Holistic Education in the AI Era: Ethical Challenges in Scientific Writing Based on a Critical Discourse Analysis Approach
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Abstract
The use of artificial intelligence (AI) in academic writing has rapidly expanded, offering significant support in literature search, language refinement, and structural organization. However, despite its advantages, AI introduces unresolved ethical challenges, particularly concerning originality, authorship credibility, and intellectual property rights. Existing literature has not sufficiently explored how these issues intersect with the values of holistic education, revealing a gap in normative academic frameworks guiding AI integration. This article aims to critically investigate the ethical implications of AI-assisted writing through the lens of holistic education, focusing on the interplay between technological utility and academic integrity. Employing a qualitative literature review approach, the study explores the concept of originality in AI-supported writing, and the role of logical reasoning, reading comprehension, and writing competence in maintaining scholarly standards. The analysis reveals that the presence of institutional policies regulating AI use can strengthen research transparency, uphold scientific credibility, and foster ethical awareness among scholars. While AI enhances productivity and supports plagiarism detection, it must not substitute the researcher’s responsibility to contribute original thought and critical engagement. One notable limitation of this study is the absence of universally accepted guidelines, which may result in inconsistent application across academic settings. This study contributes originally by proposing a regulatory framework rooted in holistic education to ensure that AI supports, rather than undermines, the cultivation of academic integrity and deep intellectual engagement. Consequently, the paper calls for comprehensive, ethically grounded policies that harmonize technology adoption with scholarly values to safeguard the quality and credibility of academic research in the AI era.
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