From AI‑personalized learning to green purchasing: A TPB-S‑D logic pathway via self-regulated learning, perceived knowledge gain, and attitudes in Jordan and Palestine

Abstract

This study examines the possibilities of AI-enabled learning to be prolonged from the classroom to enable greener lifestyle decisions on an everyday basis, and conceptualizes that process as a platform governance and telecommunications policy problem. AI-powered personalization is thought of here as a data-hungry platform in markets for connectivity and in data, privacy, and algorithmic accountability regimes. Based on the theory of planned behavior and the service-dominant logic of value co-creation, we propose that personalization increases perceived knowledge and self-directed learning, which yield favorable attitudes toward sustainable consumption and thus green purchasing. Based on empirical data from Palestine and Jordan, we illustrate how infrastructure, affordability, and trust act as mediators of using, crediting, and converting personalization to social value. The contribution is twofold: it links learning gains to market-relevant dispositions in the platform governance setting, and it presents a design blueprint for regulators, ministries, and providers that pairs greater access with open data practices and incentives tied to authenticated learning outcomes. In general, the study positions AI-personalized learning as an editable digital platform whose social dividend is enhanced when telecommunications policy and data regulation are aligned with education and sustainability goals.