Personalised learning and artificial intelligence in science education: current state and future perspectives

Özkan Yılmaz
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Abstract

This paper presents a comprehensive examination of the integration of artificial intelligence (AI) in science education and its impact on personalised learning. The research explores current applications, challenges, and future perspectives of AI technologies in educational settings. Through a systematic literature review, we identify the advantages of AI, such as enhanced individualised instruction, data-informed insights, and increased student engagement. The study combines quantitative and qualitative analyses, case studies, expert interviews, and technology assessments to offer a multidimensional understanding of AI's role in personalising science education. Despite the potential benefits, the research highlights barriers, including financial costs, infrastructure requirements, data privacy, and the need for teacher training. The future of AI in education suggests a trajectory towards advanced personalisation capabilities through adaptable learning systems, virtual tutors, and immersive learning environments. We underscore the importance of addressing the identified challenges to fully realise the transformative power of AI in science education. The findings illustrate that, with thoughtful implementation, AI holds promise for tailoring science learning experiences, making them more effective, inclusive, and engaging for students of varied needs and abilities.
科学教育中的个性化学习和人工智能:现状与未来展望
本文全面探讨了人工智能(AI)在科学教育中的整合及其对个性化学习的影响。研究探讨了人工智能技术在教育环境中的当前应用、挑战和未来前景。通过系统的文献综述,我们确定了人工智能的优势,如增强个性化教学、数据化洞察力和提高学生参与度。研究结合了定量和定性分析、案例研究、专家访谈和技术评估,从多维度理解了人工智能在个性化科学教育中的作用。尽管人工智能具有潜在的优势,但研究也强调了一些障碍,包括财务成本、基础设施要求、数据隐私以及教师培训需求。人工智能在教育领域的未来发展轨迹是,通过可适应的学习系统、虚拟导师和沉浸式学习环境,实现先进的个性化能力。我们强调,要充分实现人工智能在科学教育中的变革力量,就必须应对已确定的挑战。研究结果表明,通过深思熟虑的实施,人工智能有望定制科学学习体验,使其更加有效、更具包容性,并吸引不同需求和能力的学生。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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