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Posters Advancing Comprehensive Early Childhood Intervention ECI INTERVENTION DOMAINS Topic - Technology p4.31 AI-Enabled Solutions in Early Intervention: Bridging Research, Teaching, and Practice Presenting Author: John B. Nash (USA) Affiliation: University of Kentucky Co-Authors: Rena Hallam, Beth Rous
Session 4
Artificial Intelligence (AI) offers transformative potential for early intervention research, teaching, and practice. This interactive poster explores how AI tools can enhance efficiency, accuracy, and innovation across these areas, providing practical insights for early intervention professionals. In research, AI can support design and analysis across research approaches, including single case, qualitative, quantitative, and mixed methods designs. In teaching, AI-powered learning platforms offer adaptive training and personalized feedback to support professional development. For practice, AI applications can support creating and identifying evidence-based practices that can be implemented to achieve children’s and families’ goals. Through embedded QR codes, attendees will instantly access curated resources including ready-to-use AI prompts, tool demonstrations, and implementation guides. The poster provides concrete examples of AI tools, illustrating their benefits and limitations. Attendees will leave with immediately actionable strategies for integrating AI to improve outcomes for children and families. p4.32 Artificial Intelligence in Early Education: Advancing Personalized and Inclusive Learning Artificial Intelligence (AI) is transforming education by offering innovative tools for teaching and learning. Its ability to personalize education enables the adaptation of content to the needs, interests, and abilities of each student, optimizing teaching processes and enhancing engagement and effectiveness. AI-powered adaptive systems design tailored learning paths, facilitate early detection of educational challenges, and enable timely interventions to improve academic performance. Additionally, AI enriches content with interactive resources, increasing student participation. It also streamlines administrative and assessment tasks, allowing educators to focus on personalized feedback. From gamified platforms in primary education to advanced tools in higher education, AI analyzes behavioral patterns and adjusts educational recommendations. This presentation explores the benefits, challenges, and implications of AI in advancing personalized and inclusive learning across diverse educational contexts. p4.33 Bridging Communication Gaps in Special Education: Development and Usability Testing of the 'My Buddy' Conversational System Presenting Author: Pei-Ju Lin (Taiwan) Presenting Author: Cristina Sánchez Romero, Pilar Gutiez Cuevas (Spain) Affiliation: National Distance Education University (UNED) y AMPAT Co-Authors: Paloma Antón Ares, Pilar Gutiez Cuevas, Cristina Sánchez Romero Students with intellectual disabilities often face challenges in expressing their opinions due to cognitive and verbal limitations. This study developed the "My Buddy" conversational system to enhance their learning motivation, and verbal expression skills. The system integrates ChatGPT, automatic speech recognition (ASR), and text-to-speech (TTS) technologies, covering topics such as daily needs, interactive communication, emotional expression, and learning support. Usability testing involved 10 special education teachers from elementary schools in Taiwan. Results indicated high teacher satisfaction, with usability evaluation scores ranging from 62.5 to 92.5 and an average score of 75. Students also demonstrated strong focus and high satisfaction with the interactions. While improvements in speech recognition accuracy and interface design are still needed, the system shows significant potential in promoting communication and learning outcomes. Future work will focus on optimizing the system and conducting further testing. p4.34 Effects of AI-Enhanced Social Stories on Pragmatic Language Skills of Young Children With Limited Peer Acceptance Presenting Author: Çiğdem Keleş Karaşahin (Turkey) Affiliation: Hasan Kalyoncu University Co-Author: Latife Özaydın This study aimed to investigate the effect of AI-based social stories on the pragmatic language skills of 60-72-month-old children with limited peer interactions attending preschool. The study used a quasi-experimental pretest-posttest design with a matched control group. Participants of study involved 20 preschool children, divided into an experimental group (n=10) and a control group (n=10). The experimental group was exposed to AI-based social stories twice a week for six weeks, while the control group received traditional social stories delivered by their preschool teacher. Results from the Pragmatic Language Skills Test showed that AI- based social stories improved the pragmatic language skills of children in the experimental group. These results suggest that integrating AI technologies into early childhood education may be an effective approach to improving children's social communication skills, particularly for those with limited opportunities for peer interaction. Affiliation: Dept. of Special Education, National Taitung University, Taiwan Co-Authors: Ya-Tzu Liao, Kai-Chih Pai, Hui-Ching Su, Chao-Tung Yang
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