ChildEC: A Developmentally Stratified Chinese Dialogue Corpus for Child Emotion Coaching

Abstract

Existing dialogue resources for minors mainly focus on general psychological support, adolescent positive mental health promotion, or broad emotional companionship, and therefore do not adequately support the task of everyday emotion coaching for Chinese children. To address this gap, we construct ChildEC, a developmentally stratified multi-turn dialogue corpus for everyday emotion coaching, targeting Chinese children aged 8--12. The corpus contains 1,709 multi-turn dialogues spanning two developmental stages and five core themes. To support corpus construction and evaluation, we further propose the Theory-Grounded Emotion Coaching Framework (TGEC). Within this framework, TGEC-Synth operationalizes the five-step emotion coaching model and Socratic dialogue into a multi-stage dialogue synthesis pipeline, while TGEC-Eval assesses the quality of child emotion coaching dialogues along six key dimensions. Experimental results show that models fine-tuned on ChildEC consistently outperform their corresponding base models under both automatic metrics and LLM-as-a-Judge evaluation, demonstrating the downstream training value of the corpus for child emotion coaching. Overall, ChildEC provides a specialized data resource and an evaluation reference for developmentally sensitive and theory-consistent research on Chinese child emotion coaching. Our dataset will be publicly released upon acceptance of the paper.