Integrating Generative AI in Educational Psychology Assessments: Preliminary Ethical and Practical Guidelines

Abstract

This article presents an examination of the intersection between generative AI and psycho-educational assessments, offering a comprehensive overview of their integration. It begins by exploring the fundamentals of artificial intelligence, emphasizing the role of generative AI in Natural Language Processing (NLP) and its potential implications for psychological research and clinical practices. Concurrently, the manuscript delves into the intricate steps of a psycho-educational assessment for children, elucidating the multifaceted process encompassing cognitive, emotional, and academic evaluations. Through this integrated exploration, the article not only provides detailed guidelines, an ethical framework, and nuanced insights into potential challenges but also addresses the global shortage of trained clinicians. By examining how advanced technologies including Generative AI can assist in enhancing diagnostic efficiency, when outputs are interpreted and validated by trained professionals. Drawing on the perspectives highlighted by Duff and Roberts (2016) and insights from generative AI, the article proposes guidelines that streamline assessments, prioritize ethical considerations, and maximize the benefits of human expertise.

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