TY - GEN
T1 - StoryLab
T2 - 26th International Conference on Artificial Intelligence in Education, AIED 2025
AU - Li, Zhaohui
AU - Xiao, Feiwen
AU - Lin, Jiaju
AU - Zou, Xiaohan
AU - Zheng, Qingxiao
AU - Xiong, Jinjun
N1 - Publisher Copyright: © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.
PY - 2025
Y1 - 2025
N2 - Personalized story reading enhances child literacy by aligning content with individual interests, backgrounds, and developmental needs. However, implementing such systems presents challenges, including data privacy concerns, the need for culturally diverse materials, limited resources, and balancing personalization with standardized benchmark objectives. To address these challenges, we introduce StoryLab, a multimodal system designed for K-2 teachers and students. The system leverages advanced generative AI to integrate students’ personal interests with teacher-defined learning objectives to generate comprehensive learning materials, including story text, illustrated figures, vocabulary support, and a consistent narrative voice. A teacher-in-the-loop design ensures pedagogical alignment and trust. Evaluations demonstrate StoryLab’s effectiveness and usability, positioning it as a promising and scalable tool for personalized literacy instruction.
AB - Personalized story reading enhances child literacy by aligning content with individual interests, backgrounds, and developmental needs. However, implementing such systems presents challenges, including data privacy concerns, the need for culturally diverse materials, limited resources, and balancing personalization with standardized benchmark objectives. To address these challenges, we introduce StoryLab, a multimodal system designed for K-2 teachers and students. The system leverages advanced generative AI to integrate students’ personal interests with teacher-defined learning objectives to generate comprehensive learning materials, including story text, illustrated figures, vocabulary support, and a consistent narrative voice. A teacher-in-the-loop design ensures pedagogical alignment and trust. Evaluations demonstrate StoryLab’s effectiveness and usability, positioning it as a promising and scalable tool for personalized literacy instruction.
KW - Early Literacy
KW - Large Language Models
KW - Multimodal Learning Environment
KW - Personalized Learning
KW - Story Generation
UR - https://www.scopus.com/pages/publications/105012029747
U2 - 10.1007/978-3-031-98462-4_36
DO - 10.1007/978-3-031-98462-4_36
M3 - Conference contribution
SN - 9783031984617
T3 - Lecture Notes in Computer Science
SP - 285
EP - 292
BT - Artificial Intelligence in Education - 26th International Conference, AIED 2025, Proceedings
A2 - Cristea, Alexandra I.
A2 - Walker, Erin
A2 - Lu, Yu
A2 - Santos, Olga C.
A2 - Isotani, Seiji
PB - Springer Science and Business Media Deutschland GmbH
Y2 - 22 July 2025 through 26 July 2025
ER -