Artificial intelligence and big data-driven evaluation research and practices: A systematic literature review

Abstract

The widespread adoption of digitalization and artificial intelligence, alongside the abundance of big data, has significantly transformed societies. Recently, there has been an increasing interest in leveraging big data and artificial intelligence to capture and analyze social transformative change in evaluation. However, there is no consensus on the ethical and appropriate use of these tools in evaluation. This article used a systematic literature review to provide an overview of using big data and artificial intelligence for evaluation purposes, identifying challenges faced. Unresolved issues encompass ethical, methodological, and ownership concerns. The study suggests ways to address these challenges and advocates for united efforts to mix big data and artificial intelligence with traditional approaches. To achieve this, it emphasizes the necessity of leveraging interconnected data platforms, mitigating ethical risks, and enhancing evaluators’ competencies in computer and data science, which is essential for the integration of big data and artificial intelligence in the evaluation field.

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