Application of Artificial Intelligence in Psychological Counseling Education, Supervision and Training

1. Purpose: The core research purpose of this project focuses on three aspects. First, the construction, implementation effects and existing challenges of AI/LLM-based counseling training tools, including AI simulated client systems, AI simulated supervision tools, and AI training tools. Second, the integration of AI with different counseling schools (cognitive behavioral therapy, psychodynamic therapy, humanistic therapy etc) and general counseling skills. Third, the attitudes of psychology students and teachers towards AI counseling training technology. 2. Method: This study is a systematic review that follows the PRISMA 2020 guidelines. The design is structured as follows: 2.1 Search strategy: A comprehensive search will be conducted in multiple databases (e.g., PubMed, PsycInfo, Scopus, ERIC, IEEE) using predefined keywords related to LLMs and psychology education. The search will be restricted to English-language, full-text articles published after ChatGPT's debut to reflect recent developments. 2.2 Study selection: Two independent reviewers will screen titles and abstracts for relevance. Discrepancies will be resolved through discussion or consultation with a third reviewer. Full-text articles will then be evaluated against predefined inclusion and exclusion criteria. 2.3 Data extraction: A standardized form will be used to extract key data from included studies, including AI application scenarios，schools of psychological counseling. 2.4 Synthesis: A qualitative thematic synthesis will be conducted to identify common themes, patterns, and gaps in the literature regarding the application of LLMs in psychology education. This design ensures transparency, reproducibility, and minimizes bias in the review process. 3. Expected outcomes: The research expects to achieve the following key outcomes: 3.1 It will systematically review the application status and research progress of Artificial Intelligence/Large Language Models (AI/LLMs) in psychological counseling training from 2020 to 2025, establishing a comprehensive overview to enable researchers, educators, and practitioners to efficiently understand the current landscape of the field. 3.2 It will validate the practical value of AI in counseling training and confirm that AI can effectively address the limitations of conventional training approaches. 3.3 It will identify key challenges and ethical risks in current and propose targeted improvement strategies, offering advice for the optimization of AI training tools, instructional integration, and the development of ethical frameworks. 3.4 It will outline directions for future research on AI in counseling training.