Fostering sustainable Development Through Artificial Intelligence in Education (ESD): A Comprehensive Evaluation Framework and Key Criteria Analysis

Abstract

Abstract The good implementation of artificial intelligence (AI) for Education Sustainability Development (ESD) in Higher Education (HE) will be a relevant factor in the successful ranking of universities. Therefore, Higher Education must evaluate the performance of this implementation and integrate adequate criteria of performance in its Quality Assurance System. This research paper aims to identify relevant evaluation criteria of the implementation of artificial intelligence (AI) for Education Sustainability Development (ESD) in Higher Education (HE) and propose how HE can integrate those criteria into their quality assurance systems. The study utilizes a combination of qualitative content analysis and the Analytic Hierarchy Process (AHP) to identify criteria for assessment and generate a weight matrix of those criteria. Based on the findings, a framework of evaluation is proposed to assess the performance of integrating AI to promote sustainable learning outcomes by elucidating the relationship between key elements, such as the SKE (Skills, Knowledge, Ethics) Model, Learning Objectives, Learning Outcomes, and Key Performance. Continuous improvement is a vital element in our framework to maintain its relevance in fostering quality in implementing AI in education for sustainable development. It emphasizes the importance of a feedback loop involving stakeholders to identify areas for enhancement and ensure ethical and inclusive AI application.