将人工智能生成技术融入高等教育形成性评估过程的潜力

A. Paskova
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引用次数: 0

摘要

在教育领域使用生成式人工智能技术有可能通过个性化学习体验、提供即时反馈和改善整体学习体验来彻底改变学习和教育评估。研究的现实意义在于人工智能技术的普及和高等教育中缺乏对教育成果进行形成性评估的实践。问题陈述:现有的国内电子学习系统功能有限,在形成性测试过程中难以使用。研究的目标是考虑在评估知识、技能和能力时使用生成式人工智能工具的理论基础,并分析我们自己在一所大学的形成性测试中使用大型语言模型的经验。研究的方法论基础是对互联网资源和文学资料的分析、数理统计方法和综合。研究成果:研究了在大学生形成性测试中使用生成式人工智能技术的可能性和有效性,分析了我们自己在形成性测试中使用大型语言模型的经验,确定了将这些技术引入教育过程的主要局限性,提出了使用大型语言模型组织形成性测试的建议:主要结论:大型语言模型可以融入学习过程,用于评估形成性测试和终结性测试,这将大大减轻教师的工作量,提供更客观的结果,并最终提高学习过程的有效性。
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Potentials of integrating generative artificial intelligence technologies into formative assessment processes in higher education
The use of generative artificial intelligence technologies in education has the potential to revolutionize learning and educational assessment by personalizing the learning experience, providing immediate feedback, and improving the overall learning experience.The relevance of the research is due to the spread of artificial intelligence technologies and the lack of practices for formative assessment of educational achievements in higher education.The problem statement: existing domestic e-learning systems have limited functionality, which makes them difficult to use in the process of formative testing.The goal of the research is to study the possibility and effectiveness of using generative artificial intelligence technologies in formative assessment in higher education.The objectives of the research are to consider the theoretical foundations of using generative artificial intelligence tools in assessing knowledge, skills and abilities, and to analyze our own experience of using large language models in formative testing at a university.The methodological basis of the research is analysis of Internet resources and literary sources, methods of mathematical statistics, and synthesis.The research results: the possibilities of using and the effectiveness of generative artificial intelligence technologies in formative testing of university students have been studied, our own experience of using large language models in formative testing have been analyzed, the main limitations of introducing these technologies into the educational process have been identified, recommendations have been given for organizing formative testing using large language models.Key conclusions: Large language models can be integrated into the learning process to assess formative and summative tests, which will significantly reduce the workload of teachers, provide more objective results and, ultimately, increase the effectiveness of the learning process.
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