An AI powered system to enhance self-reflection practice in coaching

Abstract

Self-reflection practice in coaching can help with time management by promoting self-awareness. Through this process, a coach can identify habits, tendencies and behaviours that may be causing distraction or make them less productive. This insight can be used to make changes in behaviour and establish new habits that promote effective use of time. This can also help the coach to prioritise goals and create a clear roadmap. An AI powered system has been proposed that maps the conversion onto topics and relations that could help the coach with note-taking and progress identification throughout the session. This system enables the coach to actively self-reflect on time management and make sure the conversation follows the target framework. This will help the coach to better understand the goal setting, breakthrough moment, and client accountability. The proposed end-to-end system is capable of identifying coaching segments (Goal, Option, Reality, and Way forward) across a session with 85% accuracy. Experimental evaluation has also been conducted on the coaching dataset which includes over 1k one-to-one English coaching sessions. In regards to the novelty, there are no datasets of such nor study of this kind to enable self-reflection actively and evaluate in-session performance of the coach.