeline for human-ai story rewriting that uses prompts and the few-shot capabilities of gpt-3. in future work, finding well-performing models for each subtask in the pipeline and conducting evaluation of such models are our immediate next steps. for entity extraction, we are planning to experiment with extraction methods that prior work adopted, such as leveraging qa models to extract story dimensions @xcite and extracting candidate spans through heuristics designed based on a pedagogical framework @xcite . in the case of question generation, it is necessary to identify more concrete types of questions that parents would need to build meaningful relationships with their children. we have a plan to conduct formative interviews and an extensive literature survey to identify them. we then plan to use llms to generate diverse sets of questions based on these question types. to engage children more in the parent-child interaction, asking multi-turn questions might be a better solution than asking independent questions in separate rounds @xcite . moreover, through multi-turn questions, children can be elicited for choices on multiple spans. by passing multiple span changes to the model at once, additional semantically relevant spans can be found and rewrit-ten by considering the post context of stories. for story rewriting, although our system lets users accept or dismiss the additional entity changes generated by lms, it is necessary to identify what people expect for how much a story should change based on seed changes. a preliminary study to identify and meet users' expectations can serve as a first step toward understanding how to rewrite stories. moreover, rewritten stories made by a generative model could propagate and may even amplify various biases (e.g., gender, race, and culture) found in text corpora, which can cause negative outcomes like reinforcing gender stereotypes or building narrow understandings of normative behavior. as a first step to prevent this, our system can apply various nlp techniques for recognizing and mitigating biases @xcite and warn users that a given generation might have a specific bias and help them deal with this bias.