Ensuring Quality Education for Out-of-School-Children using AI Based ROFSET Framework

Abstract

It is estimated that there are over 300 million out-of-school children (OOSC) worldwide. The United Nations Sustainable Development Goal (UNSDG) 4 aims to significantly reduce this number by the year 2030. A tremendous amount of effort and resources are being directed by national and international organizations to meet the UN SDG 4. Unfortunately, in some countries, the donated money for the OOSC goes into setting up fake schools often referred to as ghost schools. A large amount of the donated money is also being spent on monitoring and evaluation (ME) as well as other checks and balances to ensure transparency and accountability. But, unfortunately, the ME methods and the accuracy of information obtained are highly questionable. When such doubt arises, the money donated to such causes is stopped. In this paper, we present a radically new approach to ensure equity, quality, and accountability in education using a new ROFSET Framework. The ROFSET Framework allows us to introduce for the first time automation and artificial intelligence techniques for ME of teaching and learning effectiveness. It is cost-effective, easily deployable, and scalable. It is believed that the ROFSET Framework will make a significant impact on achieving the UNSDG 4 by 2030.

Artificial intelligence tools and higher education student’s engagement

“…These tools have the potential to provide personalized learning experiences, real-time feedback, customize content, and facilitate a more interactive and engaging learning environment, ultimately redefine the educational landscape. (Flores-Vivar, 2023;Haq 2022;Jokhan, et al, 2022;Kabudi, 2022;Yuskovych-Zhukovska et al, 2022). According to scholars, AI tools such as Chatbots, Virtual Assistance tools, and Adaptive Learning Systems offer immersive and engaging learning experiences that allow students to discover complex theories and solutions in a more interactive and meaningful manner (Chaudhry et al, 2023;Pradana et al, 2023).…”