Renier Steyn, Pumela Msweli
Ubuntu, a key philosophical concept from Africa focusing on community and human connections, lacks a robust, standardized measurement scale. This study aimed to develop a comprehensive Ubuntu scale by synthesizing elements from existing tools and employing artificial intelligence (AI). Extensive review of existing Ubuntu measurement tools lead to compiling a comprehensive list of 104 items across five measures. These items were then processed through an AI language model (ChatGPT) to simulate exploratory factor analysis (EFA) for initial scale development. Subsequently, a confirmatory factor analysis (CFA)-like approach was used to refine the scale, adhering to a structured Ubuntu framework. The initial analysis led to two new measures. The EFA simulation identified five themes resonating with Ubuntu’s essence, while the CFA-like approach, constrained by the 104 items, was less effective, yielding a suboptimal item selection. Removing these constraints and allowing ChatGPT to access broader resources resulted in a more effective Ubuntu scale. This scale demonstrates strong content validity and relevance. This research not only presents a new, comprehensive tool for measuring Ubuntu but also highlights AI’s potential in developing psychometric instruments by leveraging extensive data pools. This scale is recommended for further research and application in studies involving Ubuntu.