SET-PAiREd: Designing for Parental Involvement in Learning with an AI-Assisted Educational Robot
Project Overview
The document explores the integration of generative AI, particularly through AI-assisted educational robots, in early childhood education to enhance parental involvement in children's learning. It underscores the critical role of parental engagement while acknowledging the challenges that parents face, such as limited skills, time, and motivation. The introduction of a card-based activity kit (SET) and a prototype AI-assisted robot (PAiREd) aims to foster collaboration between parents and AI, facilitating personalized learning experiences. Research findings indicate that parents value the pedagogical insights offered by AI-generated content but also express concerns regarding its appropriateness and quality. Key factors influencing parental engagement include energy, time, and trust in AI, suggesting that design considerations must address these elements to optimize educational outcomes. Overall, the document highlights the potential of generative AI to support parents in guiding their children's education while emphasizing the need for adaptability and quality in AI-generated materials to effectively enhance the learning experience.
Key Applications
PAiREd - AI-assisted educational robot and LLM interface
Context: Early childhood education involving parent-child interactions with children aged 3-5 years, where parents collaborate with an educational robot using LLM-generated content to engage in learning activities.
Implementation: Developed a prototype system that allows parents to generate, review, and revise educational content with the help of a large language model (LLM). The implementation involved conducting an in-home field study where parents and children interacted with the educational robot to enhance learning experiences, using AI-generated content to facilitate these interactions.
Outcomes: Enhanced parental involvement in children’s learning activities; increased understanding among parents of their children's abilities; provided pedagogical strategies to facilitate learning; and created personalized educational content tailored to individual needs.
Challenges: Concerns about content appropriateness and accuracy of AI-generated content; the risk of over-reliance on technology; varying levels of trust among parents; and the necessity for parental supervision.
Implementation Barriers
Perceptual Barrier
Parents express skepticism about AI-generated content due to concerns regarding quality, safety, age appropriateness, and the appropriateness, accuracy, and reliability of AI-generated content, which influences their willingness to use it.
Proposed Solutions: Encouraging parental review and verification of content, providing transparency about AI training data and models, ensuring expert involvement in content creation, and improving the transparency and explainability of AI content generation processes to build parental trust.
Technical Barrier
The effectiveness of AI in handling complex learning tasks and ensuring accurate content generation is limited.
Proposed Solutions: Improving AI training processes, using high-quality datasets, and allowing parents to customize and review generated content.
Time and Energy Barrier
Limited time and energy affected parents' willingness to review and engage with AI-generated content.
Proposed Solutions: Designing user-friendly interfaces that adapt to parents' needs, offering options for quick reviews or in-depth editing.
Project Team
Hui-Ru Ho
Researcher
Nitigya Kargeti
Researcher
Ziqi Liu
Researcher
Bilge Mutlu
Researcher
Contact Information
For information about the paper, please contact the authors.
Authors: Hui-Ru Ho, Nitigya Kargeti, Ziqi Liu, Bilge Mutlu
Source Publication: View Original PaperLink opens in a new window
Project Contact: Dr. Jianhua Yang
LLM Model Version: gpt-4o-mini-2024-07-18
Analysis Provider: Openai