Bartın University Journal of Faculty of Education · 2024 · 36 citations · 61 references
EducationEducation PolicyEducational TechnologyArtificial IntelligenceArtificial Intelligence In EducationEducation ReformArtificial Intelligence AdoptionArtificial Intelligence PolicyEthics Of Automated Decision-makingGenerative Ai In EducationAi Ethics In AdoptionAi LiteracyAi Risk ManagementArtificial Intelligence EducationArtificial Intelligence LiteracyArtificial Intelligence RiskEducation Policy For AiWorkforce Impacts Of Ai
Artificial Intelligence (AI) technologies are rapidly advancing and causing profound transformations in all aspects of life. In particular, the widespread adoption of generative AI systems like ChatGPT is taking this transformation to even more dramatic dimensions. In this context, the most comprehensive impact is observed in educational systems. Educational systems, on one hand, are faced with the urgent need to rapidly restructure education in response to skill changes in professions caused by the proliferation of such systems in the labor market. On the other hand, challenging questions arise about whether and to what extent these systems should be integrated into education, how they should be integrated if at all, and how ethical issues arising from AI systems can be addressed. This study evaluates the potential benefits and possible risks of using AI systems in educational systems from the perspectives of students, teachers, and education administrators. Therefore, the study discusses the potential uses of AI systems in education, as well as the risks they may pose. Policy recommendations are developed to maximize the benefits of AI systems while mitigating the ethical and other issues they may cause. Additionally, the study emphasizes the importance of increasing AI literacy for all education stakeholders. It suggests that raising awareness of both the benefits and ethical issues caused by AI systems can contribute to enhancing the benefits of these systems in education while minimizing their potential harms.
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CRITICAL QUESTIONS FOR BIG DATA
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