A System to Ensure Information Trustworthiness in Artificial Intelligence Enhanced Higher Education

Aim/Purpose The purpose of this paper is to address the challenges posed by disinformation in an educational context. The paper aims to review existing information assess-ment techniques, highlight their limitations, and propose a conceptual design for a multimodal, explainable information assessment system for higher educa-tion. The ultimate goal is to provide a roadmap for researchers that meets cur-rent requirements of information assessment in education. Background The background of this paper is rooted in the growing concern over disinfor-mation, especially in higher education, where it can impact critical thinking and decision-making. The issue is exacerbated by the rise of AI-based analytics on social media and their use in educational settings. Existing information assess-ment techniques have limitations, requiring a more comprehensive AI-based ap-proach that considers a wide range of data types and multiple dimensions of disinformation. Methodology Our approach involves an extensive literature review of current methods for in-formation assessment, along with their limitations. We then establish theoretical foundations and design concepts for EMIAS based on AI techniques and knowledge graph theory. Contribution We introduce a comprehensive theoretical framework for an AI-based multi-modal information assessment system specifically designed for the education sector. It not only provides a novel approach to assessing information credibil-ity but also proposes the use of explainable AI and a three-pronged approach to information evaluation, addressing a critical gap in the current literature. This research also serves as a guide for educational institutions considering the de-ployment of advanced AI-based systems for information evaluation. Recommendations for Practitioners Implement the proposed EMIAS system to enhance the credibility of infor-mation in educational settings and foster critical thinking among students and teachers. Recommendations for Researchers Explore domain-specific adaptations of EMIAS, research on user feedback mechanisms, and investigate seamless integration techniques within existing aca-demic infrastructure. Impact on Society This paper’s findings could strengthen academic integrity and foster a more in-formed society by improving the quality of information in education. Future Research Further research should investigate the practical implementation, effectiveness, and adaptation of EMIAS across various educational contexts.