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The application of large language models in coaching: A knowledge-based framework for AI-Driven coaching

Lixian Xie & Erek J. Ostrowski

International Coaching Psychology Review2025https://doi.org/10.53841/bpsicpr.2025.20.2.83article
AJG 1
Weight
0.37

What the paper says

Coaching is the practice of facilitating individuals’ learning, growth, performance, and wellbeing. The rapid advancement of artificial intelligence (AI), particularly through the development of large language models (LLMs), has demonstrated remarkable potential across various fields, including coaching. This study investigates the transformative role of LLMs in coaching. It investigates individuals’ receptivity to AI-driven coaching through a survey involving 49 university students. Results indicate a strong openness to AI coaching, with over 50% of participants expressing a willingness to use such tools while also raising concerns about privacy, effectiveness, and cultural understanding. This paper also proposes a knowledge-based framework for AI-driven coaching rooted in prominent psychological theories and coaching models. Through a structured three-step process, the framework enables LLMs to emulate professional coaching practices by leveraging prompt engineering and psychological insights to deliver personalised, accessible, cost-effective, and scalable coaching. This study underscores the significant potential of AI-driven coaching to promote human wellbeing and personal development at scale while laying a foundation for future research to further validate its efficacy and applications.

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https://doi.org/https://doi.org/10.53841/bpsicpr.2025.20.2.83

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@article{lixian2025,
  title        = {{The application of large language models in coaching: A knowledge-based framework for AI-Driven coaching}},
  author       = {Lixian Xie & Erek J. Ostrowski},
  journal      = {International Coaching Psychology Review},
  year         = {2025},
  doi          = {https://doi.org/https://doi.org/10.53841/bpsicpr.2025.20.2.83},
}

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The application of large language models in coaching: A knowledge-based framework for AI-Driven coaching

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Evidence weight

0.37

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.16 × 0.4 = 0.06
M · momentum0.53 × 0.15 = 0.08
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.