Artificial Intelligence (AI) mediated systems have become important in educational set-ups, and it is still debatable whether or not they can be useful in special needs education. This qualitative research scrutinizes the experiences and perceptions of exceptional learners, as an example of special needs education, engaged in AI-mediated discussions versus traditional classroom dialogues. The study aims to reveal how these learners process and construct knowledge differently when AI is incorporated into their discussions and how it compares to conventional learning environments. The methodology entailed a detailed qualitative analysis, drawing upon cognitive psychology to assess how exceptional learners process information and engage in higher-order thinking. Data were collected through interviews, observation, and content analysis of AI-mediated discussions. from the study highlighted the capacity of AI technologies to offer personalized and intellectually stimulating educational experiences that resonate with constructivist approaches, promoting active learning and tailored instruction for exceptional learners. However, the research also brought to light certain challenges, including the tendency for confirmation bias and the risk of information overload within AI-mediated environments, which can complicate the learning trajectory within the zone of proximal development. The study underscores the dynamic interplay between AI technologies and educational processes for exceptional learners. It suggests that while AI can enhance personalized learning, it also introduces unique challenges that must be navigated carefully. Ultimately, this research lays a theoretical and empirical groundwork for the thoughtful integration of AI in supporting inclusive education, emphasizing the importance of continuous evaluation and adaptation.

中文翻译：

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加强阿联酋的全纳教育：整合人工智能以满足多样化的学习需求

人工智能（AI）介导的系统在教育机构中已经变得很重要，但它们在特殊需要教育中是否有用仍然存在争议。这项定性研究审视了特殊学习者的经历和看法，作为特殊需要教育的一个例子，参与人工智能介导的讨论与传统的课堂对话。该研究旨在揭示当人工智能纳入他们的讨论时，这些学习者如何以不同的方式处理和构建知识，以及它与传统学习环境的比较。该方法需要进行详细的定性分析，利用认知心理学来评估优秀学习者如何处理信息和进行高阶思维。通过访谈、观察和对人工智能介导的讨论的内容分析来收集数据。该研究强调了人工智能技术提供个性化和智力刺激的教育体验的能力，这些体验与建构主义方法产生共鸣，促进主动学习和为优秀学习者量身定制指导。然而，该研究也揭示了某些挑战，包括确认偏差的趋势和人工智能介导的环境中信息过载的风险，这可能会使最近发展区域内的学习轨迹变得复杂。该研究强调了人工智能技术与优秀学习者的教育过程之间的动态相互作用。它表明，虽然人工智能可以增强个性化学习，但它也带来了必须谨慎应对的独特挑战。最终，这项研究为人工智能在支持全纳教育方面的深思熟虑的整合奠定了理论和实证基础，强调了持续评估和适应的重要性。