An AI-Based Decision Model for Art Therapy Social Services Integrating Learning Analytics
Year: 2026
Type: conference-paper
Abstract: This study proposes an AI-based decision model for art therapy social services integrating learning analytics, addressing challenges in traditional service decision-making such as reliance on subjective experience, opaque intervention matching, and lack of quantitative outcome evaluation. The model consists of three core modules: data collection and feature modeling, decision reasoning and intervention matching, and service effectiveness evaluation. Service object characteristics, participation behaviors, and emotional feedback are structured into multidimensional feature vectors, and decision rules are generated using machine learning algorithms to provide personalized, explainable intervention recommendations. Evaluation metrics include decision accuracy, service matching rationality, and outcome stability. Results demonstrate high decision precision and stable service effectiveness across diverse service object groups, highlighting the potential of AI and learning analytics integration in enhancing social service decision quality. The model provides a systematic, data-driven framework for optimizing art therapy interventions and guiding resource allocation in social services, offering practical implications for service institutions and policy-making.
Authors: Fuwen Xin, Chao Zhang
Institution: Dalian Art College
Language: English
Subfield: Clinical Psychology
Field: Psychology
Domain: Social Sciences
Open Access status: hybrid
OpenAlex ID: W7208729470