Frontiers in Sustainable Cities (Jul 2022)
Sustainable Participatory Governance: Data-Driven Discovery of Parameters for Planning Online and In-Class Education in Saudi Arabia During COVID-19
Abstract
Everything about our life is complex. It should not be so. New approaches to governance are needed to tackle these complexities and the rising global challenges. Smartization of cities and societies has the potential to unite us, humans, on a sustainable future for us through its focus on the triple bottom line (TBL) – social, environmental, and economic sustainability. Data-driven analytics are at the heart of this smartization. This study provides a case study on sustainable participatory governance using a data-driven parameter discovery for planning online, in-class, and blended learning in Saudi Arabia evidenced during the COVID-19 pandemic. For this purpose, we developed a software tool comprising a complete machine learning pipeline and used a dataset comprising around 2 million tweets in the Arabic language collected during a period of over 14 months (October 2020 to December 2021). We discovered fourteen governance parameters grouped into four governance macro parameters. These discovered parameters by the tool demonstrate the possibility and benefits of our sustainable participatory planning and governance approach, allowing the discovery and grasp of important dimensions of the education sector in Saudi Arabia, the complexity of the policy, the procedural and practical issues in continuing learning during the pandemic, the factors that have contributed to the success of teaching and learning during the pandemic times, both its transition to online learning and its return to in-class learning, the challenges public and government have faced related to learning during the pandemic times, and the new opportunities for social, economical, and environmental benefits that can be drawn out of the situation created by the pandemic. The parameters and information learned through the tool can allow governments to have a participatory approach to governance and improve their policies, procedures, and practices, perpetually through public and stakeholder feedback. The data-driven parameter discovery approach we propose is generic and can be applied to the governance of any sector. The specific case study is used to elaborate on the proposed approach.
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